Products recognition on shop-racks from local scale-invariant features

NASA Astrophysics Data System (ADS)

Zawistowski, Jacek; Kurzejamski, Grzegorz; Garbat, Piotr; Naruniec, Jacek

2016-04-01

This paper presents a system designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. System uses well known binary keypoint detection algorithms for finding characteristic points in the image. One of the main idea is object recognition based on Implicit Shape Model method. Authors of the article proposed many improvements of the algorithm. Originally fiducial points are matched with a very simple function. This leads to the limitations in the number of objects parts being success- fully separated, while various methods of classification may be validated in order to achieve higher performance. Such an extension implies research on training procedure able to deal with many objects categories. Proposed solution opens a new possibilities for many algorithms demanding fast and robust multi-object recognition.

Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

PubMed

Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

2017-05-01

Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

Fiducial migration following small peripheral lung tumor image-guided CyberKnife stereotactic radiosurgery

NASA Astrophysics Data System (ADS)

Strulik, Konrad L.; Cho, Min H.; Collins, Brian T.; Khan, Noureen; Banovac, Filip; Slack, Rebecca; Cleary, Kevin

2008-03-01

To track respiratory motion during CyberKnife stereotactic radiosurgery in the lung, several (three to five) cylindrical gold fiducials are implanted near the planned target volume (PTV). Since these fiducials remain in the human body after treatment, we hypothesize that tracking fiducial movement over time may correlate with the tumor response to treatment and pulmonary fibrosis, thereby serving as an indicator of treatment success. In this paper, we investigate fiducial migration in 24 patients through examination of computed tomography (CT) volume images at four time points: pre-treatment, three, six, and twelve month post-treatment. We developed a MATLAB based GUI environment to display the images, identify the fiducials, and compute our performance measure. After we semi-automatically segmented and detected fiducial locations in CT images of the same patient over time, we identified them according to their configuration and introduced a relative performance measure (ACD: average center distance) to detect their migration. We found that the migration tended to result in a movement towards the fiducial center of the radiated tissue area (indicating tumor regression) and may potentially be linked to the patient prognosis.

Matching Real and Synthetic Panoramic Images Using a Variant of Geometric Hashing

NASA Astrophysics Data System (ADS)

Li-Chee-Ming, J.; Armenakis, C.

2017-05-01

This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object's texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building.

An algorithm for the beat-to-beat assessment of cardiac mechanics during sleep on Earth and in microgravity from the seismocardiogram.

PubMed

Di Rienzo, Marco; Vaini, Emanuele; Lombardi, Prospero

2017-11-15

Seismocardiogram, SCG, is the measure of precordial vibrations produced by the beating heart, from which cardiac mechanics may be explored on a beat-to-beat basis. We recently collected a large amount of SCG data (>69 recording hours) from an astronaut to investigate cardiac mechanics during sleep aboard the International Space Station and on Earth. SCG sleep recordings are characterized by a prolonged duration and wide heart rate swings, thus a specific algorithm was developed for their analysis. In this article we describe the new algorithm and its performance. The algorithm is composed of three parts: 1) artifacts removal, 2) identification in each SCG waveform of four fiducial points associated with the opening and closure of the aortic and mitral valves, 3) beat-to-beat computation of indexes of cardiac mechanics from the SCG fiducial points. The algorithm was tested on two sleep recordings and yielded the identification of the fiducial points in more than 36,000 beats with a precision, quantified by the Positive Predictive Value, ≥99.2%. These positive findings provide the first evidence that cardiac mechanics may be explored by the automatic analysis of SCG long-lasting recordings, taken out of the laboratory setting, and in presence of significant heart rate modulations.

Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding

PubMed Central

Lee, Chia-Yen; Wang, Hao-Jen; Lai, Jhih-Hao; Chang, Yeun-Chung; Huang, Chiun-Sheng

2017-01-01

Long-term comparisons of infrared image can facilitate the assessment of breast cancer tissue growth and early tumor detection, in which longitudinal infrared image registration is a necessary step. However, it is hard to keep markers attached on a body surface for weeks, and rather difficult to detect anatomic fiducial markers and match them in the infrared image during registration process. The proposed study, automatic longitudinal infrared registration algorithm, develops an automatic vascular intersection detection method and establishes feature descriptors by shape context to achieve robust matching, as well as to obtain control points for the deformation model. In addition, competitive winner-guided mechanism is developed for optimal corresponding. The proposed algorithm is evaluated in two ways. Results show that the algorithm can quickly lead to accurate image registration and that the effectiveness is superior to manual registration with a mean error being 0.91 pixels. These findings demonstrate that the proposed registration algorithm is reasonably accurate and provide a novel method of extracting a greater amount of useful data from infrared images. PMID:28145474

Comparison of low‐dose, half‐rotation, cone‐beam CT with electronic portal imaging device for registration of fiducial markers during prostate radiotherapy

PubMed Central

Wee, Leonard; Hackett, Sara Lyons; Jones, Andrew; Lim, Tee Sin; Harper, Christopher Stirling

2013-01-01

This study evaluated the agreement of fiducial marker localization between two modalities — an electronic portal imaging device (EPID) and cone‐beam computed tomography (CBCT) — using a low‐dose, half‐rotation scanning protocol. Twenty‐five prostate cancer patients with implanted fiducial markers were enrolled. Before each daily treatment, EPID and half‐rotation CBCT images were acquired. Translational shifts were computed for each modality and two marker‐matching algorithms, seed‐chamfer and grey‐value, were performed for each set of CBCT images. The localization offsets, and systematic and random errors from both modalities were computed. Localization performances for both modalities were compared using Bland‐Altman limits of agreement (LoA) analysis, Deming regression analysis, and Cohen's kappa inter‐rater analysis. The differences in the systematic and random errors between the modalities were within 0.2 mm in all directions. The LoA analysis revealed a 95% agreement limit of the modalities of 2 to 3.5 mm in any given translational direction. Deming regression analysis demonstrated that constant biases existed in the shifts computed by the modalities in the superior–inferior (SI) direction, but no significant proportional biases were identified in any direction. Cohen's kappa analysis showed good agreement between the modalities in prescribing translational corrections of the couch at 3 and 5 mm action levels. Images obtained from EPID and half‐rotation CBCT showed acceptable agreement for registration of fiducial markers. The seed‐chamfer algorithm for tracking of fiducial markers in CBCT datasets yielded better agreement than the grey‐value matching algorithm with EPID‐based registration. PACS numbers: 87.55.km, 87.55.Qr PMID:23835391

Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werner, F., E-mail: f.werner@uke.de; Hofmann, M.; Them, K.

Purpose: Magnetic particle imaging (MPI) is a quantitative imaging modality that allows the distribution of superparamagnetic nanoparticles to be visualized. Compared to other imaging techniques like x-ray radiography, computed tomography (CT), and magnetic resonance imaging (MRI), MPI only provides a signal from the administered tracer, but no additional morphological information, which complicates geometry planning and the interpretation of MP images. The purpose of the authors’ study was to develop bimodal fiducial markers that can be visualized by MPI and MRI in order to create MP–MR fusion images. Methods: A certain arrangement of three bimodal fiducial markers was developed and usedmore » in a combined MRI/MPI phantom and also during in vivo experiments in order to investigate its suitability for geometry planning and image fusion. An algorithm for automated marker extraction in both MR and MP images and rigid registration was established. Results: The developed bimodal fiducial markers can be visualized by MRI and MPI and allow for geometry planning as well as automated registration and fusion of MR–MP images. Conclusions: To date, exact positioning of the object to be imaged within the field of view (FOV) and the assignment of reconstructed MPI signals to corresponding morphological regions has been difficult. The developed bimodal fiducial markers and the automated image registration algorithm help to overcome these difficulties.« less

Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis

PubMed Central

Dehghan, Ehsan; Moradi, Mehdi; Wen, Xu; French, Danny; Lobo, Julio; Morris, W. James; Salcudean, Septimiu E.; Fichtinger, Gabor

2011-01-01

Purpose: Accurate localization of prostate implants from several C-arm images is necessary for ultrasound-fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C-arm oscillation and sagging. Methods: Five C-arm images are captured by rotating the C-arm around its primary axis, while measuring its rotation angle using a protractor or the C-arm joint encoder. The C-arm images are processed to obtain binary seed-only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C-arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C-arm full pose tracking traditionally implemented using radio-opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets. Results: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 ± 0.44 mm (Mean ± STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching-based reconstruction method and showed relative localization difference of 0.5 ± 0.4 mm. Conclusions: The motion compensation method can successfully compensate for large C-arm motion without using radio-opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use. PMID:21992346

Evaluation of mathematical algorithms for automatic patient alignment in radiosurgery.

PubMed

Williams, Kenneth M; Schulte, Reinhard W; Schubert, Keith E; Wroe, Andrew J

2015-06-01

Image registration techniques based on anatomical features can serve to automate patient alignment for intracranial radiosurgery procedures in an effort to improve the accuracy and efficiency of the alignment process as well as potentially eliminate the need for implanted fiducial markers. To explore this option, four two-dimensional (2D) image registration algorithms were analyzed: the phase correlation technique, mutual information (MI) maximization, enhanced correlation coefficient (ECC) maximization, and the iterative closest point (ICP) algorithm. Digitally reconstructed radiographs from the treatment planning computed tomography scan of a human skull were used as the reference images, while orthogonal digital x-ray images taken in the treatment room were used as the captured images to be aligned. The accuracy of aligning the skull with each algorithm was compared to the alignment of the currently practiced procedure, which is based on a manual process of selecting common landmarks, including implanted fiducials and anatomical skull features. Of the four algorithms, three (phase correlation, MI maximization, and ECC maximization) demonstrated clinically adequate (ie, comparable to the standard alignment technique) translational accuracy and improvements in speed compared to the interactive, user-guided technique; however, the ICP algorithm failed to give clinically acceptable results. The results of this work suggest that a combination of different algorithms may provide the best registration results. This research serves as the initial groundwork for the translation of automated, anatomy-based 2D algorithms into a real-world system for 2D-to-2D image registration and alignment for intracranial radiosurgery. This may obviate the need for invasive implantation of fiducial markers into the skull and may improve treatment room efficiency and accuracy. © The Author(s) 2014.

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers.

PubMed

Wognum, S; Heethuis, S E; Rosario, T; Hoogeman, M S; Bel, A

2014-07-01

The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images of ex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Five excised porcine bladders with a grid of 30-40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100-400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. The authors found good structure accuracy without dependency on bladder volume difference for all but one algorithm, and with the best result for the structure-based algorithm. Spatial accuracy as assessed from marker errors was disappointing for all algorithms, especially for large volume differences, implying that the deformations described by the registration did not represent anatomically correct deformations. The structure-based algorithm performed the best in terms of marker error for the large volume difference (100-400 ml). In general, for the small volume difference (100-150 ml) the algorithms performed relatively similarly. The structure-based algorithm exhibited the best balance in performance between small and large volume differences, and among the intensity-based algorithms, the algorithm implemented in VelocityAI exhibited the best balance. Validation of multiple DIR algorithms on a novel physiological bladder phantom revealed that the structure accuracy was good for most algorithms, but that the spatial accuracy as assessed from markers was low for all algorithms, especially for large deformations. Hence, many of the available algorithms exhibit sufficient accuracy for contour propagation purposes, but possibly not for accurate dose accumulation.

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

PubMed Central

2017-01-01

Rapid automatic detection of the fiducial points—namely, the P wave, QRS complex, and T wave—is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs. PMID:29065613

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

PubMed

Park, Jeong-Seon; Lee, Sang-Woong; Park, Unsang

2017-01-01

Rapid automatic detection of the fiducial points-namely, the P wave, QRS complex, and T wave-is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.

B-Mode ultrasound pose recovery via surgical fiducial segmentation and tracking

NASA Astrophysics Data System (ADS)

Asoni, Alessandro; Ketcha, Michael; Kuo, Nathanael; Chen, Lei; Boctor, Emad; Coon, Devin; Prince, Jerry L.

2015-03-01

Ultrasound Doppler imaging may be used to detect blood clots after surgery, a common problem. However, this requires consistent probe positioning over multiple time instances and therefore significant sonographic expertise. Analysis of ultrasound B-mode images of a fiducial implanted at the surgical site offers a landmark to guide a user to the same location repeatedly. We demonstrate that such an implanted fiducial may be successfully detected and tracked to calculate pose and guide a clinician consistently to the site of surgery, potentially reducing the ultrasound experience required for point of care monitoring.

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wognum, S., E-mail: s.wognum@gmail.com; Heethuis, S. E.; Bel, A.

2014-07-15

Purpose: The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images ofex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Methods: Fivemore » excised porcine bladders with a grid of 30–40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100–400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. Results: The authors found good structure accuracy without dependency on bladder volume difference for all but one algorithm, and with the best result for the structure-based algorithm. Spatial accuracy as assessed from marker errors was disappointing for all algorithms, especially for large volume differences, implying that the deformations described by the registration did not represent anatomically correct deformations. The structure-based algorithm performed the best in terms of marker error for the large volume difference (100–400 ml). In general, for the small volume difference (100–150 ml) the algorithms performed relatively similarly. The structure-based algorithm exhibited the best balance in performance between small and large volume differences, and among the intensity-based algorithms, the algorithm implemented in VelocityAI exhibited the best balance. Conclusions: Validation of multiple DIR algorithms on a novel physiological bladder phantom revealed that the structure accuracy was good for most algorithms, but that the spatial accuracy as assessed from markers was low for all algorithms, especially for large deformations. Hence, many of the available algorithms exhibit sufficient accuracy for contour propagation purposes, but possibly not for accurate dose accumulation.« less

SU-G-BRA-05: Application of a Feature-Based Tracking Algorithm to KV X-Ray Fluoroscopic Images Toward Marker-Less Real-Time Tumor Tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakamura, M; Matsuo, Y; Mukumoto, N

Purpose: To detect target position on kV X-ray fluoroscopic images using a feature-based tracking algorithm, Accelerated-KAZE (AKAZE), for markerless real-time tumor tracking (RTTT). Methods: Twelve lung cancer patients treated with RTTT on the Vero4DRT (Mitsubishi Heavy Industries, Japan, and Brainlab AG, Feldkirchen, Germany) were enrolled in this study. Respiratory tumor movement was greater than 10 mm. Three to five fiducial markers were implanted around the lung tumor transbronchially for each patient. Before beam delivery, external infrared (IR) markers and the fiducial markers were monitored for 20 to 40 s with the IR camera every 16.7 ms and with an orthogonalmore » kV x-ray imaging subsystem every 80 or 160 ms, respectively. Target positions derived from the fiducial markers were determined on the orthogonal kV x-ray images, which were used as the ground truth in this study. Meanwhile, tracking positions were identified by AKAZE. Among a lot of feature points, AKAZE found high-quality feature points through sequential cross-check and distance-check between two consecutive images. Then, these 2D positional data were converted to the 3D positional data by a transformation matrix with a predefined calibration parameter. Root mean square error (RMSE) was calculated to evaluate the difference between 3D tracking and target positions. A total of 393 frames was analyzed. The experiment was conducted on a personal computer with 16 GB RAM, Intel Core i7-2600, 3.4 GHz processor. Results: Reproducibility of the target position during the same respiratory phase was 0.6 +/− 0.6 mm (range, 0.1–3.3 mm). Mean +/− SD of the RMSEs was 0.3 +/− 0.2 mm (range, 0.0–1.0 mm). Median computation time per frame was 179 msec (range, 154–247 msec). Conclusion: AKAZE successfully and quickly detected the target position on kV X-ray fluoroscopic images. Initial results indicate that the differences between 3D tracking and target position would be clinically acceptable.« less

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghose, Soumya, E-mail: soumya.ghose@case.edu; Mitra, Jhimli; Rivest-Hénault, David

Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contoursmore » were selected in a spectral clustering manifold learning framework. This aids in clustering “similar” gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.« less

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection.

PubMed

Ghose, Soumya; Mitra, Jhimli; Rivest-Hénault, David; Fazlollahi, Amir; Stanwell, Peter; Pichler, Peter; Sun, Jidi; Fripp, Jurgen; Greer, Peter B; Dowling, Jason A

2016-05-01

The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.

Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

NASA Astrophysics Data System (ADS)

Harit, Aditya; Joshi, J. C., Col; Gupta, K. K.

2018-03-01

The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

Semi-automated based ground-truthing GUI for airborne imagery

NASA Astrophysics Data System (ADS)

Phan, Chung; Lydic, Rich; Moore, Tim; Trang, Anh; Agarwal, Sanjeev; Tiwari, Spandan

2005-06-01

Over the past several years, an enormous amount of airborne imagery consisting of various formats has been collected and will continue into the future to support airborne mine/minefield detection processes, improve algorithm development, and aid in imaging sensor development. The ground-truthing of imagery is a very essential part of the algorithm development process to help validate the detection performance of the sensor and improving algorithm techniques. The GUI (Graphical User Interface) called SemiTruth was developed using Matlab software incorporating signal processing, image processing, and statistics toolboxes to aid in ground-truthing imagery. The semi-automated ground-truthing GUI is made possible with the current data collection method, that is including UTM/GPS (Universal Transverse Mercator/Global Positioning System) coordinate measurements for the mine target and fiducial locations on the given minefield layout to support in identification of the targets on the raw imagery. This semi-automated ground-truthing effort has developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division, Airborne Application Branch with some support by the University of Missouri-Rolla.

Automated patient setup and gating using cone beam computed tomography projections

NASA Astrophysics Data System (ADS)

Wan, Hanlin; Bertholet, Jenny; Ge, Jiajia; Poulsen, Per; Parikh, Parag

2016-03-01

In radiation therapy, fiducial markers are often implanted near tumors and used for patient positioning and respiratory gating purposes. These markers are then used to manually align the patients by matching the markers in the cone beam computed tomography (CBCT) reconstruction to those in the planning CT. This step is time-intensive and user-dependent, and often results in a suboptimal patient setup. We propose a fully automated, robust method based on dynamic programming (DP) for segmenting radiopaque fiducial markers in CBCT projection images, which are then used to automatically optimize the treatment couch position and/or gating window bounds. The mean of the absolute 2D segmentation error of our DP algorithm is 1.3+/- 1.0 mm for 87 markers on 39 patients. Intrafraction images were acquired every 3 s during treatment at two different institutions. For gated patients from Institution A (8 patients, 40 fractions), the DP algorithm increased the delivery accuracy (96+/- 6% versus 91+/- 11% , p  <  0.01) compared to the manual setup using kV fluoroscopy. For non-gated patients from Institution B (6 patients, 16 fractions), the DP algorithm performed similarly (1.5+/- 0.8 mm versus 1.6+/- 0.9 mm, p  =  0.48) compared to the manual setup matching the fiducial markers in the CBCT to the mean position. Our proposed automated patient setup algorithm only takes 1-2 s to run, requires no user intervention, and performs as well as or better than the current clinical setup.

Fiducial Marker Detection and Pose Estimation From LIDAR Range Data

DTIC Science & Technology

2010-03-01

of View FPA Focal Plane Array FPS Frames Per Second FRE Fiducial Registration Error GIS Geographic Information Systems GPS Global...applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381–395. Bradski, G., & Kaehler, A. (2008). Learning OpenCV

Using dynamic programming to improve fiducial marker localization

NASA Astrophysics Data System (ADS)

Wan, Hanlin; Ge, Jiajia; Parikh, Parag

2014-04-01

Fiducial markers are used in a wide range of medical imaging applications. In radiation therapy, they are often implanted near tumors and used as motion surrogates that are tracked with fluoroscopy. We propose a novel and robust method based on dynamic programming (DP) for retrospectively localizing radiopaque fiducial markers in fluoroscopic images. Our method was compared to template matching (TM) algorithms on 407 data sets from 24 patients. We found that the performance of TM varied dramatically depending on the template used (ranging from 47% to 92% of data sets with a mean error <1 mm). DP by itself requires no template and performed as well as the best TM method, localizing the markers in 91% of the data sets with a mean error <1 mm. Finally, by combining DP and TM, we were able to localize the markers in 99% of the data sets with a mean error <1 mm, regardless of the template used. Our results show that DP can be a powerful tool for analyzing tumor motion, capable of accurately locating fiducial markers in fluoroscopic images regardless of marker type, shape, and size.

Fully automatic segmentation of arbitrarily shaped fiducial markers in cone-beam CT projections

NASA Astrophysics Data System (ADS)

Bertholet, J.; Wan, H.; Toftegaard, J.; Schmidt, M. L.; Chotard, F.; Parikh, P. J.; Poulsen, P. R.

2017-02-01

Radio-opaque fiducial markers of different shapes are often implanted in or near abdominal or thoracic tumors to act as surrogates for the tumor position during radiotherapy. They can be used for real-time treatment adaptation, but this requires a robust, automatic segmentation method able to handle arbitrarily shaped markers in a rotational imaging geometry such as cone-beam computed tomography (CBCT) projection images and intra-treatment images. In this study, we propose a fully automatic dynamic programming (DP) assisted template-based (TB) segmentation method. Based on an initial DP segmentation, the DPTB algorithm generates and uses a 3D marker model to create 2D templates at any projection angle. The 2D templates are used to segment the marker position as the position with highest normalized cross-correlation in a search area centered at the DP segmented position. The accuracy of the DP algorithm and the new DPTB algorithm was quantified as the 2D segmentation error (pixels) compared to a manual ground truth segmentation for 97 markers in the projection images of CBCT scans of 40 patients. Also the fraction of wrong segmentations, defined as 2D errors larger than 5 pixels, was calculated. The mean 2D segmentation error of DP was reduced from 4.1 pixels to 3.0 pixels by DPTB, while the fraction of wrong segmentations was reduced from 17.4% to 6.8%. DPTB allowed rejection of uncertain segmentations as deemed by a low normalized cross-correlation coefficient and contrast-to-noise ratio. For a rejection rate of 9.97%, the sensitivity in detecting wrong segmentations was 67% and the specificity was 94%. The accepted segmentations had a mean segmentation error of 1.8 pixels and 2.5% wrong segmentations.

SU-F-BRF-09: A Non-Rigid Point Matching Method for Accurate Bladder Dose Summation in Cervical Cancer HDR Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, H; Zhen, X; Zhou, L

2014-06-15

Purpose: To propose and validate a deformable point matching scheme for surface deformation to facilitate accurate bladder dose summation for fractionated HDR cervical cancer treatment. Method: A deformable point matching scheme based on the thin plate spline robust point matching (TPSRPM) algorithm is proposed for bladder surface registration. The surface of bladders segmented from fractional CT images is extracted and discretized with triangular surface mesh. Deformation between the two bladder surfaces are obtained by matching the two meshes' vertices via the TPS-RPM algorithm, and the deformation vector fields (DVFs) characteristic of this deformation is estimated by B-spline approximation. Numerically, themore » algorithm is quantitatively compared with the Demons algorithm using five clinical cervical cancer cases by several metrics: vertex-to-vertex distance (VVD), Hausdorff distance (HD), percent error (PE), and conformity index (CI). Experimentally, the algorithm is validated on a balloon phantom with 12 surface fiducial markers. The balloon is inflated with different amount of water, and the displacement of fiducial markers is benchmarked as ground truth to study TPS-RPM calculated DVFs' accuracy. Results: In numerical evaluation, the mean VVD is 3.7(±2.0) mm after Demons, and 1.3(±0.9) mm after TPS-RPM. The mean HD is 14.4 mm after Demons, and 5.3mm after TPS-RPM. The mean PE is 101.7% after Demons and decreases to 18.7% after TPS-RPM. The mean CI is 0.63 after Demons, and increases to 0.90 after TPS-RPM. In the phantom study, the mean Euclidean distance of the fiducials is 7.4±3.0mm and 4.2±1.8mm after Demons and TPS-RPM, respectively. Conclusions: The bladder wall deformation is more accurate using the feature-based TPS-RPM algorithm than the intensity-based Demons algorithm, indicating that TPS-RPM has the potential for accurate bladder dose deformation and dose summation for multi-fractional cervical HDR brachytherapy. This work is supported in part by the National Natural ScienceFoundation of China (no 30970866 and no 81301940)« less

Visibility of solid and liquid fiducial markers used for image-guided radiation therapy on optical coherence tomography: an esophageal phantom study (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jelvehgaran, Pouya; Alderliesten, Tanja; Weda, Jelmer J. A.; de Bruin, Daniel M.; Faber, Dirk J.; Hulshof, Maarten C. C. M.; van Leeuwen, Ton G.; van Herk, Marcel B.; de Boer, Johannes F.

2017-03-01

Radiation therapy (RT) is used in operable and inoperable esophageal cancer patients. Endoscopic ultrasound-guided fiducial marker placement allows improved translation of the disease extent on endoscopy to computed tomography (CT) images used for RT planning and enables image-guided RT. However, microscopic tumor extent at the time of RT planning is unknown. Endoscopic optical coherence tomography (OCT) is a high-resolution (10-30µm) imaging modality with the potential for accurately determining the longitudinal disease extent. Visibility of fiducial markers on OCT is crucial for integrating OCT findings with the RT planning CT. We investigated the visibility on OCT (NinePoint Medical, Inc.) of 13 commercially available solid (Visicoil, Gold Anchor, Flexicoil, Polymark, and QLRAD) and liquid (BioXmark, Lipiodol, and Hydrogel) fiducial markers of different diameter. We designed and manufactured a set of dedicated Silicone-based esophageal phantoms to perform imaging in a controlled environment. The esophageal phantoms consist of several layers with different TiO2 concentrations to simulate the scattering properties of a typical healthy human esophagus. Markers were placed at various depths (0.5, 1.1, 2.0, and 3.0mm). OCT imaging allowed detection of all fiducial markers and phantom layers. The signal to background ratio was 6-fold higher for the solid fiducial markers than the liquid fiducial markers, yet OCT was capable of visualizing all 13 fiducial markers at all investigated depths. We conclude that RT fiducial markers can be visualized with OCT. This allows integration of OCT findings with CT for image-guided RT.

Optimizing fiducial visibility on periodically acquired megavoltage and kilovoltage image pairs during prostate volumetric modulated arc therapy

PubMed Central

Zhang, Pengpeng; Happersett, Laura; Ravindranath, Bosky; Zelefsky, Michael; Mageras, Gig; Hunt, Margie

2016-01-01

Purpose: Robust detection of implanted fiducials is essential for monitoring intrafractional motion during hypofractionated treatment. The authors developed a plan optimization strategy to ensure clear visibility of implanted fiducials and facilitate 3D localization during volumetric modulated arc therapy (VMAT). Methods: Periodic kilovoltage (kV) images were acquired at 20° gantry intervals and paired with simultaneously acquired 4.4° short arc megavoltage digital tomosynthesis (MV-DTS) to localize three fiducials during VMAT delivery for hypofractionated prostate cancer treatment. Beginning with the original optimized plan, control point segments where fiducials were consistently blocked by multileaf collimator (MLC) within each 4.4° MV-DTS interval were first identified. For each segment, MLC apertures were edited to expose the fiducial that led to the least increase in the cost function. Subsequently, MLC apertures of all control points not involved with fiducial visualization were reoptimized to compensate for plan quality losses and match the original dose–volume histogram. MV dose for each MV-DTS was also kept above 0.4 MU to ensure acceptable image quality. Different imaging (gantry) intervals and visibility margins around fiducials were also evaluated. Results: Fiducials were consistently blocked by the MLC for, on average, 36% of the imaging control points for five hypofractionated prostate VMAT plans but properly exposed after reoptimization. Reoptimization resulted in negligible dosimetric differences compared with original plans and outperformed simple aperture editing: on average, PTV D98 recovered from 87% to 94% of prescription, and PTV dose homogeneity improved from 9% to 7%. Without violating plan objectives and compromising delivery efficiency, the highest imaging frequency and largest margin that can be achieved are a 10° gantry interval, and 15 mm, respectively. Conclusions: VMAT plans can be made to accommodate MV-kV imaging of fiducials. Fiducial visualization rate and workflow efficiency are significantly improved with an automatic modification and reoptimization approach. PMID:27147314

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pettersson, N; Murphy, J; Simpson, D

Purpose: The use of respiratory gating for management of breathing motion during stereotactic body radiation therapy (SBRT) relies on a consistent relationship between the breathing signal and the actual position of the internal target. This relationship was investigated in patients treated for pancreatic cancer. Methods: Four patients with pancreatic cancer undergoing SBRT that had implanted fiducials in the tumor were included in this study. Treatment plans were generated based on the exhale phases (30–70%) from the pre-treatment 4DCT. The margin between the internal target volume (ITV) and the planning target volume was three mm. After patient setup using cone-beam CT,more » simultaneous fluoroscopic imaging and breathing motion monitoring were used during at least three breathing cycles to verify the fiducial position and to optimize the gating window. After treatment, fluoroscopic images were acquired for verification purposes and exported for retrospective analyses. Fiducial positions were determined using a template-matching algorithm. For each dataset, we established a linear relationship between the fiducial position and the anterior-posterior (AP) breathing signal. The relationships before and after treatment were compared and the dose distribution impact evaluated. Results: Seven pre- and post-treatment fluoroscopic pairs were available for fiducial position analyses in the superior-inferior (SI) and left-right (LR) directions, and five in the AP direction. Time between image acquisitions was typically six to eight minutes. An average absolute change of 1.2±0.7 mm (range: 0.1–1.7) of the SI fiducial position relative to the external signal was found. Corresponding numbers for the LR and AP fiducial positions were 0.9±1.0 mm (range: 0.2–3.0) and 0.5±0.4 mm (range: 0.2–1.2), respectively. The dose distribution impact was small in both the ITV and organs-at-risk. Conclusion: The relationship change between fiducial position and external breathing signal has been observed to be about 1 mm in four pancreas SBRT patients, leading to small dose distribution impact. Pettersson and Cervino are funded by a Varian Medical Systems grant.« less

Localization accuracy of sphere fiducials in computed tomography images

NASA Astrophysics Data System (ADS)

Kobler, Jan-Philipp; Díaz Díaz, Jesus; Fitzpatrick, J. Michael; Lexow, G. Jakob; Majdani, Omid; Ortmaier, Tobias

2014-03-01

In recent years, bone-attached robots and microstereotactic frames have attracted increasing interest due to the promising targeting accuracy they provide. Such devices attach to a patient's skull via bone anchors, which are used as landmarks during intervention planning as well. However, as simulation results reveal, the performance of such mechanisms is limited by errors occurring during the localization of their bone anchors in preoperatively acquired computed tomography images. Therefore, it is desirable to identify the most suitable fiducials as well as the most accurate method for fiducial localization. We present experimental results of a study focusing on the fiducial localization error (FLE) of spheres. Two phantoms equipped with fiducials made from ferromagnetic steel and titanium, respectively, are used to compare two clinically available imaging modalities (multi-slice CT (MSCT) and cone-beam CT (CBCT)), three localization algorithms as well as two methods for approximating the FLE. Furthermore, the impact of cubic interpolation applied to the images is investigated. Results reveal that, generally, the achievable localization accuracy in CBCT image data is significantly higher compared to MSCT imaging. The lowest FLEs (approx. 40 μm) are obtained using spheres made from titanium, CBCT imaging, template matching based on cross correlation for localization, and interpolating the images by a factor of sixteen. Nevertheless, the achievable localization accuracy of spheres made from steel is only slightly inferior. The outcomes of the presented study will be valuable considering the optimization of future microstereotactic frame prototypes as well as the operative workflow.

Biological fiducial point based registration for multiple brain tissues reconstructed from different imaging modalities

NASA Astrophysics Data System (ADS)

Wu, Huiqun; Zhou, Gangping; Geng, Xingyun; Zhang, Xiaofeng; Jiang, Kui; Tang, Lemin; Zhou, Guomin; Dong, Jiancheng

2013-10-01

With the development of computer aided navigation system, more and more tissues shall be reconstructed to provide more useful information for surgical pathway planning. In this study, we aimed to propose a registration framework for different reconstructed tissues from multi-modalities based on some fiducial points on lateral ventricles. A male patient with brain lesion was admitted and his brain scans were performed by different modalities. Then, the different brain tissues were segmented in different modality with relevant suitable algorithms. Marching cubes were calculated for three dimensional reconstructions, and then the rendered tissues were imported to a common coordinate system for registration. Four pairs of fiducial markers were selected to calculate the rotation and translation matrix using least-square measure method. The registration results were satisfied in a glioblastoma surgery planning as it provides the spatial relationship between tumors and surrounding fibers as well as vessels. Hence, our framework is of potential value for clinicians to plan surgery.

Lung tumor tracking in fluoroscopic video based on optical flow

PubMed Central

Xu, Qianyi; Hamilton, Russell J.; Schowengerdt, Robert A.; Alexander, Brian; Jiang, Steve B.

2008-01-01

Respiratory gating and tumor tracking for dynamic multileaf collimator delivery require accurate and real-time localization of the lung tumor position during treatment. Deriving tumor position from external surrogates such as abdominal surface motion may have large uncertainties due to the intra- and interfraction variations of the correlation between the external surrogates and internal tumor motion. Implanted fiducial markers can be used to track tumors fluoroscopically in real time with sufficient accuracy. However, it may not be a practical procedure when implanting fiducials bronchoscopically. In this work, a method is presented to track the lung tumor mass or relevant anatomic features projected in fluoroscopic images without implanted fiducial markers based on an optical flow algorithm. The algorithm generates the centroid position of the tracked target and ignores shape changes of the tumor mass shadow. The tracking starts with a segmented tumor projection in an initial image frame. Then, the optical flow between this and all incoming frames acquired during treatment delivery is computed as initial estimations of tumor centroid displacements. The tumor contour in the initial frame is transferred to the incoming frames based on the average of the motion vectors, and its positions in the incoming frames are determined by fine-tuning the contour positions using a template matching algorithm with a small search range. The tracking results were validated by comparing with clinician determined contours on each frame. The position difference in 95% of the frames was found to be less than 1.4 pixels (∼0.7 mm) in the best case and 2.8 pixels (∼1.4 mm) in the worst case for the five patients studied. PMID:19175094

Lung tumor tracking in fluoroscopic video based on optical flow.

PubMed

Xu, Qianyi; Hamilton, Russell J; Schowengerdt, Robert A; Alexander, Brian; Jiang, Steve B

2008-12-01

Respiratory gating and tumor tracking for dynamic multileaf collimator delivery require accurate and real-time localization of the lung tumor position during treatment. Deriving tumor position from external surrogates such as abdominal surface motion may have large uncertainties due to the intra- and interfraction variations of the correlation between the external surrogates and internal tumor motion. Implanted fiducial markers can be used to track tumors fluoroscopically in real time with sufficient accuracy. However, it may not be a practical procedure when implanting fiducials bronchoscopically. In this work, a method is presented to track the lung tumor mass or relevant anatomic features projected in fluoroscopic images without implanted fiducial markers based on an optical flow algorithm. The algorithm generates the centroid position of the tracked target and ignores shape changes of the tumor mass shadow. The tracking starts with a segmented tumor projection in an initial image frame. Then, the optical flow between this and all incoming frames acquired during treatment delivery is computed as initial estimations of tumor centroid displacements. The tumor contour in the initial frame is transferred to the incoming frames based on the average of the motion vectors, and its positions in the incoming frames are determined by fine-tuning the contour positions using a template matching algorithm with a small search range. The tracking results were validated by comparing with clinician determined contours on each frame. The position difference in 95% of the frames was found to be less than 1.4 pixels (approximately 0.7 mm) in the best case and 2.8 pixels (approximately 1.4 mm) in the worst case for the five patients studied.

A Solar Aspect System for the HEROES Mission

NASA Technical Reports Server (NTRS)

Christe, Steven; Shih, Albert; Rodriguez, Marcello; Gregory, Kyle; Cramer, Alexander; Edgerton, Melissa; Gaskin, Jessica; O'Connor, Brian; Sobey, Alexander

2014-01-01

A new Solar Aspect System (SAS) has been developed to provide the ability to observe the Sun on an existing balloon payload HERO (short for High Energy Replicated Optics). Developed under the HEROES program (High Energy Replicated Optics to Explore the Sun), the SAS aspect system provides solar pointing knowledge in pitch, yaw, and roll. The required precision of these measurements must be better than the HEROES X-ray resolution of approximately 20 arcsec Full Width at Half Maximum (FWHM) so as to not degrade the image resolution. The SAS consists of two separate systems: the Pitch-Yaw Aspect System (PYAS) and the Roll Aspect System (RAS). The PYAS functions by projecting an image of the Sun onto a screen with precision fiducials. A CCD camera takes an image of these fiducials, and an automated algorithm determines the location of the Sun as well as the location of the fiducials. The spacing between fiducials is unique and allows each to be identified so that the location of the Sun on the screen can be precisely determined. The RAS functions by imaging the Earth's horizon in opposite directions using a silvered prism imaged by a CCD camera. The design and first results of the performance of these systems during the HEROES flight which occurred in September 2013 are presented here.

Analyzing Thorough QT Study 1 & 2 in the Telemetric and Holter ECG Warehouse (THEW) using Hannover ECG System HES : A validation study.

PubMed

Khawaja, A; Petrovic, R; Safer, A; Baas, T; Dössel, O; Fischer, R

2010-01-01

Following the ICH E14 clinical evaluation guideline [1], the measurement of QT/QTc interval prolongation has become the standard surrogate biomarker for cardiac drug safety assessment and the faith of a drug development. In Thorough QT (TQT) study, a so-called positive control is employed to assess the ability of this study to detect the endpoint of interest, i.e. the QT prolongation by about five milliseconds. In other words the lower bound of the one-sided 95% confidence interval (CI) must be above 0 [ms]. Fully automated detection of ECG fiducial points and measurement of the corresponding intervals including QT intervals and RR intervals vary between different computerized algorithms. In this work we demonstrate the ability and reliability of Hannover ECG System (HES(®)) to assess drug effects by detecting QT/QTc prolongation effects that meet the threshold of regulatory concern as mentioned by using THEW database studies namely TQT studies one and two.

Full automatic fiducial marker detection on coil arrays for accurate instrumentation placement during MRI guided breast interventions

NASA Astrophysics Data System (ADS)

Filippatos, Konstantinos; Boehler, Tobias; Geisler, Benjamin; Zachmann, Harald; Twellmann, Thorsten

2010-02-01

With its high sensitivity, dynamic contrast-enhanced MR imaging (DCE-MRI) of the breast is today one of the first-line tools for early detection and diagnosis of breast cancer, particularly in the dense breast of young women. However, many relevant findings are very small or occult on targeted ultrasound images or mammography, so that MRI guided biopsy is the only option for a precise histological work-up [1]. State-of-the-art software tools for computer-aided diagnosis of breast cancer in DCE-MRI data offer also means for image-based planning of biopsy interventions. One step in the MRI guided biopsy workflow is the alignment of the patient position with the preoperative MR images. In these images, the location and orientation of the coil localization unit can be inferred from a number of fiducial markers, which for this purpose have to be manually or semi-automatically detected by the user. In this study, we propose a method for precise, full-automatic localization of fiducial markers, on which basis a virtual localization unit can be subsequently placed in the image volume for the purpose of determining the parameters for needle navigation. The method is based on adaptive thresholding for separating breast tissue from background followed by rigid registration of marker templates. In an evaluation of 25 clinical cases comprising 4 different commercial coil array models and 3 different MR imaging protocols, the method yielded a sensitivity of 0.96 at a false positive rate of 0.44 markers per case. The mean distance deviation between detected fiducial centers and ground truth information that was appointed from a radiologist was 0.94mm.

Accuracy and Consistency of Respiratory Gating in Abdominal Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ge, Jiajia; Santanam, Lakshmi; Yang, Deshan

2013-03-01

Purpose: To evaluate respiratory gating accuracy and intrafractional consistency for abdominal cancer patients treated with respiratory gated treatment on a regular linear accelerator system. Methods and Materials: Twelve abdominal patients implanted with fiducials were treated with amplitude-based respiratory-gated radiation therapy. On the basis of daily orthogonal fluoroscopy, the operator readjusted the couch position and gating window such that the fiducial was within a setup margin (fiducial-planning target volume [f-PTV]) when RPM indicated “beam-ON.” Fifty-five pre- and post-treatment fluoroscopic movie pairs with synchronized respiratory gating signal were recorded. Fiducial motion traces were extracted from the fluoroscopic movies using a template matchingmore » algorithm and correlated with f-PTV by registering the digitally reconstructed radiographs with the fluoroscopic movies. Treatment was determined to be “accurate” if 50% of the fiducial area stayed within f-PTV while beam-ON. For movie pairs that lost gating accuracy, a MATLAB program was used to assess whether the gating window was optimized, the external-internal correlation (EIC) changed, or the patient moved between movies. A series of safety margins from 0.5 mm to 3 mm was added to f-PTV for reassessing gating accuracy. Results: A decrease in gating accuracy was observed in 44% of movie pairs from daily fluoroscopic movies of 12 abdominal patients. Three main causes for inaccurate gating were identified as change of global EIC over time (∼43%), suboptimal gating setup (∼37%), and imperfect EIC within movie (∼13%). Conclusions: Inconsistent respiratory gating accuracy may occur within 1 treatment session even with a daily adjusted gating window. To improve or maintain gating accuracy during treatment, we suggest using at least a 2.5-mm safety margin to account for gating and setup uncertainties.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scherman Rydhög, Jonas, E-mail: per.jonas.scherman.rydhoeg@regionh.dk; Munck af Rosenschöld, Per; Irming Jølck, Rasmus

Purpose: A new biodegradable liquid fiducial marker was devised to allow for easy insertion in lung tumors using thin needles. The purpose of this study was to evaluate the visibility of the liquid fiducial markers for image-guided radiation therapy and compare to existing solid fiducial markers and to one existing liquid fiducial marker currently commercially available. Methods: Fiducial marker visibility was quantified in terms of contrast to noise ratio (CNR) on planar kilovoltage x-ray images in a thorax phantom for different concentrations of the radio-opaque component of the new liquid fiducial marker, four solid fiducial markers, and one existing liquidmore » fiducial marker. Additionally, the image artifacts produced on computer tomography (CT) and cone-beam CT (CBCT) of all fiducial markers were quantified. Results: The authors found that the new liquid fiducial marker with the highest concentration of the radio-opaque component had a CNR > 2.05 for 62/63 exposures, which compared favorably to the existing solid fiducial markers and to the existing liquid fiducial marker evaluated. On CT and CBCT, the new liquid fiducial marker with the highest concentration produced lower streaking index artifact (30 and 14, respectively) than the solid gold markers (113 and 20, respectively) and the existing liquid fiducial marker (39 and 20, respectively). The size of the image artifact was larger for all of the liquid fiducial markers compared to the solid fiducial markers because of their larger physical size. Conclusions: The visibility and the image artifacts produced by the new liquid fiducial markers were comparable to existing solid fiducial markers and the existing liquid fiducial marker. The authors conclude that the new liquid fiducial marker represents an alternative to the fiducial markers tested.« less

Optical CT imaging of solid radiochromic dosimeters in mismatched refractive index solutions using a scanning laser and large area detector.

PubMed

Dekker, Kurtis H; Battista, Jerry J; Jordan, Kevin J

2016-08-01

The practical use of the PRESAGE® solid plastic dosimeter is limited by the inconvenience of immersing it in high-viscosity oils to achieve refractive index matching for optical computed tomography (CT) scanning. The oils are slow to mix and difficult to clean from surfaces, and the dosimeter rotation can generate dynamic Schlieren inhomogeneity patterns in the reference liquid, limiting the rotational and overall scan speed. Therefore, it would be beneficial if lower-viscosity, water-based solutions with slightly unmatched refractive index could be used instead. The purpose of this work is to demonstrate the feasibility of allowing mismatched conditions when using a scanning laser system with a large acceptance angle detector. A fiducial-based ray path measurement technique is combined with an iterative CT reconstruction algorithm to reconstruct images. A water based surrounding liquid with a low viscosity was selected for imaging PRESAGE® solid dosimeters. Liquid selection was optimized to achieve as high a refractive index as possible while avoiding rotation-induced Schlieren effects. This led to a refractive index mismatch of 6% between liquid and dosimeters. Optical CT scans were performed with a fan-beam scanning-laser optical CT system with a large area detector to capture most of the refracted rays. A fiducial marker placed on the wall of a cylindrical sample occludes a given light ray twice. With knowledge of the rotation angle and the radius of the cylindrical object, the actual internal path of each ray through the dosimeter can be calculated. Scans were performed with 1024 projections of 512 data samples each, and rays were rebinned to form 512 parallel-beam projections. Reconstructions were performed on a 512 × 512 grid using 100 iterations of the SIRT iterative CT algorithm. Proof of concept was demonstrated with a uniformly attenuating solution phantom. PRESAGE® dosimeters (11 cm diameter) were irradiated with Cobalt-60 irradiator to achieve either a uniform dose or a 2-level "step-dose" pattern. With 6% refractive index mismatching, a circular field of view of 85% of the diameter of a cylindrical sample can be reconstructed accurately. Reconstructed images of the test solution phantom were uniform (within 3%) inside this radius. However, the dose responses of the PRESAGE® samples were not spatially uniform, with variations of at least 5% in sensitivity. The variation appears as a "cupping" artifact with less sensitivity in the middle than at the periphery of the PRESAGE® cylinder. Polarization effects were also detected for these samples. The fiducial-based ray path measurement scheme, coupled with an iterative reconstruction algorithm, enabled optical CT scanning of PRESAGE® dosimeters immersed in mismatched refractive index solutions. However, improvements to PRESAGE® dose response uniformity are required.

Evaluation of an image-based tracking workflow using a passive marker and resonant micro-coil fiducials for automatic image plane alignment in interventional MRI.

PubMed

Neumann, M; Breton, E; Cuvillon, L; Pan, L; Lorenz, C H; de Mathelin, M

2012-01-01

In this paper, an original workflow is presented for MR image plane alignment based on tracking in real-time MR images. A test device consisting of two resonant micro-coils and a passive marker is proposed for detection using image-based algorithms. Micro-coils allow for automated initialization of the object detection in dedicated low flip angle projection images; then the passive marker is tracked in clinical real-time MR images, with alternation between two oblique orthogonal image planes along the test device axis; in case the passive marker is lost in real-time images, the workflow is reinitialized. The proposed workflow was designed to minimize dedicated acquisition time to a single dedicated acquisition in the ideal case (no reinitialization required). First experiments have shown promising results for test-device tracking precision, with a mean position error of 0.79 mm and a mean orientation error of 0.24°.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers

NASA Astrophysics Data System (ADS)

Haring, Martijn T.; Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Voortman, Lenard M.; Kruit, Pieter; Hoogenboom, Jacob P.

2017-03-01

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers.

PubMed

Haring, Martijn T; Liv, Nalan; Zonnevylle, A Christiaan; Narvaez, Angela C; Voortman, Lenard M; Kruit, Pieter; Hoogenboom, Jacob P

2017-03-02

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers

PubMed Central

Haring, Martijn T.; Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Voortman, Lenard M.; Kruit, Pieter; Hoogenboom, Jacob P.

2017-01-01

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample. PMID:28252673

Orthogonal Rings, Fiducial Markers, and Overlay Accuracy When Image Fusion is Used for EVAR Guidance.

PubMed

Koutouzi, G; Sandström, C; Roos, H; Henrikson, O; Leonhardt, H; Falkenberg, M

2016-11-01

Evaluation of orthogonal rings, fiducial markers, and overlay accuracy when image fusion is used for endovascular aortic repair (EVAR). This was a prospective single centre study. In 19 patients undergoing standard EVAR, 3D image fusion was used for intra-operative guidance. Renal arteries and targeted stent graft positions were marked with rings orthogonal to the respective centre lines from pre-operative computed tomography (CT). Radiopaque reference objects attached to the back of the patient were used as fiducial markers to detect patient movement intra-operatively. Automatic 3D-3D registration of the pre-operative CT with an intra-operative cone beam computed tomography (CBCT) as well as 3D-3D registration after manual alignment of nearby vertebrae were evaluated. Registration was defined as being sufficient for EVAR guidance if the deviation of the origin of the lower renal artery was less than 3 mm. For final overlay registration, the renal arteries were manually aligned using aortic calcification and vessel outlines. The accuracy of the overlay before stent graft deployment was evaluated using digital subtraction angiography (DSA) as direct comparison. Fiducial markers helped in detecting misalignment caused by patient movement during the procedure. Use of automatic intensity based registration alone was insufficient for EVAR guidance. Manual registration based on vertebrae L1-L2 was sufficient in 7/19 patients (37%). Using the final adjusted registration as overlay, the median alignment error of the lower renal artery marking at pre-deployment DSA was 2 mm (0-5) sideways and 2 mm (0-9) longitudinally, mostly in a caudal direction. 3D image fusion can facilitate intra-operative guidance during EVAR. Orthogonal rings and fiducial markers are useful for visualization and overlay correction. However, the accuracy of the overlaid 3D image is not always ideal and further technical development is needed. Copyright © 2016 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging

DTIC Science & Technology

2008-10-01

concentrated aqueous 99m Tc and taped to the exterior surface of the breast phantom to act as fiducial markers for registration purposes. Two...34 Physica Medica, vol. 21, pp. 48-55, 2006. [16] H. Erdogan and J. A. Fessler, "Ordered subsets algorithms for transmission tomography," Phys Med Biol

Precision instrument placement using a 4-DOF robot with integrated fiducials for minimally invasive interventions

NASA Astrophysics Data System (ADS)

Stenzel, Roland; Lin, Ralph; Cheng, Peng; Kronreif, Gernot; Kornfeld, Martin; Lindisch, David; Wood, Bradford J.; Viswanathan, Anand; Cleary, Kevin

2007-03-01

Minimally invasive procedures are increasingly attractive to patients and medical personnel because they can reduce operative trauma, recovery times, and overall costs. However, during these procedures, the physician has a very limited view of the interventional field and the exact position of surgical instruments. We present an image-guided platform for precision placement of surgical instruments based upon a small four degree-of-freedom robot (B-RobII; ARC Seibersdorf Research GmbH, Vienna, Austria). This platform includes a custom instrument guide with an integrated spiral fiducial pattern as the robot's end-effector, and it uses intra-operative computed tomography (CT) to register the robot to the patient directly before the intervention. The physician can then use a graphical user interface (GUI) to select a path for percutaneous access, and the robot will automatically align the instrument guide along this path. Potential anatomical targets include the liver, kidney, prostate, and spine. This paper describes the robotic platform, workflow, software, and algorithms used by the system. To demonstrate the algorithmic accuracy and suitability of the custom instrument guide, we also present results from experiments as well as estimates of the maximum error between target and instrument tip.

Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and fiducial point selection.

PubMed

Ferrer-Mileo, V; Guede-Fernandez, F; Fernandez-Chimeno, M; Ramos-Castro, J; Garcia-Gonzalez, M A

2015-08-01

This work compares several fiducial points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and fiducial point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.

The use of virtual fiducials in image-guided kidney surgery

NASA Astrophysics Data System (ADS)

Glisson, Courtenay; Ong, Rowena; Simpson, Amber; Clark, Peter; Herrell, S. D.; Galloway, Robert

2011-03-01

The alignment of image-space to physical-space lies at the heart of all image-guided procedures. In intracranial surgery, point-based registrations can be used with either skin-affixed or bone-implanted extrinsic objects called fiducial markers. The advantages of point-based registration techniques are that they are robust, fast, and have a well developed mathematical foundation for the assessment of registration quality. In abdominal image-guided procedures such techniques have not been successful. It is difficult to accurately locate sufficient homologous intrinsic points in imagespace and physical-space, and the implantation of extrinsic fiducial markers would constitute "surgery before the surgery." Image-space to physical-space registration for abdominal organs has therefore been dominated by surfacebased registration techniques which are iterative, prone to local minima, sensitive to initial pose, and sensitive to percentage coverage of the physical surface. In our work in image-guided kidney surgery we have developed a composite approach using "virtual fiducials." In an open kidney surgery, the perirenal fat is removed and the surface of the kidney is dotted using a surgical marker. A laser range scanner (LRS) is used to obtain a surface representation and matching high definition photograph. A surface to surface registration is performed using a modified iterative closest point (ICP) algorithm. The dots are extracted from the high definition image and assigned the three dimensional values from the LRS pixels over which they lie. As the surgery proceeds, we can then use point-based registrations to re-register the spaces and track deformations due to vascular clamping and surgical tractions.

Objective assessment of the aesthetic outcomes of breast cancer treatment: toward automatic localization of fiducial points on digital photographs

NASA Astrophysics Data System (ADS)

Udpa, Nitin; Sampat, Mehul P.; Kim, Min Soon; Reece, Gregory P.; Markey, Mia K.

2007-03-01

The contemporary goals of breast cancer treatment are not limited to cure but include maximizing quality of life. All breast cancer treatment can adversely affect breast appearance. Developing objective, quantifiable methods to assess breast appearance is important to understand the impact of deformity on patient quality of life, guide selection of current treatments, and make rational treatment advances. A few measures of aesthetic properties such as symmetry have been developed. They are computed from the distances between manually identified fiducial points on digital photographs. However, this is time-consuming and subject to intra- and inter-observer variability. The purpose of this study is to investigate methods for automatic localization of fiducial points on anterior-posterior digital photographs taken to document the outcomes of breast reconstruction. Particular emphasis is placed on automatic localization of the nipple complex since the most widely used aesthetic measure, the Breast Retraction Assessment, quantifies the symmetry of nipple locations. The nipple complexes are automatically localized using normalized cross-correlation with a template bank of variants of Gaussian and Laplacian of Gaussian filters. A probability map of likely nipple locations determined from the image database is used to reduce the number of false positive detections from the matched filter operation. The accuracy of the nipple detection was evaluated relative to markings made by three human observers. The impact of using the fiducial point locations as identified by the automatic method, as opposed to the manual method, on the calculation of the Breast Retraction Assessment was also evaluated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poels, Kenneth, E-mail: kenneth.poels@uzbrussel.be; Verellen, Dirk; Van de Vondel, Iwein

Purpose: Because frame rates on current clinical available electronic portal imaging devices (EPID’s) are limited to 7.5 Hz, a new commercially available PerkinElmer EPID (XRD 1642 AP19) with a maximum frame rate of 30 Hz and a new scintillator (Kyokko PI200) with improved sensitivity (light output) for megavolt (MV) irradiation was evaluated. In this work, the influence of MV pulse artifacts and pulsing artifact suppression techniques on fiducial marker and marker-less detection of a lung lesion was investigated, because target localization is an important component of uncertainty in geometrical verification of real-time tumor tracking. Methods: Visicoil™ markers with a diametermore » of 0.05 and 0.075 cm were used for MV marker tracking with a frame rate of, respectively, 7.5, 15, and 30 Hz. A 30 Hz readout of the detector was obtained by a 2 × 2 pixel binning, reducing spatial resolution. Static marker detection was conducted in function of increasing phantom thickness. Additionally, marker-less tracking was conducted and compared with the ground-truth fiducial marker motion. Performance of MV target detection was investigated by comparing the least-square sine wave fit of the detected marker positions with the predefined sine wave motion. For fiducial marker detection, a Laplacian-of-Gaussian enhancement was applied after which normalized cross correlation was used to find the most probable marker position. Marker-less detection was performed by using the scale and orientation adaptive mean shift tracking algorithm. For each MV fluoroscopy, a free running (FR-nF) (ignoring MV pulsing during readout) acquisition mode was compared with two acquisition modes intending to reduce MV pulsing artifacts, i.e., combined wavelet-FFT filtering (FR-wF) and electronic readout synchronized with respect to MV pulses. Results: A 0.05 cm Visicoil marker resulted in an unacceptable root-mean square error (RMSE) > 0.2 cm with a maximum frame rate of 30 Hz during FR-nF readout. With a 30 Hz synchronized readout (S-nF) and during 15 Hz readout (independent of readout mode), RMSE was submillimeter for a static 0.05 cm Visicoil. A dynamic 0.05 cm Visicoil was not detectable on the XRD 1642 AP19, despite a fast synchronized readout. For a 0.075 cm Visicoil, deviations of sine wave motion were submillimeter (RMSE < 0.08 cm), independent of the acquisition mode (FR, S). For marker-less tumor detection, FR-nF images resulted in RMSE > 0.3 cm, while for MV fluoroscopy in S-mode RMSE < 0.1 cm for 15 Hz and RMSE < 0.16 cm for 30 Hz. Largest consistency in target localization was experienced during 15 Hz S-nF readout. Conclusions: In general, marker contrast decreased in function of higher frame rates, which was detrimental for marker detection success. In this work, Visicoils with a thickness of 0.075 cm were showing best results for a 15 Hz frame rate, while non-MV compatible 0.05 cm Visicoil markers were not visible on the new EPID with improved sensitivity compared to EPID models based on a Kodak Lanex Fast scintillator. No noticeable influence of pulsing artifacts on the detection of a 0.075 cm Visicoil was observed, while a synchronized readout provided most reliable detection of a marker-less soft-tissue structure.« less

THE MURCHISON WIDEFIELD ARRAY 21 cm POWER SPECTRUM ANALYSIS METHODOLOGY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacobs, Daniel C.; Beardsley, A. P.; Bowman, Judd D.

2016-07-10

We present the 21 cm power spectrum analysis approach of the Murchison Widefield Array Epoch of Reionization project. In this paper, we compare the outputs of multiple pipelines for the purpose of validating statistical limits cosmological hydrogen at redshifts between 6 and 12. Multiple independent data calibration and reduction pipelines are used to make power spectrum limits on a fiducial night of data. Comparing the outputs of imaging and power spectrum stages highlights differences in calibration, foreground subtraction, and power spectrum calculation. The power spectra found using these different methods span a space defined by the various tradeoffs between speed,more » accuracy, and systematic control. Lessons learned from comparing the pipelines range from the algorithmic to the prosaically mundane; all demonstrate the many pitfalls of neglecting reproducibility. We briefly discuss the way these different methods attempt to handle the question of evaluating a significant detection in the presence of foregrounds.« less

Cone-Beam Computed Tomography Internal Motion Tracking Should Be Used to Validate 4-Dimensional Computed Tomography for Abdominal Radiation Therapy Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rankine, Leith; Wan, Hanlin; Parikh, Parag

Purpose: To demonstrate that fiducial tracking during pretreatment Cone-Beam CT (CBCT) can accurately measure tumor motion and that this method should be used to validate 4-dimensional CT (4DCT) margins before each treatment fraction. Methods and Materials: For 31 patients with abdominal tumors and implanted fiducial markers, tumor motion was measured daily with CBCT and fluoroscopy for 202 treatment fractions. Fiducial tracking and maximum-likelihood algorithms extracted 3-dimensional fiducial trajectories from CBCT projections. The daily internal margin (IM) (ie, range of fiducial motion) was calculated for CBCT and fluoroscopy as the 5th-95th percentiles of displacement in each cardinal direction. The planning IMmore » from simulation 4DCT (IM{sub 4DCT}) was considered adequate when within ±1.2 mm (anterior–posterior, left–right) and ±3 mm (superior–inferior) of the daily measured IM. We validated CBCT fiducial tracking as an accurate predictive measure of intrafraction motion by comparing the daily measured IM{sub CBCT} with the daily IM measured by pretreatment fluoroscopy (IM{sub pre-fluoro}); these were compared with pre- and posttreatment fluoroscopy (IM{sub fluoro}) to identify those patients who could benefit from imaging during treatment. Results: Four-dimensional CT could not accurately predict intrafractional tumor motion for ≥80% of fractions in 94% (IM{sub CBCT}), 97% (IM{sub pre-fluoro}), and 100% (IM{sub fluoro}) of patients. The IM{sub CBCT} was significantly closer to IM{sub pre-fluoro} than IM{sub 4DCT} (P<.01). For patients with median treatment time t < 7.5 minutes, IM{sub CBCT} was in agreement with IM{sub fluoro} for 93% of fractions (superior–inferior), compared with 63% for the t > 7.5 minutes group, demonstrating the need for patient-specific intratreatment imaging. Conclusions: Tumor motion determined from 4DCT simulation does not accurately predict the daily motion observed on CBCT or fluoroscopy. Cone-beam CT could replace fluoroscopy for pretreatment verification of simulation IM{sub 4DCT}, reducing patient setup time and imaging dose. Patients with treatment time t > 7.5 minutes could benefit from the addition of intratreatment imaging.« less

Optical CT imaging of solid radiochromic dosimeters in mismatched refractive index solutions using a scanning laser and large area detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dekker, Kurtis H., E-mail: kdekker2@uwo.ca

Purpose: The practical use of the PRESAGE® solid plastic dosimeter is limited by the inconvenience of immersing it in high-viscosity oils to achieve refractive index matching for optical computed tomography (CT) scanning. The oils are slow to mix and difficult to clean from surfaces, and the dosimeter rotation can generate dynamic Schlieren inhomogeneity patterns in the reference liquid, limiting the rotational and overall scan speed. Therefore, it would be beneficial if lower-viscosity, water-based solutions with slightly unmatched refractive index could be used instead. The purpose of this work is to demonstrate the feasibility of allowing mismatched conditions when using amore » scanning laser system with a large acceptance angle detector. A fiducial-based ray path measurement technique is combined with an iterative CT reconstruction algorithm to reconstruct images. Methods: A water based surrounding liquid with a low viscosity was selected for imaging PRESAGE® solid dosimeters. Liquid selection was optimized to achieve as high a refractive index as possible while avoiding rotation-induced Schlieren effects. This led to a refractive index mismatch of 6% between liquid and dosimeters. Optical CT scans were performed with a fan-beam scanning-laser optical CT system with a large area detector to capture most of the refracted rays. A fiducial marker placed on the wall of a cylindrical sample occludes a given light ray twice. With knowledge of the rotation angle and the radius of the cylindrical object, the actual internal path of each ray through the dosimeter can be calculated. Scans were performed with 1024 projections of 512 data samples each, and rays were rebinned to form 512 parallel-beam projections. Reconstructions were performed on a 512 × 512 grid using 100 iterations of the SIRT iterative CT algorithm. Proof of concept was demonstrated with a uniformly attenuating solution phantom. PRESAGE® dosimeters (11 cm diameter) were irradiated with Cobalt-60 irradiator to achieve either a uniform dose or a 2-level “step-dose” pattern. Results: With 6% refractive index mismatching, a circular field of view of 85% of the diameter of a cylindrical sample can be reconstructed accurately. Reconstructed images of the test solution phantom were uniform (within 3%) inside this radius. However, the dose responses of the PRESAGE® samples were not spatially uniform, with variations of at least 5% in sensitivity. The variation appears as a “cupping” artifact with less sensitivity in the middle than at the periphery of the PRESAGE® cylinder. Polarization effects were also detected for these samples. Conclusions: The fiducial-based ray path measurement scheme, coupled with an iterative reconstruction algorithm, enabled optical CT scanning of PRESAGE® dosimeters immersed in mismatched refractive index solutions. However, improvements to PRESAGE® dose response uniformity are required.« less

P wave detection in ECG signals using an extended Kalman filter: an evaluation in different arrhythmia contexts.

PubMed

Rahimpour, M; Mohammadzadeh Asl, B

2016-07-01

Monitoring atrial activity via P waves, is an important feature of the arrhythmia detection procedure. The aim of this paper is to present an algorithm for P wave detection in normal and some abnormal records by improving existing methods in the field of signal processing. In contrast to the classical approaches, which are completely blind to signal dynamics, our proposed method uses the extended Kalman filter, EKF25, to estimate the state variables of the equations modeling the dynamic of an ECG signal. This method is a modified version of the nonlinear dynamical model previously introduced for a generation of synthetic ECG signals and fiducial point extraction in normal ones. It is capable of estimating the separate types of activity of the heart with reasonable accuracy and performs well in the presence of morphological variations in the waveforms and ectopic beats. The MIT-BIH Arrhythmia and QT databases have been used to evaluate the performance of the proposed method. The results show that this method has Se  =  98.38% and Pr  =  96.74% in the overall records (considering normal and abnormal rhythms).

Prostate Brachytherapy Seed Reconstruction with Gaussian Blurring and Optimal Coverage Cost

PubMed Central

Lee, Junghoon; Liu, Xiaofeng; Jain, Ameet K.; Song, Danny Y.; Burdette, E. Clif; Prince, Jerry L.; Fichtinger, Gabor

2009-01-01

Intraoperative dosimetry in prostate brachytherapy requires localization of the implanted radioactive seeds. A tomosynthesis-based seed reconstruction method is proposed. A three-dimensional volume is reconstructed from Gaussian-blurred projection images and candidate seed locations are computed from the reconstructed volume. A false positive seed removal process, formulated as an optimal coverage problem, iteratively removes “ghost” seeds that are created by tomosynthesis reconstruction. In an effort to minimize pose errors that are common in conventional C-arms, initial pose parameter estimates are iteratively corrected by using the detected candidate seeds as fiducials, which automatically “focuses” the collected images and improves successive reconstructed volumes. Simulation results imply that the implanted seed locations can be estimated with a detection rate of ≥ 97.9% and ≥ 99.3% from three and four images, respectively, when the C-arm is calibrated and the pose of the C-arm is known. The algorithm was also validated on phantom data sets successfully localizing the implanted seeds from four or five images. In a Phase-1 clinical trial, we were able to localize the implanted seeds from five intraoperative fluoroscopy images with 98.8% (STD=1.6) overall detection rate. PMID:19605321

Evaluation of deformable image registration and a motion model in CT images with limited features.

PubMed

Liu, F; Hu, Y; Zhang, Q; Kincaid, R; Goodman, K A; Mageras, G S

2012-05-07

Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.

Detecting fiducials affected by trombone delay in ARC and the main laser alignment at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Awwal, Abdul A. S.; Bliss, Erlan S.; Miller Kamm, Victoria; Leach, Richard R.; Roberts, Randy; Rushford, Michael C.; Lowe-Webb, Roger; Wilhelmsen, Karl

2015-09-01

Four of the 192 beams of the National Ignition Facility (NIF) are currently being diverted into the Advanced Radiographic Capability (ARC) system to generate a sequence of short (1-50 picoseconds) 1053 nm laser pulses. When focused onto high Z wires in vacuum, these pulses create high energy x-ray pulses capable of penetrating the dense, imploding fusion fuel plasma during ignition scale experiments. The transmitted x-rays imaged with x-ray diagnostics can create movie radiographs that are expected to provide unprecedented insight into the implosion dynamics. The resulting images will serve as a diagnostic for tuning the experimental parameters towards successful fusion reactions. Beam delays introduced into the ARC pulses via independent, free-space optical trombones create the desired x-ray image sequence, or movie. However, these beam delays cause optical distortion of various alignment fiducials viewed by alignment sensors in the NIF and ARC beamlines. This work describes how the position of circular alignment fiducials is estimated in the presence of distortion.

Real-time automatic fiducial marker tracking in low contrast cine-MV images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Wei-Yang; Lin, Shu-Fang; Yang, Sheng-Chang

2013-01-15

Purpose: To develop a real-time automatic method for tracking implanted radiographic markers in low-contrast cine-MV patient images used in image-guided radiation therapy (IGRT). Methods: Intrafraction motion tracking using radiotherapy beam-line MV images have gained some attention recently in IGRT because no additional imaging dose is introduced. However, MV images have much lower contrast than kV images, therefore a robust and automatic algorithm for marker detection in MV images is a prerequisite. Previous marker detection methods are all based on template matching or its derivatives. Template matching needs to match object shape that changes significantly for different implantation and projection angle.more » While these methods require a large number of templates to cover various situations, they are often forced to use a smaller number of templates to reduce the computation load because their methods all require exhaustive search in the region of interest. The authors solve this problem by synergetic use of modern but well-tested computer vision and artificial intelligence techniques; specifically the authors detect implanted markers utilizing discriminant analysis for initialization and use mean-shift feature space analysis for sequential tracking. This novel approach avoids exhaustive search by exploiting the temporal correlation between consecutive frames and makes it possible to perform more sophisticated detection at the beginning to improve the accuracy, followed by ultrafast sequential tracking after the initialization. The method was evaluated and validated using 1149 cine-MV images from two prostate IGRT patients and compared with manual marker detection results from six researchers. The average of the manual detection results is considered as the ground truth for comparisons. Results: The average root-mean-square errors of our real-time automatic tracking method from the ground truth are 1.9 and 2.1 pixels for the two patients (0.26 mm/pixel). The standard deviations of the results from the 6 researchers are 2.3 and 2.6 pixels. The proposed framework takes about 128 ms to detect four markers in the first MV images and about 23 ms to track these markers in each of the subsequent images. Conclusions: The unified framework for tracking of multiple markers presented here can achieve marker detection accuracy similar to manual detection even in low-contrast cine-MV images. It can cope with shape deformations of fiducial markers at different gantry angles. The fast processing speed reduces the image processing portion of the system latency, therefore can improve the performance of real-time motion compensation.« less

Augmented kludge waveforms for detecting extreme-mass-ratio inspirals

NASA Astrophysics Data System (ADS)

Chua, Alvin J. K.; Moore, Christopher J.; Gair, Jonathan R.

2017-08-01

The extreme-mass-ratio inspirals (EMRIs) of stellar-mass compact objects into massive black holes are an important class of source for the future space-based gravitational-wave detector LISA. Detecting signals from EMRIs will require waveform models that are both accurate and computationally efficient. In this paper, we present the latest implementation of an augmented analytic kludge (AAK) model, publicly available at https://github.com/alvincjk/EMRI_Kludge_Suite as part of an EMRI waveform software suite. This version of the AAK model has improved accuracy compared to its predecessors, with two-month waveform overlaps against a more accurate fiducial model exceeding 0.97 for a generic range of sources; it also generates waveforms 5-15 times faster than the fiducial model. The AAK model is well suited for scoping out data analysis issues in the upcoming round of mock LISA data challenges. A simple analytic argument shows that it might even be viable for detecting EMRIs with LISA through a semicoherent template bank method, while the use of the original analytic kludge in the same approach will result in around 90% fewer detections.

SU-D-18A-07: Towards 6-Degree-Of-Freedom Real-Time Motion Management in Cancer Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, C.Y.; Keall, P; Nasehi Tehrani, J

2014-06-01

Purpose: Lung tumor motion has been identified as a major issue that deteriorates treatment efficacy for radiotherapy, especially for SBRT. As tighter PTV margins are applied due to translational compensation, tumor rotation will become the dominant factor limiting tumor targeting accuracy. This is the world-first study quantifies lung tumor rotation by utilizing kV images with fiducial markers and a step towards 6-degree-of-freedom real-time cancer radiotherapy. Methods: Three or four gold coils were implanted as tumor surrogates in 3 lung cancer patients. 50 fractions of 8- minute, 10 Hz 4D CBCT projections were acquired for the patients immediately prior or aftermore » radiotherapy. The fiducial marker positions are segmented, reconstructed and used to determine tumour rotation by the iterative closest point algorithm. Different data acceptance and filtering methods were applied to accept data or smooth the marker trajectory. Results: The average rotation angles around the left/ right (LR), superior/inferior (SI), anterior/posterior (AP) rotations were found to be 0.8±4.2, -0.8±4.5 and 1.7±3.1 degrees respectively. For 28% of the treatment time, the lung tumors rotated more than 5° around the SI axis. Respiration-induced rotational motion was detected in 2 of the 3 lung patients. This can be explained by the patient developed atelectasis during the treatment period. Interestingly, no heart beating component of rotation was observed in the power spectrum. Different rotational types were observed within the patient cohort with large variations in the magnitude of the rotation between patients. Conclusions: For the first time, continuous tumor rotation has been measured for lung patients with gold fiducial markers. Tumors were found to undergo rotations of more than 5° for almost a third of the total treatment time. The study also demonstrated the feasibility of using continuously kV images for real-time lung tumour motion adaptive radiotherapy which can potentially reduce treatment margins and side effects. The authors acknowledge the financial support of an NHMRC Australia Fellowship.« less

SU-G-JeP1-08: Dual Modality Verification for Respiratory Gating Using New Real- Time Tumor Tracking Radiotherapy System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shiinoki, T; Hanazawa, H; Shibuya, K

Purpose: The respirato ry gating system combined the TrueBeam and a new real-time tumor-tracking radiotherapy system (RTRT) was installed. The RTRT system consists of two x-ray tubes and color image intensifiers. Using fluoroscopic images, the fiducial marker which was implanted near the tumor was tracked and was used as the internal surrogate for respiratory gating. The purposes of this study was to develop the verification technique of the respiratory gating with the new RTRT using cine electronic portal image device images (EPIDs) of TrueBeam and log files of the RTRT. Methods: A patient who underwent respiratory gated SBRT of themore » lung using the RTRT were enrolled in this study. For a patient, the log files of three-dimensional coordinate of fiducial marker used as an internal surrogate were acquired using the RTRT. Simultaneously, the cine EPIDs were acquired during respiratory gated radiotherapy. The data acquisition was performed for one field at five sessions during the course of SBRT. The residual motion errors were calculated using the log files (E{sub log}). The fiducial marker used as an internal surrogate into the cine EPIDs was automatically extracted by in-house software based on the template-matching algorithm. The differences between the the marker positions of cine EPIDs and digitally reconstructed radiograph were calculated (E{sub EPID}). Results: Marker detection on EPID using in-house software was influenced by low image contrast. For one field during the course of SBRT, the respiratory gating using the RTRT showed the mean ± S.D. of 95{sup th} percentile E{sub EPID} were 1.3 ± 0.3 mm,1.1 ± 0.5 mm,and those of E{sub log} were 1.5 ± 0.2 mm, 1.1 ± 0.2 mm in LR and SI directions, respectively. Conclusion: We have developed the verification method of respiratory gating combined TrueBeam and new real-time tumor-tracking radiotherapy system using EPIDs and log files.« less

Correction of rotational distortion for catheter-based en face OCT and OCT angiography

PubMed Central

Ahsen, Osman O.; Lee, Hsiang-Chieh; Giacomelli, Michael G.; Wang, Zhao; Liang, Kaicheng; Tsai, Tsung-Han; Potsaid, Benjamin; Mashimo, Hiroshi; Fujimoto, James G.

2015-01-01

We demonstrate a computationally efficient method for correcting the nonuniform rotational distortion (NURD) in catheter-based imaging systems to improve endoscopic en face optical coherence tomography (OCT) and OCT angiography. The method performs nonrigid registration using fiducial markers on the catheter to correct rotational speed variations. Algorithm performance is investigated with an ultrahigh-speed endoscopic OCT system and micromotor catheter. Scan nonuniformity is quantitatively characterized, and artifacts from rotational speed variations are significantly reduced. Furthermore, we present endoscopic en face OCT and OCT angiography images of human gastrointestinal tract in vivo to demonstrate the image quality improvement using the correction algorithm. PMID:25361133

Line fiducial material and thickness considerations for ultrasound calibration

NASA Astrophysics Data System (ADS)

Ameri, Golafsoun; McLeod, A. J.; Baxter, John S. H.; Chen, Elvis C. S.; Peters, Terry M.

2015-03-01

Ultrasound calibration is a necessary procedure in many image-guided interventions, relating the position of tools and anatomical structures in the ultrasound image to a common coordinate system. This is a necessary component of augmented reality environments in image-guided interventions as it allows for a 3D visualization where other surgical tools outside the imaging plane can be found. Accuracy of ultrasound calibration fundamentally affects the total accuracy of this interventional guidance system. Many ultrasound calibration procedures have been proposed based on a variety of phantom materials and geometries. These differences lead to differences in representation of the phantom on the ultrasound image which subsequently affect the ability to accurately and automatically segment the phantom. For example, taut wires are commonly used as line fiducials in ultrasound calibration. However, at large depths or oblique angles, the fiducials appear blurred and smeared in ultrasound images making it hard to localize their cross-section with the ultrasound image plane. Intuitively, larger diameter phantoms with lower echogenicity are more accurately segmented in ultrasound images in comparison to highly reflective thin phantoms. In this work, an evaluation of a variety of calibration phantoms with different geometrical and material properties for the phantomless calibration procedure was performed. The phantoms used in this study include braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. Conventional B-mode and synthetic aperture images of the phantoms at different positions were obtained. The phantoms were automatically segmented from the ultrasound images using an ellipse fitting algorithm, the centroid of which is subsequently used as a fiducial for calibration. Calibration accuracy was evaluated for these procedures based on the leave-one-out target registration error. It was shown that larger diameter phantoms with lower echogenicity are more accurately segmented in comparison to highly reflective thin phantoms. This improvement in segmentation accuracy leads to a lower fiducial localization error, which ultimately results in low target registration error. This would have a profound effect on calibration procedures and the feasibility of different calibration procedures in the context of image-guided procedures.

SU-E-J-37: Feasibility of Utilizing Carbon Fiducials to Increase Localization Accuracy of Lumpectomy Cavity for Partial Breast Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Y; Hieken, T; Mutter, R

2015-06-15

Purpose To investigate the feasibility of utilizing carbon fiducials to increase localization accuracy of lumpectomy cavity for partial breast irradiation (PBI). Methods Carbon fiducials were placed intraoperatively in the lumpectomy cavity following resection of breast cancer in 11 patients. The patients were scheduled to receive whole breast irradiation (WBI) with a boost or 3D-conformal PBI. WBI patients were initially setup to skin tattoos using lasers, followed by orthogonal kV on-board-imaging (OBI) matching to bone per clinical practice. Cone beam CT (CBCT) was acquired weekly for offline review. For the boost component of WBI and PBI, patients were setup with lasers,more » followed by OBI matching to fiducials, with final alignment by CBCT matching to fiducials. Using carbon fiducials as a surrogate for the lumpectomy cavity and CBCT matching to fiducials as the gold standard, setup uncertainties to lasers, OBI bone, OBI fiducials, and CBCT breast were compared. Results Minimal imaging artifacts were introduced by fiducials on the planning CT and CBCT. The fiducials were sufficiently visible on OBI for online localization. The mean magnitude and standard deviation of setup errors were 8.4mm ± 5.3 mm (n=84), 7.3mm ± 3.7mm (n=87), 2.2mm ± 1.6mm (n=40) and 4.8mm ± 2.6mm (n=87), for lasers, OBI bone, OBI fiducials and CBCT breast tissue, respectively. Significant migration occurred in one of 39 implanted fiducials in a patient with a large postoperative seroma. Conclusion OBI carbon fiducial-based setup can improve localization accuracy with minimal imaging artifacts. With increased localization accuracy, setup uncertainties can be reduced from 8mm using OBI bone matching to 3mm using OBI fiducial matching for PBI treatment. This work demonstrates the feasibility of utilizing carbon fiducials to increase localization accuracy to the lumpectomy cavity for PBI. This may be particularly attractive for localization in the setting of proton therapy and other scenarios in which metal clips are contraindicated.« less

WE-AB-303-05: Breathing Motion of Liver Segments From Fiducial Tracking During Robotic Radiosurgery and Comparison with 4D-CT-Derived Fiducial Motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sutherland, J; Pantarotto, J; Nair, V

Purpose: To quantify respiratory-induced motion of liver segments using the positions of implanted fiducials during robotic radiosurgery. This study also compared fiducial motion derived from four-dimensional computed tomography (4D-CT) maximum intensity projections (MIP) with motion derived from imaging during treatment. Methods: Forty-two consecutive liver patients treated with liver ablative radiotherapy were accrued to an ethics approved retrospective study. The liver segment in which each fiducial resided was identified. Fiducial positions throughout each treatment fraction were determined using orthogonal kilovoltage images. Any data due to patient repositioning or motion was removed. Mean fiducial positions were calculated. Fiducial positions beyond two standardmore » deviations of the mean were discarded and remaining positions were fit to a line segment using least squares minimization (LSM). For eight patients, fiducial motion was derived from 4D-CT MIPs by calculating the CT number weighted mean position of the fiducial on each slice and fitting a line segment to these points using LSM. Treatment derived fiducial trajectories were corrected for patient rotation and compared to MIP derived trajectories. Results: The mean total magnitude of fiducial motion across all liver segments in left-right, anteroposterior, and superoinferior (SI) directions were 3.0 ± 0.2 mm, 9.3 ± 0.4 mm, and 20.5 ± 0.5 mm, respectively. Differences in per-segment mean fiducial motion were found with SI motion ranging from 12.6 ± 0.8 mm to 22.6 ± 0.9 mm for segments 3 and 8, respectively. Large, varied differences between treatment and MIP derived motion at simulation were found with the mean difference for SI motion being 2.6 mm (10.8 mm standard deviation). Conclusion: The magnitude of liver fiducial motion was found to differ by liver segment. MIP derived liver fiducial motion differed from motion observed during treatment, implying that 4D-CTs may not accurately capture the range of liver motion across fractions and during treatment. Author V. Nair was funded by the Cushing estate for a SABR clinical research fellowship.« less

Visibility of fiducial markers used for image-guided radiation therapy on optical coherence tomography for registration with CT: An esophageal phantom study.

PubMed

Jelvehgaran, Pouya; Alderliesten, Tanja; Weda, Jelmer J A; de Bruin, Martijn; Faber, Dirk J; Hulshof, Maarten C C M; van Leeuwen, Ton G; van Herk, Marcel; de Boer, Johannes F

2017-12-01

Optical coherence tomography (OCT) is of interest to visualize microscopic esophageal tumor extensions to improve tumor delineation for radiation therapy (RT) planning. Fiducial marker placement is a common method to ensure target localization during planning and treatment. Visualization of these fiducial markers on OCT permits integrating OCT and computed tomography (CT) images used for RT planning via image registration. We studied the visibility of 13 (eight types) commercially available solid and liquid fiducial markers in OCT images at different depths using dedicated esophageal phantoms and evaluated marker placement depth in clinical practice. We designed and fabricated dedicated esophageal phantoms, in which three layers mimic the anatomical wall structures of a healthy human esophagus. We successfully implanted 13 commercially available fiducial markers that varied in diameter and material property at depths between 0.5 and 3.0 mm. The resulting esophageal phantoms were imaged with OCT, and marker visibility was assessed qualitatively and quantitatively using the contrast-to-background-noise ratio (CNR). The CNR was defined as the difference between the mean intensity of the fiducial markers and the mean intensity of the background divided by the standard deviation of the background intensity. To determine whether, in current clinical practice, the implanted fiducial markers are within the OCT visualization range (up to 3.0 mm depth), we retrospectively measured the distance of 19 fiducial markers to the esophageal lumen on CT scans of 16 esophageal cancer patients. In the esophageal phantoms, all the included fiducial markers were visible on OCT at all investigated depths. Solid fiducial markers were better visible on OCT than liquid fiducial markers with a 1.74-fold higher CNR. Although fiducial marker identification per type and size was slightly easier for superficially implanted fiducial markers, we observed no difference in the ability of OCT to visualize the markers over the investigated depth range. Retrospective distance measurements of 19 fiducial markers on the CT scan of esophageal cancer patients showed that 84% (distance from the closest border of the marker to the lumen) and 53% (distance from the center of the marker to the lumen) of the fiducial markers were located within the OCT visualization range of up to 3.0 mm. We studied the visibility of eight types of commercially available fiducial markers at different depths on OCT using dedicated esophageal phantoms. All tested fiducial markers were visible at depths ≤3.0 mm and most, but not all, clinically implanted markers were at a depth accessible to OCT. Consequently, the use of fiducial markers as a reference for OCT to CT registration is feasible. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Experimental Validation of Advanced Dispersed Fringe Sensing (ADFS) Algorithm Using Advanced Wavefront Sensing and Correction Testbed (AWCT)

NASA Technical Reports Server (NTRS)

Wang, Xu; Shi, Fang; Sigrist, Norbert; Seo, Byoung-Joon; Tang, Hong; Bikkannavar, Siddarayappa; Basinger, Scott; Lay, Oliver

2012-01-01

Large aperture telescope commonly features segment mirrors and a coarse phasing step is needed to bring these individual segments into the fine phasing capture range. Dispersed Fringe Sensing (DFS) is a powerful coarse phasing technique and its alteration is currently being used for JWST.An Advanced Dispersed Fringe Sensing (ADFS) algorithm is recently developed to improve the performance and robustness of previous DFS algorithms with better accuracy and unique solution. The first part of the paper introduces the basic ideas and the essential features of the ADFS algorithm and presents the some algorithm sensitivity study results. The second part of the paper describes the full details of algorithm validation process through the advanced wavefront sensing and correction testbed (AWCT): first, the optimization of the DFS hardware of AWCT to ensure the data accuracy and reliability is illustrated. Then, a few carefully designed algorithm validation experiments are implemented, and the corresponding data analysis results are shown. Finally the fiducial calibration using Range-Gate-Metrology technique is carried out and a <10nm or <1% algorithm accuracy is demonstrated.

Incorporation of a laser range scanner into image-guided liver surgery: surface acquisition, registration, and tracking.

PubMed

Cash, David M; Sinha, Tuhin K; Chapman, William C; Terawaki, Hiromi; Dawant, Benoit M; Galloway, Robert L; Miga, Michael I

2003-07-01

As image guided surgical procedures become increasingly diverse, there will be more scenarios where point-based fiducials cannot be accurately localized for registration and rigid body assumptions no longer hold. As a result, procedures will rely more frequently on anatomical surfaces for the basis of image alignment and will require intraoperative geometric data to measure and compensate for tissue deformation in the organ. In this paper we outline methods for which a laser range scanner may be used to accomplish these tasks intraoperatively. A laser range scanner based on the optical principle of triangulation acquires a dense set of three-dimensional point data in a very rapid, noncontact fashion. Phantom studies were performed to test the ability to link range scan data with traditional modes of image-guided surgery data through localization, registration, and tracking in physical space. The experiments demonstrate that the scanner is capable of localizing point-based fiducials to within 0.2 mm and capable of achieving point and surface based registrations with target registration error of less than 2.0 mm. Tracking points in physical space with the range scanning system yields an error of 1.4 +/- 0.8 mm. Surface deformation studies were performed with the range scanner in order to determine if this device was capable of acquiring enough information for compensation algorithms. In the surface deformation studies, the range scanner was able to detect changes in surface shape due to deformation comparable to those detected by tomographic image studies. Use of the range scanner has been approved for clinical trials, and an initial intraoperative range scan experiment is presented. In all of these studies, the primary source of error in range scan data is deterministically related to the position and orientation of the surface within the scanner's field of view. However, this systematic error can be corrected, allowing the range scanner to provide a rapid, robust method of acquiring anatomical surfaces intraoperatively.

SU-E-J-133: Evaluation of Inter- and Intra-Fractional Pancreas Tumor Residual Motions with Abdominal Compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Y; Shi, F; Tian, Z

2014-06-01

Purpose: Abdominal compression (AC) has been widely used to reduce pancreas motion due to respiration for pancreatic cancer patients undergoing stereotactic body radiotherapy (SBRT). However, the inter-fractional and intra-fractional patient motions may degrade the treatment. The purpose of this work is to study daily CBCT projections and 4DCT to evaluate the inter-fractional and intra-fractional pancreatic motions. Methods: As a standard of care at our institution, 4D CT scan was performed for treatment planning. At least two CBCT scans were performed for daily treatment. Retrospective studies were performed on patients with implanted internal fiducial markers or surgical clips. The initial motionmore » pattern was obtained by extracting marker positions on every phase of 4D CT images. Daily motions were presented by marker positions on CBCT scan projection images. An adaptive threshold segmentation algorithm was used to extract maker positions. Both marker average positions and motion ranges were compared among three sets of scans, 4D CT, positioning CBCT, and conformal CBCT, for inter-fractional and intra-fractional motion variations. Results: Data from four pancreatic cancer patients were analyzed. These patients had three fiducial markers implanted. All patients were treated by an Elekta Synergy with single fraction SBRT. CBCT projections were acquired by XVI. Markers were successfully detected on most of the projection images. The inter-fractional changes were determined by 4D CT and the first CBCT while the intra-fractional changes were determined by multiple CBCT scans. It is found that the average motion range variations are within 2 mm, however, the average marker positions may drift by 6.5 mm. Conclusion: The patients respiratory motion variation for pancreas SBRT with AC was evaluated by detecting markers from CBCT projections and 4DCT, both the inter-fraction and intra-fraction motion range change is small but the drift of marker positions may be comparable to motion ranges.« less

A real-time approach for heart rate monitoring using a Hilbert transform in seismocardiograms.

PubMed

Jafari Tadi, Mojtaba; Lehtonen, Eero; Hurnanen, Tero; Koskinen, Juho; Eriksson, Jonas; Pänkäälä, Mikko; Teräs, Mika; Koivisto, Tero

2016-11-01

Heart rate monitoring helps in assessing the functionality and condition of the cardiovascular system. We present a new real-time applicable approach for estimating beat-to-beat time intervals and heart rate in seismocardiograms acquired from a tri-axial microelectromechanical accelerometer. Seismocardiography (SCG) is a non-invasive method for heart monitoring which measures the mechanical activity of the heart. Measuring true beat-to-beat time intervals from SCG could be used for monitoring of the heart rhythm, for heart rate variability analysis and for many other clinical applications. In this paper we present the Hilbert adaptive beat identification technique for the detection of heartbeat timings and inter-beat time intervals in SCG from healthy volunteers in three different positions, i.e. supine, left and right recumbent. Our method is electrocardiogram (ECG) independent, as it does not require any ECG fiducial points to estimate the beat-to-beat intervals. The performance of the algorithm was tested against standard ECG measurements. The average true positive rate, positive prediction value and detection error rate for the different positions were, respectively, supine (95.8%, 96.0% and ≃0.6%), left (99.3%, 98.8% and ≃0.001%) and right (99.53%, 99.3% and ≃0.01%). High correlation and agreement was observed between SCG and ECG inter-beat intervals (r  >  0.99) for all positions, which highlights the capability of the algorithm for SCG heart monitoring from different positions. Additionally, we demonstrate the applicability of the proposed method in smartphone based SCG. In conclusion, the proposed algorithm can be used for real-time continuous unobtrusive cardiac monitoring, smartphone cardiography, and in wearable devices aimed at health and well-being applications.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing

PubMed Central

2011-01-01

Background Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. Methods This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. Results The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. Conclusions The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra. PMID:21457580

A wavelet-based ECG delineation algorithm for 32-bit integer online processing.

PubMed

Di Marco, Luigi Y; Chiari, Lorenzo

2011-04-03

Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.

Fiducial and differential cross sections of Higgs boson production measured in the four-lepton decay channel in pp collisions at √{ s} = 8 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; Abouzeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baas, A. E.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batley, J. R.; Battaglia, M.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertsche, C.; Bertsche, D.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilbao de Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boddy, C. R.; Boehler, M.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozic, I.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, J.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camarda, S.; Cameron, D.; Caminada, L. M.; Caminal Armadans, R.; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caudron, J.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B. C.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J. A.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; de, K.; de Asmundis, R.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Nooij, L.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Domenico, A.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Mattia, A.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Do Valle Wemans, A.; Dobos, D.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Fernandez Perez, S.; Ferrag, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Florez Bustos, A. C.; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Franz, S.; Fraternali, M.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y. S.; Garay Walls, F. M.; Garberson, F.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gianotti, F.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Glonti, G. L.; Goblirsch-Kolb, M.; Goddard, J. R.; Godlewski, J.; Goeringer, C.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gomez Fajardo, L. S.; Gonçalo, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, L.; González de La Hoz, S.; Gonzalez Parra, G.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Gozpinar, S.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Grebenyuk, O. G.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grishkevich, Y. V.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Groth-Jensen, J.; Grout, Z. J.; Guan, L.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Guicheney, C.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Gupta, S.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Haefner, P.; Hageböck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Hall, D.; Halladjian, G.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamer, M.; Hamilton, A.; Hamilton, S.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harper, D.; Harrington, R. D.; Harris, O. M.; Harrison, P. F.; Hartjes, F.; Hasegawa, M.; Hasegawa, S.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hawkins, A. D.; Hayashi, T.; Hayden, D.; Hays, C. P.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, L.; Hejbal, J.; Helary, L.; Heller, C.; Heller, M.; Hellman, S.; Hellmich, D.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Hengler, C.; Henrichs, A.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Hernández Jiménez, Y.; Herrberg-Schubert, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hoffman, J.; Hoffmann, D.; Hohlfeld, M.; Holmes, T. R.; Hong, T. M.; Hooft van Huysduynen, L.; Hopkins, W. H.; Horii, Y.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Hurwitz, M.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikematsu, K.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Inamaru, Y.; Ince, T.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Irles Quiles, A.; Isaksson, C.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Iturbe Ponce, J. M.; Iuppa, R.; Ivarsson, J.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, M.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jakubek, J.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansen, H.; Janssen, J.; Janus, M.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Jeanty, L.; Jejelava, J.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, Y.; Jimenez Belenguer, M.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Joergensen, M. D.; Johansson, K. E.; Johansson, P.; Johns, K. A.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Joshi, K. D.; Jovicevic, J.; Ju, X.; Jung, C. A.; Jungst, R. M.; Jussel, P.; Juste Rozas, A.; Kaci, M.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kajomovitz, E.; Kalderon, C. W.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneda, M.; Kaneti, S.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kashif, L.; Kasieczka, G.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Katre, A.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazama, S.; Kazanin, V. F.; Kazarinov, M. Y.; Keeler, R.; Kehoe, R.; Keil, M.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Kessoku, K.; Keung, J.; Khalil-Zada, F.; Khandanyan, H.; Khanov, A.; Khodinov, A.; Khomich, A.; Khoo, T. J.; Khoriauli, G.; Khoroshilov, A.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kim, H. Y.; Kim, H.; Kim, S. H.; Kimura, N.; Kind, O.; King, B. T.; King, M.; King, R. S. B.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kittelmann, T.; Kiuchi, K.; Kladiva, E.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klioutchnikova, T.; Klok, P. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koevesarki, P.; Koffas, T.; Koffeman, E.; Kogan, L. A.; Kohlmann, S.; Kohout, Z.; Kohriki, T.; Koi, T.; Kolanoski, H.; Koletsou, I.; Koll, J.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; König, S.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Korotkov, V. A.; Kortner, O.; Kortner, S.; Kostyukhin, V. V.; Kotov, V. M.; Kotwal, A.; Kourkoumelis, C.; Kouskoura, V.; Koutsman, A.; Kowalewski, R.; Kowalski, T. Z.; Kozanecki, W.; Kozhin, A. S.; Kral, V.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasznahorkay, A.; Kraus, J. K.; Kravchenko, A.; Kreiss, S.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Kruker, T.; Krumnack, N.; Krumshteyn, Z. V.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuehn, S.; Kugel, A.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunkle, J.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kurumida, R.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; La Rosa, A.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Laier, H.; Lambourne, L.; Lammers, S.; Lampen, C. L.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lang, V. S.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Le Dortz, O.; Le Guirriec, E.; Le Menedeu, E.; Lecompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, H.; Lee, J. S. H.; Lee, S. C.; Lee, L.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmacher, M.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leisos, A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzen, G.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Leontsinis, S.; Leroy, C.; Lester, C. G.; Lester, C. M.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, A.; Lewis, G. H.; Leyko, A. M.; Leyton, M.; Li, B.; Li, B.; Li, H.; Li, H. L.; Li, L.; Li, L.; Li, S.; Li, Y.; Liang, Z.; Liao, H.; Liberti, B.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limbach, C.; Limosani, A.; Lin, S. C.; Lin, T. H.; Linde, F.; Lindquist, B. E.; Linnemann, J. T.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lissauer, D.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y.; Livan, M.; Livermore, S. S. A.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loddenkoetter, T.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Lombardo, V. P.; Long, B. A.; Long, J. D.; Long, R. E.; Lopes, L.; Lopez Mateos, D.; Lopez Paredes, B.; Lopez Paz, I.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Loscutoff, P.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lowe, A. J.; Lu, F.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lungwitz, M.; Lynn, D.; Lysak, R.; Lytken, E.; Ma, H.; Ma, L. L.; Maccarrone, G.; Macchiolo, A.; Machado Miguens, J.; Macina, D.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeno, M.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahboubi, K.; Mahlstedt, J.; Mahmoud, S.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Mal, P.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyshev, V. M.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, B.; Mandelli, L.; Mandić, I.; Mandrysch, R.; Maneira, J.; Manfredini, A.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J. A.; Mann, A.; Manning, P. M.; Manousakis-Katsikakis, A.; Mansoulie, B.; Mantifel, R.; Mapelli, L.; March, L.; Marchand, J. F.; Marchiori, G.; Marcisovsky, M.; Marino, C. P.; Marjanovic, M.; Marques, C. N.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti, L. F.; Marti-Garcia, S.; Martin, B.; Martin, B.; Martin, T. A.; Martin, V. J.; Martin Dit Latour, B.; Martinez, H.; Martinez, M.; Martin-Haugh, S.; Martyniuk, A. C.; Marx, M.; Marzano, F.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Massol, N.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazzaferro, L.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McCubbin, N. A.; McFarlane, K. W.; McFayden, J. A.; McHedlidze, G.; McMahon, S. J.; McPherson, R. A.; Mechnich, J.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melachrinos, C.; Mellado Garcia, B. R.; Meloni, F.; Mengarelli, A.; Menke, S.; Meoni, E.; Mercurio, K. M.; Mergelmeyer, S.; Meric, N.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Merritt, H.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Middleton, R. P.; Migas, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Milstein, D.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mirabelli, G.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Mitsui, S.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Mochizuki, K.; Mohapatra, S.; Mohr, W.; Molander, S.; Moles-Valls, R.; Mönig, K.; Monini, C.; Monk, J.; Monnier, E.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, M.; Morii, M.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, K.; Mueller, T.; Mueller, T.; Muenstermann, D.; Munwes, Y.; Murillo Quijada, J. A.; Murray, W. J.; Musheghyan, H.; Musto, E.; Myagkov, A. G.; Myska, M.; Nackenhorst, O.; Nadal, J.; Nagai, K.; Nagai, R.; Nagai, Y.; Nagano, K.; Nagarkar, A.; Nagasaka, Y.; Nagel, M.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Nanava, G.; Narayan, R.; Nattermann, T.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Nef, P. D.; Negri, A.; Negri, G.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nickerson, R. B.; Nicolaidou, R.; Nicquevert, B.; Nielsen, J.; Nikiforou, N.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Norberg, S.; Nordberg, M.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nunes Hanninger, G.; Nunnemann, T.; Nurse, E.; Nuti, F.; O'Brien, B. J.; O'Grady, F.; O'Neil, D. C.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, M. I.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Okamura, W.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Olchevski, A. G.; Olivares Pino, S. A.; Oliveira Damazio, D.; Oliver Garcia, E.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Oropeza Barrera, C.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ouellette, E. A.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Ovcharova, A.; Owen, M.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paganis, E.; Pahl, C.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Palka, M.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Panduro Vazquez, J. G.; Pani, P.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pasqualucci, E.; Passaggio, S.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N. D.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pearce, J.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Peng, H.; Penning, B.; Penwell, J.; Perepelitsa, D. V.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Perini, L.; Pernegger, H.; Perrella, S.; Perrino, R.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Pettersson, N. E.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Piegaia, R.; Pignotti, D. T.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Pingel, A.; Pinto, B.; Pires, S.; Pitt, M.; Pizio, C.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poddar, S.; Podlyski, F.; Poettgen, R.; Poggioli, L.; Pohl, D.; Pohl, M.; Polesello, G.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Portell Bueso, X.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pralavorio, P.; Pranko, A.; Prasad, S.; Pravahan, R.; Prell, S.; Price, D.; Price, J.; Price, L. E.; Prieur, D.; Primavera, M.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopapadaki, E.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Przysiezniak, H.; Ptacek, E.; Puddu, D.; Pueschel, E.; Puldon, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Qureshi, A.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Rajagopalan, S.; Rammensee, M.; Randle-Conde, A. S.; Rangel-Smith, C.; Rao, K.; Rauscher, F.; Rave, T. C.; Ravenscroft, T.; Raymond, M.; Read, A. L.; Readioff, N. P.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reisin, H.; Relich, M.; Rembser, C.; Ren, H.; Ren, Z. L.; Renaud, A.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Ridel, M.; Rieck, P.; Rieger, J.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodrigues, L.; Roe, S.; Røhne, O.; Rolli, S.; Romaniouk, A.; Romano, M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, M.; Rose, P.; Rosendahl, P. L.; Rosenthal, O.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rubinskiy, I.; Rud, V. I.; Rudolph, C.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Saddique, A.; Sadeh, I.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Saleem, M.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sartisohn, G.; Sasaki, O.; Sasaki, Y.; Sauvage, G.; Sauvan, E.; Savard, P.; Savu, D. O.; Sawyer, C.; Sawyer, L.; Saxon, D. H.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schaefer, R.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schneider, B.; Schnellbach, Y. J.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schorlemmer, A. L. S.; Schott, M.; Schouten, D.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schroeder, C.; Schuh, N.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Schwoerer, M.; Sciacca, F. G.; Scifo, E.; Sciolla, G.; Scott, W. G.; Scuri, F.; Scutti, F.; Searcy, J.; Sedov, G.; Sedykh, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekula, S. J.; Selbach, K. E.; Seliverstov, D. M.; Sellers, G.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Serre, T.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Shushkevich, S.; Sicho, P.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simoniello, R.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skottowe, H. P.; Skovpen, K. Yu.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopczak, A.; Sopko, B.; Sopko, V.; Sorin, V.; Sosebee, M.; Soualah, R.; Soueid, P.; Soukharev, A. M.; South, D.; Spagnolo, S.; Spanò, F.; Spearman, W. R.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Stavina, P.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Swedish, S.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tannenwald, B. B.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Topilin, N. D.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Tran, H. L.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turk Cakir, I.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urbaniec, D.; Urquijo, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van der Leeuw, R.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Virzi, J.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weigell, P.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilkens, H. G.; Will, J. Z.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winter, B. T.; Wittgen, M.; Wittig, T.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wright, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xiao, M.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamada, M.; Yamaguchi, H.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yanush, S.; Yao, L.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yurkewicz, A.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zevi Della Porta, G.; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, X.; Zhang, Z.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, L.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.; Atlas Collaboration

2014-11-01

Measurements of fiducial and differential cross sections of Higgs boson production in the H → ZZ* → 4 ℓ decay channel are presented. The cross sections are determined within a fiducial phase space and corrected for detection efficiency and resolution effects. They are based on 20.3 fb-1 of pp collision data, produced at √{ s} = 8 TeV centre-of-mass energy at the LHC and recorded by the ATLAS detector. The differential measurements are performed in bins of transverse momentum and rapidity of the four-lepton system, the invariant mass of the subleading lepton pair and the decay angle of the leading lepton pair with respect to the beam line in the four-lepton rest frame, as well as the number of jets and the transverse momentum of the leading jet. The measured cross sections are compared to selected theoretical calculations of the Standard Model expectations. No significant deviation from any of the tested predictions is found.

SU-E-T-27: A Dosimetric Evaluation of Boney Anatomy Versus Fiducial Marker Alignment for the Treatment of Prostate Cancer Using Scanned Beam Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freund, D; Ding, X; Zhang, J

Purpose: In prostate proton radiotherapy, three fiducial markers are used for patient daily alignment. However fiducial alignment can change beamline heterogeneity in proton therapy. The purpose of this study is to determine the difference in fiducial and boney anatomy alignment for patient treatment. Methods and materials: Prostate cancer patients who received proton treatment were included in this study. 3 fiducial markers were implanted before the initial CT. All the patients were re-CT’d every 2 weeks to check the fiducial marker position reproducibility as well as dosimetric consistence of target coverage. In geometry study, re-CT were fused to the initial CTmore » base on the boney anatomy and the average fiducial marker displacement was measured the centers of the fiducials. Dosimetrically, the initial plan was recalculated directly to re-CT image set based on the boney alignment and fiducial alignment to determine the difference from daily treatment. Prostate coverage and hotspots were evaluated using the dose to 98% of the CTV (D98) and dose to 2% (D2), respectively. Results: The shift from the initial 6 patient CT image sets resulted in an average change in the fiducial location of 5.70 +/− 3 mm. Dosimetric comparison from a single patient revealed that differences from the planned dose resulted from both boney and fiducial alignment. Planned clinical treatment volume coverage resulted in a D98 of 70.44Gy and D2 of 70.84Gy compared to a D98 of 70.13Gy and D2 70.94Gy for boney alignment and a D98 of 70.08Gy and D2 71.18Gy for fiducial alignment respectively. Conclusion: This study demonstrates that with boney anatomy alignment there is little change to CTV coverage and only slightly worse CTV coverage and hotspot production with fiducial alignment. An increase patient cohort and further investigation is necessary to determine the whether boney alignment can help better control dose heterogeneity.« less

Reactor antineutrino detector iDREAM.

NASA Astrophysics Data System (ADS)

Gromov, M. B.; Lukyanchenko, G. A.; Novikova, G. J.; Obinyakov, B. A.; Oralbaev, A. Y.; Skorokhvatov, M. D.; Sukhotin, S. V.; Chepurnov, A. S.; Etenko, A. V.

2017-09-01

Industrial Detector for Reactor Antineutrino Monitoring (iDREAM) is a compact (≈ 3.5m 2) industrial electron antineutrino spectrometer. It is dedicated for remote monitoring of PWR reactor operational modes by neutrino method in real-time. Measurements of antineutrino flux from PWR allow to estimate a fuel mixture in active zone and to check the status of the reactor campaign for non-proliferation purposes. LAB-based gadolinium doped scintillator is exploited as a target. Multizone architecture of the detector with gamma-catcher surrounding fiducial volume and plastic muon veto above and below ensure high efficiency of IBD detection and background suppression. DAQ is based on Flash ADC with PSD discrimination algorithms while digital trigger is programmable and flexible due to FPGA. The prototype detector was started up in 2014. Preliminary works on registration Cerenkov radiation produced by cosmic muons were established with distilled water inside the detector in order to test electronic and slow control systems. Also in parallel a long-term measurements with different scintillator samples were conducted.

ShellFit: Reconstruction in the MiniCLEAN Detector

NASA Astrophysics Data System (ADS)

Seibert, Stanley

2010-02-01

The MiniCLEAN dark matter experiment is an ultra-low background liquid cryogen detector with a fiducial volume of approximately 150 kg. Dark matter candidate events produce ultraviolet scintillation light in argon at 128 nm and in neon at 80 nm. In order to detect this scintillation light, the target volume is enclosed by acrylic plates forming a spherical shell upon which an organic fluor, tetraphenyl butadiene (TPB), has been applied. TPB absorbs UV light and reemits visible light isotropically which can be detected by photomultiplier tubes. Two significant sources of background events in MiniCLEAN are decays of radon daughters embedded in the acrylic surface and external sources of neutrons, such as the photomultiplier tubes themselves. Both of these backgrounds can be mitigated by reconstructing the origin of the scintillation light and cutting events beyond a particular radius. The scrambling of photon trajectories at the TPB surface makes this task very challenging. The ``ShellFit'' algorithm for reconstructing event position and energy in a detector with a spherical wavelength-shifting shell will be described. The performance of ShellFit will be demonstrated using Monte Carlo simulation of several event types in the MiniCLEAN detector. )

SU-G-BRA-06: Quantification of Tracking Performance of a Multi-Layer Electronic Portal Imaging Device

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Y; Rottmann, J; Myronakis, M

2016-06-15

Purpose: The purpose of this study was to quantify the improvement in tumor tracking, with and without fiducial markers, afforded by employing a multi-layer (MLI) electronic portal imaging device (EPID) over the current state-of-the-art, single-layer, digital megavolt imager (DMI) architecture. Methods: An ideal observer signal-to-noise ratio (d’) approach was used to quantify the ability of an MLI EPID and a current, state-of-the-art DMI EPID to track lung tumors from the treatment beam’s-eye-view. Using each detector modulation transfer function (MTF) and noise power spectrum (NPS) as inputs, a detection task was employed with object functions describing simple three-dimensional Cartesian shapes (spheresmore » and cylinders). Marker-less tumor tracking algorithms often use texture discrimination to differentiate benign and malignant tissue. The performance of such algorithms is simulated by employing a discrimination task for the ideal observer, which measures the ability of a system to differentiate two image quantities. These were defined as the measured textures for benign and malignant lung tissue. Results: The NNPS of the MLI ∼25% of that of the DMI at the expense of decreased MTF at intermediate frequencies (0.25≤« less

A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

PubMed Central

Balter, Peter; Morice, Rodolfo C.; Choi, Bum; Kudchadker, Rajat J.; Bucci, Kara; Chang, Joe Y.; Dong, Lei; Tucker, Susan; Vedam, Sastry; Briere, Tina; Starkschall, George

2008-01-01

This study aimed to validate and implement a methodology in which fiducials implanted in the periphery of lung tumors can be used to reduce uncertainties in tumor location. Alignment software that matches marker positions on two‐dimensional (2D) kilovoltage portal images to positions on three‐dimensional (3D) computed tomography data sets was validated using static and moving phantoms. This software also was used to reduce uncertainties in tumor location in a patient with fiducials implanted in the periphery of a lung tumor. Alignment of fiducial locations in orthogonal projection images with corresponding fiducial locations in 3D data sets can position both static and moving phantoms with an accuracy of 1 mm. In a patient, alignment based on fiducial locations reduced systematic errors in the left–right direction by 3 mm and random errors by 2 mm, and random errors in the superior–inferior direction by 3 mm as measured by anterior–posterior cine images. Software that matches fiducial markers on 2D and 3D images is effective for aligning both static and moving fiducials before treatment and can be implemented to reduce patient setup uncertainties. PACS number: 81.40.Wx

The STIS CCD Spectroscopic Line Spread Functions

NASA Technical Reports Server (NTRS)

Gull, T.; Lindler, D.; Tennant, D.; Bowers, C.; Grady, C.; Hill, R. S.; Malumuth, E.

2002-01-01

We characterize the spectroscopic line spread functions of the spectroscopic CCD modes for high contrast objects. Our long range goal is to develop tools that accurately extract spectroscopic information of faint, point or extended sources in the vicinity of bright, point sources at separations approaching the realizable angular limits of HST with STIS. Diffracted and scattered light due to the HST optics, and scattered light effects within the STIS are addressed. Filter fringing, CCD fringing, window reflections, and scattering within the detector and other effects are noted. We have obtained spectra of several reference stars, used for flux calibration or for coronagraphic standards, that have spectral distributions ranging from very red to very blue. Spectra of each star were recorded with the star in the aperture and with the star blocked by either the F1 or F2 fiducial. Plots of the detected starlight along the spatial axis of the aperture are provided for four stars. With the star in the aperture, the line spread function is quite noticeable. Placing the star behind one of the fiducials cuts the scattered light and the diffracted light, is detectable even out to 1OOOOA. When the star is placed behind either fiducial, the scattered and diffracted light components, at three arcseconds displacement from the star, are below lop6 the peak of the star at wavelengths below 6000A; at the same angular distance, scattered light does contaminate the background longward of 6000A up to a level of 10(exp -5).

Fiducial Marker Placement

MedlinePlus

... such as stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT) , or proton therapy . Fiducial markers are small ... Proton Therapy Stereotactic Radiosurgery (SRS) and Stereotactic Body Radiotherapy (SBRT) Images related to Fiducial Marker Placement Sponsored ...

FILM FORMAT AND FIDUCIAL MARKS OF THE 20$sub 4$ BUBBLE CHAMBER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, E.L.

1962-12-31

A description is given of the 20-in. bubble chamber film format. The film format consists of: chamber image; Arabic picture number; binary data box; Arabic view number; and the Hough-Powell road fiducial marks. The fiducial marks and their relation to the chamber optical constants are discussed. The constants are based on the standard measuring fiducials a and d. (P.C.H.)

SU-F-T-660: Evaluating the Benefit of Using Dual-Function Fiducial Markers for In-Situ Delivery of Radiosenistizing Gold Nanoparticles During Image-Guided Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

AlMansour, S; Chin, J; Sajo, E

Purpose: Dual-function fiducials loaded with radiosensitizers, like gold nanoparticles (GNP), offer an innovative approach for ensuring geometric accuracy during image-guided radiotherapy (IGRT) and significantly increasing therapeutic efficacy due to controlled in-situ release of the radiosensitizers. This study retrospectively investigates the dosimetric benefit of using up to two such dual-function fiducial markers instead of traditional single function fiducials during IGRT. Methods: A computational code was developed to investigate the dosimetric benefit for 10 real patient tumor volumes of up to 6.5 cm diameter. The intra-tumoral space-time biodistribution of the GNP was modeled as in previous studies based on Fick’s second law.more » The corresponding dose-enhancement for each tumor voxel due to the GNP was also calculated for clinical 6MV beam configurations. Various loading concentrations (25–50 mg/g) were studied, as a function of GNP size, to determine potential for clinically significant dose enhancement. The time between initial implantation of dual-function fiducials to the beginning of radiotherapy was assumed to be 14 days as typical for many clinics. Results: A single dual-function fiducial could achieve at least a DEF of 1.2 for patients with tumors less than 1.4 cm diameter after 14 days. Replacing two single function fiducials with dual-function ones at the same locations achieved at least the required minimal DEF for tumors that are 2 cm diameter in 3 patients. The results also revealed dosimetrically better fiducial locations which could enable significant DEF when using one or two dual function fiducials. 2 nm sizes showed the most feasibility. Conclusion: The results highlight the potential of tumor sub-volume radiation boosting using GNP released from fiducials, and the ability to customize the DEF throughout the tumor by using two dual-function fiducials, varying the initial concentration and nanoparticle size. The results demonstrate potential for employing dual-function fiducials in the development of GNP-aided radiotherapy.« less

Imaging arrangement and microscope

DOEpatents

Pertsinidis, Alexandros; Chu, Steven

2015-12-15

An embodiment of the present invention is an imaging arrangement that includes imaging optics, a fiducial light source, and a control system. In operation, the imaging optics separate light into first and second tight by wavelength and project the first and second light onto first and second areas within first and second detector regions, respectively. The imaging optics separate fiducial light from the fiducial light source into first and second fiducial light and project the first and second fiducial light onto third and fourth areas within the first and second detector regions, respectively. The control system adjusts alignment of the imaging optics so that the first and second fiducial light projected onto the first and second detector regions maintain relatively constant positions within the first and second detector regions, respectively. Another embodiment of the present invention is a microscope that includes the imaging arrangement.

SU-G-JeP1-10: Feasibility of CyberKnife Tracking Using the Previously-Implanted Permanent Brachytherapy Seed Cloud

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheung, J; Cunha, J; Sudhyadhom, A

Purpose: Robotic radiosurgery is a salvage treatment option for patients with recurrent prostate cancer. We explored the feasibility of tracking the bolus of permanent prostate implants (PPI) using image recognition software optimized to track spinal anatomy. Methods: Forty-five inert iodine seeds were implanted into a gelatin-based prostate phantom. Four superficial gold seeds were inserted to provide ground-truth alignment. A CT scan of the phantom (120 kVp, 1 mm slice thickness) was acquired and a single-energy iterative metal artifact reduction (MAR) algorithm was used to enhance the quality of the DRR used for tracking. CyberKnife treatment plans were generated from themore » MAR CT and regular CT (no-MAR) using spine tracking. The spine-tracking grid was centered on the bolus of seeds and resized to encompass the full seed cloud. A third plan was created from the regular CT scan, using fiducial tracking based on the 4 superficial gold seeds with identical align-center coordinates. The phantom was initially aligned using the fiducial-tracking plan. Then the MAR and no-MAR spine-tracking plans were loaded without moving the phantom. Differences in couch correction parameters were recorded in the case of perfect alignment and after the application of known rotations and translations (roll/pitch of 2 degrees; translations XYZ of 2 cm). Results: The spine tracking software was able to lock on to the bolus of seeds and provide couch corrections both in the MAR and no-MAR plans. In all cases, differences in the couch correction parameters from fiducial alignment were <0.5 mm in translations and <1 degree in rotations. Conclusion: We were able to successfully track the bolus of seeds with the spine-tracking grid in phantom experiments. For clinical applications, further investigation and developments to adapt the spine-tracking algorithm to optimize for PPI seed cloud tracking is needed to provide reliable tracking in patients. One of the authors (MD) has received research support and speaker honoraria from Accuray.« less

Fluoroscopic tumor tracking for image-guided lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Lin, Tong; Cerviño, Laura I.; Tang, Xiaoli; Vasconcelos, Nuno; Jiang, Steve B.

2009-02-01

Accurate lung tumor tracking in real time is a keystone to image-guided radiotherapy of lung cancers. Existing lung tumor tracking approaches can be roughly grouped into three categories: (1) deriving tumor position from external surrogates; (2) tracking implanted fiducial markers fluoroscopically or electromagnetically; (3) fluoroscopically tracking lung tumor without implanted fiducial markers. The first approach suffers from insufficient accuracy, while the second may not be widely accepted due to the risk of pneumothorax. Previous studies in fluoroscopic markerless tracking are mainly based on template matching methods, which may fail when the tumor boundary is unclear in fluoroscopic images. In this paper we propose a novel markerless tumor tracking algorithm, which employs the correlation between the tumor position and surrogate anatomic features in the image. The positions of the surrogate features are not directly tracked; instead, we use principal component analysis of regions of interest containing them to obtain parametric representations of their motion patterns. Then, the tumor position can be predicted from the parametric representations of surrogates through regression. Four regression methods were tested in this study: linear and two-degree polynomial regression, artificial neural network (ANN) and support vector machine (SVM). The experimental results based on fluoroscopic sequences of ten lung cancer patients demonstrate a mean tracking error of 2.1 pixels and a maximum error at a 95% confidence level of 4.6 pixels (pixel size is about 0.5 mm) for the proposed tracking algorithm.

Novel method for measuring a dense 3D strain map of robotic flapping wings

NASA Astrophysics Data System (ADS)

Li, Beiwen; Zhang, Song

2018-04-01

Measuring dense 3D strain maps of the inextensible membranous flapping wings of robots is of vital importance to the field of bio-inspired engineering. Conventional high-speed 3D videography methods typically reconstruct the wing geometries through measuring sparse points with fiducial markers, and thus cannot obtain the full-field mechanics of the wings in detail. In this research, we propose a novel system to measure a dense strain map of inextensible membranous flapping wings by developing a superfast 3D imaging system and a computational framework for strain analysis. Specifically, first we developed a 5000 Hz 3D imaging system based on the digital fringe projection technique using the defocused binary patterns to precisely measure the dynamic 3D geometries of rapidly flapping wings. Then, we developed a geometry-based algorithm to perform point tracking on the precisely measured 3D surface data. Finally, we developed a dense strain computational method using the Kirchhoff-Love shell theory. Experiments demonstrate that our method can effectively perform point tracking and measure a highly dense strain map of the wings without many fiducial markers.

Evaluation of the dose perturbation around gold and steel fiducial markers in a medical linac through Geant4 Monte Carlo simulation.

PubMed

Pontoriero, Antonio; Amato, Ernesto; Iatí, Giuseppe; De Renzis, Costantino; Pergolizzi, Stefano

2015-01-01

Purpose of this work was to study the dose perturbation within the target volume of a external MV radiation therapy when using metal fiducials. We developed a Monte Carlo simulation in Geant4 of a cylindrical fiducial made either of gold or of steel and simulated the photon irradiation beam originating from a medical Linac operating at 6, 10 or 15 MV. For each energy, two different irradiation schemes were simulated: a single 5 × 5-cm square field in the -x direction, and five 5 × 5-cm fields at 0°, 80°, 165°, 195° and 280°. In a single beam irradiation scheme, we observed a dose reduction behind fiducials varying from -20% for gold at 6 MV to -5% for steel at 15 MV, and a dose increment in front of the fiducial ranging from +33% for gold at 15 MV to +10% for steel at 6 MV. When five beams were employed, a dose increment ranging from +28% to +46% has been found around gold. Around a steel fiducial, an average increment of +17% was found, irrespective of the photon energy. When using a single beam, the decrement of dose behind both steel and gold markers increases with the photon energy. This effect vanishes when a multifield treatment is delivered; in this instance there is a dose increment around fiducials, according to both fiducial material and photon energy, with lower values for steel and 6 MV. This energy represents the best choice when fiducial markers are present inside the irradiated volume.

Swept Frequency Laser Metrology System

NASA Technical Reports Server (NTRS)

Zhao, Feng (Inventor)

2010-01-01

A swept frequency laser ranging system having sub-micron accuracy that employs multiple common-path heterodyne interferometers, one coupled to a calibrated delay-line for use as an absolute reference for the ranging system. An exemplary embodiment uses two laser heterodyne interferometers to create two laser beams at two different frequencies to measure distance and motions of target(s). Heterodyne fringes generated from reflections off a reference fiducial X(sub R) and measurement (or target) fiducial X(sub M) are reflected back and are then detected by photodiodes. The measured phase changes Delta phi(sub R) and Delta phi (sub m) resulting from the laser frequency swept gives target position. The reference delay-line is the only absolute reference needed in the metrology system and this provides an ultra-stable reference and simple/economical system.

Preoperative fiducial coil placement facilitates robot-assisted laparoscopic excision of retroperitoneal small solitary metastasis of kidney cancer.

PubMed

Agrawal, Vineet; Sharma, Ashwani; Wu, Guan

2014-11-01

Image-guided fiducial markers are being used in surgery, especially in spine and breast surgery, and radiotherapy, allowing localization of tumor sites precisely. We report a case of fiducial coil use in a man undergoing a robot-assisted laparoscopic resection of a metastatic nodule under the ipsilateral diaphragm after robot-assisted partial nephrectomy performed 2 years ago for a left upper pole renal tumor. The fiducial coil facilitated the localization of the lesion, which would otherwise have been challenging because of its small size and location. In addition, the fiducial coil was helpful to avoid cutting into the lesion directly. Copyright © 2014 Elsevier Inc. All rights reserved.

SU-F-J-43: Positional Variation of Implanted Fiducial Markers Over the Course of Image Guided Radiotherapy for Pancreatic Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, S; Jacob, R; Popple, R

2016-06-15

Purpose: Pancreas is a soft-tissue organ, implanted fiducials can change positions due to migration or tissue deformation. This study quantified positional variation of fiducials in IGRT for pancreatic cancer. Methods: 20 patients had at least 3 gold fiducials implanted in pancreas under EUS guidance. Patients had 4D-CT simulation for gated treatment. Daily gated OBI kV images (Turebeam) were used for positional alignment with fiducials for total of 25 or 28 fractions. Relative distances among 3 fiducials (d{sub 1–} {sub 2}, d{sub 1–3}, d{sub 2–3}) were measured from 4D-CT end-of-expiration phase bin; and from gated kV images in first, mid, andmore » last fraction (n=180). Results: The median duration between implant and simulation was 11 (range 0–41) days. The median duration between simulation and first fraction was 17 (range 8–24) days. The median relative distance was 12 (range 4–78) mm for d{sub 1–2}, 24 (range 6–80) mm for d{sub 1–3}, and 19 (range 5–63) mm for d{sub 2–3}. The median deviation was 1 mm for d{sub 1–2}, d{sub 1–3}, d{sub 2–3} between simulation and first fraction, first and mid fraction, mid and last fraction (n=180). Two patients (10%) had deviation >= 5 mm (5, 11 mm) between simulation and first fraction. One patient (5%) had deviation >= 5 mm (11 mm) between first and mid fraction. No patient (0%) had deviation >= 5 mm between mid and last fraction. In all 3 cases with deviation >=5 mm, only one fiducial was significantly deviated. No clear evidence that deviation size was associated with time interval between implant and first fraction. Conclusion: Implanted gold fiducials were quite stable over time in their relative positions in pancreas. Our data suggested at least 3 fiducials are needed. In cases that one fiducial was significantly deviated in daily kV images, this fiducial should be excluded in image guidance.« less

Image-guided ex-vivo targeting accuracy using a laparoscopic tissue localization system

NASA Astrophysics Data System (ADS)

Bieszczad, Jerry; Friets, Eric; Knaus, Darin; Rauth, Thomas; Herline, Alan; Miga, Michael; Galloway, Robert; Kynor, David

2007-03-01

In image-guided surgery, discrete fiducials are used to determine a spatial registration between the location of surgical tools in the operating theater and the location of targeted subsurface lesions and critical anatomic features depicted in preoperative tomographic image data. However, the lack of readily localized anatomic landmarks has greatly hindered the use of image-guided surgery in minimally invasive abdominal procedures. To address these needs, we have previously described a laser-based system for localization of internal surface anatomy using conventional laparoscopes. During a procedure, this system generates a digitized, three-dimensional representation of visible anatomic surfaces in the abdominal cavity. This paper presents the results of an experiment utilizing an ex-vivo bovine liver to assess subsurface targeting accuracy achieved using our system. During the experiment, several radiopaque targets were inserted into the liver parenchyma. The location of each target was recorded using an optically-tracked insertion probe. The liver surface was digitized using our system, and registered with the liver surface extracted from post-procedure CT images. This surface-based registration was then used to transform the position of the inserted targets into the CT image volume. The target registration error (TRE) achieved using our surface-based registration (given a suitable registration algorithm initialization) was 2.4 mm +/- 1.0 mm. A comparable TRE (2.6 mm +/- 1.7 mm) was obtained using a registration based on traditional fiducial markers placed on the surface of the same liver. These results indicate the potential of fiducial-free, surface-to-surface registration for image-guided lesion targeting in minimally invasive abdominal surgery.

Feasibility study for image guided kidney surgery: assessment of required intraoperative surface for accurate image to physical space registrations

NASA Astrophysics Data System (ADS)

Benincasa, Anne B.; Clements, Logan W.; Herrell, S. Duke; Chang, Sam S.; Cookson, Michael S.; Galloway, Robert L.

2006-03-01

Currently, the removal of kidney tumor masses uses only direct or laparoscopic visualizations, resulting in prolonged procedure and recovery times and reduced clear margin. Applying current image guided surgery (IGS) techniques, as those used in liver cases, to kidney resections (nephrectomies) presents a number of complications. Most notably is the limited field of view of the intraoperative kidney surface, which constrains the ability to obtain a surface delineation that is geometrically descriptive enough to drive a surface-based registration. Two different phantom orientations were used to model the laparoscopic and traditional partial nephrectomy views. For the laparoscopic view, fiducial point sets were compiled from a CT image volume using anatomical features such as the renal artery and vein. For the traditional view, markers attached to the phantom set-up were used for fiducials and targets. The fiducial points were used to perform a point-based registration, which then served as a guide for the surface-based registration. Laser range scanner (LRS) obtained surfaces were registered to each phantom surface using a rigid iterative closest point algorithm. Subsets of each phantom's LRS surface were used in a robustness test to determine the predictability of their registrations to transform the entire surface. Results from both orientations suggest that about half of the kidney's surface needs to be obtained intraoperatively for accurate registrations between the image surface and the LRS surface, suggesting the obtained kidney surfaces were geometrically descriptive enough to perform accurate registrations. This preliminary work paves the way for further development of kidney IGS systems.

A fiducial skull marker for precise MRI-based stereotaxic surgery in large animal models.

PubMed

Glud, Andreas Nørgaard; Bech, Johannes; Tvilling, Laura; Zaer, Hamed; Orlowski, Dariusz; Fitting, Lise Moberg; Ziedler, Dora; Geneser, Michael; Sangill, Ryan; Alstrup, Aage Kristian Olsen; Bjarkam, Carsten Reidies; Sørensen, Jens Christian Hedemann

2017-06-15

Stereotaxic neurosurgery in large animals is used widely in different sophisticated models, where precision is becoming more crucial as desired anatomical target regions are becoming smaller. Individually calculated coordinates are necessary in large animal models with cortical and subcortical anatomical differences. We present a convenient method to make an MRI-visible skull fiducial for 3D MRI-based stereotaxic procedures in larger experimental animals. Plastic screws were filled with either copper-sulfate solution or MRI-visible paste from a commercially available cranial head marker. The screw fiducials were inserted in the animal skulls and T1 weighted MRI was performed allowing identification of the inserted skull marker. Both types of fiducial markers were clearly visible on the MRÍs. This allows high precision in the stereotaxic space. The use of skull bone based fiducial markers gives high precision for both targeting and evaluation of stereotaxic systems. There are no metal artifacts and the fiducial is easily removed after surgery. The fiducial marker can be used as a very precise reference point, either for direct targeting or in evaluation of other stereotaxic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and Optimization of a Dedicated, Hybrid Dual-Modality SPECT-CmT System for Improved Breast Lesion Diagnosis

DTIC Science & Technology

2008-01-01

CT contrast agent, four 6.0mm nylon balls (Small Parts, Inc. Miami Lakes, FL) soaked in aqueous 99mTc-pertechnetate were used as markers and taped ...Inc, Miramar, Fl) were soaked in concentrated aqueous 99mTc and taped to the exterior surface of the breast phantom to act as fiducial markers for...vol. 21, pp. 48-55, 2006. [16] H. Erdogan and J. A. Fessler, "Ordered subsets algorithms for transmission tomography," Phys Med Biol, vol. 44, pp

The Mathematics of Four or More N-Localizers for Stereotactic Neurosurgery.

PubMed

Brown, Russell A

2015-10-13

The mathematics that were originally developed for the N-localizer apply to three N-localizers that produce three sets of fiducials in a tomographic image. Some applications of the N-localizer use four N-localizers that produce four sets of fiducials; however, the mathematics that apply to three sets of fiducials do not apply to four sets of fiducials. This article presents mathematics that apply to four or more sets of fiducials that all lie within one planar tomographic image. In addition, these mathematics are extended to apply to four or more fiducials that do not all lie within one planar tomographic image, as may be the case with magnetic resonance (MR) imaging where a volume is imaged instead of a series of planar tomographic images. Whether applied to a planar image or a volume image, the mathematics of four or more N-localizers provide a statistical measure of the quality of the image data that may be influenced by factors, such as the nonlinear distortion of MR images.

Position reconstruction in LUX

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Alsum, S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Brás, P.; Byram, D.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; Dobi, A.; Druszkiewicz, E.; Edwards, B. N.; Fallon, S. R.; Fan, A.; Fiorucci, S.; Gaitskell, R. J.; Genovesi, J.; Ghag, C.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Jacobsen, R. G.; Ji, W.; Kamdin, K.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Manalaysay, A.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O'Sullivan, K.; Oliver-Mallory, K. C.; Palladino, K. J.; Pease, E. K.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Solmaz, M.; Solovov, V. N.; Sorensen, P.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W. C.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Velan, V.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Xu, J.; Yazdani, K.; Young, S. K.; Zhang, C.

2018-02-01

The (x, y) position reconstruction method used in the analysis of the complete exposure of the Large Underground Xenon (LUX) experiment is presented. The algorithm is based on a statistical test that makes use of an iterative method to recover the photomultiplier tube (PMT) light response directly from the calibration data. The light response functions make use of a two dimensional functional form to account for the photons reflected on the inner walls of the detector. To increase the resolution for small pulses, a photon counting technique was employed to describe the response of the PMTs. The reconstruction was assessed with calibration data including 83mKr (releasing a total energy of 41.5 keV) and 3H (β- with Q = 18.6 keV) decays, and a deuterium-deuterium (D-D) neutron beam (2.45 MeV) . Within the detector's fiducial volume, the reconstruction has achieved an (x, y) position uncertainty of σ = 0.82 cm and σ = 0.17 cm for events of only 200 and 4,000 detected electroluminescence photons respectively. Such signals are associated with electron recoils of energies ~0.25 keV and ~10 keV, respectively. The reconstructed position of the smallest events with a single electron emitted from the liquid surface (22 detected photons) has a horizontal (x, y) uncertainty of 2.13 cm.

A Fiducial Approach to Extremes and Multiple Comparisons

ERIC Educational Resources Information Center

Wandler, Damian V.

2010-01-01

Generalized fiducial inference is a powerful tool for many difficult problems. Based on an extension of R. A. Fisher's work, we used generalized fiducial inference for two extreme value problems and a multiple comparison procedure. The first extreme value problem is dealing with the generalized Pareto distribution. The generalized Pareto…

4D ultrasound speckle tracking of intra-fraction prostate motion: a phantom-based comparison with x-ray fiducial tracking using CyberKnife

NASA Astrophysics Data System (ADS)

O'Shea, Tuathan P.; Garcia, Leo J.; Rosser, Karen E.; Harris, Emma J.; Evans, Philip M.; Bamber, Jeffrey C.

2014-04-01

This study investigates the use of a mechanically-swept 3D ultrasound (3D-US) probe for soft-tissue displacement monitoring during prostate irradiation, with emphasis on quantifying the accuracy relative to CyberKnife® x-ray fiducial tracking. An US phantom, implanted with x-ray fiducial markers was placed on a motion platform and translated in 3D using five real prostate motion traces acquired using the Calypso system. Motion traces were representative of all types of motion as classified by studying Calypso data for 22 patients. The phantom was imaged using a 3D swept linear-array probe (to mimic trans-perineal imaging) and, subsequently, the kV x-ray imaging system on CyberKnife. A 3D cross-correlation block-matching algorithm was used to track speckle in the ultrasound data. Fiducial and US data were each compared with known phantom displacement. Trans-perineal 3D-US imaging could track superior-inferior (SI) and anterior-posterior (AP) motion to ≤0.81 mm root-mean-square error (RMSE) at a 1.7 Hz volume rate. The maximum kV x-ray tracking RMSE was 0.74 mm, however the prostate motion was sampled at a significantly lower imaging rate (mean: 0.04 Hz). Initial elevational (right-left RL) US displacement estimates showed reduced accuracy but could be improved (RMSE <2.0 mm) using a correlation threshold in the ultrasound tracking code to remove erroneous inter-volume displacement estimates. Mechanically-swept 3D-US can track the major components of intra-fraction prostate motion accurately but exhibits some limitations. The largest US RMSE was for elevational (RL) motion. For the AP and SI axes, accuracy was sub-millimetre. It may be feasible to track prostate motion in 2D only. 3D-US also has the potential to improve high tracking accuracy for all motion types. It would be advisable to use US in conjunction with a small (˜2.0 mm) centre-of-mass displacement threshold in which case it would be possible to take full advantage of the accuracy and high imaging rate capability.

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery.

PubMed

Rottmann, Joerg; Keall, Paul; Berbeco, Ross

2013-09-01

To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm. The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.

RANDOM PULSE GENERATOR PRODUCING FIDUCIAL MARKS

DOEpatents

Nielsen, W.F.

1960-02-01

The apparatus for automatically applying a fiducial marking, having a nonrepetitive pattern, to a plurality of simultaneously made records comprises, in series, a bypass filter, a trigger circuit, and a pulse generator, with printing means connected to and controlled by the pulse generator for simultaneously making the visible fiducial marks on a plurality of simultaneously produced records.

Implementation of facial recognition with Microsoft Kinect v2 sensor for patient verification.

PubMed

Silverstein, Evan; Snyder, Michael

2017-06-01

The aim of this study was to present a straightforward implementation of facial recognition using the Microsoft Kinect v2 sensor for patient identification in a radiotherapy setting. A facial recognition system was created with the Microsoft Kinect v2 using a facial mapping library distributed with the Kinect v2 SDK as a basis for the algorithm. The system extracts 31 fiducial points representing various facial landmarks which are used in both the creation of a reference data set and subsequent evaluations of real-time sensor data in the matching algorithm. To test the algorithm, a database of 39 faces was created, each with 465 vectors derived from the fiducial points, and a one-to-one matching procedure was performed to obtain sensitivity and specificity data of the facial identification system. ROC curves were plotted to display system performance and identify thresholds for match determination. In addition, system performance as a function of ambient light intensity was tested. Using optimized parameters in the matching algorithm, the sensitivity of the system for 5299 trials was 96.5% and the specificity was 96.7%. The results indicate a fairly robust methodology for verifying, in real-time, a specific face through comparison from a precollected reference data set. In its current implementation, the process of data collection for each face and subsequent matching session averaged approximately 30 s, which may be too onerous to provide a realistic supplement to patient identification in a clinical setting. Despite the time commitment, the data collection process was well tolerated by all participants and most robust when consistent ambient light conditions were maintained across both the reference recording session and subsequent real-time identification sessions. A facial recognition system can be implemented for patient identification using the Microsoft Kinect v2 sensor and the distributed SDK. In its present form, the system is accurate-if time consuming-and further iterations of the method could provide a robust, easy to implement, and cost-effective supplement to traditional patient identification methods. © 2017 American Association of Physicists in Medicine.

How to estimate the 3D power spectrum of the Lyman-α forest

NASA Astrophysics Data System (ADS)

Font-Ribera, Andreu; McDonald, Patrick; Slosar, Anže

2018-01-01

We derive and numerically implement an algorithm for estimating the 3D power spectrum of the Lyman-α (Lyα) forest flux fluctuations. The algorithm exploits the unique geometry of Lyα forest data to efficiently measure the cross-spectrum between lines of sight as a function of parallel wavenumber, transverse separation and redshift. We start by approximating the global covariance matrix as block-diagonal, where only pixels from the same spectrum are correlated. We then compute the eigenvectors of the derivative of the signal covariance with respect to cross-spectrum parameters, and project the inverse-covariance-weighted spectra onto them. This acts much like a radial Fourier transform over redshift windows. The resulting cross-spectrum inference is then converted into our final product, an approximation of the likelihood for the 3D power spectrum expressed as second order Taylor expansion around a fiducial model. We demonstrate the accuracy and scalability of the algorithm and comment on possible extensions. Our algorithm will allow efficient analysis of the upcoming Dark Energy Spectroscopic Instrument dataset.

How to estimate the 3D power spectrum of the Lyman-α forest

DOE PAGES

Font-Ribera, Andreu; McDonald, Patrick; Slosar, Anže

2018-01-02

Here, we derive and numerically implement an algorithm for estimating the 3D power spectrum of the Lyman-α (Lyα) forest flux fluctuations. The algorithm exploits the unique geometry of Lyα forest data to efficiently measure the cross-spectrum between lines of sight as a function of parallel wavenumber, transverse separation and redshift. We start by approximating the global covariance matrix as block-diagonal, where only pixels from the same spectrum are correlated. We then compute the eigenvectors of the derivative of the signal covariance with respect to cross-spectrum parameters, and project the inverse-covariance-weighted spectra onto them. This acts much like a radial Fouriermore » transform over redshift windows. The resulting cross-spectrum inference is then converted into our final product, an approximation of the likelihood for the 3D power spectrum expressed as second order Taylor expansion around a fiducial model. We demonstrate the accuracy and scalability of the algorithm and comment on possible extensions. Our algorithm will allow efficient analysis of the upcoming Dark Energy Spectroscopic Instrument dataset.« less

How to estimate the 3D power spectrum of the Lyman-α forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Font-Ribera, Andreu; McDonald, Patrick; Slosar, Anže

Here, we derive and numerically implement an algorithm for estimating the 3D power spectrum of the Lyman-α (Lyα) forest flux fluctuations. The algorithm exploits the unique geometry of Lyα forest data to efficiently measure the cross-spectrum between lines of sight as a function of parallel wavenumber, transverse separation and redshift. We start by approximating the global covariance matrix as block-diagonal, where only pixels from the same spectrum are correlated. We then compute the eigenvectors of the derivative of the signal covariance with respect to cross-spectrum parameters, and project the inverse-covariance-weighted spectra onto them. This acts much like a radial Fouriermore » transform over redshift windows. The resulting cross-spectrum inference is then converted into our final product, an approximation of the likelihood for the 3D power spectrum expressed as second order Taylor expansion around a fiducial model. We demonstrate the accuracy and scalability of the algorithm and comment on possible extensions. Our algorithm will allow efficient analysis of the upcoming Dark Energy Spectroscopic Instrument dataset.« less

Alignment of leading-edge and peak-picking time of arrival methods to obtain accurate source locations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roussel-Dupre, R.; Symbalisty, E.; Fox, C.

2009-08-01

The location of a radiating source can be determined by time-tagging the arrival of the radiated signal at a network of spatially distributed sensors. The accuracy of this approach depends strongly on the particular time-tagging algorithm employed at each of the sensors. If different techniques are used across the network, then the time tags must be referenced to a common fiducial for maximum location accuracy. In this report we derive the time corrections needed to temporally align leading-edge, time-tagging techniques with peak-picking algorithms. We focus on broadband radio frequency (RF) sources, an ionospheric propagation channel, and narrowband receivers, but themore » final results can be generalized to apply to any source, propagation environment, and sensor. Our analytic results are checked against numerical simulations for a number of representative cases and agree with the specific leading-edge algorithm studied independently by Kim and Eng (1995) and Pongratz (2005 and 2007).« less

Novel Technique for Hepatic Fiducial Marker Placement for Stereotactic Body Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarraya, Hajer, E-mail: h-jarraya@o-lambret.fr; Chalayer, Chloé; Tresch, Emmanuelle

2014-09-01

Purpose: To report experience with fiducial marker insertion and describe an advantageous, novel technique for fiducial placement in the liver for stereotactic body radiation therapy with respiratory tracking. Methods and Materials: We implanted 1444 fiducials (single: 834; linked: 610) in 328 patients with 424 hepatic lesions. Two methods of implantation were compared: the standard method (631 single fiducials) performed on 153 patients from May 2007 to May 2010, and the cube method (813 fiducials: 610 linked/203 single) applied to 175 patients from April 2010 to March 2013. The standard method involved implanting a single marker at a time. The novel techniquemore » entailed implanting 2 pairs of linked markers when possible in a way to occupy the perpendicular edges of a cube containing the tumor inside. Results: Mean duration of the cube method was shorter than the standard method (46 vs 61 minutes; P<.0001). Median numbers of skin and subcapsular entries were significantly smaller with the cube method (2 vs 4, P<.0001, and 2 vs 4, P<.0001, respectively). The rate of overall complications (total, major, and minor) was significantly lower in the cube method group compared with the standard method group (5.7% vs 13.7%; P=.013). Major complications occurred while using single markers only. The success rate was 98.9% for the cube method and 99.3% for the standard method. Conclusions: We propose a new technique of hepatic fiducial implantation that makes use of linked fiducials and involves fewer skin entries and shorter time of implantation. The technique is less complication-prone and is migration-resistant.« less

Use of implanted gold fiducial markers with MV-CBCT image-guided IMRT for pancreatic tumours.

PubMed

Packard, Matthew; Gayou, Olivier; Gurram, Krishna; Weiss, Brandon; Thakkar, Shyam; Kirichenko, Alexander

2015-08-01

Visualisation of soft tissues such as pancreatic tumours by mega-voltage cone beam CT (MV-CBCT) is frequently difficult and daily localisation is often based on more easily seen adjacent bony anatomy. Fiducial markers implanted into pancreatic tumours serve as surrogates for tumour position and may more accurately represent absolute tumour position. Differences in daily shifts based on alignment to implanted fiducial markers vs. alignment to adjacent bony anatomy were compared. Gold fiducial markers were placed into the pancreatic tumour under endoscopic ultrasound (EUS) guidance in 12 patients. Patients subsequently received image-guided intensity-modulated radiation therapy (IG-IMRT). MV-CBCT was performed prior to each fraction and isocentre shifts were performed based on alignment to the fiducial markers. We retrospectively reviewed archived MV-CBCT datasets and calculated shift differences in the left-right (LR), superior-inferior (SI) and anterior-posterior (AP) axes relative to shifts based on alignment to adjacent bony anatomy. Two hundred forty-three fractions were analysed. The mean absolute difference in isocentre shifts between the fiducial markers and those aligned to bony anatomy was 3.4 mm (range 0-13 mm), 6.3 mm (range 0-21 mm) and 2.6 mm (range 0-12 mm), in LR, SI and AP directions, respectively. The mean three-dimensional vector shift difference between markers vs. bony anatomy alignment was 8.6 mm. These data suggest that fiducial markers used in conjunction with MV-CBCT improve the accuracy of daily target delineation compared with localisation using adjacent bony anatomy and that gold fiducial markers using MV-CBCT alignment are a viable option for target localisation during IG-IMRT. © 2015 The Royal Australian and New Zealand College of Radiologists.

Fiducial-based fusion of 3D dental models with magnetic resonance imaging.

PubMed

Abdi, Amir H; Hannam, Alan G; Fels, Sidney

2018-04-16

Magnetic resonance imaging (MRI) is widely used in study of maxillofacial structures. While MRI is the modality of choice for soft tissues, it fails to capture hard tissues such as bone and teeth. Virtual dental models, acquired by optical 3D scanners, are becoming more accessible for dental practice and are starting to replace the conventional dental impressions. The goal of this research is to fuse the high-resolution 3D dental models with MRI to enhance the value of imaging for applications where detailed analysis of maxillofacial structures are needed such as patient examination, surgical planning, and modeling. A subject-specific dental attachment was digitally designed and 3D printed based on the subject's face width and dental anatomy. The attachment contained 19 semi-ellipsoidal concavities in predetermined positions where oil-based ellipsoidal fiducial markers were later placed. The MRI was acquired while the subject bit on the dental attachment. The spatial position of the center of mass of each fiducial in the resultant MR Image was calculated by averaging its voxels' spatial coordinates. The rigid transformation to fuse dental models to MRI was calculated based on the least squares mapping of corresponding fiducials and solved via singular-value decomposition. The target registration error (TRE) of the proposed fusion process, calculated in a leave-one-fiducial-out fashion, was estimated at 0.49 mm. The results suggest that 6-9 fiducials suffice to achieve a TRE of equal to half the MRI voxel size. Ellipsoidal oil-based fiducials produce distinguishable intensities in MRI and can be used as registration fiducials. The achieved accuracy of the proposed approach is sufficient to leverage the merged 3D dental models with the MRI data for a finer analysis of the maxillofacial structures where complete geometry models are needed.

Method and system for processing optical elements using magnetorheological finishing

DOEpatents

Menapace, Joseph Arthur; Schaffers, Kathleen Irene; Bayramian, Andrew James; Molander, William A

2012-09-18

A method of finishing an optical element includes mounting the optical element in an optical mount having a plurality of fiducials overlapping with the optical element and obtaining a first metrology map for the optical element and the plurality of fiducials. The method also includes obtaining a second metrology map for the optical element without the plurality of fiducials, forming a difference map between the first metrology map and the second metrology map, and aligning the first metrology map and the second metrology map. The method further includes placing mathematical fiducials onto the second metrology map using the difference map to form a third metrology map and associating the third metrology map to the optical element. Moreover, the method includes mounting the optical element in the fixture in an MRF tool, positioning the optical element in the fixture; removing the plurality of fiducials, and finishing the optical element.

Fast Prediction and Evaluation of Gravitational Waveforms Using Surrogate Models

NASA Astrophysics Data System (ADS)

Field, Scott E.; Galley, Chad R.; Hesthaven, Jan S.; Kaye, Jason; Tiglio, Manuel

2014-07-01

We propose a solution to the problem of quickly and accurately predicting gravitational waveforms within any given physical model. The method is relevant for both real-time applications and more traditional scenarios where the generation of waveforms using standard methods can be prohibitively expensive. Our approach is based on three offline steps resulting in an accurate reduced order model in both parameter and physical dimensions that can be used as a surrogate for the true or fiducial waveform family. First, a set of m parameter values is determined using a greedy algorithm from which a reduced basis representation is constructed. Second, these m parameters induce the selection of m time values for interpolating a waveform time series using an empirical interpolant that is built for the fiducial waveform family. Third, a fit in the parameter dimension is performed for the waveform's value at each of these m times. The cost of predicting L waveform time samples for a generic parameter choice is of order O(mL+mcfit) online operations, where cfit denotes the fitting function operation count and, typically, m ≪L. The result is a compact, computationally efficient, and accurate surrogate model that retains the original physics of the fiducial waveform family while also being fast to evaluate. We generate accurate surrogate models for effective-one-body waveforms of nonspinning binary black hole coalescences with durations as long as 105M, mass ratios from 1 to 10, and for multiple spherical harmonic modes. We find that these surrogates are more than 3 orders of magnitude faster to evaluate as compared to the cost of generating effective-one-body waveforms in standard ways. Surrogate model building for other waveform families and models follows the same steps and has the same low computational online scaling cost. For expensive numerical simulations of binary black hole coalescences, we thus anticipate extremely large speedups in generating new waveforms with a surrogate. As waveform generation is one of the dominant costs in parameter estimation algorithms and parameter space exploration, surrogate models offer a new and practical way to dramatically accelerate such studies without impacting accuracy. Surrogates built in this paper, as well as others, are available from GWSurrogate, a publicly available python package.

Ionization imaging—A new method to search for 0- ν ββ decay

NASA Astrophysics Data System (ADS)

Chinowski, W.; Goldschmidt, A.; Nygren, D.; Bernstein, A.; Heffner, M.; Millaud, J.

2007-10-01

We present a new method to search for 0- ν ββ decay in 136Xe, the Ionization Imaging Chamber. This concept is based on 3-D track reconstruction by detection of ionization, without avalanche gain, in a novel time projection chamber (TPC) geometry. The rejection efficiency of external charged particle backgrounds is optimized by the realization of a maximal, fully active, closed, and ex post facto variable fiducial surface. Event localization within the fiducial volume and detailed event reconstruction mitigate external neutral particle backgrounds; larger detectors offer higher rejection efficiencies. Energy resolution at the Q-value of 2.5 MeV is expected to be better than 1% FWHM, reducing the potential impact of allowed 2- ν ββ decays. Scaling from ˜25 kg prototype to 1000+ kg target mass is graceful. A new possible methodology for the identification of the daughter barium nucleus is also described.

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

NASA Astrophysics Data System (ADS)

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.; Church, Sarah E.; Wechsler, Risa H.

2017-09-01

Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN-halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small for our fiducial model, which is based on current understanding of the galaxy-halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.

Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small for ourmore » fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.

Here, line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small formore » our fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

DOE PAGES

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.; ...

2017-08-31

Here, line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small formore » our fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohta, Kengo, E-mail: yesterday.is.yesterday@gmail.com; Shimohira, Masashi, E-mail: mshimohira@gmail.com; Sasaki, Shigeru, E-mail: ssasaki916@yahoo.co.jp

PurposeThe aim of this study is to analyze the technical and clinical success rates and safety of transarterial fiducial marker placement for image-guided proton therapy for malignant liver tumors.Methods and MaterialsFifty-five patients underwent this procedure as an interventional treatment. Five patients had 2 tumors, and 4 tumors required 2 markers each, so the total number of procedures was 64. The 60 tumors consisted of 46 hepatocellular carcinomas and 14 liver metastases. Five-mm-long straight microcoils of 0.018 inches in diameter were used as fiducial markers and placed in appropriate positions for each tumor. We assessed the technical and clinical success ratesmore » of transarterial fiducial marker placement, as well as the complications associated with it. Technical success was defined as the successful delivery and placement of the fiducial coil, and clinical success was defined as the completion of proton therapy.ResultsAll 64 fiducial coils were successfully installed, so the technical success rate was 100 % (64/64). Fifty-four patients underwent proton therapy without coil migration. In one patient, proton therapy was not performed because of obstructive jaundice due to bile duct invasion by hepatocellular carcinoma. Thus, the clinical success rate was 98 % (54/55). Slight bleeding was observed in one case, but it was stopped immediately and then observed. None of the patients developed hepatic infarctions due to fiducial marker migration.ConclusionTransarterial fiducial marker placement appears to be a useful and safe procedure for proton therapy for malignant liver tumors.« less

Digital stereophotogrammetry based on circular markers and zooming cameras: evaluation of a method for 3D analysis of small motions in orthopaedic research

PubMed Central

2011-01-01

Background Orthopaedic research projects focusing on small displacements in a small measurement volume require a radiation free, three dimensional motion analysis system. A stereophotogrammetrical motion analysis system can track wireless, small, light-weight markers attached to the objects. Thereby the disturbance of the measured objects through the marker tracking can be kept at minimum. The purpose of this study was to develop and evaluate a non-position fixed compact motion analysis system configured for a small measurement volume and able to zoom while tracking small round flat markers in respect to a fiducial marker which was used for the camera pose estimation. Methods The system consisted of two web cameras and the fiducial marker placed in front of them. The markers to track were black circles on a white background. The algorithm to detect a centre of the projected circle on the image plane was described and applied. In order to evaluate the accuracy (mean measurement error) and precision (standard deviation of the measurement error) of the optical measurement system, two experiments were performed: 1) inter-marker distance measurement and 2) marker displacement measurement. Results The first experiment of the 10 mm distances measurement showed a total accuracy of 0.0086 mm and precision of ± 0.1002 mm. In the second experiment, translations from 0.5 mm to 5 mm were measured with total accuracy of 0.0038 mm and precision of ± 0.0461 mm. The rotations of 2.25° amount were measured with the entire accuracy of 0.058° and the precision was of ± 0.172°. Conclusions The description of the non-proprietary measurement device with very good levels of accuracy and precision may provide opportunities for new, cost effective applications of stereophotogrammetrical analysis in musculoskeletal research projects, focusing on kinematics of small displacements in a small measurement volume. PMID:21284867

TH-AB-209-07: High Resolution X-Ray-Induced Acoustic Computed Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiang, L; Tang, S; Ahmad, M

Purpose: X-ray radiographic absorption imaging is an invaluable tool in medical diagnostics, biology and materials science. However, the use of conventional CT is limited by two factors: the detection sensitivity to weak absorption material and the radiation dose from CT scanning. The purpose of this study is to explore X-ray induced acoustic computed tomography (XACT), a new imaging modality, which combines X-ray absorption contrast and high ultrasonic resolution to address these challenges. Methods: First, theoretical models was built to analyze the XACT sensitivity to X-ray absorption and calculate the minimal radiation dose in XACT imaging. Then, an XACT system comprisedmore » of an ultrashort X-ray pulse, a low noise ultrasound detector and a signal acquisition system was built to evaluate the X-ray induced acoustic signal generation. A piece of chicken bone and a phantom with two golden fiducial markers were exposed to 270 kVp X-ray source with 60 ns exposure time, and the X-ray induced acoustic signal was received by a 2.25MHz ultrasound transducer in 200 positions. XACT images were reconstructed by a filtered back-projection algorithm. Results: The theoretical analysis shows that X-ray induced acoustic signals have 100% relative sensitivity to X-ray absorption, but not to X-ray scattering. Applying this innovative technology to breast imaging, we can reduce radiation dose by a factor of 50 compared with newly FDA approved breast CT. The reconstructed images of chicken bone and golden fiducial marker phantom reveal that the spatial resolution of the built XACT system is 350µm. Conclusion: In XACT, the imaging sensitivity to X-ray absorption is improved and the imaging dose is dramatically reduced by using ultrashort pulsed X-ray. Taking advantage of the high ultrasonic resolution, we can also perform 3D imaging with a single X-ray pulse. This new modality has the potential to revolutionize x-ray imaging applications in medicine and biology.« less

SU-E-J-38: Improved DRR Image Quality Using Polyetheretherketone (PEEK) Fiducial in Image Guided Radiotherapy (IGRT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, S; Jacob, R; Popple, R

Purpose Fiducial-based imaging is often used in IGRT. Traditional gold fiducial marker often has substantial reconstruction artifacts. These artifacts Result in poor image quality of DRR for online kV-to-DRR matching. This study evaluated the image quality of PEEK in DRR in static and moving phantom. Methods CT scan of the Gold and PEEK fiducial (both 1×3 mm) was acquired in a 22 cm cylindrical phantom filled with water. Image artifacts was evaluated with maximum CT value deviated from water due to artifacts; volume of artifacts in 10×10 cm in the center slice; maximum length of streak artifacts from the fiducial.more » DRR resolution were measured using FWHM and FWTM. 4DCT of PEEK fiducial was acquired with the phantom moving sinusoidally in superior-inferior direction. Motion artifacts were assessed for various 4D phase angles. Results The maximum CT value deviation was −174 for Gold and −24 for PEEK. The volume of artifacts in a 10x10 cm 3 mm slice was 0.369 for Gold and 0.074 cm3 for PEEK. The maximum length of streak artifact was 80mm for Gold and 7 mm for PEEK. PEEK in DRR, FWHM was close to actual (1.0 mm for Gold and 1.1 mm for PEEK). FWTM was 1.8 mm for Gold and 1.3 mm for PEEK in DRR. Barrel motion artifact of PEEK fiducial was noticeable for free-breathing scan. The apparent PEEK length due to residual motion was in close agreement with the calculated length (13 mm for 30–70 phase, 10 mm in 40–60 phase). Conclusion Streak artifacts on planning CT associated with use of gold fiducial can be significantly reduced by PEEK fiducial, while having adequate kV image contrast. DRR image resolution at FWTM was improved from 1.8 mm to 1.3 mm. Because of this improvement, we have been routinely use PEEK for liver IGRT.« less

The Mini-CAPTAIN Neutron Run and Future CAPTAIN Program

NASA Astrophysics Data System (ADS)

Cooper, Robert; CAPTAIN Collaboration

2016-09-01

The Cryogenic Apparatus for Precision Tests of Argon Interaction with Neutrinos (CAPTAIN) is an experimental program to measure critical neutrino interaction cross sections in argon for the DUNE long-baseline program. These cross sections are important for understanding and improving the energy resolution of measurements for neutrino oscillations and supernova detection in argon. The full CAPTAIN detector is a 5-ton fiducial volume liquid argon (LAr) time-projection chamber (TPC) with an independently triggered photon detection system (PDS) for fast-timing capabilities on accelerators. To test the full CAPTAIN concept, the 1-ton fiducial volume mini-CAPTAIN detector has been deployed. Mini-CAPTAIN is another LAr TPC with PDS. It was recently deployed to the Weapons Neutron Research (WNR) facility at Los Alamos National Laboratory to measure high-energy neutron interactions in argon. The WNR is a pulsed accelerator capable of delivering neutrons up to 800 MeV in energy. In this talk, I will report on the analysis of the first time-of-flight tagged, high-energy neutron response in liquid argon from our February 2016 run. I will also highlight a second neutron run at the WNR scheduled for Summer 2017 and discuss the implications these data have on the future CAPTAIN program.

Poster - Thurs Eve-12: A needle-positioning robot co-registered with volumetric x-ray micro-computed tomography images for minimally-invasive small-animal interventions.

PubMed

Waspe, A C; Holdsworth, D W; Lacefield, J C; Fenster, A

2008-07-01

Preclinical research protocols often require the delivery of biological substances to specific targets in small animal disease models. To target biologically relevant locations in mice accurately, the needle positioning error needs to be < 200 μm. If targeting is inaccurate, experimental results can be inconclusive or misleading. We have developed a robotic manipulator that is capable of positioning a needle with a mean error < 100 μm. An apparatus and method were developed for integrating the needle-positioning robot with volumetric micro-computed tomography image guidance for interventions in small animals. Accurate image-to-robot registration is critical for integration as it enables targets identified in the image to be mapped to physical coordinates inside the animal. Registration is accomplished by injecting barium sulphate into needle tracks as the robot withdraws the needle from target points in a tissue-mimicking phantom. Registration accuracy is therefore affected by the positioning error of the robot and is assessed by measuring the point-to-line fiducial and target registration errors (FRE, TRE). Centroid points along cross-sectional slices of the track are determined using region growing segmentation followed by application of a center-of-mass algorithm. The centerline points are registered to needle trajectories in robot coordinates by applying an iterative closest point algorithm between points and lines. Implementing this procedure with four fiducial needle tracks produced a point-to-line FRE and TRE of 246 ± 58 μm and 194 ± 18 μm, respectively. The proposed registration technique produced a TRE < 200 μm, in the presence of robot positioning error, meeting design specification. © 2008 American Association of Physicists in Medicine.

Three-phase Interstellar Medium in Galaxies Resolving Evolution with Star Formation and Supernova Feedback (TIGRESS): Algorithms, Fiducial Model, and Convergence

NASA Astrophysics Data System (ADS)

Kim, Chang-Goo; Ostriker, Eve C.

2017-09-01

We introduce TIGRESS, a novel framework for multi-physics numerical simulations of the star-forming interstellar medium (ISM) implemented in the Athena MHD code. The algorithms of TIGRESS are designed to spatially and temporally resolve key physical features, including: (1) the gravitational collapse and ongoing accretion of gas that leads to star formation in clusters; (2) the explosions of supernovae (SNe), both near their progenitor birth sites and from runaway OB stars, with time delays relative to star formation determined by population synthesis; (3) explicit evolution of SN remnants prior to the onset of cooling, which leads to the creation of the hot ISM; (4) photoelectric heating of the warm and cold phases of the ISM that tracks the time-dependent ambient FUV field from the young cluster population; (5) large-scale galactic differential rotation, which leads to epicyclic motion and shears out overdense structures, limiting large-scale gravitational collapse; (6) accurate evolution of magnetic fields, which can be important for vertical support of the ISM disk as well as angular momentum transport. We present tests of the newly implemented physics modules, and demonstrate application of TIGRESS in a fiducial model representing the solar neighborhood environment. We use a resolution study to demonstrate convergence and evaluate the minimum resolution {{Δ }}x required to correctly recover several ISM properties, including the star formation rate, wind mass-loss rate, disk scale height, turbulent and Alfvénic velocity dispersions, and volume fractions of warm and hot phases. For the solar neighborhood model, all these ISM properties are converged at {{Δ }}x≤slant 8 {pc}.

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery

PubMed Central

Rottmann, Joerg; Keall, Paul; Berbeco, Ross

2013-01-01

Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm. Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time. PMID:24007146

Thoracic spine localization using preoperative placement of fiducial markers and subsequent CT. A technical report.

PubMed

Anaizi, Amjad Nasr; Kalhorn, Christopher; McCullough, Michael; Voyadzis, Jean-Marc; Sandhu, Faheem A

2015-01-01

A retrospective case series evaluating the use of fiducial markers with subsequent computed tomography (CT) or CT myelography for intraoperative localization. To evaluate the safety and utility of preoperative fiducial placement, confirmed with CT myelography, for intraoperative localization of thoracic spinal levels. Thoracic spine surgery is associated with serious complications, not the least of which is the potential for wrong-level surgery. Intraoperative fluoroscopy is often used but can be unreliable due to the patient's body habitus and anatomical variation. Sixteen patients with thoracic spine pathology requiring surgical intervention underwent preoperative fiducial placement at the pedicle of the level of interest in the interventional radiology suite. CT or CT myelogram was then done to evaluate fiducial location relative to the level of pathology. Surgical treatment followed at a later date in all patients. All patients underwent preoperative fiducial placement and CT or CT myelography, which was done on an outpatient basis in 14 of the 16 patients. Intraoperatively, fiducial localization was easily and quickly done with intraoperative fluoroscopy leading to correct localization of spinal level in all cases. All patients had symptomatic improvement following surgery. There were no complications from preoperative localization or operative intervention. Preoperative placement of fiducial markers confirmed with a CT or CT myelogram allows for reliable and fast intraoperative localization of the spinal level of interest with minimal risks and potential complications to the patient. In most cases, a noncontrast CT should be sufficient. This should be an equally reliable means of localization while further decreasing potential for complications. CT myelography should be reserved for pathology that is not evident on noncontrast CT. Accuracy of localization is independent of variations in rib number or vertebral segmentation. The technique is a safe, reliable, and rapid means of localizing spinal level during surgery. Georg Thieme Verlag KG Stuttgart · New York.

Position reconstruction in LUX

DOE PAGES

Akerib, D. S.; Alsum, S.; Araújo, H. M.; ...

2018-02-01

The (x, y) position reconstruction method used in the analysis of the complete exposure of the Large Underground Xenon (LUX) experiment is presented. The algorithm is based on a statistical test that makes use of an iterative method to recover the photomultiplier tube (PMT) light response directly from the calibration data. The light response functions make use of a two dimensional functional form to account for the photons reflected on the inner walls of the detector. To increase the resolution for small pulses, a photon counting technique was employed to describe the response of the PMTs. The reconstruction was assessedmore » with calibration data including 83mKr (releasing a total energy of 41.5 keV) and 3H (β - with Q = 18.6 keV) decays, and a deuterium-deuterium (D-D) neutron beam (2.45 MeV). Within the detector's fiducial volume, the reconstruction has achieved an (x, y) position uncertainty of σ = 0.82 cm and σ = 0.17 cm for events of only 200 and 4,000 detected electroluminescence photons respectively. Such signals are associated with electron recoils of energies ~0.25 keV and ~10 keV, respectively. Lastly, the reconstructed position of the smallest events with a single electron emitted from the liquid surface (22 detected photons) has a horizontal (x, y) uncertainty of 2.13 cm.« less

Position reconstruction in LUX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akerib, D. S.; Alsum, S.; Araújo, H. M.

The (x, y) position reconstruction method used in the analysis of the complete exposure of the Large Underground Xenon (LUX) experiment is presented. The algorithm is based on a statistical test that makes use of an iterative method to recover the photomultiplier tube (PMT) light response directly from the calibration data. The light response functions make use of a two dimensional functional form to account for the photons reflected on the inner walls of the detector. To increase the resolution for small pulses, a photon counting technique was employed to describe the response of the PMTs. The reconstruction was assessedmore » with calibration data including 83mKr (releasing a total energy of 41.5 keV) and 3H (β - with Q = 18.6 keV) decays, and a deuterium-deuterium (D-D) neutron beam (2.45 MeV). Within the detector's fiducial volume, the reconstruction has achieved an (x, y) position uncertainty of σ = 0.82 cm and σ = 0.17 cm for events of only 200 and 4,000 detected electroluminescence photons respectively. Such signals are associated with electron recoils of energies ~0.25 keV and ~10 keV, respectively. Lastly, the reconstructed position of the smallest events with a single electron emitted from the liquid surface (22 detected photons) has a horizontal (x, y) uncertainty of 2.13 cm.« less

Position reconstruction in LUX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akerib, D. S.; Alsum, S.; Araújo, H. M.

© 2018 IOP Publishing Ltd and Sissa Medialab. The (x, y) position reconstruction method used in the analysis of the complete exposure of the Large Underground Xenon (LUX) experiment is presented. The algorithm is based on a statistical test that makes use of an iterative method to recover the photomultiplier tube (PMT) light response directly from the calibration data. The light response functions make use of a two dimensional functional form to account for the photons reflected on the inner walls of the detector. To increase the resolution for small pulses, a photon counting technique was employed to describe themore » response of the PMTs. The reconstruction was assessed with calibration data including 83m Kr (releasing a total energy of 41.5 keV) and 3 H (andbeta; - with Q = 18.6 keV) decays, and a deuterium-deuterium (D-D) neutron beam (2.45 MeV) . Within the detector's fiducial volume, the reconstruction has achieved an (x, y) position uncertainty of andsigma; = 0.82 cm and andsigma; = 0.17 cm for events of only 200 and 4,000 detected electroluminescence photons respectively. Such signals are associated with electron recoils of energies andsim;0.25 keV and andsim;10 keV, respectively. The reconstructed position of the smallest events with a single electron emitted from the liquid surface (22 detected photons) has a horizontal (x, y) uncertainty of 2.13 cm.« less

Position reconstruction in LUX

DOE PAGES

Akerib, D. S.; Alsum, S.; Araújo, H. M.; ...

2018-02-01

© 2018 IOP Publishing Ltd and Sissa Medialab. The (x, y) position reconstruction method used in the analysis of the complete exposure of the Large Underground Xenon (LUX) experiment is presented. The algorithm is based on a statistical test that makes use of an iterative method to recover the photomultiplier tube (PMT) light response directly from the calibration data. The light response functions make use of a two dimensional functional form to account for the photons reflected on the inner walls of the detector. To increase the resolution for small pulses, a photon counting technique was employed to describe themore » response of the PMTs. The reconstruction was assessed with calibration data including 83m Kr (releasing a total energy of 41.5 keV) and 3 H (andbeta; - with Q = 18.6 keV) decays, and a deuterium-deuterium (D-D) neutron beam (2.45 MeV) . Within the detector's fiducial volume, the reconstruction has achieved an (x, y) position uncertainty of andsigma; = 0.82 cm and andsigma; = 0.17 cm for events of only 200 and 4,000 detected electroluminescence photons respectively. Such signals are associated with electron recoils of energies andsim;0.25 keV and andsim;10 keV, respectively. The reconstructed position of the smallest events with a single electron emitted from the liquid surface (22 detected photons) has a horizontal (x, y) uncertainty of 2.13 cm.« less

Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

NASA Astrophysics Data System (ADS)

Riboldi, M.; Baroni, G.; Spadea, M. F.; Tagaste, B.; Garibaldi, C.; Cambria, R.; Orecchia, R.; Pedotti, A.

2007-09-01

In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process.

Quantifying Rigid and Nonrigid Motion of Liver Tumors During Stereotactic Body Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Qianyi, E-mail: xuqianyi@gmail.com; Hanna, George; Grimm, Jimm

2014-09-01

Purpose: To quantify rigid and nonrigid motion of liver tumors using reconstructed 3-dimensional (3D) fiducials from stereo imaging during CyberKnife-based stereotactic body radiation therapy (SBRT). Methods and Materials: Twenty-three liver patients treated with 3 fractions of SBRT were used in this study. After 2 orthogonal kilovoltage images were taken during treatment, the 3D locations of the fiducials were generated by the CyberKnife system and validated using geometric derivations. A total of 4824 pairs of kilovoltage images from start to end of treatment were analyzed. For rigid motion, the rotational angles and translational shifts were reported by aligning 3D fiducial groupsmore » from different image pairs, using least-squares fitting. For nonrigid motion, we quantified interfractional tumor volume variations by using the proportional volume derived from the fiducials, which correlates to the sum of interfiducial distances. The individual fiducial displacements were also reported (1) after rigid corrections and (2) without angle corrections. Results: The proportional volume derived by the fiducials demonstrated a volume-increasing trend in the second (101.9% ± 3.6%) and third (101.0 ± 5.9%) fractions among most patients, possibly due to radiation-induced edema. For all patients, the translational shifts in left-right, anteroposterior, and superoinferior directions were 2.1 ± 2.3 mm, 2.9 ± 2.8 mm, and 6.4 ± 5.5 mm, respectively. The greatest translational shifts occurred in the superoinferior direction, likely due to respiratory motion from the diaphragm. The rotational angles in roll, pitch, and yaw were 1.2° ± 1.8°, 1.8° ± 2.4°, and 1.7° ± 2.1°, respectively. The 3D individual fiducial displacements with rigid corrections were 0.2 ± 0.2 mm and increased to 0.5 ± 0.4 mm without rotational corrections. Conclusions: Accurate 3D locations of internal fiducials can be reconstructed from stereo imaging during treatment. As an effective surrogate to tumor motion, fiducials provide a close estimation of both rigid and nonrigid motion of liver tumors. The reported displacements could be further utilized for tumor margin definition and motion management in conventional linear accelerator–based liver SBRT.« less

SU-E-J-225: Quantitative Evaluation of Rigid and Non-Rigid Motion of Liver Tumors Using Stereo Imaging During SBRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Q; Hanna, G; Kubicek, G

2014-06-01

Purpose: To quantitatively evaluate rigid and nonrigid motion of liver tumors based on fiducial tracking in 3D by stereo imaging during CyberKnife SBRT. Methods: Twenty-five liver patients previously treated with three-fractions of SBRT were retrospectively recruited in this study. During treatment, the 3D locations of fiducials were reported by the CyberKnife system after two orthogonal kV X-ray images were taken and further validated by geometry derivations. A total of 5004 pairs of X-ray images acquired during the course of treatment for all the patients, were analyzed. For rigid motion, the rotational angles and translational shifts by aligning 3D fiducial groupsmore » in different image pairs after least-square fitting were reported. For nonrigid motion, the relative interfractional tumor shape variations were reported and correlated to the sum of inter-fiducial distances. The individual fiducial displacements were also reported after rigid corrections and without angle corrections. Results: The relative tumor volume variation indicated by the inter-fiducial distances demonstrated an increasing trend in the second (101.6±3.4%) and third fraction (101.2±5.6%) among most patients. The cause could be possibly due to radiation-induced edema. For all the patients, the translational shift was 8.1±5.7 mm, with shifts in LR, AP and SI were 2.1±2.4 mm, 2.8±2.9 mm and 6.7±5.1 mm, respectively. The greatest translation shift occurred in SI, mainly due the breathing motion of diaphragm The rotational angles were 1.1±1.7°, 1.9±2.6° and 1.6±2.2°, in roll, pitch, and yaw, respectively. The 3D fiducial displacement with rigid corrections were 0.2±0.2 mm and increased to 0.6±0.3 mm without rotational corrections. Conclusion: The fiducial locations in 3D can be precisely reconstructed from CyberKnife stereo imaging system during treatment. The fiducials provide close estimation of both rigid and nonrigid motion of .liver tumors. The reported data could be further utilized for tumor margin design and motion management in in conventional linac-based treatments.« less

Real-time automatic registration in optical surgical navigation

NASA Astrophysics Data System (ADS)

Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming

2016-05-01

An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

International global network of fiducial stations: Scientific and implementation issues

NASA Astrophysics Data System (ADS)

1991-11-01

In this report, an ad hoc panel of the National Research Council's Committee on Geodesy, Board of Earth Sciences and Resources (1) evaluates the scientific importance of a global network of fiducial sites, monitored very precisely, using a combination of surface- and space-geodetic techniques; (2) examines strategies for implementing and operating such a network; and (3) assesses whether such a network would provide a suitable global infrastructure for geodetic and other geophysical systems of the next century. The panel concludes that a global network of fiducial sites would be a valuable tool for addressing global change issues and play a critical role in providing a reference frame for scientific Earth missions. The panel suggests that existing global networks be integrated and anticipates that such a network would grow from about 30 to the ultimate size of about 200 fiducial sites. It is noted that such a global network will provide a long-term infrastructure for geodetic and geophysical studies. The panel expects that these fiducial sites would evolve into terrestrial observatories or laboratories that would permit more comprehensive studies of the Earth than those now possible.

International global network of fiducial stations: Scientific and implementation issues

NASA Technical Reports Server (NTRS)

1991-01-01

In this report, an ad hoc panel of the National Research Council's Committee on Geodesy, Board of Earth Sciences and Resources (1) evaluates the scientific importance of a global network of fiducial sites, monitored very precisely, using a combination of surface- and space-geodetic techniques; (2) examines strategies for implementing and operating such a network; and (3) assesses whether such a network would provide a suitable global infrastructure for geodetic and other geophysical systems of the next century. The panel concludes that a global network of fiducial sites would be a valuable tool for addressing global change issues and play a critical role in providing a reference frame for scientific Earth missions. The panel suggests that existing global networks be integrated and anticipates that such a network would grow from about 30 to the ultimate size of about 200 fiducial sites. It is noted that such a global network will provide a long-term infrastructure for geodetic and geophysical studies. The panel expects that these fiducial sites would evolve into terrestrial observatories or laboratories that would permit more comprehensive studies of the Earth than those now possible.

Optical fiducial timing system for X-ray streak cameras with aluminum coated optical fiber ends

DOEpatents

Nilson, David G.; Campbell, E. Michael; MacGowan, Brian J.; Medecki, Hector

1988-01-01

An optical fiducial timing system is provided for use with interdependent groups of X-ray streak cameras (18). The aluminum coated (80) ends of optical fibers (78) are positioned with the photocathodes (20, 60, 70) of the X-ray streak cameras (18). The other ends of the optical fibers (78) are placed together in a bundled array (90). A fiducial optical signal (96), that is comprised of 2.omega. or 1.omega. laser light, after introduction to the bundled array (90), travels to the aluminum coated (82) optical fiber ends and ejects quantities of electrons (84) that are recorded on the data recording media (52) of the X-ray streak cameras (18). Since both 2.omega. and 1.omega. laser light can travel long distances in optical fiber with only a slight attenuation, the initial arial power density of the fiducial optical signal (96) is well below the damage threshold of the fused silica or other material that comprises the optical fibers (78, 90). Thus the fiducial timing system can be repeatably used over long durations of time.

Phase-space representations of symmetric informationally complete positive-operator-valued-measure fiducial states

NASA Astrophysics Data System (ADS)

Saraceno, Marcos; Ermann, Leonardo; Cormick, Cecilia

2017-03-01

The problem of finding symmetric informationally complete positive-operator-valued-measures (SIC-POVMs) has been solved numerically for all dimensions d up to 67 [A. J. Scott and M. Grassl, J. Math. Phys. 51, 042203 (2010), 10.1063/1.3374022], but a general proof of existence is still lacking. For each dimension, it was shown that it is possible to find a SIC-POVM that is generated from a fiducial state upon application of the operators of the Heisenberg-Weyl group. We draw on the numerically determined fiducial states to study their phase-space features, as displayed by the characteristic function and the Wigner, Bargmann, and Husimi representations, adapted to a Hilbert space of finite dimension. We analyze the phase-space localization of fiducial states, and observe that the SIC-POVM condition is equivalent to a maximal delocalization property. Finally, we explore the consequences in phase space of the conjectured Zauner symmetry. In particular, we construct a Hermitian operator commuting with this symmetry that leads to a representation of fiducial states in terms of eigenfunctions with definite semiclassical features.

Note: A simple image processing based fiducial auto-alignment method for sample registration.

PubMed

Robertson, Wesley D; Porto, Lucas R; Ip, Candice J X; Nantel, Megan K T; Tellkamp, Friedjof; Lu, Yinfei; Miller, R J Dwayne

2015-08-01

A simple method for the location and auto-alignment of sample fiducials for sample registration using widely available MATLAB/LabVIEW software is demonstrated. The method is robust, easily implemented, and applicable to a wide variety of experiment types for improved reproducibility and increased setup speed. The software uses image processing to locate and measure the diameter and center point of circular fiducials for distance self-calibration and iterative alignment and can be used with most imaging systems. The method is demonstrated to be fast and reliable in locating and aligning sample fiducials, provided here by a nanofabricated array, with accuracy within the optical resolution of the imaging system. The software was further demonstrated to register, load, and sample the dynamically wetted array.

Comparative assessment of techniques for initial pose estimation using monocular vision

NASA Astrophysics Data System (ADS)

Sharma, Sumant; D`Amico, Simone

2016-06-01

This work addresses the comparative assessment of initial pose estimation techniques for monocular navigation to enable formation-flying and on-orbit servicing missions. Monocular navigation relies on finding an initial pose, i.e., a coarse estimate of the attitude and position of the space resident object with respect to the camera, based on a minimum number of features from a three dimensional computer model and a single two dimensional image. The initial pose is estimated without the use of fiducial markers, without any range measurements or any apriori relative motion information. Prior work has been done to compare different pose estimators for terrestrial applications, but there is a lack of functional and performance characterization of such algorithms in the context of missions involving rendezvous operations in the space environment. Use of state-of-the-art pose estimation algorithms designed for terrestrial applications is challenging in space due to factors such as limited on-board processing power, low carrier to noise ratio, and high image contrasts. This paper focuses on performance characterization of three initial pose estimation algorithms in the context of such missions and suggests improvements.

Semi-automated intra-operative fluoroscopy guidance for osteotomy and external-fixator.

PubMed

Lin, Hong; Samchukov, Mikhail L; Birch, John G; Cherkashin, Alexander

2006-01-01

This paper outlines a semi-automated intra-operative fluoroscopy guidance and monitoring approach for osteotomy and external-fixator application in orthopedic surgery. Intra-operative Guidance module is one component of the "LegPerfect Suite" developed for assisting the surgical correction of lower extremity angular deformity. The Intra-operative Guidance module utilizes information from the preoperative surgical planning module as a guideline to overlay (register) its bone outline semi-automatically with the bone edge from the real-time fluoroscopic C-Arm X-Ray image in the operating room. In the registration process, scaling factor is obtained automatically through matching a fiducial template in the fluoroscopic image and a marker in the module. A triangle metal plate, placed on the operating table is used as fiducial template. The area of template image within the viewing area of the fluoroscopy machine is obtained by the image processing techniques such as edge detection and Hough transformation to extract the template from other objects in the fluoroscopy image. The area of fiducial template from fluoroscopic image is then compared with the area of the marker from the planning so as to obtain the scaling factor. After the scaling factor is obtained, the user can use simple operations by mouse to shift and rotate the preoperative planning to overlay the bone outline from planning with the bone edge from fluoroscopy image. In this way osteotomy levels and external fixator positioning on the limb can guided by the computerized preoperative plan.

Towards active image-guidance: tracking of a fiducial in the thorax during respiration under X-ray fluoroscopy

NASA Astrophysics Data System (ADS)

Siddique, Sami; Jaffray, David

2007-03-01

A central purpose of image-guidance is to assist the interventionalist with feedback of geometric performance in the direction of therapy delivery. Tradeoffs exist between accuracy, precision and the constraints imposed by parameters used in the generation of images. A framework that uses geometric performance as feedback to control these parameters can balance such tradeoffs in order to maintain the requisite localization precision for a given clinical procedure. We refer to this principle as Active Image-Guidance (AIG). This framework requires estimates of the uncertainty in the estimated location of the object of interest. In this study, a simple fiducial marker detected under X-ray fluoroscopy is considered and it is shown that a relation exists between the applied imaging dose and the uncertainty in localization for a given observer. A robust estimator of the location of a fiducial in the thorax during respiration under X-ray fluoroscopy is demonstrated using a particle filter based approach that outputs estimates of the location and the associated spatial uncertainty. This approach gives an rmse of 1.3mm and the uncertainty estimates are found to be correlated with the error in the estimates. Furthermore, the particle filtering approach is employed to output location estimates and the associated uncertainty not only at instances of pulsed exposure but also between exposures. Such a system has applications in image-guided interventions (surgery, radiotherapy, interventional radiology) where there are latencies between the moment of imaging and the act of intervention.

Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.

PubMed

Kong, Seong-Ho; Haouchine, Nazim; Soares, Renato; Klymchenko, Andrey; Andreiuk, Bohdan; Marques, Bruno; Shabat, Galyna; Piechaud, Thierry; Diana, Michele; Cotin, Stéphane; Marescaux, Jacques

2017-07-01

Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials. Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials. Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images. Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking.

SU-F-P-40: Analysis of Pelvic Lymph Node Margin Using Prostate Fiducial Markers, for SBRT Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Torres, J; Castro Pena, P; Garrigo, E

2016-06-15

Purpose: The use of fiducials markers in prostate treatment allows a precise localization of this volume. Typical prostate SBRT margins with fiducials markers are 5mm in all directions, except toward the rectum, where 3mm is used. For some patients nearby pelvic lymph nodes with 5mm margin need to be irradiate assuming that its localization is linked to the prostate fiducial markers instead of bony anatomy. The purpose of this work was to analyze the geometric impact of locate the lymph node regions through the patient positioning by prostate fiducial markers. Methods: 10 patients with prostate SBRT with lymph nodes irradiationmore » were selected. Each patient had 5 implanted titanium fiducial markers. A Novalis TX (BrainLAB-Varian) with ExacTrac and aSi1000 portal image was used. Treatment plan uses 11 beams with a dose prescription (D95%) of 40Gy to the prostate and 25Gy to the lymph node in 5 fractions. Daily positioning was carried out by ExacTrac system based on the implanted fiducials as the reference treatment position; further position verification was performed using the ExacTrac and two portal images (gantry angle 0 and 90) based on bony structures. Comparison between reference position with bony based ExacTrac and portal image localization, was done for each treatment fraction Results: A total of 50 positioning analysis were done. The average discrepancy between reference treatment position and ExacTrac based on bony anatomy (pubic area) was 4.2mm [0.3; 11.2]. The discrepancy was <5mm in 61% of the cases and <9mm in 92%. Using portal images the average discrepancy was 3.7mm [0.0; 11.1]. The discrepancy was <5mm in 69% of the cases and <9mm in 96%. Conclusion: Localizing lymph node by prostate fiducial markers may produce large discrepancy as large as 11mm compared to bony based localization. Dosimetric impact of this discrepancy should be studied.« less

TU-H-CAMPUS-TeP3-02: In-Situ Dose Painting Using Gold Nanoparticles Released From Cylindrically Shaped Fiducials During External Beam Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, R; University Medical Center Mannheim, Mannheim; Heidelberg University, Heidelberg

Purpose: Recent studies have shown that the presence of Gold Nanoparticles (GNPs) in tumor tissue can lead to significant dose enhancement (DE) during External Beam Radiation Therapy (EBRT). In this in-silico study we investigate EBRT with in-situ dose painting using GNPs released from cylindrically shaped GNP-loaded fiducials. Methods: Reported Biologically Target/Tumor Volumes (BTVs) for 12 prostate carcinoma patients were employed in this study. Distribution of the GNPs after burst release from the fiducial (1.5mm diameter and 5mm length) located in the center of the spherically assumed BTV were modeled by isotropic and free diffusion without boundary condition and under themore » assumption of superposition. An experimentally determined diffusion coefficient for 10nm nanoparticles was adapted for investigating other GNP sizes (2, 5, 15, and 20nm) using the Stokes-Einstein equation. The maximum size of GNPs to achieve a minimal DE Factor (DEF) of 1.1 for 6MV EBRT using a fiducial-load of 30mg/g was calculated for typical periods of 14 and 21 days after implantation. Further, the minimal fiducial-load needed to achieve a clinically significant DEF of 1.2 was computed for 2nm GNPs. Results: Results showed that a minimal DEF of 1.1 could be reached for the smallest patient BTV using a maximal GNP size of 10nm and 20nm after 14 and 21 days, respectively. With increasing BTV smaller GNPs are required to ensure the same DEF. In particular, the largest BTV requires 2nm GNPs for periods of 14 and 21 days. Meanwhile, the required fiducial-load to reach a minimal DEF of 1.2 after 14 days was found in the range of 17mg/g and 59mg/g for all reported BTVs. Conclusion: This preliminary study indicates a strong dependence on GNP size and fiducial-load to realize a significant DE. The findings avail further research towards development of GNP-loaded fiducials for significantly enhancing radiotherapy for cancer patients.« less

The Detection Rate of Early UV Emission from Supernovae: A Dedicated Galex/PTF Survey and Calibrated Theoretical Estimates

NASA Astrophysics Data System (ADS)

Ganot, Noam; Gal-Yam, Avishay; Ofek, Eran. O.; Sagiv, Ilan; Waxman, Eli; Lapid, Ofer; Kulkarni, Shrinivas R.; Ben-Ami, Sagi; Kasliwal, Mansi M.; The ULTRASAT Science Team; Chelouche, Doron; Rafter, Stephen; Behar, Ehud; Laor, Ari; Poznanski, Dovi; Nakar, Ehud; Maoz, Dan; Trakhtenbrot, Benny; WTTH Consortium, The; Neill, James D.; Barlow, Thomas A.; Martin, Christofer D.; Gezari, Suvi; the GALEX Science Team; Arcavi, Iair; Bloom, Joshua S.; Nugent, Peter E.; Sullivan, Mark; Palomar Transient Factory, The

2016-03-01

The radius and surface composition of an exploding massive star, as well as the explosion energy per unit mass, can be measured using early UV observations of core-collapse supernovae (SNe). We present the first results from a simultaneous GALEX/PTF search for early ultraviolet (UV) emission from SNe. Six SNe II and one Type II superluminous SN (SLSN-II) are clearly detected in the GALEX near-UV (NUV) data. We compare our detection rate with theoretical estimates based on early, shock-cooling UV light curves calculated from models that fit existing Swift and GALEX observations well, combined with volumetric SN rates. We find that our observations are in good agreement with calculated rates assuming that red supergiants (RSGs) explode with fiducial radii of 500 R ⊙, explosion energies of 1051 erg, and ejecta masses of 10 M ⊙. Exploding blue supergiants and Wolf-Rayet stars are poorly constrained. We describe how such observations can be used to derive the progenitor radius, surface composition, and explosion energy per unit mass of such SN events, and we demonstrate why UV observations are critical for such measurements. We use the fiducial RSG parameters to estimate the detection rate of SNe during the shock-cooling phase (<1 day after explosion) for several ground-based surveys (PTF, ZTF, and LSST). We show that the proposed wide-field UV explorer ULTRASAT mission is expected to find >85 SNe per year (˜0.5 SN per deg2), independent of host galaxy extinction, down to an NUV detection limit of 21.5 mag AB. Our pilot GALEX/PTF project thus convincingly demonstrates that a dedicated, systematic SN survey at the NUV band is a compelling method to study how massive stars end their life.

An automated A-value measurement tool for accurate cochlear duct length estimation.

PubMed

Iyaniwura, John E; Elfarnawany, Mai; Ladak, Hanif M; Agrawal, Sumit K

2018-01-22

There has been renewed interest in the cochlear duct length (CDL) for preoperative cochlear implant electrode selection and postoperative generation of patient-specific frequency maps. The CDL can be estimated by measuring the A-value, which is defined as the length between the round window and the furthest point on the basal turn. Unfortunately, there is significant intra- and inter-observer variability when these measurements are made clinically. The objective of this study was to develop an automated A-value measurement algorithm to improve accuracy and eliminate observer variability. Clinical and micro-CT images of 20 cadaveric cochleae specimens were acquired. The micro-CT of one sample was chosen as the atlas, and A-value fiducials were placed onto that image. Image registration (rigid affine and non-rigid B-spline) was applied between the atlas and the 19 remaining clinical CT images. The registration transform was applied to the A-value fiducials, and the A-value was then automatically calculated for each specimen. High resolution micro-CT images of the same 19 specimens were used to measure the gold standard A-values for comparison against the manual and automated methods. The registration algorithm had excellent qualitative overlap between the atlas and target images. The automated method eliminated the observer variability and the systematic underestimation by experts. Manual measurement of the A-value on clinical CT had a mean error of 9.5 ± 4.3% compared to micro-CT, and this improved to an error of 2.7 ± 2.1% using the automated algorithm. Both the automated and manual methods correlated significantly with the gold standard micro-CT A-values (r = 0.70, p < 0.01 and r = 0.69, p < 0.01, respectively). An automated A-value measurement tool using atlas-based registration methods was successfully developed and validated. The automated method eliminated the observer variability and improved accuracy as compared to manual measurements by experts. This open-source tool has the potential to benefit cochlear implant recipients in the future.

Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis.

PubMed

Padgett, Kyle R; Stoyanova, Radka; Pirozzi, Sara; Johnson, Perry; Piper, Jon; Dogan, Nesrin; Pollack, Alan

2018-03-01

Validating deformable multimodality image registrations is challenging due to intrinsic differences in signal characteristics and their spatial intensity distributions. Evaluating multimodality registrations using these spatial intensity distributions is also complicated by the fact that these metrics are often employed in the registration optimization process. This work evaluates rigid and deformable image registrations of the prostate in between diagnostic-MRI and radiation treatment planning-CT by utilizing a planning-MRI after fiducial marker placement as a surrogate. The surrogate allows for the direct quantitative analysis that can be difficult in the multimodality domain. For thirteen prostate patients, T2 images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day as the planning-CT (planning-MRI). The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available algorithm which synthesizes a deformable image registration (DIR) algorithm from local rigid registrations. The planning-MRI provided an independent surrogate for the planning-CT for assessing registration accuracy using image similarity metrics, including Pearson correlation and normalized mutual information (NMI). A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb, and combined areas. The planning-MRI provided an excellent surrogate for the planning-CT with residual error in fiducial alignment between the two datasets being submillimeter, 0.78 mm. DIR was superior to the rigid registration in 11 of 13 cases demonstrating a 27.37% improvement in NMI (P < 0.009) within a regional area surrounding the prostate and associated critical organs. Pearson correlations showed similar results, demonstrating a 13.02% improvement (P < 0.013). By utilizing the planning-MRI as a surrogate for the planning-CT, an independent evaluation of registration accuracy is possible. This population provides an ideal testing ground for MRI to CT DIR by obviating the need for multimodality comparisons which are inherently more challenging. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Automatic segmentation and centroid detection of skin sensors for lung interventions

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Xu, Sheng; Xue, Zhong; Wong, Stephen T.

2012-02-01

Electromagnetic (EM) tracking has been recognized as a valuable tool for locating the interventional devices in procedures such as lung and liver biopsy or ablation. The advantage of this technology is its real-time connection to the 3D volumetric roadmap, i.e. CT, of a patient's anatomy while the intervention is performed. EM-based guidance requires tracking of the tip of the interventional device, transforming the location of the device onto pre-operative CT images, and superimposing the device in the 3D images to assist physicians to complete the procedure more effectively. A key requirement of this data integration is to find automatically the mapping between EM and CT coordinate systems. Thus, skin fiducial sensors are attached to patients before acquiring the pre-operative CTs. Then, those sensors can be recognized in both CT and EM coordinate systems and used calculate the transformation matrix. In this paper, to enable the EM-based navigation workflow and reduce procedural preparation time, an automatic fiducial detection method is proposed to obtain the centroids of the sensors from the pre-operative CT. The approach has been applied to 13 rabbit datasets derived from an animal study and eight human images from an observation study. The numerical results show that it is a reliable and efficient method for use in EM-guided application.

PET/CT image registration: preliminary tests for its application to clinical dosimetry in radiotherapy.

PubMed

Baños-Capilla, M C; García, M A; Bea, J; Pla, C; Larrea, L; López, E

2007-06-01

The quality of dosimetry in radiotherapy treatment requires the accurate delimitation of the gross tumor volume. This can be achieved by complementing the anatomical detail provided by CT images through fusion with other imaging modalities that provide additional metabolic and physiological information. Therefore, use of multiple imaging modalities for radiotherapy treatment planning requires an accurate image registration method. This work describes tests carried out on a Discovery LS positron emission/computed tomography (PET/CT) system by General Electric Medical Systems (GEMS), for its later use to obtain images to delimit the target in radiotherapy treatment. Several phantoms have been used to verify image correlation, in combination with fiducial markers, which were used as a system of external landmarks. We analyzed the geometrical accuracy of two different fusion methods with the images obtained with these phantoms. We first studied the fusion method used by the PET/CT system by GEMS (hardware fusion) on the basis that there is satisfactory coincidence between the reconstruction centers in CT and PET systems; and secondly the fiducial fusion, a registration method, by means of least-squares fitting algorithm of a landmark points system. The study concluded with the verification of the centroid position of some phantom components in both imaging modalities. Centroids were estimated through a calculation similar to center-of-mass, weighted by the value of the CT number and the uptake intensity in PET. The mean deviations found for the hardware fusion method were: deltax/ +/-sigma = 3.3 mm +/- 1.0 mm and /deltax/ +/-sigma = 3.6 mm +/- 1.0 mm. These values were substantially improved upon applying fiducial fusion based on external landmark points: /deltax/ +/-sigma = 0.7 mm +/- 0.8 mm and /deltax/ +/-sigma = 0.3 mm 1.7 mm. We also noted that differences found for each of the fusion methods were similar for both the axial and helical CT image acquisition protocols.

Intravascular Placement of Metallic Coils as Lung Tumor Markers for CyberKnife Stereotactic Radiation Therapy.

PubMed

Karaman, Kutlay; Dokdok, A Murat; Karadeniz, Oktay; Ceylan, Cemile; Engin, Kayıhan

2015-01-01

To present our experience with placing endovascular coils in pulmonary arteries used as a fiducial marker for CyberKnife therapy and to describe the technical details and complications of the procedure. Between June 2005 and September 2013, 163 patients with primary or secondary lung malignancies, referred for fiducial placement for stereotactic radiosurgery, were retrospectively reviewed. Fourteen patients (9 men, 5 women; mean age, 70 years) with a history of pneumonectomy (n = 3), lobectomy (n = 3) or with severe cardiopulmonary co-morbidity (n = 8) underwent coil (fiducial marker) placement. Pushable or detachable platinum micro coils (n = 49) 2-3 mm in size were inserted through coaxial microcatheters into a small distal pulmonary artery in the vicinity of the tumor under biplane angiography/fluoroscopy guidance. Forty nine coils with a median number of 3 coils per tumor were placed with a mean tumor-coil distance of 2.7 cm. Forty three (87.7%) of 49 coils were successfully used as fiducial markers. Two coils could not be used due to a larger tumor-coil distance (> 50 mm). Four coils were in an acceptable position but their non-coiling shape precluded tumor tracking for CyberKnife treatment. No major complications needing further medication other than nominal therapy, hospitalization more than one night or permanent adverse sequale were observed. Endovascular placement of coil as a fiducial marker is safe and feasible during CyberKnife therapy, and might be an option for the patients in which percutaneous transthoracic fiducial placement might be risky.

Clinical results from first use of prostate stent as fiducial for radiotherapy of prostate cancer.

PubMed

Carl, Jesper; Nielsen, Jane; Holmberg, Mats; Larsen, Erik Hoejkjaer; Fabrin, Knud; Fisker, Rune V

2011-05-01

A clinical feasibility study using a removable prostate stent as fiducial for image-guided radiotherapy (IGRT) of localized prostate cancer (PC). The study included patients with local or locally advanced PC. The clinical target volume (CTV) was outlined on magnetic resonance (MR) images co-registered to planning computer tomography (CT) images. Daily online IGRT was delivered using the stent as fiducial. Risk of migration was estimated using multiple MR. Acute urinary toxicity was scored using the international prostate symptom score (IPSS). Late gastro-intestinal (GI) and genito-urinary (GU) toxicity was scored using the Radio Therapy Oncology Group (RTOG) score, biochemical failure (BF) was defined as an elevation of prostate specific antigen (PSA) above nadir plus 2 ng/ml after radiotherapy. One hundred men were enrolled in the study. Ninety completed radiotherapy with the stent as fiducial. No migration of the stent was seen, but three cases of dislocation of the stent to the bladder were observed. Acute urinary toxicity based on IPSS was comparable to toxicity in patients who had gold markers (GM) as fiducials. Removal of the stent was associated with a high frequency of urinary retention. Late GI and GU toxicity and BF were comparable to those of other studies, but longer observation time is needed. This study reports the first clinical results of using a prostate stent as fiducial. No migration of the stent observed. Dislocation of the stent to the urinary bladder was observed in three cases, requiring removal of the stent and insertion of a new fiducial. Acute toxicity during radiotherapy evaluated from IPSS was comparable to toxicity in patients with GM. Removal of the stent was associated with a high frequency of post procedural urinary retention. Late toxicity and BF were comparable to those of other studies, though longer observation time is needed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horst, Astrid van der, E-mail: a.vanderhorst@amc.uva.nl; Lens, Eelco; Wognum, Silvia

Purpose: Because of low soft-tissue contrast of cone beam computed tomography (CBCT), fiducial markers are often used for radiation therapy patient setup verification. For pancreatic cancer patients, biliary stents have been suggested as surrogate fiducials. Using intratumoral fiducials as standard for tumor position, this study aims to quantify the suitability of biliary stents for measuring interfractional and respiratory-induced position variations of pancreatic tumors. Methods and Materials: Eleven pancreatic cancer patients with intratumoral fiducials and a biliary stent were included in this study. Daily CBCT scans (243 in total) were registered with a reference CT scan, based on bony anatomy, onmore » fiducial markers, and on the biliary stent, respectively. We analyzed the differences in tumor position (ie, markers center-of-mass position) among these 3 registrations. In addition, we measured for 9 patients the magnitude of respiratory-induced motion (MM) of the markers and of the stent on 4-dimensional CT (4DCT) and determined the difference between these 2 magnitudes (ΔMM). Results: The stent indicated tumor position better than bony anatomy in 67% of fractions; the absolute difference between the markers and stent registration was >5 mm in 46% of fractions and >10 mm in 20% of fractions. Large PTV margins (superior-inferior direction, >19 mm) would be needed to account for this interfractional position variability. On 4DCT, we found in superior-inferior direction a mean ΔMM of 0.5 mm (range, –2.6 to 4.2 mm). Conclusions: For respiratory-induced motion, the mean ΔMM is small, but for individual patients the absolute difference can be >4 mm. For interfractional position variations, a stent is, on average, a better surrogate fiducial than bony anatomy, but large PTV margins would still be required. Therefore, intratumoral fiducials are recommended for online setup verification for all pancreatic patients scheduled for radiation therapy, including patients with a biliary stent.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, S; Kim, R; Benhabib, S

Purpose: HDR brachytherapy using interstitial needle template for cervical cancer is commonly delivered in 4-5 fractions. Routine verification of needle positions before each fraction is often based on radiographic imaging of implanted fiducial markers. The current study evaluated interfractional displacement of implanted fiducial markers using CT images. Methods: 9 sequential patients with cervical interstitial needle implants were evaluated. The superior and inferior borders of the target volumes were defined by fiducial markers in planning CT. The implant position was verified with kV orthogonal images before each fraction. A second CT was acquired prior 3rd fraction (one or 2 days postmore » planning CT). Distances from inferior and superior fiducial markers to pubic symphysis plane (perpendicular to vaginal obtulator)were measured. Distance from needle tip of a reference needle (next to the inferior marker) to the pubic symphysis plane was also determined. The difference in fiducial marker distance or needle tip distance between planning CT and CT prior 3rd fraction were measured to assess markers migration and needle displacement. Results: The mean inferior marker displacement was 4.5 mm and ranged 0.9 to 11.3 mm. The mean superior marker displacement was 2.7 mm and ranged 0 to 10.4 mm. There was a good association between inferior and superior marker displacement (r=0.95). Mean averaged inferior and superior marker displacement was 3.3 mm and ranged from 0.1 to 10.9 mm, with a standard deviation of 3.2 mm. The mean needle displacement was 5.6 mm and ranged 0.2 to 15.6 mm. Needle displacements were reduced (p<0.05) after adjusting according to needle-to-fiducials distance. Conclusion: There were small fiducial marker displacements between HDR fractions. Our study suggests a target margin of 9.7 mm to cover interfractional marker displacements (in 95% cases) for pretreatment verification based on radiographic imaging.« less

Front lighted optical tooling method and apparatus

DOEpatents

Stone, W.J.

1983-06-30

An optical tooling method and apparatus uses a front lighted shadowgraphic technique to enhance visual contrast of reflected light. The apparatus includes an optical assembly including a fiducial mark, such as cross hairs, reflecting polarized light with a first polarization, a polarizing element backing the fiducial mark and a reflective surface backing the polarizing element for reflecting polarized light bypassing the fiducial mark and traveling through the polarizing element. The light reflected by the reflecting surface is directed through a second pass of the polarizing element toward the frontal direction with a polarization differing from the polarization of the light reflected by the fiducial mark. When used as a tooling target, the optical assembly may be mounted directly to a reference surface or may be secured in a mounting, such as a magnetic mounting. The optical assembly may also be mounted in a plane defining structure and used as a spherometer in conjunction with an optical depth measuring instrument.

redMaGiC: selecting luminous red galaxies from the DES Science Verification data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rozo, E.

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the color-cuts necessary to produce a luminosity-thresholded LRG sam- ple of constant comoving density. Additionally, we demonstrate that redMaGiC photo-zs are very nearly as accurate as the best machine-learning based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalog sampling the redshiftmore » range z ϵ [0.2,0.8]. Our fiducial sample has a comoving space density of 10 -3 (h -1Mpc) -3, and a median photo-z bias (z spec z photo) and scatter (σ z=(1 + z)) of 0.005 and 0.017 respectively.The corresponding 5σ outlier fraction is 1.4%. We also test our algorithm with Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8) and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1% level.« less

Comparison between skin-mounted fiducials and bone-implanted fiducials for image-guided neurosurgery

NASA Astrophysics Data System (ADS)

Rost, Jennifer; Harris, Steven S.; Stefansic, James D.; Sillay, Karl; Galloway, Robert L., Jr.

2004-05-01

Point-based registration for image-guided neurosurgery has become the industry standard. While the use of intrinsic points is appealing because of its retrospective nature, affixing extrinsic objects to the head prior to scanning has been demonstrated to provide much more accurate registrations. Points of reference between image space and physical space are called fiducials. The extrinsic objects which generate those points are fiducial markers. The markers can be broken down into two classifications: skin-mounted and bone-implanted. Each has distinct advantages and disadvantages. Skin-mounted fiducials require simply sticking them on the patient in locations suggested by the manufacturer, however, they can move with tractions placed on the skin, fall off and perhaps the most dangerous problem, they can be replaced by the patient. Bone implanted markers being rigidly affixed to the skull do not present such problems. However, a minor surgical intervention (analogous to dental work) must be performed to implant the markers prior to surgery. Therefore marker type and use has become a decision point for image-guided surgery. We have performed a series of experiments in an attempt to better quantify aspects of the two types of markers so that better informed decisions can be made. We have created a phantom composed of a full-size plastic skull [Wards Scientific Supply] with a 500 ml bag of saline placed in the brain cavity. The skull was then sealed. A skin mimicking material, DragonSkinTM [SmoothOn Company] was painted onto the surface and allowed to dry. Skin mounted fiducials [Medtronic-SNT] and bone-implanted markers [Z-Kat]were placed on the phantom. In addition, three additional bone-implanted markers were placed (two on the base of the skull and one in the eye socket for use as targets). The markers were imaged in CT and 4 MRI sequences (T1-weighted, T2 weighted, SPGR, and a functional series.) The markers were also located in physical space using an Optotrak 3020 [Northern Digital Inc]. Registrations between image space and physical space were performed and fiducial and target registration errors were determined. Finally the 5 bone-implanted makers which penetrated the skin were removed and a traction equivalent to 25% of the weight of the average human head was applied to the "skin" surface. Target and fiducial registrations were again performed.

Fast algorithm for probabilistic bone edge detection (FAPBED)

NASA Astrophysics Data System (ADS)

Scepanovic, Danilo; Kirshtein, Joshua; Jain, Ameet K.; Taylor, Russell H.

2005-04-01

The registration of preoperative CT to intra-operative reality systems is a crucial step in Computer Assisted Orthopedic Surgery (CAOS). The intra-operative sensors include 3D digitizers, fiducials, X-rays and Ultrasound (US). FAPBED is designed to process CT volumes for registration to tracked US data. Tracked US is advantageous because it is real time, noninvasive, and non-ionizing, but it is also known to have inherent inaccuracies which create the need to develop a framework that is robust to various uncertainties, and can be useful in US-CT registration. Furthermore, conventional registration methods depend on accurate and absolute segmentation. Our proposed probabilistic framework addresses the segmentation-registration duality, wherein exact segmentation is not a prerequisite to achieve accurate registration. In this paper, we develop a method for fast and automatic probabilistic bone surface (edge) detection in CT images. Various features that influence the likelihood of the surface at each spatial coordinate are combined using a simple probabilistic framework, which strikes a fair balance between a high-level understanding of features in an image and the low-level number crunching of standard image processing techniques. The algorithm evaluates different features for detecting the probability of a bone surface at each voxel, and compounds the results of these methods to yield a final, low-noise, probability map of bone surfaces in the volume. Such a probability map can then be used in conjunction with a similar map from tracked intra-operative US to achieve accurate registration. Eight sample pelvic CT scans were used to extract feature parameters and validate the final probability maps. An un-optimized fully automatic Matlab code runs in five minutes per CT volume on average, and was validated by comparison against hand-segmented gold standards. The mean probability assigned to nonzero surface points was 0.8, while nonzero non-surface points had a mean value of 0.38 indicating clear identification of surface points on average. The segmentation was also sufficiently crisp, with a full width at half maximum (FWHM) value of 1.51 voxels.

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

NASA Astrophysics Data System (ADS)

Luiza Bondar, M.; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-01

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer.

PubMed

Bondar, M Luiza; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-07

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

A novel method for quantification of beam's-eye-view tumor tracking performance.

PubMed

Hu, Yue-Houng; Myronakis, Marios; Rottmann, Joerg; Wang, Adam; Morf, Daniel; Shedlock, Daniel; Baturin, Paul; Star-Lack, Josh; Berbeco, Ross

2017-11-01

In-treatment imaging using an electronic portal imaging device (EPID) can be used to confirm patient and tumor positioning. Real-time tumor tracking performance using current digital megavolt (MV) imagers is hindered by poor image quality. Novel EPID designs may help to improve quantum noise response, while also preserving the high spatial resolution of the current clinical detector. Recently investigated EPID design improvements include but are not limited to multi-layer imager (MLI) architecture, thick crystalline and amorphous scintillators, and phosphor pixilation and focusing. The goal of the present study was to provide a method of quantitating improvement in tracking performance as well as to reveal the physical underpinnings of detector design that impact tracking quality. The study employs a generalizable ideal observer methodology for the quantification of tumor tracking performance. The analysis is applied to study both the effect of increasing scintillator thickness on a standard, single-layer imager (SLI) design as well as the effect of MLI architecture on tracking performance. The present study uses the ideal observer signal-to-noise ratio (d') as a surrogate for tracking performance. We employ functions which model clinically relevant tasks and generalized frequency-domain imaging metrics to connect image quality with tumor tracking. A detection task for relevant Cartesian shapes (i.e., spheres and cylinders) was used to quantitate trackability of cases employing fiducial markers. Automated lung tumor tracking algorithms often leverage the differences in benign and malignant lung tissue textures. These types of algorithms (e.g., soft-tissue localization - STiL) were simulated by designing a discrimination task, which quantifies the differentiation of tissue textures, measured experimentally and fit as a power-law in trend (with exponent β) using a cohort of MV images of patient lungs. The modeled MTF and NPS were used to investigate the effect of scintillator thickness and MLI architecture on tumor tracking performance. Quantification of MV images of lung tissue as an inverse power-law with respect to frequency yields exponent values of β = 3.11 and 3.29 for benign and malignant tissues, respectively. Tracking performance with and without fiducials was found to be generally limited by quantum noise, a factor dominated by quantum detective efficiency (QDE). For generic SLI construction, increasing the scintillator thickness (gadolinium oxysulfide - GOS) from a standard 290 μm to 1720 μm reduces noise to about 10%. However, 81% of this reduction is appreciated between 290 and 1000 μm. In comparing MLI and SLI detectors of equivalent individual GOS layer thickness, the improvement in noise is equal to the number of layers in the detector (i.e., 4) with almost no difference in MTF. Further, improvement in tracking performance was slightly less than the square-root of the reduction in noise, approximately 84-90%. In comparing an MLI detector with an SLI with a GOS scintillator of equivalent total thickness, improvement in object detectability is approximately 34-39%. We have presented a novel method for quantification of tumor tracking quality and have applied this model to evaluate the performance of SLI and MLI EPID designs. We showed that improved tracking quality is primarily limited by improvements in NPS. When compared to very thick scintillator SLI, employing MLI architecture exhibits the same gains in QDE, but by mitigating the effect of optical Swank noise, results in more dramatic improvements in tracking performance. © 2017 American Association of Physicists in Medicine.

NOTE: A feasibility study of markerless fluoroscopic gating for lung cancer radiotherapy using 4DCT templates

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Cerviño, Laura I.; Jiang, Steve B.

2009-10-01

A major difficulty in conformal lung cancer radiotherapy is respiratory organ motion, which may cause clinically significant targeting errors. Respiratory-gated radiotherapy allows for more precise delivery of prescribed radiation dose to the tumor, while minimizing normal tissue complications. Gating based on external surrogates is limited by its lack of accuracy, while gating based on implanted fiducial markers is limited primarily by the risk of pneumothorax due to marker implantation. Techniques for fluoroscopic gating without implanted fiducial markers (markerless gating) have been developed. These techniques usually require a training fluoroscopic image dataset with marked tumor positions in the images, which limits their clinical implementation. To remove this requirement, this study presents a markerless fluoroscopic gating algorithm based on 4DCT templates. To generate gating signals, we explored the application of three similarity measures or scores between fluoroscopic images and the reference 4DCT template: un-normalized cross-correlation (CC), normalized cross-correlation (NCC) and normalized mutual information (NMI), as well as average intensity (AI) of the region of interest (ROI) in the fluoroscopic images. Performance was evaluated using fluoroscopic and 4DCT data from three lung cancer patients. On average, gating based on CC achieves the highest treatment accuracy given the same efficiency, with a high target coverage (average between 91.9% and 98.6%) for a wide range of nominal duty cycles (20-50%). AI works well for two patients out of three, but failed for the third patient due to interference from the heart. Gating based on NCC and NMI usually failed below 50% nominal duty cycle. Based on this preliminary study with three patients, we found that the proposed CC-based gating algorithm can generate accurate and robust gating signals when using 4DCT reference template. However, this observation is based on results obtained from a very limited dataset, and further investigation on a larger patient population has to be done before its clinical implementation.

Method for automatic localization of MR-visible markers using morphological image processing and conventional pulse sequences: feasibility for image-guided procedures.

PubMed

Busse, Harald; Trampel, Robert; Gründer, Wilfried; Moche, Michael; Kahn, Thomas

2007-10-01

To evaluate the feasibility and accuracy of an automated method to determine the 3D position of MR-visible markers. Inductively coupled RF coils were imaged in a whole-body 1.5T scanner using the body coil and two conventional gradient echo sequences (FLASH and TrueFISP) and large imaging volumes up to (300 mm(3)). To minimize background signals, a flip angle of approximately 1 degrees was used. Morphological 2D image processing in orthogonal scan planes was used to determine the 3D positions of a configuration of three fiducial markers (FMC). The accuracies of the marker positions and of the orientation of the plane defined by the FMC were evaluated at various distances r(M) from the isocenter. Fiducial marker detection with conventional equipment (pulse sequences, imaging coils) was very reliable and highly reproducible over a wide range of experimental conditions. For r(M)

SU-C-210-06: Quantitative Evaluation of Dosimetric Effects Resulting From Positional Variations of Pancreatic Tumor Volumes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, S; Sehgal, V; Wei, R

2015-06-15

Purpose: The aim of this study is to quantify dosimetric effects resulting from variation in pancreatic tumor position assessed by bony anatomy and implanted fiducial markers Methods: Twelve pancreatic cancer patients were retrospectively analyzed for this study. All patients received modulated arc therapy (VMAT) treatment using fiducial-based Image Guided Radiation Therapy (IGRT) to the intact pancreas. Using daily orthogonal kV and/or Cone beam CT images, the shift needed to co-register the daily pre-treatment images to reference CT from fiducial to bone (Fid-Bone) were recorded as Left-Right (LR), Anterior-Posterior (AP) and Superior-Inferior (SI). The original VMAT plan iso-center was shifted basedmore » on KV bone matching positions at 5 evenly spaced fractions. Dose coverage of the planning target volumes (PTVs) (V100%), mean dose to liver, kidney and stomach/duodenum were assessed in the modified plans. Results: A total of 306 fractions were analyzed. The absolute fiducial-bone positional shifts were greatest in the SI direction, (AP = 2.7 ± 3.0, LR = 2.8 ± 2.8, and SI 6.3 ± 7.9 mm, mean ± SD). The V100% was significantly reduced by 13.5%, (Fid-Bone = 95.3 ± 2.0 vs. 82.3 ± 11.8%, p=0.02). This varied widely among patients (Fid-Bone V100% Range = 2–60%), where 33% of patients had a reduction in V100% of more than 10%. The impact on OARs was greatest to the liver (Fid-Bone= 14.6 vs. 16.1 Gy, 10%), and stomach, (Fid-Bone = 23.9 vx. 25.5 Gy, 7%), however was not statistically significant (p=0.10 both). Conclusion: Compared to matching by fiducial markers, matching by bony anatomy would have substantially reduced the PTV coverage by 13.5%. This reinforces the importance of online position verification based on fiducial markers. Hence, implantation of fiducial markers is strongly recommended for pancreatic cancer patients undergoing intensity modulated radiation therapy treatments.« less

Object representation and magnetic moments in thin alkali films

NASA Astrophysics Data System (ADS)

Garrett, Douglas C.

2008-10-01

This thesis is broken into two parts a computer vision part and a solid state physics part. In the computer vision part of the thesis (chapters 1 through 5), the concept of an architecture is discussed with a review of what is known about the brain's visual architecture as it applies to object representation. With this in mind we review the two main types of architectures that are used in computer vision for object representation. A specific object representation is then implemented and optimized to solve a problem in object tracking. This representation is then used to derive the fiducial points of a face using two distinct methods. One using evolutionary algorithms and another by a Bayesian analysis of the feature responses drawn from a gallery of faces. The evolved fiducial representation is tested as a facial detection system. It is shown that the Bayesian analysis of facial images gives an entropy measure that can be used to further improve detection results in the facial detection system. In addition, two similarity metrics are explored in the context of facial detection. It is found that a normalized vector dot product substantially outperforms the Euclidean distance measure. The solid state part of the thesis is composed of two self contained chapters. An effort has been made to reduce the redundancies between the material but some will necessarily remain (i.e., short descriptions of the experimental setup). Both chapters deal with the phenomenon of magnetism of atomic impurities in and on thin metal host films. The important difference between the chapters, besides the results, lies in the experimental technique used to measure the magnetism. In chapter 6, thin films of Pb are covered in situ with sub monolayers of V, Mo and Co in the range between 0.01 and 1 monolayers. If the surface impurities are magnetic they will reduce the superconducting transition temperature of the Pb film. From the reduction of Tc the magnetic dephasing rate of the surface impurities 1/taus and their magnetic cross section sigmas are calculated. We find that single V surface impurities are magnetic while single Mo and Co impurities are non-magnetic. Co surface clusters are magnetic. In chapter 7, thin films of Na, K, Rb and Cs are quench condensed, then covered with 1/100 of a mono-layer of Ti and finally covered with the original host. The magnetization of the films is measured by means of the anomalous Hall effect. An anomalous Hall resistance RAHE is observed for Ti on the surface of K, Rb and Cs and for Ti inside of Cs. Essentially the RAHE varies linearly with the magnetic field and is inversely proportional to the inverse temperature. A small non-linearity of RAHE suggests a Ti moment of about 1microB.

The ESA FRM4DOAS project: Towards a quality-controlled MAXDOAS Centralized Processing System

NASA Astrophysics Data System (ADS)

Hendrick, Francois; Fayt, Caroline; Friess, Udo; Kreher, Karin; Piters, Ankie; Richter, Andreas; Wagner, Thomas; Cede, Alexander; Spinei, Elena; von Bismarck, Jonas; Fehr, Thorsten; Van Roozendael, Michel

2017-04-01

The Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations (FRM4DOAS) is a two-year project funded by the European Space Agency (ESA). Started in July 2016, FRM4DOAS aims at further harmonizing MAXDOAS measurements and data sets, through (1) the specification of best practices for instrument operation, (2) the selection of state-of-the art retrieval algorithms, procedures, and settings, (3) the demonstration of a centralised rapid-delivery (6-24h latency) processing system for MAXDOAS instruments to be operated within the international Network for the Detection of Atmospheric Composition Change (NDACC). The project also links with the Pandonia initiative. In a first phase, the system concentrates on the development of 3 key products: NO2 vertical profiles, total O3 and tropospheric HCHO profiles, which will be retrieved at 11 MAXDOAS pilot stations. The system will also be tested and validated on data from the CINDI-2 campaign, and designed to allow further extension after commissioning. These activities will help and guarantee that homogenous, fully traceable, and quality-controlled datasets are generated from reference ground-based UV-vis instruments, which will play a crucial role in the validation of future ESA/Copernicus Sentinel satellite missions S-5P, S-4, and S-5.

Combined use of backscattered and transmitted images in x-ray personnel screening systems

NASA Astrophysics Data System (ADS)

Tracey, B.; Schiefele, Markus; Alvino, Christopher; Miller, Eric; Al-Kofani, Omar

2012-06-01

Current aviation security relies heavily on personnel screening using X-ray backscatter systems or other advanced imaging technologies. Passenger privacy concerns and screening times can be reduced through the use of low-dose twosided X-ray backscatter (Bx) systems, which also have the ability to collect transmission (Tx) X-ray. Bx images reveal objects placed on the body, such as contraband and security threats, as well as anatomical features at or close to the surface, such as lungs cavities and bones. While the quality of the transmission images is lower than medical imagery due to the low X-ray dose, Tx images can be of significant value in interpreting features in the Bx images, such as lung cavities, which can cause false alarms in automated threat detection (ATD) algorithms. Here we demonstrate an ATD processing chain fusing both Tx and BX images. The approach employs automatically extracted fiducial points on the body and localized active contour methods to segments lungs in acquired Tx and Bx images. Additionally, we derive metrics from the Tx image can be related to the probability of observing internal body structure in the Bx image. The combined use of Tx and Bx data can enable improved overall system performance.

LISA: Astrophysics Out to z Approximately 10 with Low-Frequency Gravitational Waves

NASA Technical Reports Server (NTRS)

Stebbins, Robin T.

2008-01-01

This viewgraph presentation reviews the Laser Interferometer Space Antenna (LISA). LISA os a joint ESA-NASA project to design, build and operate a space-based gravitational wave detector. The 5 million Kilometer long detector will consist of three spacecraft orbiting the Sun in a triangular formation. Space-Time strains induced by gravitational waves are detected by measuring changes in the separation of fiducial masses with laser interferometry. LISA is expected to detect signals from merging massive black holes, compact stellar objects spiraling into super massive black holes in galactic nuclei, thousands of close binaries of compact objects in the Milky way and possible backgrounds of cosmological origin.

A semi-automated approach to derive elevation time-series and calculate glacier mass balance from historical aerial imagery

NASA Astrophysics Data System (ADS)

Whorton, E.; Headman, A.; Shean, D. E.; McCann, E.

2017-12-01

Understanding the implications of glacier recession on water resources in the western U.S. requires quantifying glacier mass change across large regions over several decades. Very few glaciers in North America have long-term continuous field measurements of glacier mass balance. However, systematic aerial photography campaigns began in 1957 on many glaciers in the western U.S. and Alaska. These historical, vertical aerial stereo-photographs documenting glacier evolution have recently become publically available. Digital elevation models (DEM) of the transient glacier surface preserved in each imagery timestamp can be derived, then differenced to calculate glacier volume and mass change to improve regional geodetic solutions of glacier mass balance. In order to batch process these data, we use Python-based algorithms and Agisoft Photoscan structure from motion (SfM) photogrammetry software to semi-automate DEM creation, and orthorectify and co-register historical aerial imagery in a high-performance computing environment. Scanned photographs are rotated to reduce scaling issues, cropped to the same size to remove fiducials, and batch histogram equalization is applied to improve image quality and aid pixel-matching algorithms using the Python library OpenCV. Processed photographs are then passed to Photoscan through the Photoscan Python library to create DEMs and orthoimagery. To extend the period of record, the elevation products are co-registered to each other, airborne LiDAR data, and DEMs derived from sub-meter commercial satellite imagery. With the exception of the placement of ground control points, the process is entirely automated with Python. Current research is focused on: one, applying these algorithms to create geodetic mass balance time series for the 90 photographed glaciers in Washington State and two, evaluating the minimal amount of positional information required in Photoscan to prevent distortion effects that cannot be addressed during co-registration. Feature tracking and identification utilities in OpenCV have the potential to automate the georeferencing process. We aim to develop an algorithm suite that is flexible enough to enable its use for many landscape change detection and analysis problems.

Topics in the Detection of Gravitational Waves from Compact Binary Inspirals

NASA Astrophysics Data System (ADS)

Kapadia, Shasvath Jagat

Orbiting compact binaries - such as binary black holes, binary neutron stars and neutron star-black hole binaries - are among the most promising sources of gravitational waves observable by ground-based interferometric detectors. Despite numerous sophisticated engineering techniques, the gravitational wave signals will be buried deep within noise generated by various instrumental and environmental processes, and need to be extracted via a signal processing technique referred to as matched filtering. Matched filtering requires large banks of signal templates that are faithful representations of the true gravitational waveforms produced by astrophysical binaries. The accurate and efficient production of templates is thus crucial to the success of signal processing and data analysis. To that end, the dissertation presents a numerical technique that calibrates existing analytical (Post-Newtonian) waveforms, which are relatively inexpensive, to more accurate fiducial waveforms that are computationally expensive to generate. The resulting waveform family is significantly more accurate than the analytical waveforms, without incurring additional computational costs of production. Certain kinds of transient background noise artefacts, called "glitches'', can masquerade as gravitational wave signals for short durations and throw-off the matched-filter algorithm. Identifying glitches from true gravitational wave signals is a highly non-trivial exercise in data analysis which has been attempted with varying degrees of success. We present here a machine-learning based approach that exploits the various attributes of glitches and signals within detector data to provide a classification scheme that is a significant improvement over previous methods. The dissertation concludes by investigating the possibility of detecting a non-linear DC imprint, called the Christodoulou memory, produced in the arms of ground-based interferometers by the recently detected gravitational waves. The memory, which is even smaller in amplitude than the primary (detected) gravitational waves, will almost certainly not be seen in the current detection event. Nevertheless, future space-based detectors will likely be sensitive enough to observe the memory.

Front lighted optical tooling method and apparatus

DOEpatents

Stone, William J.

1985-06-18

An optical tooling method and apparatus uses a front lighted shadowgraphic technique to enhance visual contrast of reflected light. The apparatus includes an optical assembly including a fiducial mark, such as cross hairs, reflecting polarized light with a first polarization, a polarizing element backing the fiducial mark and a reflective surface backing the polarizing element for reflecting polarized light bypassing the fiducial mark and traveling through the polarizing element. The light reflected by the reflecting surface is directed through a second pass of the polarizing element toward the frontal direction with a polarization differing from the polarization of the light reflected by the fiducial mark. When used as a tooling target, the optical assembly may be mounted directly to a reference surface or may be secured in a mounting, such as a magnetic mounting. The optical assembly may also be mounted in a plane defining structure and used as a spherometer in conjunction with an optical depth measuring instrument. A method of measuring a radius of curvature of an unknown surface includes positioning the spherometer on a surface between the surface and a depth measuring optical instrument. As the spherometer is frontally illuminated, the distance from the depth measuring instrument to the fiducial mark and the underlying surface are alternately measured and the difference in these measurements is used as the sagittal height to calculate a radius of curvature.

Generating Fiducial Cuts for CLAS E5

NASA Astrophysics Data System (ADS)

Greenholt, Kristen

2005-04-01

The Thomas Jefferson National Accelerator Facility, located in Newport News, Virginia, is home to CLAS (CEBAF Large Acceptance Spectrometer) which observes the scattering effects of high-energy collisions of an electron beam and a proton or deuteron target. When data are collected with CLAS, one of the properties measured is the cross-section, which is proportional to the number of events and the efficiency and inversely proportional to the solid angle. The efficiency, or acceptance of the detector, is the ratio between the data one expects to observe in an ideal detector and the data that we actually measure with the real CLAS detector. In outlying azimuthal regions, the efficiency is less clearly understood, which leads to measurements which are reliant on the conditions of the detector itself. In order to analyze data which fall in regions of stable and well-understood efficiency, we generated fiducial cuts on CLAS. Our fiducial cuts fit a function to the edges of regions of stable efficiency. These cuts enable us to focus on the data with good acceptance/efficiency. When examining at the fiducial cuts, we required stable efficiency, or flat regions, a good visual fit, a minimized chi squared, and a reasonable behavior in each in azimuthal versus polar angle plane for each electron-momentum bin. Generating these fiducial cuts enables us to focus on data from CLAS where the efficiency of the detector is well understood.

THE DETECTION RATE OF EARLY UV EMISSION FROM SUPERNOVAE: A DEDICATED GALEX/PTF SURVEY AND CALIBRATED THEORETICAL ESTIMATES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ganot, Noam; Gal-Yam, Avishay; Ofek, Eran O.

The radius and surface composition of an exploding massive star, as well as the explosion energy per unit mass, can be measured using early UV observations of core-collapse supernovae (SNe). We present the first results from a simultaneous GALEX/PTF search for early ultraviolet (UV) emission from SNe. Six SNe II and one Type II superluminous SN (SLSN-II) are clearly detected in the GALEX near-UV (NUV) data. We compare our detection rate with theoretical estimates based on early, shock-cooling UV light curves calculated from models that fit existing Swift and GALEX observations well, combined with volumetric SN rates. We find thatmore » our observations are in good agreement with calculated rates assuming that red supergiants (RSGs) explode with fiducial radii of 500 R{sub ⊙}, explosion energies of 10{sup 51} erg, and ejecta masses of 10 M{sub ⊙}. Exploding blue supergiants and Wolf–Rayet stars are poorly constrained. We describe how such observations can be used to derive the progenitor radius, surface composition, and explosion energy per unit mass of such SN events, and we demonstrate why UV observations are critical for such measurements. We use the fiducial RSG parameters to estimate the detection rate of SNe during the shock-cooling phase (<1 day after explosion) for several ground-based surveys (PTF, ZTF, and LSST). We show that the proposed wide-field UV explorer ULTRASAT mission is expected to find >85 SNe per year (∼0.5 SN per deg{sup 2}), independent of host galaxy extinction, down to an NUV detection limit of 21.5 mag AB. Our pilot GALEX/PTF project thus convincingly demonstrates that a dedicated, systematic SN survey at the NUV band is a compelling method to study how massive stars end their life.« less

redMaGiC: Selecting luminous red galaxies from the DES Science Verification data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rozo, E.; Rykoff, E. S.; Abate, A.

Here, we introduce redMaGiC, an automated algorithm for selecting luminous red galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the colour cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photo-zs are very nearly as accurate as the best machine learning-based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalogue sampling themore » redshift range z ϵ [0.2, 0.8]. Our fiducial sample has a comoving space density of 10 –3 (h –1 Mpc) –3, and a median photo-z bias (zspec – zphoto) and scatter (σz/(1 + z)) of 0.005 and 0.017, respectively. The corresponding 5σ outlier fraction is 1.4 per cent. We also test our algorithm with Sloan Digital Sky Survey Data Release 8 and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1 per cent level.« less

redMaGiC: Selecting luminous red galaxies from the DES Science Verification data

DOE PAGES

Rozo, E.; Rykoff, E. S.; Abate, A.; ...

2016-05-30

Here, we introduce redMaGiC, an automated algorithm for selecting luminous red galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the colour cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photo-zs are very nearly as accurate as the best machine learning-based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalogue sampling themore » redshift range z ϵ [0.2, 0.8]. Our fiducial sample has a comoving space density of 10 –3 (h –1 Mpc) –3, and a median photo-z bias (zspec – zphoto) and scatter (σz/(1 + z)) of 0.005 and 0.017, respectively. The corresponding 5σ outlier fraction is 1.4 per cent. We also test our algorithm with Sloan Digital Sky Survey Data Release 8 and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1 per cent level.« less

Specimen coordinate automated measuring machine/fiducial automated measuring machine

DOEpatents

Hedglen, Robert E.; Jacket, Howard S.; Schwartz, Allan I.

1991-01-01

The Specimen coordinate Automated Measuring Machine (SCAMM) and the Fiducial Automated Measuring Machine (FAMM) is a computer controlled metrology system capable of measuring length, width, and thickness, and of locating fiducial marks. SCAMM and FAMM have many similarities in their designs, and they can be converted from one to the other without taking them out of the hot cell. Both have means for: supporting a plurality of samples and a standard; controlling the movement of the samples in the +/- X and Y directions; determining the coordinates of the sample; compensating for temperature effects; and verifying the accuracy of the measurements and repeating as necessary. SCAMM and FAMM are designed to be used in hot cells.

SU-G-JeP1-11: Feasibility Study of Markerless Tracking Using Dual Energy Fluoroscopic Images for Real-Time Tumor-Tracking Radiotherapy System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shiinoki, T; Shibuya, K; Sawada, A

Purpose: The new real-time tumor-tracking radiotherapy (RTRT) system was installed in our institution. This system consists of two x-ray tubes and color image intensifiers (I.I.s). The fiducial marker which was implanted near the tumor was tracked using color fluoroscopic images. However, the implantation of the fiducial marker is very invasive. Color fluoroscopic images enable to increase the recognition of the tumor. However, these images were not suitable to track the tumor without fiducial marker. The purpose of this study was to investigate the feasibility of markerless tracking using dual energy colored fluoroscopic images for real-time tumor-tracking radiotherapy system. Methods: Themore » colored fluoroscopic images of static and moving phantom that had the simulated tumor (30 mm diameter sphere) were experimentally acquired using the RTRT system. The programmable respiratory motion phantom was driven using the sinusoidal pattern in cranio-caudal direction (Amplitude: 20 mm, Time: 4 s). The x-ray condition was set to 55 kV, 50 mA and 105 kV, 50 mA for low energy and high energy, respectively. Dual energy images were calculated based on the weighted logarithmic subtraction of high and low energy images of RGB images. The usefulness of dual energy imaging for real-time tracking with an automated template image matching algorithm was investigated. Results: Our proposed dual energy subtraction improve the contrast between tumor and background to suppress the bone structure. For static phantom, our results showed that high tracking accuracy using dual energy subtraction images. For moving phantom, our results showed that good tracking accuracy using dual energy subtraction images. However, tracking accuracy was dependent on tumor position, tumor size and x-ray conditions. Conclusion: We indicated that feasibility of markerless tracking using dual energy fluoroscopic images for real-time tumor-tracking radiotherapy system. Furthermore, it is needed to investigate the tracking accuracy using proposed dual energy subtraction images for clinical cases.« less

SU-E-J-97: Evaluation of Multi-Modality (CT/MR/PET) Image Registration Accuracy in Radiotherapy Planning.

PubMed

Sethi, A; Rusu, I; Surucu, M; Halama, J

2012-06-01

Evaluate accuracy of multi-modality image registration in radiotherapy planning process. A water-filled anthropomorphic head phantom containing eight 'donut-shaped' fiducial markers (3 internal + 5 external) was selected for this study. Seven image sets (3CTs, 3MRs and PET) of phantom were acquired and fused in a commercial treatment planning system. First, a narrow slice (0.75mm) baseline CT scan was acquired (CT1). Subsequently, the phantom was re-scanned with a coarse slice width = 1.5mm (CT2) and after subjecting phantom to rotation/displacement (CT3). Next, the phantom was scanned in a 1.5 Tesla MR scanner and three MR image sets (axial T1, axial T2, coronal T1) were acquired at 2mm slice width. Finally, the phantom and center of fiducials were doped with 18F and a PET scan was performed with 2mm cubic voxels. All image scans (CT/MR/PET) were fused to the baseline (CT1) data using automated mutual-information based fusion algorithm. Difference between centroids of fiducial markers in various image modalities was used to assess image registration accuracy. CT/CT image registration was superior to CT/MR and CT/PET: average CT/CT fusion error was found to be 0.64 ± 0.14 mm. Corresponding values for CT/MR and CT/PET fusion were 1.33 ± 0.71mm and 1.11 ± 0.37mm. Internal markers near the center of phantom fused better than external markers placed on the phantom surface. This was particularly true for the CT/MR and CT/PET. The inferior quality of external marker fusion indicates possible distortion effects toward the edges of MR image. Peripheral targets in the PET scan may be subject to parallax error caused by depth of interaction of photons in detectors. Current widespread use of multimodality imaging in radiotherapy planning calls for periodic quality assurance of image registration process. Such studies may help improve safety and accuracy in treatment planning. © 2012 American Association of Physicists in Medicine.

System for Measuring Flexing of a Large Spaceborne Structure

NASA Technical Reports Server (NTRS)

Scharf, Daniel; Kuhnert, Andreas; Kovalik, Joseph; Hadaegh, Fred; Shaddock, Daniel

2008-01-01

An optoelectronic metrology system is used for determining the attitude and flexing of a large spaceborne radar antenna or similar structure. The measurements are needed for accurate pointing of the antenna and correction and control of the phase of the radar signal wavefront. The system includes a dual-field-of-view star tracker; a laser ranging unit (LRU) and a position-sensitive-detector (PSD)-based camera mounted on an optical bench; and fiducial targets at various locations on the structure. The fiducial targets are illuminated in sequence by laser light coupled via optical fibers. The LRU and the PSD provide measurements of the position of each fiducial target in a reference frame attached to the optical bench. During routine operation, the star tracker utilizes one field of view and functions conventionally to determine the orientation of the optical bench. During operation in a calibration mode, the star tracker also utilizes its second field of view, which includes stars that are imaged alongside some of the fiducial targets in the PSD; in this mode, the PSD measurements are traceable to star measurements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayashida, Misa; Malac, Marek; Egerton, Ray F.

Electron tomography is a method whereby a three-dimensional reconstruction of a nanoscale object is obtained from a series of projected images measured in a transmission electron microscope. We developed an electron-diffraction method to measure the tilt and azimuth angles, with Kikuchi lines used to align a series of diffraction patterns obtained with each image of the tilt series. Since it is based on electron diffraction, the method is not affected by sample drift and is not sensitive to sample thickness, whereas tilt angle measurement and alignment using fiducial-marker methods are affected by both sample drift and thickness. The accuracy ofmore » the diffraction method benefits reconstructions with a large number of voxels, where both high spatial resolution and a large field of view are desired. The diffraction method allows both the tilt and azimuth angle to be measured, while fiducial marker methods typically treat the tilt and azimuth angle as an unknown parameter. The diffraction method can be also used to estimate the accuracy of the fiducial marker method, and the sample-stage accuracy. A nano-dot fiducial marker measurement differs from a diffraction measurement by no more than ±1°.« less

Measurement of W+W- production in association with one jet in proton-proton collisions at √{ s} = 8TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao de Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de La Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Grafström, P.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Hellman, S.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Hickling, R.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hinman, R. R.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Ince, T.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, B.; Jackson, P.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Jeanneau, F.; Jeanty, L.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, W. J.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneti, S.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kapliy, A.; Kar, D.; Karakostas, K.; Karamaoun, A.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-Zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; King, M.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koehler, N. M.; Koffas, T.; Koffeman, E.; Koi, T.; Kolanoski, H.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Kravchenko, A.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunigo, T.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; Leblanc, M.; Lecompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Leontsinis, S.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Leyko, A. M.; Leyton, M.; Li, B.; Li, C.; Li, H.; Li, H. L.; Li, L.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, H.; Liu, H.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; López, J. A.; Lopez Mateos, D.; Lopez Paredes, B.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; MacDonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, L.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti-Garcia, S.; Martin, B.; Martin, T. A.; Martin, V. J.; Martin Dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; McFayden, J. A.; McHedlidze, G.; McMahon, S. J.; McPherson, R. A.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Melo, M.; Meloni, F.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Mortensen, S. S.; Morvaj, L.; Mosidze, M.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Mueller, T.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murillo Quijada, J. A.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Grady, F.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paganini, M.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shirabe, S.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, M.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2016-12-01

The production of W boson pairs in association with one jet in pp collisions at √{ s} = 8 TeV is studied using data corresponding to an integrated luminosity of 20.3 fb-1 collected by the ATLAS detector during 2012 at the CERN Large Hadron Collider. The cross section is measured in a fiducial phase-space region defined by the presence of exactly one electron and one muon, missing transverse momentum and exactly one jet with a transverse momentum above 25 GeV and a pseudorapidity of | η | < 4.5. The leptons are required to have opposite electric charge and to pass transverse momentum and pseudorapidity requirements. The fiducial cross section is found to be σWWfid,1-jet = 136 ± 6 (stat) ± 14 (syst) ± 3 (lumi) fb. In combination with a previous measurement restricted to leptonic final states with no associated jets, the fiducial cross section of WW production with zero or one jet is measured to be σWWfid,≤1-jet = 511 ± 9 (stat) ± 26 (syst) ± 10 (lumi) fb. The ratio of fiducial cross sections in final states with one and zero jets is determined to be 0.36 ± 0.05. Finally, a total cross section extrapolated from the fiducial measurement of WW production with zero or one associated jet is reported. The measurements are compared to theoretical predictions and found in good agreement.

Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial

NASA Astrophysics Data System (ADS)

Moult, E.; Burdette, E. C.; Song, D. Y.; Abolmaesumi, P.; Fichtinger, G.; Fallavollita, P.

2011-03-01

Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a 2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose. Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and clinically tested segmentation-based method. Using 169 clinical C-arm images and a +/-10° and +/-10 mm random perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm (std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was found to be clinically robust based on human patient data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huguet, Florence; Department of Radiation Oncology, Hôpitaux Universitaires Paris Est, Hôpital Tenon, University Paris VI, Paris; Yorke, Ellen D.

Purpose: To assess intrafractional positional variations of pancreatic tumors using 4-dimensional computed tomography (4D-CT), their impact on gross tumor volume (GTV) coverage, the reliability of biliary stent, fiducial seeds, and the real-time position management (RPM) external marker as tumor surrogates for setup of respiratory gated treatment, and to build a correlative model of tumor motion. Methods and Materials: We analyzed the respiration-correlated 4D-CT images acquired during simulation of 36 patients with either a biliary stent (n=16) or implanted fiducials (n=20) who were treated with RPM respiratory gated intensity modulated radiation therapy for locally advanced pancreatic cancer. Respiratory displacement relative to end-exhalationmore » was measured for the GTV, the biliary stent, or fiducial seeds, and the RPM marker. The results were compared between the full respiratory cycle and the gating interval. Linear mixed model was used to assess the correlation of GTV motion with the potential surrogate markers. Results: The average ± SD GTV excursions were 0.3 ± 0.2 cm in the left-right direction, 0.6 ± 0.3 cm in the anterior-posterior direction, and 1.3 ± 0.7 cm in the superior-inferior direction. Gating around end-exhalation reduced GTV motion by 46% to 60%. D95% was at least the prescribed 56 Gy in 76% of patients. GTV displacement was associated with the RPM marker, the biliary stent, and the fiducial seeds. The correlation was better with fiducial seeds and with biliary stent. Conclusions: Respiratory gating reduced the margin necessary for radiation therapy for pancreatic tumors. GTV motion was well correlated with biliary stent or fiducial seed displacements, validating their use as surrogates for daily assessment of GTV position during treatment. A patient-specific internal target volume based on 4D-CT is recommended both for gated and not-gated treatment; otherwise, our model can be used to predict the degree of GTV motion.« less

Adequacy of inhale/exhale breathhold CT based ITV margins and image-guided registration for free-breathing pancreas and liver SBRT.

PubMed

Yang, Wensha; Fraass, Benedick A; Reznik, Robert; Nissen, Nicholas; Lo, Simon; Jamil, Laith H; Gupta, Kapil; Sandler, Howard; Tuli, Richard

2014-01-09

To evaluate use of breath-hold CTs and implanted fiducials for definition of the internal target volume (ITV) margin for upper abdominal stereotactic body radiation therapy (SBRT). To study the statistics of inter- and intra-fractional motion information. 11 patients treated with SBRT for locally advanced pancreatic cancer (LAPC) or liver cancer were included in the study. Patients underwent fiducial implantation, free-breathing CT and breath-hold CTs at end inhalation/exhalation. All patients were planned and treated with SBRT using volumetric modulated arc therapy (VMAT). Two margin strategies were studied: Strategy I uses PTV = ITV + 3 mm; Strategy II uses PTV = GTV + 1.5 cm. Both CBCT and kV orthogonal images were taken and analyzed for setup before patient treatments. Tumor motion statistics based on skeletal registration and on fiducial registration were analyzed by fitting to Gaussian functions. All 11 patients met SBRT planning dose constraints using strategy I. Average ITV margins for the 11 patients were 2 mm RL, 6 mm AP, and 6 mm SI. Skeletal registration resulted in high probability (RL = 69%, AP = 4.6%, SI = 39%) that part of the tumor will be outside the ITV. With the 3 mm ITV expansion (Strategy 1), the probability reduced to RL 32%, AP 0.3%, SI 20% for skeletal registration; and RL 1.2%, AP 0%, SI 7% for fiducial registration. All 7 pancreatic patients and 2 liver patients failed to meet SBRT dose constraints using strategy II. The liver dose was increased by 36% for the other 2 liver patients that met the SBRT dose constraints with strategy II. Image guidance matching to skeletal anatomy is inadequate for SBRT positioning in the upper abdomen and usage of fiducials is highly recommended. Even with fiducial implantation and definition of an ITV, a minimal 3 mm planning margin around the ITV is needed to accommodate intra-fractional uncertainties.

Multiple template-based fluoroscopic tracking of lung tumor mass without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Gregory C.; Alexander, Brian; Jiang, Steve B.

2007-10-01

Precise lung tumor localization in real time is particularly important for some motion management techniques, such as respiratory gating or beam tracking with a dynamic multi-leaf collimator, due to the reduced clinical tumor volume (CTV) to planning target volume (PTV) margin and/or the escalated dose. There might be large uncertainties in deriving tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using a template matching method (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007 Phys. Med. Biol. 52 741-55). In this paper, we present an extension of this method to multiple-template matching for directly tracking the lung tumor mass in fluoroscopy video. The basic idea is as follows: (i) during the patient setup session, a pair of orthogonal fluoroscopic image sequences are taken and processed off-line to generate a set of reference templates that correspond to different breathing phases and tumor positions; (ii) during treatment delivery, fluoroscopic images are continuously acquired and processed; (iii) the similarity between each reference template and the processed incoming image is calculated; (iv) the tumor position in the incoming image is then estimated by combining the tumor centroid coordinates in reference templates with proper weights based on the measured similarities. With different handling of image processing and similarity calculation, two such multiple-template tracking techniques have been developed: one based on motion-enhanced templates and Pearson's correlation score while the other based on eigen templates and mean-squared error. The developed techniques have been tested on six sequences of fluoroscopic images from six lung cancer patients against the reference tumor positions manually determined by a radiation oncologist. The tumor centroid coordinates automatically detected using both methods agree well with the manually marked reference locations. The eigenspace tracking method performs slightly better than the motion-enhanced method, with average localization errors less than 2 pixels (1 mm) and the error at a 95% confidence level of about 2-4 pixels (1-2 mm). This work demonstrates the feasibility of direct tracking of a lung tumor mass in fluoroscopic images without implanted fiducial markers using multiple reference templates.

Planck 2015 results. XII. Full focal plane simulations

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Castex, G.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Karakci, A.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Lindholm, V.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Welikala, N.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present the 8th full focal plane simulation set (FFP8), deployed in support of the Planck 2015 results. FFP8 consists of 10 fiducial mission realizations reduced to 18 144 maps, together with the most massive suite of Monte Carlo realizations of instrument noise and CMB ever generated, comprising 104 mission realizations reduced to about 106 maps. The resulting maps incorporate the dominant instrumental, scanning, and data analysis effects, and the remaining subdominant effects will be included in future updates. Generated at a cost of some 25 million CPU-hours spread across multiple high-performance-computing (HPC) platforms, FFP8 is used to validate and verify analysis algorithms and their implementations, and to remove biases from and quantify uncertainties in the results of analyses of the real data.

Measurement of W +W - production in association with one jet in proton–proton collisions at s = 8 TeV with the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

The production of Wboson pairs in association with one jet in pp collisions at √s = 8 TeV is studied using data corresponding to an integrated luminosity of 20.3 fb -1 collected by the ATLAS detector during 2012 at the CERN Large Hadron Collider. The cross section is measured in a fiducial phase-space region defined by the presence of exactly one electron and one muon, missing transverse momentum and exactly one jet with a transverse momentum above 25 GeV and a pseudorapidity of |η| < 4.5. The leptons are required to have opposite electric charge and to pass transverse momentum and pseudorapidity requirements. The fiducial cross section is found to be σmore » $$fid,≤1-jet\\atop{WW}$$= 136 ± 6 (stat)± 14 (syst)± 3 (lumi) fb. In combination with a previous measurement restricted to leptonic final states with no associated jets, the fiducial cross section of WW production with zero or one jet is measured to be σ $$fid,≤1-jet\\atop{WW}$$ = 511 ±9 (stat)±26 (syst)±10 (lumi) fb. The ratio of fiducial cross sections in final states with one and zero jets is determined to be 0.36 ±0.05. Finally, a total cross section extrapolated from the fiducial measurement of WW production with zero or one associated jet is reported. The measurements are compared to theoretical predictions and found in good agreement.« less

Measurement of W +W - production in association with one jet in proton–proton collisions at s = 8 TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2016-10-14

The production of Wboson pairs in association with one jet in pp collisions at √s = 8 TeV is studied using data corresponding to an integrated luminosity of 20.3 fb -1 collected by the ATLAS detector during 2012 at the CERN Large Hadron Collider. The cross section is measured in a fiducial phase-space region defined by the presence of exactly one electron and one muon, missing transverse momentum and exactly one jet with a transverse momentum above 25 GeV and a pseudorapidity of |η| < 4.5. The leptons are required to have opposite electric charge and to pass transverse momentum and pseudorapidity requirements. The fiducial cross section is found to be σmore » $$fid,≤1-jet\\atop{WW}$$= 136 ± 6 (stat)± 14 (syst)± 3 (lumi) fb. In combination with a previous measurement restricted to leptonic final states with no associated jets, the fiducial cross section of WW production with zero or one jet is measured to be σ $$fid,≤1-jet\\atop{WW}$$ = 511 ±9 (stat)±26 (syst)±10 (lumi) fb. The ratio of fiducial cross sections in final states with one and zero jets is determined to be 0.36 ±0.05. Finally, a total cross section extrapolated from the fiducial measurement of WW production with zero or one associated jet is reported. The measurements are compared to theoretical predictions and found in good agreement.« less

Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

PubMed Central

Rettmann, Maryam E.; Holmes, David R.; Kwartowitz, David M.; Gunawan, Mia; Johnson, Susan B.; Camp, Jon J.; Cameron, Bruce M.; Dalegrave, Charles; Kolasa, Mark W.; Packer, Douglas L.; Robb, Richard A.

2014-01-01

Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Data from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamic in vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration improved landmark-only registration provided the noise in the surface points is not excessively high. Increased variability on the landmark fiducials resulted in increased registration errors; however, refinement of the initial landmark registration by the surface-based algorithm can compensate for small initial misalignments. The surface-based registration algorithm is quite robust to noise on the surface points and continues to improve landmark registration even at high levels of noise on the surface points. Both the canine and patient studies also demonstrate that combined landmark and surface registration has lower errors than landmark registration alone. Conclusions: In this work, we describe a model for evaluating the impact of noise variability on the input parameters of a registration algorithm in the context of cardiac ablation therapy. The model can be used to predict both registration error as well as assess which inputs have the largest effect on registration accuracy. PMID:24506630

Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rettmann, Maryam E., E-mail: rettmann.maryam@mayo.edu; Holmes, David R.; Camp, Jon J.

2014-02-15

Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Datamore » from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamicin vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration improved landmark-only registration provided the noise in the surface points is not excessively high. Increased variability on the landmark fiducials resulted in increased registration errors; however, refinement of the initial landmark registration by the surface-based algorithm can compensate for small initial misalignments. The surface-based registration algorithm is quite robust to noise on the surface points and continues to improve landmark registration even at high levels of noise on the surface points. Both the canine and patient studies also demonstrate that combined landmark and surface registration has lower errors than landmark registration alone. Conclusions: In this work, we describe a model for evaluating the impact of noise variability on the input parameters of a registration algorithm in the context of cardiac ablation therapy. The model can be used to predict both registration error as well as assess which inputs have the largest effect on registration accuracy.« less

A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

PubMed Central

Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth; Suzuki, Ryusuke; Matsuura, Taeko; Toramatsu, Chie; Takao, Seishin; Nihongi, Hideaki; Shimizu, Shinichi; Umegaki, Kikuo; Shirato, Hiroki

2015-01-01

In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. PMID:25129556

The Core Mass Function in the Massive Protocluster G286.21+0.17 Revealed by ALMA

NASA Astrophysics Data System (ADS)

Cheng, Yu; Tan, Jonathan C.; Liu, Mengyao; Kong, Shuo; Lim, Wanggi; Andersen, Morten; Da Rio, Nicola

2018-02-01

We study the core mass function (CMF) of the massive protocluster G286.21+0.17 with the Atacama Large Millimeter/submillimeter Array via 1.3 mm continuum emission at a resolution of 1.″0 (2500 au). We have mapped a field of 5.‧3 × 5.‧3 centered on the protocluster clump. We measure the CMF in the central region, exploring various core detection algorithms, which give source numbers ranging from 60 to 125, depending on parameter selection. We estimate completeness corrections due to imperfect flux recovery and core identification via artificial core insertion experiments. For masses M ≳ 1 M ⊙, the fiducial dendrogram-identified CMF can be fit with a power law of the form dN/dlog M ∝ M ‑α with α ≃ 1.24 ± 0.17, slightly shallower than, but still consistent with, the index of the Salpeter stellar initial mass function of 1.35. Clumpfind-identified CMFs are significantly shallower with α ≃ 0.64 ± 0.13. While raw CMFs show a peak near 1 M ⊙, completeness-corrected CMFs are consistent with a single power law extending down to ∼0.5 M ⊙, with only a tentative indication of a shallowing of the slope around ∼1 M ⊙. We discuss the implications of these results for star and star cluster formation theories.

Massive gravity wrapped in the cosmic web

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shim, Junsup; Lee, Jounghun; Li, Baojiu, E-mail: jsshim@astro.snu.ac.kr, E-mail: jounghun@astro.snu.ac.kr

We study how the filamentary pattern of the cosmic web changes if the true gravity deviates from general relativity (GR) on a large scale. The f(R) gravity, whose strength is controlled to satisfy the current observational constraints on the cluster scale, is adopted as our fiducial model and a large, high-resolution N-body simulation is utilized for this study. By applying the minimal spanning tree algorithm to the halo catalogs from the simulation at various epochs, we identify the main stems of the rich superclusters located in the most prominent filamentary section of the cosmic web and determine their spatial extentsmore » per member cluster to be the degree of their straightness. It is found that the f(R) gravity has the effect of significantly bending the superclusters and that the effect becomes stronger as the universe evolves. Even in the case where the deviation from GR is too small to be detectable by any other observables, the degree of the supercluster straightness exhibits a conspicuous difference between the f(R) and the GR models. Our results also imply that the supercluster straightness could be a useful discriminator of f(R) gravity from the coupled dark energy since it is shown to evolve differently between the two models. As a final conclusion, the degree of the straightness of the rich superclusters should provide a powerful cosmological test of large scale gravity.« less

A Vibrating Wire System For Quadrupole Fiducialization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, Zachary

2010-12-13

A vibrating wire system is being developed to fiducialize the quadrupoles between undulator segments in the LCLS. This note provides a detailed analysis of the system. The LCLS will have quadrupoles between the undulator segments to keep the electron beam focused. If the quadrupoles are not centered on the beam axis, the beam will receive transverse kicks, causing it to deviate from the undulator axis. Beam based alignment will be used to move the quadrupoles onto a straight line, but an initial, conventional alignment must place the quadrupole centers on a straight line to 100 {micro}m. In the fiducialization stepmore » of the initial alignment, the position of the center of the quadrupole is measured relative to tooling balls on the outside of the quadrupole. The alignment crews then use the tooling balls to place the magnet in the tunnel. The required error on the location of the quadrupole center relative to the tooling balls must be less than 25 {micro}m. In this note, we analyze a system under construction for the quadrupole fiducialization. The system uses the vibrating wire technique to position a wire onto the quadrupole magnetic axis. The wire position is then related to tooling balls using wire position detectors. The tooling balls on the wire position detectors are finally related to tooling balls on the quadrupole to perform the fiducialization. The total 25 {micro}m fiducialization error must be divided between these three steps. The wire must be positioned onto the quadrupole magnetic axis to within 10 {micro}m, the wire position must be measured relative to tooling balls on the wire position detectors to within 15 {micro}m, and tooling balls on the wire position detectors must be related to tooling balls on the quadrupole to within 10 {micro}m. The techniques used in these three steps will be discussed. The note begins by discussing various quadrupole fiducialization techniques used in the past and discusses why the vibrating wire technique is our method of choice. We then give an overview of the measurement system showing how the vibrating wire is positioned onto the quadrupole axis, how the wire position detectors locate the wire relative to tooling balls without touching the wire, and how the tooling ball positions are all measured. The novel feature of this system is the vibrating wire which we discuss in depth. We analyze the wire dynamics and calculate the expected sensitivity of the system. The note should be an aid in debugging the system by providing calculations to compare measurements to.« less

A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias.

PubMed

Koa-Wing, Michael; Nakagawa, Hiroshi; Luther, Vishal; Jamil-Copley, Shahnaz; Linton, Nick; Sandler, Belinda; Qureshi, Norman; Peters, Nicholas S; Davies, D Wyn; Francis, Darrel P; Jackman, Warren; Kanagaratnam, Prapa

2015-11-15

Ripple Mapping (RM) is designed to overcome the limitations of existing isochronal 3D mapping systems by representing the intracardiac electrogram as a dynamic bar on a surface bipolar voltage map that changes in height according to the electrogram voltage-time relationship, relative to a fiduciary point. We tested the hypothesis that standard approaches to atrial tachycardia CARTO™ activation maps were inadequate for RM creation and interpretation. From the results, we aimed to develop an algorithm to optimize RMs for future prospective testing on a clinical RM platform. CARTO-XP™ activation maps from atrial tachycardia ablations were reviewed by two blinded assessors on an off-line RM workstation. Ripple Maps were graded according to a diagnostic confidence scale (Grade I - high confidence with clear pattern of activation through to Grade IV - non-diagnostic). The RM-based diagnoses were corroborated against the clinical diagnoses. 43 RMs from 14 patients were classified as Grade I (5 [11.5%]); Grade II (17 [39.5%]); Grade III (9 [21%]) and Grade IV (12 [28%]). Causes of low gradings/errors included the following: insufficient chamber point density; window-of-interest<100% of cycle length (CL); <95% tachycardia CL mapped; variability of CL and/or unstable fiducial reference marker; and suboptimal bar height and scar settings. A data collection and map interpretation algorithm has been developed to optimize Ripple Maps in atrial tachycardias. This algorithm requires prospective testing on a real-time clinical platform. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Methods And Systems For Using Reference Images In Acoustic Image Processing

DOEpatents

Moore, Thomas L.; Barter, Robert Henry

2005-01-04

A method and system of examining tissue are provided in which a field, including at least a portion of the tissue and one or more registration fiducials, is insonified. Scattered acoustic information, including both transmitted and reflected waves, is received from the field. A representation of the field, including both the tissue and the registration fiducials, is then derived from the received acoustic radiation.

SU-C-210-05: Evaluation of Robustness: Dosimetric Effects of Anatomical Changes During Fractionated Radiation Treatment of Pancreatic Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horst, A van der; Houweling, A C; Bijveld, M M C

2015-06-15

Purpose: Pancreatic tumors show large interfractional position variations. In addition, changes in gastrointestinal air volume and body contour take place during treatment. We aim to investigate the robustness of the clinical treatment plans by quantifying the dosimetric effects of these anatomical changes. Methods: Calculations were performed for up to now 3 pancreatic cancer patients who had intratumoral fiducials for daily CBCT-based positioning during their 3-week treatment. For each patient, deformable image registration of the planning CT was used to assign Hounsfield Units to each of the 13—15 CBCTs; air volumes and body contour were copied from CBCT. The clinical treatmentmore » plan was used (CTV-PTV margin = 10 mm; 36Gy; 10MV; 1 arc VMAT). Fraction dose distributions were calculated and accumulated. The V95% of the clinical target volume (CTV) and planning target volume (PTV) were analyzed, as well as the dose to stomach, duodenum and liver. Dose accumulation was done for patient positioning based on the fiducials (as clinically used) as well as for positioning based on bony anatomy. Results: For all three patients, the V95% of the CTV remained 100%, for both fiducial- and bony anatomy-based positioning. For fiducial-based positioning, dose to duodenum en stomach showed no discernable differences with planned dose. For bony anatomy-based positioning, the PTV V95% of the patient with the largest systematic difference in tumor position (patient 1) decreased to 85%; the liver Dmax increased from 33.5Gy (planned) to 35.5Gy. Conclusion: When using intratumoral fiducials, CTV dose coverage was only mildly affected by the daily anatomical changes. When using bony anatomy for patient positioning, we found a decline in PTV dose coverage due to the interfractional tumor position variations. Photon irradiation treatment plans for pancreatic tumors are robust to variations in body contour and gastrointestinal gas, but the use of fiducial-based daily position verification is imperative. This work was supported by the foundation Bergh in het Zadel through the Dutch Cancer Society (KWF Kankerbestrijding) project No. UVA 2011-5271.« less

SU-E-J-165: Dosimetric Impact of Liver Rotations in Stereotactic Body Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinnaduwage, D; Paulsson, A; Sudhyadhom, A

2015-06-15

Purpose: Often in liver stereotactic body radiotherapy a single fiducial is implanted near the tumor for image-guided treatment delivery. In such cases, rotational corrections are calculated based on the spine. This study quantifies rotational differences between the spine and liver, and investigates the corresponding dosimetric impact. Methods: Seven patients with 3 intrahepatic fiducials and 4DCT scans were identified. The planning CT was separately co-registered with 4 phases of the 4DCT (0%, 50%, 100% inhale and 50% exhale) by 1) rigid registration of the spine, and 2) point-based registration of the 3 fiducials. Rotation vectors were calculated for each registration. Translationalmore » differences in fiducial positions between the 2 registrations methods were investigated. Dosimetric impact due to liver rotations and deformations was assessed using critical structures delineated on the 4DCT phases. For dose comparisons, a single fiducial was translationally aligned following spine alignment to represent what is typically done in the clinic. Results: On average, differences between spine and liver rotations during the 0%, 50%, 100% inhale, and 50% exhale phases were 3.23°, 3.27°, 2.26° and 3.11° (pitch), 3.00°, 2.24°, 3.12° and 1.73° (roll), and 1.57°, 1.98°, 2.09° and 1.36° (yaw), respectively. The maximum difference in rotations was 12°, with differences of >3° seen in 14/28 (pitch), 10/28 (roll), and 6/28 (yaw) cases. Average fiducial displacements of 2.73 (craniocaudal), 1.04 (lateral) and 1.82 mm (vertical) were seen. Evaluating percent dose differences for 5 patients at the peaks of the respiratory cycle, the maximum dose to the duodenum, stomach, bowel and esophagus differed on average by 11.4%, 5.3%, 11.2% and 49.1% between the 2 registration methods. Conclusion: Lack of accounting for liver rotation during treatment might Result in clinically significant dose differences to critical structures. Both rotational and translational deviations should be considered in planning margins when using spine alignment for liver treatments.« less

Free-breathing conformal irradiation of pancreatic cancer.

PubMed

Solla, Ignazio; Zucca, Sergio; Possanzini, Marco; Piras, Sara; Pusceddu, Claudio; Porru, Sergio; Meleddu, Gianfranco; Farace, Paolo

2013-07-08

The purpose of this study was to assess treatment margins in free-breathing irradiation of pancreatic cancer after bone alignment, and evaluate their impact on conformal radiotherapy. Fifteen patients with adenocarcinoma of the head of the pancreas underwent implantation of single fiducial marker. Intrafraction uncertainties were assessed on simulation four-dimensional computed tomography (4D CT) by calculating maximal intrafraction fiducial excursion (MIFE). In the first ten patients, after bony alignment, the position of the fiducial was identified on weekly acquired megavolt cone-beam CT (MV-CBCT). The interfraction residual uncertainties were estimated by measuring the fiducial displacements with respect to the position in the first session. Patient mean (pM) and patient standard deviation (pSD) of fiducial displacement, mean (μM) and standard deviation (μSD) of pM, and root-mean-square of pSD (σ(res)) were calculated. In the other five patients, MIFE was added to the residual component to obtain personalized margin. In these patients, conformal kidney sparing (CONKISS) irradiation was planned prescribing 54/45 Gy to PTV1/PTV2. The organ-at-risk limits were set according to current NCCN recommendation. No morbidity related to the fiducial marker implantation was recorded. In the first ten patients, along right-left, anterior-posterior, and inferior-superior directions, MIFE was variable (mean ± std = 0.24 ± 0.13 cm, 0.31 ± 0.14 cm, 0.83 ± 0.35 cm, respectively) and was at most 0.51, 0.53, and 1.56 cm, respectively. Along the same directions, μM were 0.09, -0.05, -0.05 cm, μSD were 0.30, 0.17, 0.33 cm, and σ(res) were 0.35, 0.26, and 0.30 cm, respectively. MIFE was not correlated with pM and pSD. In the five additional patients, it was possible to satisfy recommended dose limits, with the exception of slightly higher doses to small bowel. After bony alignment, the margins for target expansion can be obtained by adding personalized MIFE to the residual interfraction term. Using these margins, conformal free-breathing irradiation is a reliable option for the treatment of pancreatic cancer.

Free‐breathing conformal irradiation of pancreatic cancer

PubMed Central

Solla, Ignazio; Zucca, Sergio; Possanzini, Marco; Piras, Sara; Pusceddu, Claudio; Porru, Sergio; Meleddu, Gianfranco

2013-01-01

The purpose of this study was to assess treatment margins in free‐breathing irradiation of pancreatic cancer after bone alignment, and evaluate their impact on conformal radiotherapy. Fifteen patients with adenocarcinoma of the head of the pancreas underwent implantation of single fiducial marker. Intrafraction uncertainties were assessed on simulation four‐dimensional computed tomography (4D CT) by calculating maximal intrafraction fiducial excursion (MIFE). In the first ten patients, after bony alignment, the position of the fiducial was identified on weekly acquired megavolt cone‐beam CT (MV‐CBCT). The interfraction residual uncertainties were estimated by measuring the fiducial displacements with respect to the position in the first session. Patient mean (pM) and patient standard deviation (pSD) of fiducial displacement, mean (μM) and standard deviation (μSD) of pM, and root‐mean‐square of pSD (σres) were calculated. In the other five patients, MIFE was added to the residual component to obtain personalized margin. In these patients, conformal kidney sparing (CONKISS) irradiation was planned prescribing 54/45 Gy to PTV1/PTV2. The organ‐at‐risk limits were set according to current NCCN recommendation. No morbidity related to the fiducial marker implantation was recorded. In the first ten patients, along right–left, anterior–posterior, and inferior–superior directions, MIFE was variable (mean±std=0.24±0.13cm,0.31±0.14cm,0.83±0.35cm, respectively) and was at most 0.51, 0.53, and 1.56 cm, respectively. Along the same directions, μM were 0.09,−0.05,−0.05cm,μSD were 0.30, 0.17, 0.33 cm, and σres were 0.35, 0.26, and 0.30 cm, respectively. MIFE was not correlated with pM and pSD. In the five additional patients, it was possible to satisfy recommended dose limits, with the exception of slightly higher doses to small bowel. After bony alignment, the margins for target expansion can be obtained by adding personalized MIFE to the residual interfraction term. Using these margins, conformal free‐breathing irradiation is a reliable option for the treatment of pancreatic cancer. PACS number: 87.55.D‐ PMID:23835380

An anthropomorphic abdominal phantom for deformable image registration accuracy validation in adaptive radiation therapy.

PubMed

Liao, Yuliang; Wang, Linjing; Xu, Xiangdong; Chen, Haibin; Chen, Jiawei; Zhang, Guoqian; Lei, Huaiyu; Wang, Ruihao; Zhang, Shuxu; Gu, Xuejun; Zhen, Xin; Zhou, Linghong

2017-06-01

To design and construct a three-dimensional (3D) anthropomorphic abdominal phantom for geometric accuracy and dose summation accuracy evaluations of deformable image registration (DIR) algorithms for adaptive radiation therapy (ART). Organ molds, including liver, kidney, spleen, stomach, vertebra, and two metastasis tumors, were 3D printed using contours from an ovarian cancer patient. The organ molds were molded with deformable gels made of different mixtures of polyvinyl chloride (PVC) and the softener dioctyl terephthalate. Gels with different densities were obtained by a polynomial fitting curve that described the relation between the Hounsfield unit (HU) and PVC-softener blending ratio. The rigid vertebras were constructed by molding of white cement and cellulose pulp. The final abdominal phantom was assembled by arranging all the fabricated organs inside a hollow dummy according to their anatomies, and sealed by deformable gel with averaged HU of muscle and fat. Fiducial landmarks were embedded inside the phantom for spatial accuracy and dose accumulation accuracy studies. Two channels were excavated to facilitate ionization chamber insertion for dosimetric measurements. Phantom properties such as deformable gel elasticity and HU stability were studied. The dosimetric measurement accuracy in the phantom was performed, and the DIR accuracies of three DIR algorithms available in the open source DIR toolkit-DIRART were also validated. The constructed deformable gel showed elastic behavior and was stable in HU values over times, proving to be a practical material for the deformable phantom. The constructed abdominal phantom consisted of realistic anatomies in terms of both anatomical shapes and densities when compared with its reference patient. The dosimetric measurements showed a good agreement with the calculated doses from the treatment planning system. Fiducial-based accuracy analysis conducted on the constructed phantom demonstrated the feasibility of applying the phantom for organ-wise DIR accuracy assessment. We have designed and constructed an anthropomorphic abdominal deformable phantom with satisfactory elastic property, realistic organ density, and anatomy. This physical phantom can be used for routine validations of DIR geometric accuracy and dose accumulation accuracy in ART. © 2017 American Association of Physicists in Medicine.

Fiducial marker placement via conventional or electromagnetic navigation bronchoscopy (ENB): an interdisciplinary approach to the curative management of lung cancer.

PubMed

Hagmeyer, Lars; Priegnitz, Christina; Kocher, Martin; Schilcher, Burkhart; Budach, Wilfried; Treml, Marcel; Stieglitz, Sven; Randerath, Winfried

2016-05-01

Conventional and electromagnetic navigation bronchoscopy (ENB) is generally used as a diagnostic tool in suspicious pulmonary nodules. The use of this technique for the placement of fiducial markers in patients with inoperable but early-stage lung cancer could present an innovative approach enabling risk-reduced therapy. We present seven clinical cases where conventional bronchoscopy and ENB were used as part of an experimental interdisciplinary approach to clinical management and therapy planning. In each case, we analyzed the clinical indication, endoscopic procedures and post-interventional outcome. In six patients (three females, three males) with peripheral non-small cell lung cancer (NSCLC), stage cT1cN0cM0, surgery and conventional stereotactic radiation therapy was not possible because of end-stage chronic obstructive pulmonary disease. ENB was used for fiducial marker placement prior to cyberknife radiotherapy. No procedure-related complications were observed. Complete remission could be achieved in four cases, partial remission in two cases and no relevant complications induced by radiotherapy were observed. In one male patient, an endoluminal relapse in the right lower lobe was diagnosed following a right upper lobe resection for a NSCLC. The tumor could not be clearly identified by computerized tomography, so that the bronchoscopic placement of a fiducial marker in the tumor was performed in order to allow stereotactic radiochemotherapy, by which complete remission could be achieved. Fiducial marker placement may be an interesting bronchoscopic technique in the interdisciplinary therapeutic approach to inoperable early-stage lung cancer. In the described cases, therapy planning was successful and no procedure-related complications were observed. © 2014 John Wiley & Sons Ltd.

Clinical outcome of fiducial-less CyberKnife radiosurgery for stage I non-small cell lung cancer

PubMed Central

Jung, In-Hye; Jung, Jinhong; Cho, Byungchul; Kwak, Jungwon; Je, Hyoung Uk; Choi, Wonsik; Jung, Nuri Hyun; Kim, Su Ssan; Choi, Eun Kyung

2015-01-01

Purpose To evaluate the treatment results in early stage non-small cell lung cancer patients who have undergone fiducial-less CyberKnife radiosurgery (CKRS). Materials and Methods From June 2011 to November 2013, 58 patients underwent CKRS at Asan Medical Center for stage I lung cancer. After excluding 14 patients, we retrospectively reviewed the records of the remaining 44 patients. All analyses were performed using SPSS ver. 21. Results The median age at diagnosis was 75 years. Most patients had inoperable primary lung cancer with a poor pulmonary function test with comorbidity or old age. The clinical stage was IA in 30 patients (68.2%), IB in 14 (31.8%). The mean tumor size was 2.6 cm (range, 1.2 to 4.8 cm), and the tumor was smaller than 2 cm in 12 patients (27.3%). The radiation dose given was 48-60 Gy in 3-4 fractions. In a median follow-up of 23.1 months, local recurrence occurred in three patients (2-year local recurrence-free survival rate, 90.4%) and distant metastasis occurred in 13 patients. All patients tolerated the radiosurgery well, only two patients developing grade 3 dyspnea. The most common complications were radiation-induced fibrosis and pneumonitis. Eight patients died due to cancer progression. Conclusion The results showed that fiducial-less CKRS shows comparable local tumor control and survival rates to those of LINAC-based SABR or CKRS with a fiducial marker. Thus, fiducial-less CKRS using Xsight lung tracking system can be effectively and safely performed for patients with medically inoperable stage I non-small cell lung cancer without any risk of procedure-related complication. PMID:26157678

Validation of the Spatial Accuracy of the ExacTracRTM Adaptive Gating System

NASA Astrophysics Data System (ADS)

Twork, Gregory

Stereotactic body radiation therapy (SBRT) is a method of treatment that is used in extracranial locations, including the abdominal and thoracic cavities, as well as spinal and paraspinal locations. At the McGill University Health Centre, liver SBRT treatments include gating, which places the treatment beam on a duty cycle controlled by tracking of fiducial markers moving with the patient's breathing cycle. Respiratory gated treatments aim to spare normal tissue, while delivering a dose properly to a moving target. The ExacTracRTM system (BrainLAB AG Germany) is an image-guided radiotherapy system consisting of a combination of infra-red (IR) cameras and dual kilovoltage (kV) X-ray tubes. The IR system is used to track patient positioning and respiratory motion, while the kV X-rays are used to determine a positional shift based on internal anatomy or fiducial markers. In order to validate the system's ability to treat under gating conditions, each step of the SBRT process was evaluated quantitatively. Initially the system was tested under ideal static conditions, followed by a study including gated parameters. The uncertainties of the isocenters, positioning algorithm, planning computed tomography (CT) and four dimensional CT (4DCT) scans, gating window size and tumor motion were evaluated for their contributions to the total uncertainty in treatment. The mechanical isocenter and 4DCT were found to be the largest sources of uncertainty. However, for tumors with large internal amplitudes (>2.25 cm) that are treated with large gating windows (>30%) the gating parameters can contribute more than 1.1 +/- 1.8 mm.

Constraints on Pacific plate kinematics and dynamics with global positioning system measurements

NASA Technical Reports Server (NTRS)

Dixon, T. H.; Golombek, M. P.; Thornton, C. L.

1985-01-01

A measurement program designed to investigate kinematic and dynamic aspects of plate tectonics in the Pacific region by means of satellite observations is proposed. Accuracy studies are summarized showing that for short baselines (less than 100 km), the measuring accuracy of global positioning system (GPS) receivers can be in the centimeter range. For longer baselines, uncertainty in the orbital ephemerides of the GPS satellites could be a major source of error. Simultaneous observations at widely (about 300 km) separated fiducial stations over the Pacific region, should permit an accuracy in the centimeter range for baselines of up to several thousand kilometers. The optimum performance level is based on the assumption of that fiducial baselines are known a priori to the centimeter range. An example fiducial network for a GPS study of the South Pacific region is described.

Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy

NASA Astrophysics Data System (ADS)

Maspero, Matteo; van den Berg, Cornelis A. T.; Zijlstra, Frank; Sikkes, Gonda G.; de Boer, Hans C. J.; Meijer, Gert J.; Kerkmeijer, Linda G. W.; Viergever, Max A.; Lagendijk, Jan J. W.; Seevinck, Peter R.

2017-10-01

An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of 1.1 × 1.1 × 1.2 mm3 and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.

Detection of esophageal fiducial marker displacement during radiation therapy with a 2-dimensional on-board imager: analysis of internal margin for esophageal cancer.

PubMed

Fukada, Junichi; Hanada, Takashi; Kawaguchi, Osamu; Ohashi, Toshio; Takeuchi, Hiroya; Kitagawa, Yuko; Seki, Satoshi; Shiraishi, Yutaka; Ogata, Haruhiko; Shigematsu, Naoyuki

2013-03-15

To quantify the interfraction displacement of esophageal fiducial markers for primary esophageal cancer radiation therapy. Orthogonal 2-dimensional (2D) matching records fused to vertebrae were analyzed in clinically staged T1/2N0 esophageal cancer patients undergoing endoscopic clipping as fiducial metal markers. Displacement of the markers between the digitally reconstructed radiographs and on-board kilovoltage images during radiation therapy was analyzed according to direction and esophageal site. Forty-four patients, with 81 markers (10 proximal, 42 middle, and 29 distal), underwent 367 2D matching sessions during radiation therapy. The mean (SD) absolute marker displacement was 0.26 (0.30) cm in the right-left (RL), 0.50 (0.39) cm in the superior-inferior (SI), and 0.24 (0.21) cm in the anterior-posterior (AP) direction. Displacement was significantly larger in the SI than in the RL and AP directions (P<.0001). In the SI direction, mean absolute displacements of the distal, middle, and proximal esophagus were 0.67 (0.45) cm, 0.42 (0.32) cm, and 0.36 (0.30) cm, respectively. Distal esophagus displacement was significantly larger than those of the middle and proximal esophagus (P<.0001). The estimated internal margin to cover 95% of the cases was 0.75 cm in the RL and AP directions. In the SI direction, the margin was 1.25 cm for the proximal and middle esophagus and 1.75 cm for the distal esophagus. The magnitude of interfraction displacement of esophageal clips was larger in the SI direction, particularly in the distal esophagus, but substantial displacement was observed in other directions and at other esophageal sites. It is practical to take estimated movements into account with internal margins, even if vertebrae-based 2D matching is performed. Copyright © 2013 Elsevier Inc. All rights reserved.

SU-F-T-252: An Investigation of Gamma Knife Frame Definition Error When Using a Pre-Planning Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, P

Purpose: To determine causal factors related to high frame definition error when treating GK patients using a pre-planning workflow. Methods: 160 cases were retrospectively reviewed. All patients received treatment using a pre-planning workflow whereby stereotactic coordinates are determined from a CT scan acquired after framing using a fiducial box. The planning software automatically detects the fiducials and compares their location to expected values based on the rigid design of the fiducial system. Any difference is reported as mean and maximum frame definition error. The manufacturer recommends these values be less than 1.0 mm and 1.5 mm. In this study, framemore » definition error was analyzed in comparison with a variety of factors including which neurosurgeon/oncologist/physicist was involved with the procedure, number of post used during framing (3 or 4), type of lesion, and which CT scanner was utilized for acquisition. An analysis of variance (ANOVA) approach was used to statistically evaluate the data and determine causal factors related to instances of high frame definition error. Results: Two factors were identified as significant: number of post (p=0.0003) and CT scanner (p=0.0001). Further analysis showed that one of the four scanners was significantly different than the others. This diagnostic scanner was identified as an older model with localization lasers not tightly calibrated. The average value for maximum frame definition error using this scanner was 1.48 mm (4 posts) and 1.75 mm (3 posts). For the other scanners this value was 1.13 mm (4 posts) and 1.40 mm (3 posts). Conclusion: In utilizing a pre-planning workflow the choice of CT scanner matters. Any scanner utilized for GK should undergo routine QA at a level appropriate for radiation oncology. In terms of 3 vs 4 post, it is hypothesized that three posts provide less stability during CT acquisition. This will be tested in future work.« less

Detection of Esophageal Fiducial Marker Displacement During Radiation Therapy With a 2-dimensional On-board Imager: Analysis of Internal Margin for Esophageal Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fukada, Junichi, E-mail: fukada@rad.med.keio.ac.jp; Hanada, Takashi; Kawaguchi, Osamu

Purpose: To quantify the interfraction displacement of esophageal fiducial markers for primary esophageal cancer radiation therapy. Methods and Materials: Orthogonal 2-dimensional (2D) matching records fused to vertebrae were analyzed in clinically staged T1/2N0 esophageal cancer patients undergoing endoscopic clipping as fiducial metal markers. Displacement of the markers between the digitally reconstructed radiographs and on-board kilovoltage images during radiation therapy was analyzed according to direction and esophageal site. Results: Forty-four patients, with 81 markers (10 proximal, 42 middle, and 29 distal), underwent 367 2D matching sessions during radiation therapy. The mean (SD) absolute marker displacement was 0.26 (0.30) cm in themore » right–left (RL), 0.50 (0.39) cm in the superior–inferior (SI), and 0.24 (0.21) cm in the anterior–posterior (AP) direction. Displacement was significantly larger in the SI than in the RL and AP directions (P<.0001). In the SI direction, mean absolute displacements of the distal, middle, and proximal esophagus were 0.67 (0.45) cm, 0.42 (0.32) cm, and 0.36 (0.30) cm, respectively. Distal esophagus displacement was significantly larger than those of the middle and proximal esophagus (P<.0001). The estimated internal margin to cover 95% of the cases was 0.75 cm in the RL and AP directions. In the SI direction, the margin was 1.25 cm for the proximal and middle esophagus and 1.75 cm for the distal esophagus. Conclusions: The magnitude of interfraction displacement of esophageal clips was larger in the SI direction, particularly in the distal esophagus, but substantial displacement was observed in other directions and at other esophageal sites. It is practical to take estimated movements into account with internal margins, even if vertebrae-based 2D matching is performed.« less

SU-E-J-42: Motion Adaptive Image Filter for Low Dose X-Ray Fluoroscopy in the Real-Time Tumor-Tracking Radiotherapy System.

PubMed

Miyamoto, N; Ishikawa, M; Sutherland, K; Suzuki, R; Matsuura, T; Takao, S; Toramatsu, C; Nihongi, H; Shimizu, S; Onimaru, R; Umegaki, K; Shirato, H

2012-06-01

In the real-time tumor-tracking radiotherapy system, fiducial markers are detected by X-ray fluoroscopy. The fluoroscopic parameters should be optimized as low as possible in order to reduce unnecessary imaging dose. However, the fiducial markers could not be recognized due to effect of statistical noise in low dose imaging. Image processing is envisioned to be a solution to improve image quality and to maintain tracking accuracy. In this study, a recursive image filter adapted to target motion is proposed. A fluoroscopy system was used for the experiment. A spherical gold marker was used as a fiducial marker. About 450 fluoroscopic images of the marker were recorded. In order to mimic respiratory motion of the marker, the images were shifted sequentially. The tube voltage, current and exposure duration were fixed at 65 kV, 50 mA and 2.5 msec as low dose imaging condition, respectively. The tube current was 100 mA as high dose imaging. A pattern recognition score (PRS) ranging from 0 to 100 and image registration error were investigated by performing template pattern matching to each sequential image. The results with and without image processing were compared. In low dose imaging, theimage registration error and the PRS without the image processing were 2.15±1.21 pixel and 46.67±6.40, respectively. Those with the image processing were 1.48±0.82 pixel and 67.80±4.51, respectively. There was nosignificant difference in the image registration error and the PRS between the results of low dose imaging with the image processing and that of high dose imaging without the image processing. The results showed that the recursive filter was effective in order to maintain marker tracking stability and accuracy in low dose fluoroscopy. © 2012 American Association of Physicists in Medicine.

Planck 2015 results: XII. Full focal plane simulations

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

In this paper, we present the 8th full focal plane simulation set (FFP8), deployed in support of the Planck 2015 results. FFP8 consists of 10 fiducial mission realizations reduced to 18 144 maps, together with the most massive suite of Monte Carlo realizations of instrument noise and CMB ever generated, comprising 10 4 mission realizations reduced to about 10 6 maps. The resulting maps incorporate the dominant instrumental, scanning, and data analysis effects, and the remaining subdominant effects will be included in future updates. Finally, generated at a cost of some 25 million CPU-hours spread across multiple high-performance-computing (HPC) platforms,more » FFP8 is used to validate and verify analysis algorithms and their implementations, and to remove biases from and quantify uncertainties in the results of analyses of the real data.« less

Multi-camera digital image correlation method with distributed fields of view

NASA Astrophysics Data System (ADS)

Malowany, Krzysztof; Malesa, Marcin; Kowaluk, Tomasz; Kujawinska, Malgorzata

2017-11-01

A multi-camera digital image correlation (DIC) method and system for measurements of large engineering objects with distributed, non-overlapping areas of interest are described. The data obtained with individual 3D DIC systems are stitched by an algorithm which utilizes the positions of fiducial markers determined simultaneously by Stereo-DIC units and laser tracker. The proposed calibration method enables reliable determination of transformations between local (3D DIC) and global coordinate systems. The applicability of the method was proven during in-situ measurements of a hall made of arch-shaped (18 m span) self-supporting metal-plates. The proposed method is highly recommended for 3D measurements of shape and displacements of large and complex engineering objects made from multiple directions and it provides the suitable accuracy of data for further advanced structural integrity analysis of such objects.

Preclinical investigation for developing injectable fiducial markers using a mixture of BaSO{sub 4} and biodegradable polymer for proton therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahn, Sang Hee; Gil, Moon Soo; Lee, Doo Sung

Purpose: The aim of this study is to investigate the use of mixture of BaSO{sub 4} and biodegradable polymer as an injectable nonmetallic fiducial marker to reduce artifacts in x-ray images, decrease the absorbed dose distortion in proton therapy, and replace permanent metal markers. Methods: Two samples were made with 90 wt. % polymer phosphate buffer saline (PBS) and 10 wt. % BaSO{sub 4} (B1) or 20 wt. % BaSO{sub 4} (B2). Two animal models (mice and rats) were used. To test the injectability and in vivo gelation, a volume of 200 μl at a pH 5.8 were injected intomore » the Sprague-Dawley rats. After sacrificing the rats over time, the authors checked the gel morphology. Detectability of the markers in the x-ray images was tested for two sizes (diameters of 1 and 2 mm) for B1 and B2. Four samples were injected into BALB/C mice. The polymer mixed with BaSO{sub 4} transform from SOL at 20 °C with a pH of 6.0 to GEL in the living body at 37 °C with a pH of 7.4, so the size of the fiducial marker could be controlled by adjusting the injected volume. The detectability of the BaSO{sub 4} marker was measured in x-ray images of cone beam CT (CBCT), on-board imager [anterior–posterior (AP), lateral], and fluoroscopy (AP, lateral) using a Novalis-TX (Varian Medical Systems, Palo Alto, CA) repeatedly over 4 months. The volume, HU, and artifacts for the markers were measured in the CBCT images. Artifacts were compared to those of gold marker by analyzing the HU distribution. The dose distortion in proton therapy was computed by using a Monte Carlo (MC) code. A cylindrical shaped marker (diameter: 1 or 2 mm, length: 3 mm) made of gold, stainless-steel [304], titanium, and 20 wt. % BaSO{sub 4} was positioned at the center of the spread-out Bragg peak (SOBP) in parallel or perpendicular to the beam entrance. The dose distortion was measured on the depth dose profile across the markers. Results: Transformation to GEL and the biodegradation were verified. All BaSO{sub 4} markers could be detected in the CBCT. In the OBI and fluoroscopy images, all markers visible in the AP, but only B2(2 mm) could be identified in the lateral images. Changes of BaSO{sub 4} position were not detected in vivo (mice). The volume of the markers decreased by up to 65% and the HU increased by 22%, on average. The mean HU values around the B1, B2, and gold markers were 121.30 [standard deviation (SD): 54.86], 126.31 (SD: 62.13), and 1070.7 (SD: 235.16), respectively. The MC-simulated dose distortion for the BaSO{sub 4} markers was less than that of the commercially used markers. The dose reduction due to the gold marker was largest (15.05%) followed by stainless steel (7.92%) and titanium (6.92%). Dose reduction by B2 (2 mm) was 4.75% and 0.53% in parallel and perpendicular orientations, respectively. Conclusions: BaSO{sub 4} mixed with PBS is a good contrast agent in biodegradable polymer marker because of minimal artifacts in x-ray images and minimal dose reduction in proton therapy. The flexibility of the size is considered to be an advantage of this material over solid type fiducials.« less

Propagation and stability characteristics of a 500-m-long laser-based fiducial line for high-precision alignment of long-distance linear accelerators.

PubMed

Suwada, Tsuyoshi; Satoh, Masanori; Telada, Souichi; Minoshima, Kaoru

2013-09-01

A laser-based alignment system with a He-Ne laser has been newly developed in order to precisely align accelerator units at the KEKB injector linac. The laser beam was first implemented as a 500-m-long fiducial straight line for alignment measurements. We experimentally investigated the propagation and stability characteristics of the laser beam passing through laser pipes in vacuum. The pointing stability at the last fiducial point was successfully obtained with the transverse displacements of ±40 μm level in one standard deviation by applying a feedback control. This pointing stability corresponds to an angle of ±0.08 μrad. This report contains a detailed description of the experimental investigation for the propagation and stability characteristics of the laser beam in the laser-based alignment system for long-distance linear accelerators.

Propagation and stability characteristics of a 500-m-long laser-based fiducial line for high-precision alignment of long-distance linear accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suwada, Tsuyoshi; Satoh, Masanori; Telada, Souichi

2013-09-15

A laser-based alignment system with a He-Ne laser has been newly developed in order to precisely align accelerator units at the KEKB injector linac. The laser beam was first implemented as a 500-m-long fiducial straight line for alignment measurements. We experimentally investigated the propagation and stability characteristics of the laser beam passing through laser pipes in vacuum. The pointing stability at the last fiducial point was successfully obtained with the transverse displacements of ±40 μm level in one standard deviation by applying a feedback control. This pointing stability corresponds to an angle of ±0.08 μrad. This report contains a detailedmore » description of the experimental investigation for the propagation and stability characteristics of the laser beam in the laser-based alignment system for long-distance linear accelerators.« less

A method to track rotational motion for use in single-molecule biophysics.

PubMed

Lipfert, Jan; Kerssemakers, Jacob J W; Rojer, Maylon; Dekker, Nynke H

2011-10-01

The double helical nature of DNA links many cellular processes such as DNA replication, transcription, and repair to rotational motion and the accumulation of torsional strain. Magnetic tweezers (MTs) are a single-molecule technique that enables the application of precisely calibrated stretching forces to nucleic acid tethers and to control their rotational motion. However, conventional magnetic tweezers do not directly monitor rotation or measure torque. Here, we describe a method to directly measure rotational motion of particles in MT. The method relies on attaching small, non-magnetic beads to the magnetic beads to act as fiducial markers for rotational tracking. CCD images of the beads are analyzed with a tracking algorithm specifically designed to minimize crosstalk between translational and rotational motion: first, the in-plane center position of the magnetic bead is determined with a kernel-based tracker, while subsequently the height and rotation angle of the bead are determined via correlation-based algorithms. Evaluation of the tracking algorithm using both simulated images and recorded images of surface-immobilized beads demonstrates a rotational resolution of 0.1°, while maintaining a translational resolution of 1-2 nm. Example traces of the rotational fluctuations exhibited by DNA-tethered beads confined in magnetic potentials of varying stiffness demonstrate the robustness of the method and the potential for simultaneous tracking of multiple beads. Our rotation tracking algorithm enables the extension of MTs to magnetic torque tweezers (MTT) to directly measure the torque in single molecules. In addition, we envision uses of the algorithm in a range of biophysical measurements, including further extensions of MT, tethered particle motion, and optical trapping measurements.

Autonomous Vision-Based Tethered-Assisted Rover Docking

NASA Technical Reports Server (NTRS)

Tsai, Dorian; Nesnas, Issa A.D.; Zarzhitsky, Dimitri

2013-01-01

Many intriguing science discoveries on planetary surfaces, such as the seasonal flows on crater walls and skylight entrances to lava tubes, are at sites that are currently inaccessible to state-of-the-art rovers. The in situ exploration of such sites is likely to require a tethered platform both for mechanical support and for providing power and communication. Mother/daughter architectures have been investigated where a mother deploys a tethered daughter into extreme terrains. Deploying and retracting a tethered daughter requires undocking and re-docking of the daughter to the mother, with the latter being the challenging part. In this paper, we describe a vision-based tether-assisted algorithm for the autonomous re-docking of a daughter to its mother following an extreme terrain excursion. The algorithm uses fiducials mounted on the mother to improve the reliability and accuracy of estimating the pose of the mother relative to the daughter. The tether that is anchored by the mother helps the docking process and increases the system's tolerance to pose uncertainties by mechanically aligning the mating parts in the final docking phase. A preliminary version of the algorithm was developed and field-tested on the Axel rover in the JPL Mars Yard. The algorithm achieved an 80% success rate in 40 experiments in both firm and loose soils and starting from up to 6 m away at up to 40 deg radial angle and 20 deg relative heading. The algorithm does not rely on an initial estimate of the relative pose. The preliminary results are promising and help retire the risk associated with the autonomous docking process enabling consideration in future martian and lunar missions.

ESARR: enhanced situational awareness via road sign recognition

NASA Astrophysics Data System (ADS)

Perlin, V. E.; Johnson, D. B.; Rohde, M. M.; Lupa, R. M.; Fiorani, G.; Mohammad, S.

2010-04-01

The enhanced situational awareness via road sign recognition (ESARR) system provides vehicle position estimates in the absence of GPS signal via automated processing of roadway fiducials (primarily directional road signs). Sign images are detected and extracted from vehicle-mounted camera system, and preprocessed and read via a custom optical character recognition (OCR) system specifically designed to cope with low quality input imagery. Vehicle motion and 3D scene geometry estimation enables efficient and robust sign detection with low false alarm rates. Multi-level text processing coupled with GIS database validation enables effective interpretation even of extremely low resolution low contrast sign images. In this paper, ESARR development progress will be reported on, including the design and architecture, image processing framework, localization methodologies, and results to date. Highlights of the real-time vehicle-based directional road-sign detection and interpretation system will be described along with the challenges and progress in overcoming them.

Development of an advanced antineutrino detector for reactor monitoring

DOE PAGES

Classen, T.; Bernstein, A.; Bowden, N. S.; ...

2014-11-05

We present the development of a compact antineutrino detector for the purpose of nuclear reactor monitoring, improving upon a previously successful design. Our paper will describe the design improvements of the detector which increases the antineutrino detection efficiency threefold over the previous effort. There are two main design improvements over previous generations of detectors for nuclear reactor monitoring: dual-ended optical readout and single volume detection mass. The dual-ended optical readout eliminates the need for fiducialization and increases the uniformity of the detector's optical response. The containment of the detection mass in a single active volume provides more target mass permore » detector footprint, a key design criteria for operating within a nuclear power plant. This technology could allow for real-time monitoring of the evolution of a nuclear reactor core, independent of reactor operator declarations of fuel inventories, and may be of interest to the safeguards community.« less

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT

PubMed Central

Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B

2014-01-01

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second (fps) were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction. PMID:24710978

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT.

PubMed

Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B

2014-05-01

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

Measurements of fiducial cross-sections for $$t\\bar{t}$$ production with one or two additional b-jets in pp collisions at $$\\sqrt{s}$$ =8 TeV using the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.; Aad, G.; Abbott, B.

2016-01-07

Fiducial cross-sections formore » $$t\\bar{t}$$ production with one or two additional b-jets are reported, using an integrated luminosity of 20.3 fb -1 of proton-proton collisions at a centre-of-mass energy of 8 TeV at the Large Hadron Collider, collected with the ATLAS detector.« less

Global Geodesy Using GPS Without Fiducial Sites

NASA Technical Reports Server (NTRS)

Heflin, Michael B.; Blewitt, Geoffrey

1994-01-01

Global Positioning System, GPS, used to make global geodetic measurements without use of fiducial site coordinates. Baseline lengths and geocentric radii for each site determined without having to fix any site coordinates. Given n globally distributed sites, n baseline lengths and n geocentric radii form polyhedron with each site at vertex and with geocenter at intersection of all radii. Geodetic information derived from structure of polyhedron and its change with time. Approach applied to any global geodetic technique.

Measurement of the electroweak production of dijets in association with a Z-boson and distributions sensitive to vector boson fusion in proton-proton collisions at = 8 TeV using the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abajyan, T.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmad, A.; Ahmadov, F.; Aielli, G.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Gonzalez, B. Alvarez; Alviggi, M. G.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Ammosov, V. V.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belloni, A.; Beloborodova, O. L.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; De Mendizabal, J. Bilbao; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bolnet, N. M.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Branchini, P.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, G.; Brown, J.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Urbán, S. Cabrera; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarri, P.; Cameron, D.; Caminada, L. M.; Armadans, R. Caminal; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cantero, J.; Cantrill, R.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Castaneda-Miranda, E.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Barajas, C. A. Chavez; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; El Moursli, R. Cherkaoui; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Christidi, I. A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collins-Tooth, C.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Muiño, P. Conde; Coniavitis, E.; Conidi, M. C.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Ortuzar, M. Crispin; Cristinziani, M.; Crosetti, G.; Cuciuc, C.-M.; Almenar, C. Cuenca; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darlea, G. L.; Darmora, S.; Dassoulas, J. A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De La Taille, C.; De la Torre, H.; De Lorenzi, F.; De Nooij, L.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; De Zorzi, G.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Degenhardt, J.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Delemontex, T.; Deliot, F.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Domenico, A.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Wemans, A. Do Valle; Doan, T. K. O.; Dobos, D.; Dobson, E.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Anjos, A. Dos; Dotti, A.; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Dwuznik, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Curull, X. Espinal; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Perez, S. Fernandez; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; de Lima, D. E. Ferreira; Ferrer, A.; Ferrere, D.; Ferretti, C.; Parodi, A. Ferretto; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, J.; Fisher, M. J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Castillo, L. R. Flores; Bustos, A. C. Florez; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Torregrosa, E. Fullana; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gandrajula, R. P.; Gao, J.; Gao, Y. S.; Walls, F. M. Garay; Garberson, F.; García, C.; Navarro, J. E. García; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gianotti, F.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gillman, A. R.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giunta, M.; Gjelsten, B. K.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glazov, A.; Glonti, G. L.; Goblirsch-Kolb, M.; Goddard, J. R.; Godfrey, J.; Godlewski, J.; Goeringer, C.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Fajardo, L. S. Gomez; Gonçalo, R.; Da Costa, J. Goncalves Pinto Firmino; Gonella, L.; de la Hoz, S. González; Parra, G. Gonzalez; Silva, M. L. Gonzalez; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorfine, G.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Gozpinar, S.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, F.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Grebenyuk, O. G.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grigalashvili, N.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grishkevich, Y. V.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Groth-Jensen, J.; Grout, Z. J.; Grybel, K.; Guan, L.; Guescini, F.; Guest, D.; Gueta, O.; Guicheney, C.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Gunther, J.; Guo, J.; Gupta, S.; Gutierrez, P.; Ortiz, N. G. Gutierrez; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Haefner, P.; Hageboeck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Hall, D.; Halladjian, G.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamer, M.; Hamilton, A.; Hamilton, S.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Hanke, P.; Hansen, J. R.; Hansen, J. B.; Hansen, J. D.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Harkusha, S.; Harper, D.; Harrington, R. D.; Harris, O. M.; Harrison, P. F.; Hartjes, F.; Harvey, A.; Hasegawa, S.; Hasegawa, Y.; Hassani, S.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hawkins, A. D.; Hayashi, T.; Hayden, D.; Hays, C. P.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, L.; Heisterkamp, S.; Hejbal, J.; Helary, L.; Heller, C.; Heller, M.; Hellman, S.; Hellmich, D.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Hengler, C.; Henrichs, A.; Correia, A. M. Henriques; Henrot-Versille, S.; Hensel, C.; Herbert, G. H.; Jiménez, Y. Hernández; Herrberg-Schubert, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hofmann, J. I.; Hohlfeld, M.; Holmes, T. R.; Hong, T. M.; van Huysduynen, L. Hooft; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Hurwitz, M.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idarraga, J.; Ideal, E.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikematsu, K.; Ikeno, M.; Iliadis, D.; Ilic, N.; Inamaru, Y.; Ince, T.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Quiles, A. Irles; Isaksson, C.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ponce, J. M. Iturbe; Ivashin, A. V.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, J. N.; Jackson, M.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jakubek, J.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansen, H.; Janssen, J.; Janus, M.; Jarlskog, G.; Jeanty, L.; Jeng, G.-Y.; Plante, I. Jen-La; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Ji, H.; Ji, W.; Jia, J.; Jiang, Y.; Belenguer, M. Jimenez; Jin, S.; Jinaru, A.; Jinnouchi, O.; Joergensen, M. D.; Joffe, D.; Johansson, K. E.; Johansson, P.; Johns, K. A.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, T. J.; Jorge, P. M.; Joshi, K. D.; Jovicevic, J.; Ju, X.; Jung, C. A.; Jungst, R. M.; Jussel, P.; Rozas, A. Juste; Kaci, M.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kajomovitz, E.; Kama, S.; Kanaya, N.; Kaneda, M.; Kaneti, S.; Kanno, T.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kar, D.; Karakostas, K.; Karastathis, N.; Karnevskiy, M.; Karpov, S. N.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kashif, L.; Kasieczka, G.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Katre, A.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazama, S.; Kazanin, V. F.; Kazarinov, M. Y.; Keeler, R.; Keener, P. T.; Kehoe, R.; Keil, M.; Keller, J. S.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Kessoku, K.; Keung, J.; Khalil-zada, F.; Khandanyan, H.; Khanov, A.; Khodinov, A.; Khomich, A.; Khoo, T. J.; Khoriauli, G.; Khoroshilov, A.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kim, H.; Kim, S. H.; Kimura, N.; Kind, O.; King, B. T.; King, M.; King, R. S. B.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kitamura, T.; Kittelmann, T.; Kiuchi, K.; Kladiva, E.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klinkby, E. B.; Klioutchnikova, T.; Klok, P. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koenig, S.; Koevesarki, P.; Koffas, T.; Koffeman, E.; Kogan, L. A.; Kohlmann, S.; Kohout, Z.; Kohriki, T.; Koi, T.; Kolanoski, H.; Koletsou, I.; Koll, J.; Komar, A. A.; Komori, Y.; Kondo, T.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Korotkov, V. A.; Kortner, O.; Kortner, S.; Kostyukhin, V. V.; Kotov, S.; Kotov, V. M.; Kotwal, A.; Kourkoumelis, C.; Kouskoura, V.; Koutsman, A.; Kowalewski, R.; Kowalski, T. Z.; Kozanecki, W.; Kozhin, A. S.; Kral, V.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Kraus, J. K.; Kravchenko, A.; Kreiss, S.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Kruker, T.; Krumnack, N.; Krumshteyn, Z. V.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kuday, S.; Kuehn, S.; Kugel, A.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunkle, J.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kurumida, R.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; La Rosa, A.; La Rotonda, L.; Labarga, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Laier, H.; Laisne, E.; Lambourne, L.; Lampen, C. L.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lang, V. S.; Lange, C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lassnig, M.; Laurelli, P.; Lavorini, V.; Lavrijsen, W.; Laycock, P.; Le, B. T.; Le Dortz, O.; Le Guirriec, E.; Le Menedeu, E.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, H.; Lee, J. S. H.; Lee, S. C.; Lee, L.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmacher, M.; Miotto, G. Lehmann; Lei, X.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzen, G.; Lenzi, B.; Leone, R.; Leonhardt, K.; Leontsinis, S.; Leroy, C.; Lester, C. G.; Lester, C. M.; Levêque, J.; Levin, D.; Levinson, L. J.; Lewis, A.; Lewis, G. H.; Leyko, A. M.; Leyton, M.; Li, B.; Li, B.; Li, H.; Li, H. L.; Li, S.; Li, X.; Liang, Z.; Liao, H.; Liberti, B.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limbach, C.; Limosani, A.; Limper, M.; Lin, S. C.; Linde, F.; Lindquist, B. E.; Linnemann, J. T.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lissauer, D.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y.; Livan, M.; Livermore, S. S. A.; Lleres, A.; Merino, J. Llorente; Lloyd, S. L.; Sterzo, F. Lo; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loddenkoetter, T.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loginov, A.; Loh, C. W.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Lombardo, V. P.; Long, J. D.; Long, R. E.; Lopes, L.; Mateos, D. Lopez; Paredes, B. Lopez; Lorenz, J.; Martinez, N. Lorenzo; Losada, M.; Loscutoff, P.; Losty, M. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lowe, A. J.; Lu, F.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Ludwig, D.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lungwitz, M.; Lynn, D.; Lysak, R.; Lytken, E.; Ma, H.; Ma, L. L.; Maccarrone, G.; Macchiolo, A.; Maček, B.; Miguens, J. Machado; Macina, D.; Mackeprang, R.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeno, M.; Maeno, T.; Magradze, E.; Mahboubi, K.; Mahlstedt, J.; Mahmoud, S.; Maiani, C.; Maidantchik, C.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Mal, P.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyshev, V. M.; Malyukov, S.; Mamuzic, J.; Mandelli, B.; Mandelli, L.; Mandić, I.; Mandrysch, R.; Maneira, J.; Manfredini, A.; Manhaes de Andrade Filho, L.; Ramos, J. A. Manjarres; Mann, A.; Manning, P. M.; Manousakis-Katsikakis, A.; Mansoulie, B.; Mantifel, R.; Mapelli, L.; March, L.; Marchand, J. F.; Marchese, F.; Marchiori, G.; Marcisovsky, M.; Marino, C. P.; Marques, C. N.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti, L. F.; Marti-Garcia, S.; Martin, B.; Martin, B.; Martin, J. P.; Martin, T. A.; Martin, V. J.; dit Latour, B. Martin; Martinez, H.; Martinez, M.; Martin-Haugh, S.; Martyniuk, A. C.; Marx, M.; Marzano, F.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massol, N.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Matricon, P.; Matsunaga, H.; Matsushita, T.; Mättig, P.; Mättig, S.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazzaferro, L.; Goldrick, G. Mc; Kee, S. P. Mc; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McCubbin, N. A.; McFarlane, K. W.; Mcfayden, J. A.; Mchedlidze, G.; Mclaughlan, T.; McMahon, S. J.; McPherson, R. A.; Meade, A.; Mechnich, J.; Mechtel, M.; Medinnis, M.; Meehan, S.; Meera-Lebbai, R.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melachrinos, C.; Garcia, B. R. Mellado; Meloni, F.; Navas, L. Mendoza; Mengarelli, A.; Menke, S.; Meoni, E.; Mercurio, K. M.; Mergelmeyer, S.; Meric, N.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Merritt, H.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Middleton, R. P.; Migas, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Milstein, D.; Minaenko, A. A.; Moya, M. Miñano; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mirabelli, G.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Mitsui, S.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Mochizuki, K.; Moeller, V.; Mohapatra, S.; Mohr, W.; Molander, S.; Moles-Valls, R.; Mönig, K.; Monini, C.; Monk, J.; Monnier, E.; Berlingen, J. Montejo; Monticelli, F.; Monzani, S.; Moore, R. W.; Herrera, C. Mora; Moraes, A.; Morange, N.; Morel, J.; Moreno, D.; Llácer, M. Moreno; Morettini, P.; Morgenstern, M.; Morii, M.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Muanza, S. G.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, K.; Mueller, T.; Mueller, T.; Muenstermann, D.; Munwes, Y.; Quijada, J. A. Murillo; Murray, W. J.; Musto, E.; Myagkov, A. G.; Myska, M.; Nackenhorst, O.; Nadal, J.; Nagai, K.; Nagai, R.; Nagai, Y.; Nagano, K.; Nagarkar, A.; Nagasaka, Y.; Nagel, M.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Nanava, G.; Narayan, R.; Nattermann, T.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negri, G.; Negrini, M.; Nektarijevic, S.; Nelson, A.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neusiedl, A.; Neves, R. M.; Nevski, P.; Newcomer, F. M.; Newman, P. R.; Nguyen, D. H.; Nickerson, R. B.; Nicolaidou, R.; Nicquevert, B.; Nielsen, J.; Nikiforou, N.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Norberg, S.; Nordberg, M.; Novakova, J.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nuncio-Quiroz, A.-E.; Hanninger, G. Nunes; Nunnemann, T.; Nurse, E.; Nuti, F.; O'Brien, B. J.; O'grady, F.; O'Neil, D. C.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Ocariz, J.; Ochi, A.; Ochoa, M. I.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Ohshima, T.; Okamura, W.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Olchevski, A. G.; Pino, S. A. Olivares; Damazio, D. Oliveira; Garcia, E. Oliver; Olivito, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Barrera, C. Oropeza; Orr, R. S.; Osculati, B.; Ospanov, R.; y Garzon, G. Otero; Otono, H.; Ouchrif, M.; Ouellette, E. A.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Ovcharova, A.; Owen, M.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pages, A. Pacheco; Aranda, C. Padilla; Griso, S. Pagan; Paganis, E.; Pahl, C.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Vazquez, J. G. Panduro; Pani, P.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Hernandez, D. Paredes; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pasqualucci, E.; Passaggio, S.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N. D.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pearce, J.; Pedersen, M.; Lopez, S. Pedraza; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Peng, H.; Penning, B.; Penwell, J.; Perepelitsa, D. V.; Codina, E. Perez; García-Estañ, M. T. Pérez; Reale, V. Perez; Perini, L.; Pernegger, H.; Perrino, R.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, J.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Petteni, M.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Piec, S. M.; Piegaia, R.; Pignotti, D. T.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Pingel, A.; Pinto, B.; Pizio, C.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Poddar, S.; Podlyski, F.; Poettgen, R.; Poggioli, L.; Pohl, D.; Pohl, M.; Polesello, G.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Bueso, X. Portell; Pospelov, G. E.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Prabhu, R.; Pralavorio, P.; Pranko, A.; Prasad, S.; Pravahan, R.; Prell, S.; Price, D.; Price, J.; Price, L. E.; Prieur, D.; Primavera, M.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopapadaki, E.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Przysiezniak, H.; Ptacek, E.; Pueschel, E.; Puldon, D.; Purohit, M.; Puzo, P.; Pylypchenko, Y.; Qian, J.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Quilty, D.; Qureshi, A.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Ragusa, F.; Rahal, G.; Rajagopalan, S.; Rammensee, M.; Rammes, M.; Randle-Conde, A. S.; Rangel-Smith, C.; Rao, K.; Rauscher, F.; Rave, T. C.; Ravenscroft, T.; Raymond, M.; Read, A. L.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reinsch, A.; Reisin, H.; Relich, M.; Rembser, C.; Ren, Z. L.; Renaud, A.; Rescigno, M.; Resconi, S.; Resende, B.; Reznicek, P.; Rezvani, R.; Richter, R.; Ridel, M.; Rieck, P.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Santos, D. Roda Dos; Rodrigues, L.; Roe, S.; Røhne, O.; Rolli, S.; Romaniouk, A.; Romano, M.; Romeo, G.; Adam, E. Romero; Rompotis, N.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, A.; Rose, M.; Rosendahl, P. L.; Rosenthal, O.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rubinskiy, I.; Rud, V. I.; Rudolph, C.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Rutherfoord, J. P.; Ruthmann, N.; Ruzicka, P.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Saavedra, A. F.; Sacerdoti, S.; Saddique, A.; Sadeh, I.; Sadrozinski, H. F.-W.; Sadykov, R.; Tehrani, F. Safai; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Saleem, M.; Salek, D.; De Bruin, P. H. Sales; Salihagic, D.; Salnikov, A.; Salt, J.; Ferrando, B. M. Salvachua; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Martinez, V. Sanchez; Sandaker, H.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Castillo, I. Santoyo; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sartisohn, G.; Sasaki, O.; Sasaki, Y.; Satsounkevitch, I.; Sauvage, G.; Sauvan, E.; Savard, P.; Savu, D. O.; Sawyer, C.; Sawyer, L.; Saxon, D. H.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schaefer, R.; Schaelicke, A.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, C.; Schmitt, S.; Schneider, B.; Schnellbach, Y. J.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schorlemmer, A. L. S.; Schott, M.; Schouten, D.; Schovancova, J.; Schram, M.; Schramm, S.; Schreyer, M.; Schroeder, C.; Schuh, N.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwegler, Ph.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Schwoerer, M.; Sciacca, F. G.; Scifo, E.; Sciolla, G.; Scott, W. G.; Scuri, F.; Scutti, F.; Searcy, J.; Sedov, G.; Sedykh, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekula, S. J.; Selbach, K. E.; Seliverstov, D. M.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Serre, T.; Seuster, R.; Severini, H.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Sherwood, P.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shin, T.; Shiyakova, M.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Shushkevich, S.; Sicho, P.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simoniello, R.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skottowe, H. P.; Skovpen, K. Yu.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snow, J.; Snyder, S.; Sobie, R.; Socher, F.; Sodomka, J.; Soffer, A.; Soh, D. A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Camillocci, E. Solfaroli; Solodkov, A. A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopko, V.; Sopko, B.; Sosebee, M.; Soualah, R.; Soueid, P.; Soukharev, A. M.; South, D.; Spagnolo, S.; Spanò, F.; Spearman, W. R.; Spighi, R.; Spigo, G.; Spousta, M.; Spreitzer, T.; Spurlock, B.; Denis, R. D. St.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Stavina, P.; Steele, G.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Stucci, S. A.; Stugu, B.; Stumer, I.; Styles, N. A.; Su, D.; Su, J.; Subramania, HS.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Swedish, S.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tamsett, M. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tani, K.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teischinger, F. A.; Castanheira, M. Teixeira Dias; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thoma, S.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Topilin, N. D.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Tran, H. L.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Urbaniec, D.; Urquijo, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Gallego, E. Valladolid; Vallecorsa, S.; Ferrer, J. A. Valls; Van Berg, R.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; Van Der Leeuw, R.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Virzi, J.; Vitells, O.; Vivarelli, I.; Vaque, F. Vives; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Anh, T. Vu; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, W.; Wagner, P.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, X.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watanabe, I.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilkens, H. G.; Will, J. Z.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wittig, T.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wright, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xiao, M.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamada, M.; Yamaguchi, H.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yanush, S.; Yao, L.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yen, A. L.; Yildirim, E.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zaytsev, A.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; della Porta, G. Zevi; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, X.; Zhang, Z.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, L.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zitoun, R.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.

2014-04-01

Measurements of fiducial cross sections for the electroweak production of two jets in association with a Z-boson are presented. The measurements are performed using 20 .3 fb-1 of proton-proton collision data collected at a centre-of-mass energy of = 8 TeV by the ATLAS experiment at the Large Hadron Collider. The electroweak component is extracted by a fit to the dijet invariant mass distribution in a fiducial region chosen to enhance the electroweak contribution over the dominant background in which the jets are produced via the strong interaction. The electroweak cross sections measured in two fiducial regions are in good agreement with the Standard Model expectations and the background-only hypothesis is rejected with significance above the 5 σ level. The electroweak process includes the vector boson fusion production of a Z-boson and the data are used to place limits on anomalous triple gauge boson couplings. In addition, measurements of cross sections and differential distributions for inclusive Z-boson-plus-dijet production are performed in five fiducial regions, each with different sensitivity to the electroweak contribution. The results are corrected for detector effects and compared to predictions from the Sherpa and Powheg event generators. [Figure not available: see fulltext.

Radiosensitizer-eluting nanocoatings on gold fiducials for biological in-situ image-guided radio therapy (BIS-IGRT)

NASA Astrophysics Data System (ADS)

Nagesha, D. K.; Tada, D. B.; Stambaugh, C. K. K.; Gultepe, E.; Jost, E.; Levy, C. O.; Cormack, R.; Makrigiorgos, G. M.; Sridhar, S.

2010-10-01

Image-guided radiation treatments (IGRT) routinely utilize radio-opaque implantable devices, such as fiducials or brachytherapy spacers, for improved spatial accuracy. The therapeutic efficiency of IGRT can be further enhanced by biological in situ dose painting (BIS-IGRT) of radiosensitizers through localized delivery within the tumor using gold fiducial markers that have been coated with nanoporous polymer matrices loaded with nanoparticles (NPs). In this work, two approaches were studied: (i) a free drug release system consisting of Doxorubicin (Dox), a hydrophilic drug, loaded into a non-degradable polymer poly(methyl methacrylate) (PMMA) coating and (ii) poly(d,l-lactic-co-glycolic acid) (PLGA) NPs loaded with fluorescent Coumarin-6, serving as a model for a hydrophobic drug, in a biodegradable chitosan matrix. Temporal release kinetics measurements in buffer were carried out using fluorescence spectroscopy. In the first case of free Dox release, an initial release within the first few hours was followed by a sustained release over the course of the next 3 months. In the second platform, release of NPs and the free drug was controlled by the degradation rate of the chitosan matrix and PLGA. The results show that dosage and rate of release of these radiosensitizers coated on gold fiducials for IGRT can be precisely tailored to achieve the desired release profile for radiation therapy of cancer.

Kilovoltage Imaging of Implanted Fiducials to Monitor Intrafraction Motion With Abdominal Compression During Stereotactic Body Radiation Therapy for Gastrointestinal Tumors.

PubMed

Yorke, Ellen; Xiong, Ying; Han, Qian; Zhang, Pengpeng; Mageras, Gikas; Lovelock, Michael; Pham, Hai; Xiong, Jian-Ping; Goodman, Karyn A

2016-07-01

To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiation therapy (SBRT). A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during SBRT for abdominal tumors. Kilovoltage images were acquired at 5- to 6-second intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for 3 sessions for each patient. Intrafraction displacement patterns varied between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm, and 1.2% exceeded 0.75 cm. The calculated single-session dose to 95% of gross tumor volume differed from planned by an average of -1.2% (range, -11.1% to 4.8%) but only for 4 patients was the total 3-session calculated dose to 95% of gross tumor volume more than 3% different from planned. Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable. Copyright © 2015 Elsevier Inc. All rights reserved.

Kilovoltage imaging of implanted fiducials to monitor intrafraction motion with abdominal compression during stereotactic body radiotherapy for GI tumors

PubMed Central

Yorke, Ellen; Xiong, Ying; Han, Qian; Zhang, Pengpeng; Mageras, Gikas; Lovelock, Michael; Pham, Hai; Xiong, Jian-Ping; Goodman, Karyn A.

2017-01-01

Purpose/Objective To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiotherapy (sbrt). Methods and Materials A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during sbrt for abdominal tumors. Kilovoltage images were acquired at 5–6 sec intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for three sessions for each patient. Results Intrafraction displacement patterns varied between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm and 1.2% exceeded 0.75 cm. The calculated single session dose to 95% of gross tumor volume (GTVD95) differed from planned by an average of −1.2% (−11.1%−4.8%) but only for 4 patients was total 3-session calculated GTVD95 over 3% different from planned Conclusions Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable. PMID:26797539

Range verification for eye proton therapy based on proton-induced x-ray emissions from implanted metal markers

NASA Astrophysics Data System (ADS)

La Rosa, Vanessa; Kacperek, Andrzej; Royle, Gary; Gibson, Adam

2014-06-01

Metal fiducial markers are often implanted on the back of the eye before proton therapy to improve target localization and reduce patient setup errors. We aim to detect characteristic x-ray emissions from metal targets during proton therapy to verify the treatment range accuracy. Initially gold was chosen for its biocompatibility properties. Proton-induced x-ray emissions (PIXE) from a 15 mm diameter gold marker were detected at different penetration depths of a 59 MeV proton beam at the CATANA proton facility at INFN-LNS (Italy). The Monte Carlo code Geant4 was used to reproduce the experiment and to investigate the effect of different size markers, materials, and the response to both mono-energetic and fully modulated beams. The intensity of the emitted x-rays decreases with decreasing proton energy and thus decreases with depth. If we assume the range to be the depth at which the dose is reduced to 10% of its maximum value and we define the residual range as the distance between the marker and the range of the beam, then the minimum residual range which can be detected with 95% confidence level is the depth at which the PIXE peak is equal to 1.96 σbkg, which is the standard variation of the background noise. With our system and experimental setup this value is 3 mm, when 20 GyE are delivered to a gold marker of 15 mm diameter. Results from silver are more promising. Even when a 5 mm diameter silver marker is placed at a depth equal to the range, the PIXE peak is 2.1 σbkg. Although these quantitative results are dependent on the experimental setup used in this research study, they demonstrate that the real-time analysis of the PIXE emitted by fiducial metal markers can be used to derive beam range. Further analysis are needed to demonstrate the feasibility of the technique in a clinical setup.

Predictions of Planet Detections with Near-infrared Radial Velocities in the Upcoming SPIRou Legacy Survey-planet Search

NASA Astrophysics Data System (ADS)

Cloutier, Ryan; Artigau, Étienne; Delfosse, Xavier; Malo, Lison; Moutou, Claire; Doyon, René; Donati, Jean-Francois; Cumming, Andrew; Dumusque, Xavier; Hébrard, Élodie; Menou, Kristen

2018-02-01

The SPIRou near-infrared spectropolarimeter is destined to begin science operations at the Canada–France–Hawaii Telescope in mid-2018. One of the instrument’s primary science goals is to discover the closest exoplanets to the solar system by conducting a three- to five-year long radial velocity survey of nearby M dwarfs at an expected precision of ∼1 m s‑1, the SPIRou Legacy Survey-Planet Search (SLS-PS). In this study, we conduct a detailed Monte Carlo simulation of the SLS-PS using our current understanding of the occurrence rate of M dwarf planetary systems and physical models of stellar activity. From simultaneous modeling of planetary signals and activity, we predict the population of planets to be detected in the SLS-PS. With our fiducial survey strategy and expected instrument performance over a nominal survey length of ∼3 years, we expect SPIRou to detect {85.3}-12.4+29.3 planets including {20.0}-7.2+16.8 habitable-zone planets and {8.1}-3.2+7.6 Earth-like planets from a sample of 100 M1–M8.5 dwarfs out to 11 pc. By studying mid-to-late M dwarfs previously inaccessible to existing optical velocimeters, SPIRou will put meaningful constraints on the occurrence rate of planets around those stars including the value of {η }\\oplus at an expected level of precision of ≲ 45 % . We also predict that a subset of {46.7}-6.0+16.0 planets may be accessible with dedicated high-contrast imagers on the next generation of extremely large telescopes including {4.9}-2.0+4.7 potentially imagable Earth-like planets. Lastly, we compare the results of our fiducial survey strategy to other foreseeable survey versions to quantify which strategy is optimized to reach the SLS-PS science goals. The results of our simulations are made available to the community on GitHub (https://github.com/r-cloutier/SLSPS_Simulations).

Comparative imaging study in ultrasound, MRI, CT, and DSA using a multimodality renal artery phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, Deirdre M.; Fagan, Andrew J.; Moran, Carmel M.

2011-02-15

Purpose: A range of anatomically realistic multimodality renal artery phantoms consisting of vessels with varying degrees of stenosis was developed and evaluated using four imaging techniques currently used to detect renal artery stenosis (RAS). The spatial resolution required to visualize vascular geometry and the velocity detection performance required to adequately characterize blood flow in patients suffering from RAS are currently ill-defined, with the result that no one imaging modality has emerged as a gold standard technique for screening for this disease. Methods: The phantoms, which contained a range of stenosis values (0%, 30%, 50%, 70%, and 85%), were designed formore » use with ultrasound, magnetic resonance imaging, x-ray computed tomography, and x-ray digital subtraction angiography. The construction materials used were optimized with respect to their ultrasonic speed of sound and attenuation coefficient, MR relaxometry (T{sub 1},T{sub 2}) properties, and Hounsfield number/x-ray attenuation coefficient, with a design capable of tolerating high-pressure pulsatile flow. Fiducial targets, incorporated into the phantoms to allow for registration of images among modalities, were chosen to minimize geometric distortions. Results: High quality distortion-free images of the phantoms with good contrast between vessel lumen, fiducial markers, and background tissue to visualize all stenoses were obtained with each modality. Quantitative assessments of the grade of stenosis revealed significant discrepancies between modalities, with each underestimating the stenosis severity for the higher-stenosed phantoms (70% and 85%) by up to 14%, with the greatest discrepancy attributable to DSA. Conclusions: The design and construction of a range of anatomically realistic renal artery phantoms containing varying degrees of stenosis is described. Images obtained using the main four diagnostic techniques used to detect RAS were free from artifacts and exhibited adequate contrast to allow for quantitative measurements of the degree of stenosis in each phantom. Such multimodality phantoms may prove useful in evaluating current and emerging US, MRI, CT, and DSA technology.« less

Prospects for measuring cosmic microwave background spectral distortions in the presence of foregrounds

NASA Astrophysics Data System (ADS)

Abitbol, Maximilian H.; Chluba, Jens; Hill, J. Colin; Johnson, Bradley R.

2017-10-01

Measurements of cosmic microwave background (CMB) spectral distortions have profound implications for our understanding of physical processes taking place over a vast window in cosmological history. Foreground contamination is unavoidable in such measurements and detailed signal-foreground separation will be necessary to extract cosmological science. In this paper, we present Markov chain Monte Carlo based spectral distortion detection forecasts in the presence of Galactic and extragalactic foregrounds for a range of possible experimental configurations, focusing on the Primordial Inflation Explorer (PIXIE) as a fiducial concept. We consider modifications to the baseline PIXIE mission (operating ≃ 12 months in distortion mode), searching for optimal configurations using a Fisher approach. Using only spectral information, we forecast an extended PIXIE mission to detect the expected average non-relativistic and relativistic thermal Sunyaev-Zeldovich distortions at high significance (194σ and 11σ, respectively), even in the presence of foregrounds. The ΛCDM Silk damping μ-type distortion is not detected without additional modifications of the instrument or external data. Galactic synchrotron radiation is the most problematic source of contamination in this respect, an issue that could be mitigated by combining PIXIE data with future ground-based observations at low frequencies (ν ≲ 15-30 GHz). Assuming moderate external information on the synchrotron spectrum, we project an upper limit of |μ| < 3.6 × 10-7 (95 per cent c.l.), slightly more than one order of magnitude above the fiducial ΛCDM signal from the damping of small-scale primordial fluctuations, but a factor of ≃250 improvement over the current upper limit from COBE/Far Infrared Absolute Spectrophotometer. This limit could be further reduced to |μ| < 9.4 × 10-8 (95 per cent c.l.) with more optimistic assumptions about extra low-frequency information and would rule out many alternative inflation models and provide new constraints on decaying particle scenarios.

Comparison of human and algorithmic target detection in passive infrared imagery

NASA Astrophysics Data System (ADS)

Weber, Bruce A.; Hutchinson, Meredith

2003-09-01

We have designed an experiment that compares the performance of human observers and a scale-insensitive target detection algorithm that uses pixel level information for the detection of ground targets in passive infrared imagery. The test database contains targets near clutter whose detectability ranged from easy to very difficult. Results indicate that human observers detect more "easy-to-detect" targets, and with far fewer false alarms, than the algorithm. For "difficult-to-detect" targets, human and algorithm detection rates are considerably degraded, and algorithm false alarms excessive. Analysis of detections as a function of observer confidence shows that algorithm confidence attribution does not correspond to human attribution, and does not adequately correlate with correct detections. The best target detection score for any human observer was 84%, as compared to 55% for the algorithm for the same false alarm rate. At 81%, the maximum detection score for the algorithm, the same human observer had 6 false alarms per frame as compared to 29 for the algorithm. Detector ROC curves and observer-confidence analysis benchmarks the algorithm and provides insights into algorithm deficiencies and possible paths to improvement.

Spectral CT with metal artifacts reduction software for improvement of tumor visibility in the vicinity of gold fiducial markers.

PubMed

Brook, Olga R; Gourtsoyianni, Sofia; Brook, Alexander; Mahadevan, Anand; Wilcox, Carol; Raptopoulos, Vassilios

2012-06-01

To evaluate spectral computed tomography (CT) with metal artifacts reduction software (MARS) for reduction of metal artifacts associated with gold fiducial seeds. Thirteen consecutive patients with 37 fiducial seeds implanted for radiation therapy of abdominal lesions were included in this HIPAA-compliant, institutional review board-approved prospective study. Six patients were women (46%) and seven were men (54%). The mean age was 61.1 years (median, 58 years; range, 29-78 years). Spectral imaging was used for arterial phase CT. Images were reconstructed with and without MARS in axial, coronal, and sagittal planes. Two radiologists independently reviewed reconstructions and selected the best image, graded the visibility of the tumor, and assessed the amount of artifacts in all planes. A linear-weighted κ statistic and Wilcoxon signed-rank test were used to assess interobserver variability. Histogram analysis with the Kolmogorov-Smirnov test was used for objective evaluation of artifacts reduction. Fiducial seeds were placed in pancreas (n = 5), liver (n = 7), periportal lymph nodes (n = 1), and gallbladder bed (n = 1). MARS-reconstructed images received a better grade than those with standard reconstruction in 60% and 65% of patients by the first and second radiologist, respectively. Tumor visibility was graded higher with standard versus MARS reconstruction (grade, 3.7 ± 1.0 vs 2.8 ± 1.1; P = .001). Reduction of blooming was noted on MARS-reconstructed images (P = .01). Amount of artifacts, for both any and near field, was significantly smaller on sagittal and coronal MARS-reconstructed images than on standard reconstructions (P < .001 for all comparisons). Far-field artifacts were more prominent on axial MARS-reconstructed images than on standard reconstructions (P < .01). Linear-weighted κ statistic showed moderate to perfect agreement between radiologists. CT number distribution was narrower with MARS than with standard reconstruction in 35 of 37 patients (P < .001). Spectral CT with use of MARS improved tumor visibility in the vicinity of gold fiducial seeds.

Addressing the third gamma problem in PET

NASA Astrophysics Data System (ADS)

Schueller, M. J.; Mulnix, T. L.; Christian, B. T.; Jensen, M.; Holm, S.; Oakes, T. R.; Roberts, A. D.; Dick, D. W.; Martin, C. C.; Nickles, R. J.

2003-02-01

PET brings the promise of quantitative imaging of the in-vivo distribution of any positron emitting nuclide, a list with hundreds of candidates. All but a few of these, the "pure positron" emitters, have isotropic coincident gamma rays that give rise to misrepresented events in the sinogram and in the resulting reconstructed image. Of particular interest are /sup 10/C, /sup 14/O, /sup 38/K, /sup 52m/Mn, /sup 60/Cu, /sup 61/Cu, /sup 94m/Tc, and /sup 124/I, each having high-energy gammas that are Compton-scattered down into the 511 keV window. The problems arising from the "third gamma," and its accommodation by standard scatter correction algorithms, were studied empirically, employing three scanner models (CTI 933/04, CTI HR+ and GE Advance), imaging three phantoms (line source, NEMA scatter and contrast/detail), with /sup 18/F or /sup 38/K and /sup 72/As mimicking /sup 14/O and /sup 10/C, respectively, in 2-D and 3-D modes. Five findings emerge directly from the image analysis. The third gamma: 1) does, obviously, tax the single event rate of the PET scanners, particularly in the absence of septa, from activity outside of the axial field of view; 2) does, therefore, tax the random rate, which is second order in singles, although the gamma is a prompt coincidence partner; 3) does enter the sinogram as an additional flat background, like randoms, but unlike scatter; 4) is not seriously misrepresented by the scatter algorithm which fits the correction to the wings of the sinogram; and 5) does introduce additional statistical noise from the subsequent subtraction, but does not seriously compromise the detectability of lesions as seen in the contrast/detail phantom. As a safeguard against the loss of accuracy in image quantitation, fiducial sources of known activity are included in the field of view alongside of the subject. With this precaution, a much wider selection of imaging agents can enjoy the advantages of positron emission tomography.

The Long Baseline Neutrino Oscillation Experiment at DUSEL

NASA Astrophysics Data System (ADS)

Maricic, Jelena; Lbne Dusel Collaboration

2010-01-01

Rapid progress in neutrino physics in recent years has brought us closer to realization of a massive neutrino detector at the Deep Underground Science and Engineering Laboratory (DUSEL) in the Homestake mine in the town of Lead, South Dakota, USA. The detector is being designed with the following scientific goals in mind: value of CP-violation phase S in lepton sector, neutrino mass hierarchy and value of the angle θ13. In addition, the Long Baseline Neutrino Experiment (LBNE) will be able to search for proton decay, get a detailed energy spectrum in the case of galactic supernovae, detect solar and atmospheric neutrinos, possibly geoneutrinos and even relic supernovae neutrinos that have never been successfully detected before. The physics goals dictate the minimal size of 300 kton fiducial volume, and the plan is to realize it with three 100 kton fiducial volume modules that will be placed at the depth of 1480 m. LBNE will be able to obtain 3σ C.L. measurement of θ13 if the value of sin2 2θ13 >= 0.005 for any value of CP-δ phase; 3σ C.L. measurement of the neutrino mass hierarchy if sin2 2θ13 >= 0.012 for any value of CP-δ phase and measure 50% of all CP-δ phases with 3σ C.L. for sin2 2θ13 >= 0.012. This is all under the assumption that an upgraded neutrino beam is sent to LBNE from Fermilab, 1300 km away and experiment is run for 6 years. This paper describes physics reach, status and current undergoing research and development effort toward construction of the LBNE.

The Atacama Cosmology Telescope: Cosmology from Galaxy Clusters Detected Via the Sunyaev-Zel'dovich Effect

NASA Technical Reports Server (NTRS)

Sehgal, Neelima; Trac, Hy; Acquaviva, Viviana; Ade, Peter A. R.; Aguirre, Paula; Amiri, Mandana; Appel, John W.; Barrientos, L. Felipe; Battistelli, Elia S.; Bond, J. Richard;

Spectral imaging using clinical megavoltage beams and a novel multi-layer imager

NASA Astrophysics Data System (ADS)

Myronakis, Marios; Fueglistaller, Rony; Rottmann, Joerg; Hu, Yue-Houng; Wang, Adam; Baturin, Paul; Huber, Pascal; Morf, Daniel; Star-Lack, Josh; Berbeco, Ross

2017-12-01

We assess the feasibility of clinical megavoltage (MV) spectral imaging for material and bone separation with a novel multi-layer imager (MLI) prototype. The MLI provides higher detective quantum efficiency and lower noise than conventional electronic portal imagers. Simulated experiments were performed using a validated Monte Carlo model of the MLI to estimate energy absorption and energy separation between the MLI components. Material separation was evaluated experimentally using solid water and aluminum (Al), copper (Cu) and gold (Au) for 2.5 MV, 6 MV and 6 MV flattening filter free (FFF) clinical photon beams. An anthropomorphic phantom with implanted gold fiducials was utilized to further demonstrate bone/gold separation. Weighted subtraction imaging was employed for material and bone separation. The weighting factor (w) was iteratively estimated, with the optimal w value determined by minimization of the relative signal difference (Δ {{S}R} ) and signal-difference-to-noise ratio (SDNR) between material (or bone) and the background. Energy separation between layers of the MLI was mainly the result of beam hardening between components with an average energy separation between 34 and 47 keV depending on the x-ray beam energy. The minimum average energy of the detected spectrum in the phosphor layer was 123 keV in the top layer of the MLI with the 2.5 MV beam. The w values that minimized Δ {{S}R} and SDNR for Al, Cu and Au were 0.89, 0.76 and 0.64 for 2.5 MV; for 6 MV FFF, w was 0.98, 0.93 and 0.77 respectively. Bone suppression in the anthropomorphic phantom resulted in improved visibility of the gold fiducials with the 2.5 MV beam. Optimization of the MLI design is required to achieve optimal separation at clinical MV beam energies.

Intra-Operative Dosimetry in Prostate Brachytherapy

DTIC Science & Technology

2008-04-01

labels in the ith la - beled seed-only image. The seed region with label k in ith image is covered by ||Ωik|| seeds where ||Ω i k|| is the cardinal of...using acetol. The phantom consists of twelve slabs with thickness of 5 mm and each slab has at least a hundred holes with 5 mm spacing where seeds can be...fiducial & the needle insertion template can be pre-calibrated using a rigid mount.(a) A CAD model of the FTRAC fiducial mounted on the seed-insertion needle

3D non-rigid surface-based MR-TRUS registration for image-guided prostate biopsy

NASA Astrophysics Data System (ADS)

Sun, Yue; Qiu, Wu; Romagnoli, Cesare; Fenster, Aaron

2014-03-01

Two dimensional (2D) transrectal ultrasound (TRUS) guided prostate biopsy is the standard approach for definitive diagnosis of prostate cancer (PCa). However, due to the lack of image contrast of prostate tumors needed to clearly visualize early-stage PCa, prostate biopsy often results in false negatives, requiring repeat biopsies. Magnetic Resonance Imaging (MRI) has been considered to be a promising imaging modality for noninvasive identification of PCa, since it can provide a high sensitivity and specificity for the detection of early stage PCa. Our main objective is to develop and validate a registration method of 3D MR-TRUS images, allowing generation of volumetric 3D maps of targets identified in 3D MR images to be biopsied using 3D TRUS images. Our registration method first makes use of an initial rigid registration of 3D MR images to 3D TRUS images using 6 manually placed approximately corresponding landmarks in each image. Following the manual initialization, two prostate surfaces are segmented from 3D MR and TRUS images and then non-rigidly registered using a thin-plate spline (TPS) algorithm. The registration accuracy was evaluated using 4 patient images by measuring target registration error (TRE) of manually identified corresponding intrinsic fiducials (calcifications and/or cysts) in the prostates. Experimental results show that the proposed method yielded an overall mean TRE of 2.05 mm, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm.

SU-D-210-04: Using Radiotherapy Biomaterials to Brand and Track Deadly Cancer Cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Altundal, Y; Sajo, E; Ngwa, W

Purpose: Metastasis accounts for over 90% of all cancer associated suffering and death and arguably presents the most formidable challenges in cancer management. The detection of metastatic or rare circulating tumor cells (CTCs) in blood or lymph nodes remains a formidable technological challenge. In this study, we investigated the time needed to label each cancer cell in-situ (right at the source tumor) with sufficient number of GNPs that will allow enhanced non-invasive detection via photoacoustic imaging in the lymph nodes. Such in-situ labeling can be achieved via sustained release of the GNPs from Radiotherapy (RT) biomaterials (e.g. fiducials, spacers) coated/loadedmore » with the GNP. Methods: The minimum concentration (1000 GNPs/cell for 50nm GNPs) to detect GNPs with photoacoustic imaging method was experimentally measured by Mallidi et al. and fixed at the tumor sub-volume periphery. In this work, the GNPs were assumed to diffuse from a point source, placed in the middle of a 2–3cm tumor, with an initial concentration of 7–30 mg/g. The time required to label the cells with GNPs was calculated by solving the three dimensional diffusion-reaction equation analytically. The diffusion coefficient of 10nm GNPs was experimentally determined previously. Stokes-Einstein equation was used to calculate the diffusion coefficients for other sizes (2–50nm) of GNPs. The cellular uptake rate constants for several sizes of GNPs were experimentally measured by Jin et al. Results: The time required to label the cells was found 0.635–15.91 days for 2–50nm GNPs with an initial concentration of 7 mg/g GNPs in a 2 cm tumor; 1.379–34.633 days for 2–50nm GNPs with an initial concentration of 30 mg/g GNPs in a 3cm tumor. Conclusion: Our results highlight new potential for labeling CTCs with GNPs released from smart RT biomaterials (i.e. fiducials or spacers loaded with the GNP) towards enhanced non-invasive imaging/detection via photoacoustic imaging.« less

Autonomous surgical robotics using 3-D ultrasound guidance: feasibility study.

PubMed

Whitman, John; Fronheiser, Matthew P; Ivancevich, Nikolas M; Smith, Stephen W

2007-10-01

The goal of this study was to test the feasibility of using a real-time 3D (RT3D) ultrasound scanner with a transthoracic matrix array transducer probe to guide an autonomous surgical robot. Employing a fiducial alignment mark on the transducer to orient the robot's frame of reference and using simple thresholding algorithms to segment the 3D images, we tested the accuracy of using the scanner to automatically direct a robot arm that touched two needle tips together within a water tank. RMS measurement error was 3.8% or 1.58 mm for an average path length of 41 mm. Using these same techniques, the autonomous robot also performed simulated needle biopsies of a cyst-like lesion in a tissue phantom. This feasibility study shows the potential for 3D ultrasound guidance of an autonomous surgical robot for simple interventional tasks, including lesion biopsy and foreign body removal.

Magnetic Field Monitoring in the SNS and LANL Neutron EDM Experiments

NASA Astrophysics Data System (ADS)

Aleksandrova, Alina; SNS nEDM Collaboration; LANL nEDM Collaboration

2017-09-01

The SNS neutron EDM experiment requires the ability to precisely control and monitor the magnetic field inside of the fiducial volume. However, it is not always practical (or even possible) to measure the field within the region of interest directly. To remedy this issue, we have designed a field monitoring system that will allow us to reconstruct the field inside of the fiducial volume using noninvasive measurements of the field components at discrete locations external to this volume. A prototype probe array (consisting of 12 single-axis fluxgate magnetometer sensors) was used to monitor the magnetic field within the fiducial volume of an in-house magnetic testing apparatus. In this talk, the design and results of this test will be presented, and the possible implementation of this field monitoring method may have in the room temperature LANL neutron EDM experiment will be discussed. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, under Award Number DE-SC-0014622.

Development and validation of a multilateration test bench for particle accelerator pre-alignment

NASA Astrophysics Data System (ADS)

Kamugasa, Solomon William; Rothacher, Markus; Gayde, Jean-Christophe; Mainaud Durand, Helene

2018-03-01

The development and validation of a portable coordinate measurement solution for fiducialization of compact linear collider (CLIC) components is presented. This new solution addresses two limitations of high-accuracy state-of-the-art coordinate measuring machines, i.e. lack of portability and limited measurement volume. The solution is based on frequency scanning interferometry (FSI) distances and the multilateration coordinate measurement technique. The developments include a reference sphere for localizing the FSI optical fiber tip and a kinematic mount for repositioning the reference sphere with sub-micrometric repeatability. This design enables absolute distance measurements in different directions from the same point, which is essential for multilateration. A multilateration test bench built using these prototypes has been used to fiducialize a CLIC cavity beam position monitor and 420 mm-long main beam quadrupole magnet. The combined fiducialization uncertainty achieved is 3.5 μm (k  =  1), which is better than the CLIC 5 μm (k  =  1) uncertainty specification.

Global geodesy using GPS without fiducial sites

NASA Technical Reports Server (NTRS)

Heflin, Michael; Bertiger, Willy; Blewitt, Geoff; Freedman, Adam; Hurst, Ken; Lichten, Steve; Lindqwister, Ulf; Vigue, Yvonne; Webb, Frank; Yunck, Tom

1992-01-01

Baseline lengths and geocentric radii have been determined from GPS data without the use of fiducial sites. Data from the first GPS experiment for the IERS and Geodynamics (GIG '91) have been analyzed with a no-fiducial strategy. A baseline length daily repeatability of 2 mm + 4 parts per billion was obtained for baselines in the Northern Hemisphere. Comparison of baseline lengths from GPS and the global VLBI solution GLB659 (Caprette et al. 1990) show rms agreement of 2.1 parts per billion. The geocentric radius mean daily repeatability for all sites was 15 cm. Comparison of geocentric radii from GPS and SV5 (Murray et al. 1990) show rms agreement of 3.8 cm. Given n globally distributed stations, the n(n - 1)/2 baseline lengths and n geocentric radii uniquely define a rigid closed polyhedron with a well-defined center of mass. Geodetic information can be obtained by examining the structure of the polyhedron and its change with time.

Patient Positioning Based on a Radioactive Tracer Implanted in Patients With Localized Prostate Cancer: A Performance and Safety Evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kruijf, Willy J.M. de, E-mail: kruijf.de.w@bvi.nl; Verstraete, Jan; Neustadter, David

2013-02-01

Purpose: To evaluate the performance and safety of a radiation therapy positioning system (RealEye) based on tracking a radioactive marker (Tracer) implanted in patients with localized prostate cancer. Methods and Materials: We performed a single-arm multi-institutional trial in 20 patients. The iridium-192 ({sup 192}Ir)-containing Tracer was implanted in the patient together with 4 standard gold seed fiducials. Patient prostate-related symptoms were evaluated with the International Prostate Symptom Score (IPSS) questionnaire. Computed tomography (CT) was performed for treatment planning, during treatment, and after treatment to evaluate the migration stability of the Tracer. At 5 treatment sessions, cone beam CT was performedmore » to test the positioning accuracy of the RealEye. Results: The Tracer was successfully implanted in all patients. No device or procedure-related adverse events occurred. Changes in IPSS scores were limited. The difference between the mean change in Tracer-fiducial distance and the mean change in fiducial-fiducial distance was -0.39 mm (95% confidence interval [CI] upper boundary, -0.22 mm). The adjusted mean difference between Tracer position according to RealEye and the Tracer position on the CBCT for all patients was 1.34 mm (95% CI upper boundary, 1.41 mm). Conclusions: Implantation of the Tracer is feasible and safe. Migration stability of the Tracer is good. Prostate patients can be positioned and monitored accurately by using RealEye.« less

Patient positioning based on a radioactive tracer implanted in patients with localized prostate cancer: a performance and safety evaluation.

PubMed

de Kruijf, Willy J M; Verstraete, Jan; Neustadter, David; Corn, Benjamin W; Hol, Sandra; Venselaar, Jack L M; Davits, Rob J; Wijsman, Bart P; Van den Bergh, Laura; Budiharto, Tom; Oyen, Raymond; Haustermans, Karin; Poortmans, Philip M P

2013-02-01

To evaluate the performance and safety of a radiation therapy positioning system (RealEye) based on tracking a radioactive marker (Tracer) implanted in patients with localized prostate cancer. We performed a single-arm multi-institutional trial in 20 patients. The iridium-192 ((192)Ir)-containing Tracer was implanted in the patient together with 4 standard gold seed fiducials. Patient prostate-related symptoms were evaluated with the International Prostate Symptom Score (IPSS) questionnaire. Computed tomography (CT) was performed for treatment planning, during treatment, and after treatment to evaluate the migration stability of the Tracer. At 5 treatment sessions, cone beam CT was performed to test the positioning accuracy of the RealEye. The Tracer was successfully implanted in all patients. No device or procedure-related adverse events occurred. Changes in IPSS scores were limited. The difference between the mean change in Tracer-fiducial distance and the mean change in fiducial-fiducial distance was -0.39 mm (95% confidence interval [CI] upper boundary, -0.22 mm). The adjusted mean difference between Tracer position according to RealEye and the Tracer position on the CBCT for all patients was 1.34 mm (95% CI upper boundary, 1.41 mm). Implantation of the Tracer is feasible and safe. Migration stability of the Tracer is good. Prostate patients can be positioned and monitored accurately by using RealEye. Copyright © 2013 Elsevier Inc. All rights reserved.

Evaluation of portable CT scanners for otologic image-guided surgery

PubMed Central

Balachandran, Ramya; Schurzig, Daniel; Fitzpatrick, J Michael; Labadie, Robert F

2011-01-01

Purpose Portable CT scanners are beneficial for diagnosis in the intensive care unit, emergency room, and operating room. Portable fixed-base versus translating-base CT systems were evaluated for otologic image-guided surgical (IGS) applications based on geometric accuracy and utility for percutaneous cochlear implantation. Methods Five cadaveric skulls were fitted with fiducial markers and scanned using both a translating-base, 8-slice CT scanner (CereTom®) and a fixed-base, flat-panel, volume-CT (fpVCT) scanner (Xoran xCAT®). Images were analyzed for: (a) subjective quality (i.e. noise), (b) consistency of attenuation measurements (Hounsfield units) across similar tissue, and (c) geometric accuracy of fiducial marker positions. The utility of these scanners in clinical IGS cases was tested. Results Five cadaveric specimens were scanned using each of the scanners. The translating-base, 8-slice CT scanner had spatially consistent Hounsfield units, and the image quality was subjectively good. However, because of movement variations during scanning, the geometric accuracy of fiducial marker positions was low. The fixed-base, fpVCT system had high spatial resolution, but the images were noisy and had spatially inconsistent attenuation measurements; while the geometric representation of the fiducial markers was highly accurate. Conclusion Two types of portable CT scanners were evaluated for otologic IGS. The translating-base, 8-slice CT scanner provided better image quality than a fixed-base, fpVCT scanner. However, the inherent error in three-dimensional spatial relationships by the translating-based system makes it suboptimal for otologic IGS use. PMID:21779768

Line-of-sight measurements for the NIF Neutron Imaging System and determination of line-of-sight offsets in OPAS 90-135 images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frank, Matthias; Fittinghoff, David N.; Bower, Dan E.

2011-05-13

This report describes line-of-sight (LOS) measurements for the NIF Neutron Imaging System (NIS) and a characterization of the NIS LOS relative to OPAS 90-135 that were performed during the NIS commissioning Nov. 2010 – Jan. 2011. As described here, data from those measurements were used to determine the relative offsets between the TCC position (x and y pixel coordinates in OPAS images) and the NIS LOS as functions of the OPAS focal distance. This data is needed to place the NIS pinhole array (PHA) onto the NIS LOS with high precision using OPAS imaging of alignment fiducials attached to themore » front and the back of the PHA. (A description of the PHA alignment fiducials, data from metrology performed on the fiducials and a description on how these fiducials were used to align the PHA for the first NIS imaging shot on Feb,. 17, 2011 will be summarized in an upcoming separate report. This report consists of an overview given in this document and a main body that consists of a set of viewgraphs (see Appendix 1) that were iterated and refined within the NIS team and with the Alignment Working Group and that contain more detailed information, schematics and calculations of the NIS line of sight offset from the OPAS LOS. See also Drury, “OPAS 90-135 Registration of Neutron Imaging System Line of Sight,” January 2011, NIF-5035484.« less

Kilovoltage Imaging of Implanted Fiducials to Monitor Intrafraction Motion With Abdominal Compression During Stereotactic Body Radiation Therapy for Gastrointestinal Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yorke, Ellen, E-mail: yorke@mskcc.org; Xiong, Ying; Han, Qian

2016-07-01

Purpose: To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiation therapy (SBRT). Methods and Materials: A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during SBRT for abdominal tumors. Kilovoltage images were acquired at 5- to 6-second intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for 3 sessions for each patient. Results: Intrafraction displacement patterns variedmore » between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm, and 1.2% exceeded 0.75 cm. The calculated single-session dose to 95% of gross tumor volume differed from planned by an average of −1.2% (range, −11.1% to 4.8%) but only for 4 patients was the total 3-session calculated dose to 95% of gross tumor volume more than 3% different from planned. Conclusions: Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable.« less

Technical aspects of real time positron emission tracking for gated radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chamberland, Marc; Xu, Tong, E-mail: txu@physics.carleton.ca; McEwen, Malcolm R.

2016-02-15

Purpose: Respiratory motion can lead to treatment errors in the delivery of radiotherapy treatments. Respiratory gating can assist in better conforming the beam delivery to the target volume. We present a study of the technical aspects of a real time positron emission tracking system for potential use in gated radiotherapy. Methods: The tracking system, called PeTrack, uses implanted positron emission markers and position sensitive gamma ray detectors to track breathing motion in real time. PeTrack uses an expectation–maximization algorithm to track the motion of fiducial markers. A normalized least mean squares adaptive filter predicts the location of the markers amore » short time ahead to account for system response latency. The precision and data collection efficiency of a prototype PeTrack system were measured under conditions simulating gated radiotherapy. The lung insert of a thorax phantom was translated in the inferior–superior direction with regular sinusoidal motion and simulated patient breathing motion (maximum amplitude of motion ±10 mm, period 4 s). The system tracked the motion of a {sup 22}Na fiducial marker (0.34 MBq) embedded in the lung insert every 0.2 s. The position of the was marker was predicted 0.2 s ahead. For sinusoidal motion, the equation used to model the motion was fitted to the data. The precision of the tracking was estimated as the standard deviation of the residuals. Software was also developed to communicate with a Linac and toggle beam delivery. In a separate experiment involving a Linac, 500 monitor units of radiation were delivered to the phantom with a 3 × 3 cm photon beam and with 6 and 10 MV accelerating potential. Radiochromic films were inserted in the phantom to measure spatial dose distribution. In this experiment, the period of motion was set to 60 s to account for beam turn-on latency. The beam was turned off when the marker moved outside of a 5-mm gating window. Results: The precision of the tracking in the IS direction was 0.53 mm for a sinusoidally moving target, with an average count rate ∼250 cps. The average prediction error was 1.1 ± 0.6 mm when the marker moved according to irregular patient breathing motion. Across all beam deliveries during the radiochromic film measurements, the average prediction error was 0.8 ± 0.5 mm. The maximum error was 2.5 mm and the 95th percentile error was 1.5 mm. Clear improvement of the dose distribution was observed between gated and nongated deliveries. The full-width at halfmaximum of the dose profiles of gated deliveries differed by 3 mm or less than the static reference dose distribution. Monitoring of the beam on/off times showed synchronization with the location of the marker within the latency of the system. Conclusions: PeTrack can track the motion of internal fiducial positron emission markers with submillimeter precision. The system can be used to gate the delivery of a Linac beam based on the position of a moving fiducial marker. This highlights the potential of the system for use in respiratory-gated radiotherapy.« less

Stereotactic Robotic Body Radiotherapy for Patients With Unresectable Hepatic Oligorecurrence.

PubMed

Berkovic, Patrick; Gulyban, Akos; Nguyen, Paul Viet; Dechambre, David; Martinive, Philippe; Jansen, Nicolas; Lakosi, Ferenc; Janvary, Levente; Coucke, Philippe A

2017-12-01

The purpose of this study was to analyze local control (LC), liver progression-free survival (PFS), and distant PFS (DFS), overall survival (OS), and toxicity in a cohort of patients treated with stereotactic body radiotherapy (SBRT) with fiducial tracking for oligorecurrent liver lesions; and to evaluate the potential influence of lesion size, systemic treatment, physical and biologically effective dose (BED), treatment calculation algorithms and other parameters on the obtained results. Unoperable patients with sufficient liver function had [18F]-fluorodeoxyglucose-positron emission tomography-computed tomography and liver magnetic resonance imaging to confirm the oligorecurrent nature of the disease and to further delineate the gross tumor volume (GTV). An intended dose of 45 Gy in 3 fractions was prescribed on the 80% isodose and adapted if risk-related. Treatment was executed with the CyberKnife system (Accuray Inc) platform using fiducials tracking. Initial plans were recalculated using the Monte Carlo algorithm. Patient and treatment data were processed using the Kaplan-Meier method and log rank test for survival analysis. Between 2010 and 2015, 42 patients (55 lesions) were irradiated. The mean GTV and planning target volume (PTV) were 30.5 cc and 96.8 cc, respectively. Treatments were delivered 3 times per week in a median of 3 fractions to a PTV median dose of 54.6 Gy. The mean GTV and PTV D98% were 51.6 Gy and 51.2 Gy, respectively. Heterogeneity corrections did not influence dose parameters. After a median follow-up of 18.9 months, the 1- and 2-year LC/liver PFS/DFS/OS were 81.3%/55%/62.4%/86.9%, and 76.3%/42.3%/52%/78.3%, respectively. Performance status and histology had a significant effect on LC, whereas age (older than 65 years) marginally influenced liver PFS. Clinical target volume physical dose V45 Gy > 95%, generalized equivalent uniform dose (a = -30) > 45 Gy and a BED (α/β = 10) V105 Gy > 96% showed statistically significant effect on the LC. Acute Grade 3 gastrointestinal (GI) and late Grade 2 GI and fatigue toxicity were found in 5% and 11% patients, respectively. Favorable survival and toxicity results support the potential paradigm shift in which the use of SBRT in oligorecurrent liver disease could benefit patients with unresectable or resectable liver metastases. Copyright © 2017 Elsevier Inc. All rights reserved.

NOTE: Fluoroscopic gating without implanted fiducial markers for lung cancer radiotherapy based on support vector machines

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Alexander, Brian; Jiang, Steve B.

2008-08-01

Various problems with the current state-of-the-art techniques for gated radiotherapy have prevented this new treatment modality from being widely implemented in clinical routine. These problems are caused mainly by applying various external respiratory surrogates. There might be large uncertainties in deriving the tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using template matching methods (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007b Phys. Med. Biol. 52 741-55). In this note, our main contribution is to provide a totally different new view of the gating problem by recasting it as a classification problem. Then, we solve this classification problem by a well-studied powerful classification method called a support vector machine (SVM). Note that the goal of an automated gating tool is to decide when to turn the beam ON or OFF. We treat ON and OFF as the two classes in our classification problem. We create our labeled training data during the patient setup session by utilizing the reference gating signal, manually determined by a radiation oncologist. We then pre-process these labeled training images and build our SVM prediction model. During treatment delivery, fluoroscopic images are continuously acquired, pre-processed and sent as an input to the SVM. Finally, our SVM model will output the predicted labels as gating signals. We test the proposed technique on five sequences of fluoroscopic images from five lung cancer patients against the reference gating signal as ground truth. We compare the performance of the SVM to our previous template matching method (Cui et al 2007b Phys. Med. Biol. 52 741-55). We find that the SVM is slightly more accurate on average (1-3%) than the template matching method, when delivering the target dose. And the average duty cycle is 4-6% longer. Given the very limited patient dataset, we cannot conclude that the SVM is more accurate and efficient than the template matching method. However, our preliminary results show that the SVM is a potentially precise and efficient algorithm for generating gating signals for radiotherapy. This work demonstrates that the gating problem can be considered as a classification problem and solved accordingly.

Neutrino mass from cosmology: impact of high-accuracy measurement of the Hubble constant

NASA Astrophysics Data System (ADS)

Sekiguchi, Toyokazu; Ichikawa, Kazuhide; Takahashi, Tomo; Greenhill, Lincoln

2010-03-01

Non-zero neutrino mass would affect the evolution of the Universe in observable ways, and a strong constraint on the mass can be achieved using combinations of cosmological data sets. We focus on the power spectrum of cosmic microwave background (CMB) anisotropies, the Hubble constant H0, and the length scale for baryon acoustic oscillations (BAO) to investigate the constraint on the neutrino mass, mν. We analyze data from multiple existing CMB studies (WMAP5, ACBAR, CBI, BOOMERANG, and QUAD), recent measurement of H0 (SHOES), with about two times lower uncertainty (5 %) than previous estimates, and recent treatments of BAO from the Sloan Digital Sky Survey (SDSS). We obtained an upper limit of mν < 0.2eV (95 % C.L.), for a flat ΛCDM model. This is a 40 % reduction in the limit derived from previous H0 estimates and one-third lower than can be achieved with extant CMB and BAO data. We also analyze the impact of smaller uncertainty on measurements of H0 as may be anticipated in the near term, in combination with CMB data from the Planck mission, and BAO data from the SDSS/BOSS program. We demonstrate the possibility of a 5σ detection for a fiducial neutrino mass of 0.1 eV or a 95 % upper limit of 0.04 eV for a fiducial of mν = 0 eV. These constraints are about 50 % better than those achieved without external constraint. We further investigate the impact on modeling where the dark-energy equation of state is constant but not necessarily -1, or where a non-flat universe is allowed. In these cases, the next-generation accuracies of Planck, BOSS, and 1 % measurement of H0 would all be required to obtain the limit mν < 0.05-0.06 eV (95 % C.L.) for the fiducial of mν = 0 eV. The independence of systematics argues for pursuit of both BAO and H0 measurements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rottmann, J; Myronakis, M; Hu, Y

Purpose: Beams-eye-view imaging applications such as real-time soft-tissue motion estimation and MV-CBCT are hindered by the inherently low image contrast of electronic portal imaging devices (EPID) currently in clinical use. We investigate a cost effective scintillating glass that provides substantially increased detective quantum efficiency (DQE) and contrast to noise ratio (CNR). Methods: A pixelated scintillator prototype was built from LKH-5 glass. The array is 12mm thick; 42.4×42.4cm2 wide and features 1.51mm pixel pitch with 20µm separation (glue+septa). The LKH-5 array was mounted on the active matrix flat panel imager (AMPFI) of an AS-1200 (Varian) with the GdO2S2:Tb removed. A secondmore » AS-1200 was utilized as reference detector. The prototype EPID was characterized in terms of CNR, modulation transfer function (MTF) and DQE. Additionally, the visibility of various fiducial markers typically used in the clinic as well as a realistic 3D-printed lung tumor model was assessed. All items were placed in a 12cm thick solid water phantom. CNR is estimated using a Las Vegas contrast phantom, presampled MTF is estimated using a slanted slit technique and the DQE is calculated from measured normalized noise power spectra (NPS) and the MTF. Results: DQE(0) for the LKH-5 prototype increased by a factor of 8× to about 10%, compared to the AS-1200 equipped with its standard GdO2S2:Tb scintillator. CNR increased by a factor of 5.3×. Due to the pixel size the MTF50 decreased by about 55% to 0.23lp/mm. The visibility of all fiducial markers as well as the tumor model were however markedly improved in comparison to an acquisition with the same parameters using the GdO2S2:Tb scintillator. Conclusion: LKH-5 scintillating glasses allow the cost effective construction of thick pixelated scintillators for portal imaging which can yield a substantial increase in DQE and CNR. Soft tissue and fiducial marker visibility was found to be markedly improved. The project was supported in part by NIH grant R01CA188446-01 and a grant from Varian Medical Systems.« less

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

MRI signal intensity based B-spline nonrigid registration for pre- and intraoperative imaging during prostate brachytherapy.

PubMed

Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M C; Hata, Nobuhiko

2009-11-01

To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts' visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was -0.19 +/- 0.07 and FRE presented a value of 2.3 +/- 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy.

AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments

NASA Astrophysics Data System (ADS)

Penzias, Gregory; Janowczyk, Andrew; Singanamalli, Asha; Rusu, Mirabela; Shih, Natalie; Feldman, Michael; Stricker, Phillip D.; Delprado, Warick; Tiwari, Sarita; Böhm, Maret; Haynes, Anne-Maree; Ponsky, Lee; Viswanath, Satish; Madabhushi, Anant

2016-07-01

In applications involving large tissue specimens that have been sectioned into smaller tissue fragments, manual reconstruction of a “pseudo whole-mount” histological section (PWMHS) can facilitate (a) pathological disease annotation, and (b) image registration and correlation with radiological images. We have previously presented a program called HistoStitcher, which allows for more efficient manual reconstruction than general purpose image editing tools (such as Photoshop). However HistoStitcher is still manual and hence can be laborious and subjective, especially when doing large cohort studies. In this work we present AutoStitcher, a novel automated algorithm for reconstructing PWMHSs from digitized tissue fragments. AutoStitcher reconstructs (“stitches”) a PWMHS from a set of 4 fragments by optimizing a novel cost function that is domain-inspired to ensure (i) alignment of similar tissue regions, and (ii) contiguity of the prostate boundary. The algorithm achieves computational efficiency by performing reconstruction in a multi-resolution hierarchy. Automated PWMHS reconstruction results (via AutoStitcher) were quantitatively and qualitatively compared to manual reconstructions obtained via HistoStitcher for 113 prostate pathology sections. Distances between corresponding fiducials placed on each of the automated and manual reconstruction results were between 2.7%-3.2%, reflecting their excellent visual similarity.

Feasibility study on image guided patient positioning for stereotactic body radiation therapy of liver malignancies guided by liver motion.

PubMed

Heinz, Christian; Gerum, Sabine; Freislederer, Philipp; Ganswindt, Ute; Roeder, Falk; Corradini, Stefanie; Belka, Claus; Niyazi, Maximilian

2016-06-27

Fiducial markers are the superior method to compensate for interfractional motion in liver SBRT. However this method is invasive and thereby limits its application range. In this retrospective study, the compensation method for the interfractional motion using fiducial markers (gold standard) was compared to a new non-invasive approach, which does rely on the organ motion of the liver and the relative tumor position within this volume. We analyzed six patients (3 m, 3f) treated with SBRT in 2014. After fiducial marker implantation, all patients received a treatment CT (free breathing, without abdominal compression) and a 4D-CT (consisting of 10 respiratory phases). For all patients the gross tumor volumes (GTVs), internal target volume (ITV), planning target volume (PTV), internal marker target volumes (IMTVs) and the internal liver target volume (ILTV) were delineated based on the CT and 4D-CT images. CBCT imaging was used for the standard treatment setup based on the fiducial markers. According to the patient coordinates the 3 translational compensation values (t x , t y , t z ) for the interfractional motion were calculated by matching the blurred fiducial markers with the corresponding IMTV structures. 4 observers were requested to recalculate the translational compensation values for each CBCT (31) based on the ILTV structures. The differences of the translational compensation values between the IMTV and ILTV approach were analyzed. The magnitude of the mean absolute 3D registration error with regard to the gold standard overall patients and observers was 0.50 cm ± 0.28 cm. Individual registration errors up to 1.3 cm were observed. There was no significant overall linear correlation between the respiratory motion and the registration error of the ILTV approach. Two different methods to calculate the translational compensation values for interfractional motion in stereotactic liver therapy were evaluated. The registration accuracy of the ILTV approach is mainly limited by the non-rigid behavior of the liver and the individual registration experience of the observer. The ILTV approach lacks the accuracy that would be desired for stereotactic radiotherapy of the liver.

SU-E-J-229: Magnetic Resonance Imaging of Small Fiducial Markers for Proton Beam Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Y; James, J; Panda, A

2015-06-15

Purpose: For proton beam therapy, small fiducial markers are preferred for patient alignment due to less interference with the proton beam. Visualizing small fiducial markers can be challenging in MRI. This study intends to investigate MRI imaging protocols for better visualization of small fiducial markers. Methods: Two carbon and two coil-shaped gold markers were placed into a gel phantom. Both carbon markers had a diameter of 1mm and a length of 3mm. Both gold markers had a length of 5mm. One gold marker had a diameter of 0.5mm and the other had a diameter of 0.75mm. T1 VIBE, T2 SPACE,more » TrueFISP and susceptibility weighted (SW) images were acquired. To improve marker contrast, high spatial resolution was used to reduce partial volume effect. Slice thickness was 1.5mm for all four sequences and in-plane resolution was 0.6mm for TrueFISP, 0.7mm for T1 VIBE, and 0.8mm for T2 SPACE and SW. For comparison purpose, a 3D T1 VIBE image set at 3mm slice thickness and 1.2mm in-plane resolution was also acquired. Results: All markers were visible in all high-resolution image sets. In each image set, marker-induced signal void was the smallest (in diameter) for carbon markers, followed by the 0.5mm gold marker and the largest for the 0.75mm gold marker. The SW images had the largest marker-induced signal void. However, those might be confused by susceptibility-gradient-induced signal voids. T1 VIBE had good visualization of markers with nicely defined edges. T2 SPACE had reasonable visualization of markers but edges were slightly blurred. TrueFISP had good visualization of markers only if they were not masked by banding artifacts. As a comparison, all markers were hardly visible in the standard resolution T1 VIBE images. Conclusion: 3D high-resolution T1 VIBE and SW have great potential in providing good visualization of small fiducial markers for proton beam therapy.« less

SU-G-JeP1-09: Evaluation of Transperineal Ultrasound Imaging as a Potential Solution for Target Tracking During Ablative Body Radiotherapy for Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Najafi, M; Han, B; Hancock, S

Purpose: Prostate SABR is emerging as a clinically viable, potentially cost effective alternative to prostate IMRT but its adoption is contingent on providing solutions for accurate tracking during beam delivery. Our goal is to evaluate the performance of the Clarity Autoscan ultrasound monitoring system for inter-fractional prostate motion tracking in both phantoms and in-vivo. Methods: In-vivo evaluation was performed under IRB protocol to allow data collection in prostate patients treated with VMAT whereby prostate was imaged through the acoustic window of the perineum. The probe was placed before KV imaging and real-time tracking was started and continued until the endmore » of treatment. Initial absolute 3D positions of fiducials were estimated from KV images. Fiducial positions in MV images subsequently acquired during beam delivery were compared with predicted positions based on Clarity estimated motion. Results: Phantom studies with motion amplitudes of ±1.5, ±3, ±6 mm in lateral direction and ±2 mm in longitudinal direction resulted in tracking errors of −0.03 ± 0.3, −0.04 ± 0.6, −0.2 ± 0.9 mm, respectively, in lateral direction and −0.05 ± 0.30 mm in longitudinal direction. In phantom, measured and predicted fiducial positions in MV images were within 0.1 ± 0.6 mm. Four patients consented to participate in the study and data was acquired over a total of 140 fractions. MV imaging tracking was possible in about 75% of the time (due to occlusion of fiducials) compared to 100% with Clarity. Overall range of estimated motion by Clarity was 0 to 4.0 mm. In-vivo fiducial localization error was 1.2 ± 1.0 mm compared to 1.8 ± 1.9 mm if not taking Clarity estimated motion into account. Conclusion: Real-time transperineal ultrasound tracking reduces uncertainty in prostate position due to intrafractional motion. Research was supported by Elekta.« less

A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.

PubMed

Madan, Hennadii; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

2017-02-01

Advanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard  dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework. The framework is based on rigid registration of fiducial markers. The main novelty is spatial grouping of fiducial markers on the carrier device, which enables automatic marker localization and identification across the 3D and 2D images. The proposed framework was demonstrated on clinical angiograms of 20 patients. Rigid 32R computed by the framework was more accurate than that obtained manually, with the respective target registration error below 0.027 mm compared to 0.040 mm. The framework is applicable for gold standard setup on any rigid anatomy, provided that the acquired images contain spatially grouped fiducial markers. The gold standard datasets and software will be made publicly available.

Measurement of differential and integrated fiducial cross sections for Higgs boson production in the four-lepton decay channel in pp collisions at $$ \\sqrt{s}=7 $$ and 8 TeV

DOE PAGES

Khachatryan, Vardan

2016-04-01

Integrated fiducial cross sections for the production of four leptons via the H → 4ℓ decays (ℓ = e, μ) are measured in pp collisions atmore » $$ \\sqrt{s}=7 $$ and 8TeV. Measurements are performed with data corresponding to integrated luminosities of 5.1 fb$$^{–1}$$ at 7TeV, and 19.7 fb$$^{–1}$$ at 8 TeV, collected with the CMS experiment at the LHC. Differential cross sections are measured using the 8 TeV data, and are determined as functions of the transverse momentum and rapidity of the four-lepton system, accompanying jet multiplicity, transverse momentum of the leading jet, and difference in rapidity between the Higgs boson candidate and the leading jet. A measurement of the Z → 4ℓ cross section, and its ratio to the H → 4ℓ cross section is also performed. All cross sections are measured within a fiducial phase space defined by the requirements on lepton kinematics and event topology. Here, the integrated H → 4ℓ fiducial cross section is measured to be 0.56$$_{–0.44}^{+0.67}$$ (stat)$$_{–0.06}^{+0.21}$$ (syst) fb at 7 TeV, and 1.11$$_{–0.35}^{+0.41}$$ (stat)$$_{–0.10}^{+0.14}$$ (syst) fb at 8 TeV. The measurements are found to be compatible with theoretical calculations based on the standard model.« less

Measurements of fiducial and differential cross sections for Higgs boson production in the diphoton decay channel at TeV with ATLAS

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Almond, J.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baas, A.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batley, J. R.; Battaglia, M.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertsche, C.; Bertsche, D.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boddy, C. R.; Boehler, M.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, J.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camarda, S.; Cameron, D.; Caminada, L. M.; Caminal Armadans, R.; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J. A.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Nooij, L.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Domenico, A.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobos, D.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Fernandez Perez, S.; Ferrag, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Florez Bustos, A. C.; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Franz, S.; Fraternali, M.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y. S.; Garay Walls, F. M.; Garberson, F.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gianotti, F.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Glonti, G. L.; Goblirsch-Kolb, M.; Goddard, J. R.; Godfrey, J.; Godlewski, J.; Goeringer, C.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gomez Fajardo, L. S.; GonCcalo, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, L.; González de la Hoz, S.; Gonzalez Parra, G.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Gozpinar, S.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Grebenyuk, O. G.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grishkevich, Y. V.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Groth-Jensen, J.; Grout, Z. J.; Guan, L.; Guescini, F.; Guest, D.; Gueta, O.; Guicheney, C.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Gunther, J.; Guo, J.; Gupta, S.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Haefner, P.; Hageböck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Hall, D.; Halladjian, G.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamer, M.; Hamilton, A.; Hamilton, S.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harper, D.; Harrington, R. D.; Harris, O. M.; Harrison, P. F.; Hartjes, F.; Hasegawa, M.; Hasegawa, S.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hawkins, A. D.; Hayashi, T.; Hayden, D.; Hays, C. P.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, L.; Hejbal, J.; Helary, L.; Heller, C.; Heller, M.; Hellman, S.; Hellmich, D.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Hengler, C.; Henrichs, A.; Henriques Correia, A. M.; Henrot-Versille, S.; Hensel, C.; Herbert, G. H.; Hernández Jiménez, Y.; Herrberg-Schubert, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hoffman, J.; Hoffmann, D.; Hofmann, J. I.; Hohlfeld, M.; Holmes, T. R.; Hong, T. M.; Hooft van Huysduynen, L.; Horii, Y.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Hurwitz, M.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikematsu, K.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Inamaru, Y.; Ince, T.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Irles Quiles, A.; Isaksson, C.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Iturbe Ponce, J. M.; Iuppa, R.; Ivarsson, J.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, M.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jakubek, J.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansen, H.; Janssen, J.; Janus, M.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Jeanty, L.; Jejelava, J.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, Y.; Jimenez Belenguer, M.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Joergensen, M. D.; Johansson, K. E.; Johansson, P.; Johns, K. A.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Joshi, K. D.; Jovicevic, J.; Ju, X.; Jung, C. A.; Jungst, R. M.; Jussel, P.; Rozas, A. Juste; Kaci, M.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kajomovitz, E.; Kalderon, C. W.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneda, M.; Kaneti, S.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kar, D.; Karakostas, K.; Karastathis, N.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kashif, L.; Kasieczka, G.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Katre, A.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazama, S.; Kazanin, V. F.; Kazarinov, M. Y.; Keeler, R.; Kehoe, R.; Keil, M.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Kessoku, K.; Keung, J.; Khalil-zada, F.; Khandanyan, H.; Khanov, A.; Khodinov, A.; Khomich, A.; Khoo, T. J.; Khoriauli, G.; Khoroshilov, A.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kim, H. Y.; Kim, H.; Kim, S. H.; Kimura, N.; Kind, O.; King, B. T.; King, M.; King, R. S. B.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kittelmann, T.; Kiuchi, K.; Kladiva, E.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klioutchnikova, T.; Klok, P. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koevesarki, P.; Koffas, T.; Koffeman, E.; Kogan, L. A.; Kohlmann, S.; Kohout, Z.; Kohriki, T.; Koi, T.; Kolanoski, H.; Koletsou, I.; Koll, J.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; König, S.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Korotkov, V. A.; Kortner, O.; Kortner, S.; Kostyukhin, V. V.; Kotov, V. M.; Kotwal, A.; Kourkoumelis, C.; Kouskoura, V.; Koutsman, A.; Kowalewski, R.; Kowalski, T. Z.; Kozanecki, W.; Kozhin, A. S.; Kral, V.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasznahorkay, A.; Kraus, J. K.; Kravchenko, A.; Kreiss, S.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Kruker, T.; Krumnack, N.; Krumshteyn, Z. V.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kuday, S.; Kuehn, S.; Kugel, A.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunkle, J.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kurumida, R.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; La Rosa, A.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Laier, H.; Lambourne, L.; Lammers, S.; Lampen, C. L.; Lampl, W.; LanCcon, E.; Landgraf, U.; Landon, M. P. J.; Lang, V. S.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Le Dortz, O.; Le Guirriec, E.; Le Menedeu, E.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, H.; Lee, J. S. H.; Lee, S. C.; Lee, L.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmacher, M.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leisos, A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzen, G.; Lenzi, B.; Leone, R.; Leone, S.; Leonhardt, K.; Leonidopoulos, C.; Leontsinis, S.; Leroy, C.; Lester, C. G.; Lester, C. M.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, A.; Lewis, G. H.; Leyko, A. M.; Leyton, M.; Li, B.; Li, B.; Li, H.; Li, H. L.; Li, L.; Li, L.; Li, S.; Li, Y.; Liang, Z.; Liao, H.; Liberti, B.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limbach, C.; Limosani, A.; Lin, S. C.; Lin, T. H.; Linde, F.; Lindquist, B. E.; Linnemann, J. T.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lissauer, D.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y.; Livan, M.; Livermore, S. S. A.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loddenkoetter, T.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Lombardo, V. P.; Long, B. A.; Long, J. D.; Long, R. E.; Lopes, L.; Lopez Mateos, D.; Lopez Paredes, B.; Lopez Paz, I.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Loscutoff, P.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lowe, A. J.; Lu, F.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lungwitz, M.; Lynn, D.; Lysak, R.; Lytken, E.; Ma, H.; Ma, L. L.; Maccarrone, G.; Macchiolo, A.; Machado Miguens, J.; Macina, D.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeno, M.; Maeno, T.; Magradze, E.; Mahboubi, K.; Mahlstedt, J.; Mahmoud, S.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Mal, P.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyshev, V. M.; Malyukov, S.; Mamuzic, J.; Mandelli, B.; Mandelli, L.; Mandić, I.; Mandrysch, R.; Maneira, J.; Manfredini, A.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J. A.; Mann, A.; Manning, P. M.; Manousakis-Katsikakis, A.; Mansoulie, B.; Mantifel, R.; Mapelli, L.; March, L.; Marchand, J. F.; Marchiori, G.; Marcisovsky, M.; Marino, C. P.; Marjanovic, M.; Marques, C. N.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti, L. F.; Marti-Garcia, S.; Martin, B.; Martin, B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, H.; Martinez, M.; Martin-Haugh, S.; Martyniuk, A. C.; Marx, M.; Marzano, F.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Massol, N.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazzaferro, L.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McCubbin, N. A.; McFarlane, K. W.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McPherson, R. A.; Meade, A.; Mechnich, J.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melachrinos, C.; Mellado Garcia, B. R.; Meloni, F.; Mengarelli, A.; Menke, S.; Meoni, E.; Mercurio, K. M.; Mergelmeyer, S.; Meric, N.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Merritt, H.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Middleton, R. P.; Migas, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Milstein, D.; Minaenko, A. A.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mirabelli, G.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Mitsui, S.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Mochizuki, K.; Mohapatra, S.; Mohr, W.; Molander, S.; Moles-Valls, R.; Mönig, K.; Monini, C.; Monk, J.; Monnier, E.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, M.; Morii, M.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, K.; Mueller, T.; Mueller, T.; Muenstermann, D.; Munwes, Y.; Murillo Quijada, J. A.; Murray, W. J.; Musheghyan, H.; Musto, E.; Myagkov, A. G.; Myska, M.; Nackenhorst, O.; Nadal, J.; Nagai, K.; Nagai, R.; Nagai, Y.; Nagano, K.; Nagarkar, A.; Nagasaka, Y.; Nagel, M.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Nanava, G.; Narayan, R.; Nattermann, T.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Nef, P. D.; Negri, A.; Negri, G.; Negrini, M.; Nektarijevic, S.; Nelson, A.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nickerson, R. B.; Nicolaidou, R.; Nicquevert, B.; Nielsen, J.; Nikiforou, N.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Norberg, S.; Nordberg, M.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nunes Hanninger, G.; Nunnemann, T.; Nurse, E.; Nuti, F.; O'Brien, B. J.; O'grady, F.; O'Neil, D. C.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, M. I.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Okamura, W.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Olchevski, A. G.; Olivares Pino, S. A.; Oliveira Damazio, D.; Oliver Garcia, E.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Oropeza Barrera, C.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ouellette, E. A.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Ovcharova, A.; Owen, M.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paganis, E.; Pahl, C.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Palka, M.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Panduro Vazquez, J. G.; Pani, P.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pasqualucci, E.; Passaggio, S.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N. D.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pearce, J.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Peng, C.; Peng, H.; Penning, B.; Penwell, J.; Perepelitsa, D. V.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Perini, L.; Pernegger, H.; Perrella, S.; Perrino, R.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Pettersson, N. E.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Piegaia, R.; Pignotti, D. T.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Pingel, A.; Pinto, B.; Pires, S.; Pitt, M.; Pizio, C.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Poddar, S.; Podlyski, F.; Poettgen, R.; Poggioli, L.; Pohl, D.; Pohl, M.; Polesello, G.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Portell Bueso, X.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pralavorio, P.; Pranko, A.; Prasad, S.; Pravahan, R.; Prell, S.; Price, D.; Price, J.; Price, L. E.; Prieur, D.; Primavera, M.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopapadaki, E.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Przysiezniak, H.; Ptacek, E.; Puddu, D.; Pueschel, E.; Puldon, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Qureshi, A.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Rajagopalan, S.; Rammensee, M.; Randle-Conde, A. S.; Rangel-Smith, C.; Rao, K.; Rauscher, F.; Rave, T. C.; Ravenscroft, T.; Raymond, M.; Read, A. L.; Readioff, N. P.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reisin, H.; Relich, M.; Rembser, C.; Ren, H.; Ren, Z. L.; Renaud, A.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Ridel, M.; Rieck, P.; Rieger, J.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodrigues, L.; Roe, S.; Røhne, O.; Rolli, S.; Romaniouk, A.; Romano, M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, M.; Rose, P.; Rosendahl, P. L.; Rosenthal, O.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rubinskiy, I.; Rud, V. I.; Rudolph, C.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Saavedra, A. F.; Sacerdoti, S.; Saddique, A.; Sadeh, I.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Saleem, M.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sartisohn, G.; Sasaki, O.; Sasaki, Y.; Sauvage, G.; Sauvan, E.; Savard, P.; Savu, D. O.; Sawyer, C.; Sawyer, L.; Saxon, D. H.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schaefer, R.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schneider, B.; Schnellbach, Y. J.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schorlemmer, A. L. S.; Schott, M.; Schouten, D.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schroeder, C.; Schuh, N.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwegler, Ph.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Schwoerer, M.; Sciacca, F. G.; Scifo, E.; Sciolla, G.; Scott, W. G.; Scuri, F.; Scutti, F.; Searcy, J.; Sedov, G.; Sedykh, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekula, S. J.; Selbach, K. E.; Seliverstov, D. M.; Sellers, G.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Serre, T.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Shushkevich, S.; Sicho, P.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simoniello, R.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skottowe, H. P.; Skovpen, K. Yu.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopczak, A.; Sopko, B.; Sopko, V.; Sorin, V.; Sosebee, M.; Soualah, R.; Soueid, P.; Soukharev, A. M.; South, D.; Spagnolo, S.; Spanò, F.; Spearman, W. R.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Stavina, P.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Struebig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Swedish, S.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tannenwald, B. B.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Topilin, N. D.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Tran, H. L.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urbaniec, D.; Urquijo, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; Van Der Leeuw, R.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Virzi, J.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weigell, P.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilkens, H. G.; Will, J. Z.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winter, B. T.; Wittgen, M.; Wittig, T.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wright, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xiao, M.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamada, M.; Yamaguchi, H.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yanush, S.; Yao, L.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yurkewicz, A.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zevi della Porta, G.; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, X.; Zhang, Z.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, L.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.

2014-09-01

Measurements of fiducial and differential cross sections are presented for Higgs boson production in proton-proton collisions at a centre-of-mass energy of TeV. The analysis is performed in the H → γγ decay channel using 20.3 fb-1 of data recorded by the ATLAS experiment at the CERN Large Hadron Collider. The signal is extracted using a fit to the diphoton invariant mass spectrum assuming that the width of the resonance is much smaller than the experimental resolution. The signal yields are corrected for the effects of detector inefficiency and resolution. The pp → H → γγ fiducial cross section is measured to be 43.2 ±9.4(stat.) {-/2.9 + 3.2} (syst.) ±1.2(lumi)fb for a Higgs boson of mass 125.4GeV decaying to two isolated photons that have transverse momentum greater than 35% and 25% of the diphoton invariant mass and each with absolute pseudorapidity less than 2.37. Four additional fiducial cross sections and two cross-section limits are presented in phase space regions that test the theoretical modelling of different Higgs boson production mechanisms, or are sensitive to physics beyond the Standard Model. Differential cross sections are also presented, as a function of variables related to the diphoton kinematics and the jet activity produced in the Higgs boson events. The observed spectra are statistically limited but broadly in line with the theoretical expectations. [Figure not available: see fulltext.

Search for magnetic monopoles in sqrt[s]=7  TeV pp collisions with the ATLAS detector.

PubMed

Aad, G; Abajyan, T; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdelalim, A A; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Acerbi, E; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Adomeit, S; Adragna, P; Adye, T; Aefsky, S; Aguilar-Saavedra, J A; Agustoni, M; Aharrouche, M; Ahlen, S P; Ahles, F; Ahmad, A; Ahsan, M; Aielli, G; Akdogan, T; Åkesson, T P A; Akimoto, G; Akimov, A V; Alam, M S; Alam, M A; Albert, J; Albrand, S; Aleksa, M; Aleksandrov, I N; Alessandria, F; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Aliev, M; Alimonti, G; Alison, J; Allbrooke, B M M; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alonso, F; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amelung, C; Ammosov, V V; Amorim, A; Amram, N; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoki, M; Aoun, S; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Arce, A T H; Arfaoui, S; Arguin, J-F; Arik, E; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnault, C; Artamonov, A; Artoni, G; Arutinov, D; Asai, S; Asfandiyarov, R; Ask, S; Åsman, B; Asquith, L; Assamagan, K; Astbury, A; Atkinson, M; Aubert, B; Auge, E; Augsten, K; Aurousseau, M; Avolio, G; Avramidou, R; Axen, D; Azuelos, G; Azuma, Y; Baak, M A; Baccaglioni, G; Bacci, C; Bach, A M; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Badescu, E; Bagnaia, P; Bahinipati, S; Bai, Y; Bailey, D C; Bain, T; Baines, J T; Baker, O K; Baker, M D; Baker, S; Banas, E; Banerjee, P; Banerjee, Sw; Banfi, D; Bangert, A; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barbaro Galtieri, A; Barber, T; Barberio, E L; Barberis, D; Barbero, M; Bardin, D Y; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnett, B M; Barnett, R M; Baroncelli, A; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Barrillon, P; Bartoldus, R; Barton, A E; Bartsch, V; Bates, R L; Batkova, L; Batley, J R; Battaglia, A; Battistin, M; Bauer, F; Bawa, H S; Beale, S; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, A K; Becker, S; Beckingham, M; Becks, K H; Beddall, A J; Beddall, A; Bedikian, S; Bednyakov, V A; Bee, C P; Beemster, L J; Begel, M; Behar Harpaz, S; Beimforde, M; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellina, F; Bellomo, M; Belloni, A; Beloborodova, O; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Benoit, M; Bensinger, J R; Benslama, K; Bentvelsen, S; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Berglund, E; Beringer, J; Bernat, P; Bernhard, R; Bernius, C; Berry, T; Bertella, C; Bertin, A; Bertolucci, F; Besana, M I; Besjes, G J; Besson, N; Bethke, S; Bhimji, W; Bianchi, R M; Bianco, M; Biebel, O; Bieniek, S P; Bierwagen, K; Biesiada, J; Biglietti, M; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Biscarat, C; Bitenc, U; Black, K M; Blair, R E; Blanchard, J-B; Blanchot, G; Blazek, T; Blocker, C; Blocki, J; Blondel, A; Blum, W; Blumenschein, U; Bobbink, G J; Bobrovnikov, V B; Bocchetta, S S; Bocci, A; Boddy, C R; Boehler, M; Boek, J; Boelaert, N; Bogaerts, J A; Bogdanchikov, A; Bogouch, A; Bohm, C; Bohm, J; Boisvert, V; Bold, T; Boldea, V; Bolnet, N M; Bomben, M; Bona, M; Boonekamp, M; Booth, C N; Bordoni, S; Borer, C; Borisov, A; Borissov, G; Borjanovic, I; Borri, M; Borroni, S; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Boterenbrood, H; Bouchami, J; Boudreau, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Bousson, N; Boveia, A; Boyd, J; Boyko, I R; Bozovic-Jelisavcic, I; Bracinik, J; Branchini, P; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Brazzale, S F; Brelier, B; Bremer, J; Brendlinger, K; Brenner, R; Bressler, S; Britton, D; Brochu, F M; Brock, I; Brock, R; Broggi, F; Bromberg, C; Bronner, J; Brooijmans, G; Brooks, T; Brooks, W K; Brown, G; Brown, H; Bruckman de Renstrom, P A; Bruncko, D; Bruneliere, R; Brunet, S; Bruni, A; Bruni, G; Bruschi, M; Buanes, T; Buat, Q; Bucci, F; Buchanan, J; Buchholz, P; Buckingham, R M; Buckley, A G; Buda, S I; Budagov, I A; Budick, B; Büscher, V; Bugge, L; Bulekov, O; Bundock, A C; Bunse, M; Buran, T; Burckhart, H; Burdin, S; Burgess, T; Burke, S; Busato, E; Bussey, P; Buszello, C P; Butler, B; Butler, J M; Buttar, C M; Butterworth, J M; Buttinger, W; Byszewski, M; Cabrera Urbán, S; Caforio, D; Cakir, O; Calafiura, P; Calderini, G; Calfayan, P; Calkins, R; Caloba, L P; Caloi, R; Calvet, D; Calvet, S; Camacho Toro, R; Camarri, P; Cameron, D; Caminada, L M; Campana, S; Campanelli, M; Canale, V; Canelli, F; Canepa, A; Cantero, J; Cantrill, R; Capasso, L; Capeans Garrido, M D M; Caprini, I; Caprini, M; Capriotti, D; Capua, M; Caputo, R; Cardarelli, R; Carli, T; Carlino, G; Carminati, L; Caron, B; Caron, S; Carquin, E; Carrillo Montoya, G D; Carter, A A; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Cascella, M; Caso, C; Castaneda Hernandez, A M; Castaneda-Miranda, E; Castillo Gimenez, V; Castro, N F; Cataldi, G; Catastini, P; Catinaccio, A; Catmore, J R; Cattai, A; Cattani, G; Caughron, S; Cavaliere, V; Cavalleri, P; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cetin, S A; Chafaq, A; Chakraborty, D; Chalupkova, I; Chan, K; Chapleau, B; Chapman, J D; Chapman, J W; Chareyre, E; Charlton, D G; Chavda, V; Chavez Barajas, C A; Cheatham, S; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, S; Chen, X; Chen, Y; Cheplakov, A; Cherkaoui El Moursli, R; Chernyatin, V; Cheu, E; Cheung, S L; Chevalier, L; Chiefari, G; Chikovani, L; Childers, J T; Chilingarov, A; Chiodini, G; Chisholm, A S; Chislett, R T; Chitan, A; Chizhov, M V; Choudalakis, G; Chouridou, S; Christidi, I A; Christov, A; Chromek-Burckhart, D; Chu, M L; Chudoba, J; Ciapetti, G; Ciftci, A K; Ciftci, R; Cinca, D; Cindro, V; Ciocca, C; Ciocio, A; Cirilli, M; Cirkovic, P; Citterio, M; Ciubancan, M; Clark, A; Clark, P J; Clarke, R N; Cleland, W; Clemens, J C; Clement, B; Clement, C; Coadou, Y; Cobal, M; Coccaro, A; Cochran, J; Cogan, J G; Coggeshall, J; Cogneras, E; Colas, J; Cole, S; Colijn, A P; Collins, N J; Collins-Tooth, C; Collot, J; Colombo, T; Colon, G; Conde Muiño, P; Coniavitis, E; Conidi, M C; Consonni, S M; Consorti, V; Constantinescu, S; Conta, C; Conti, G; Conventi, F; Cooke, M; Cooper, B D; Cooper-Sarkar, A M; Copic, K; Cornelissen, T; Corradi, M; Corriveau, F; Cortes-Gonzalez, A; Cortiana, G; Costa, G; Costa, M J; Costanzo, D; Costin, T; Côté, D; Courneyea, L; Cowan, G; Cowden, C; Cox, B E; Cranmer, K; Crescioli, F; Cristinziani, M; Crosetti, G; Crépé-Renaudin, S; Cuciuc, C-M; Cuenca Almenar, C; Cuhadar Donszelmann, T; Curatolo, M; Curtis, C J; Cuthbert, C; Cwetanski, P; Czirr, H; Czodrowski, P; Czyczula, Z; D'Auria, S; D'Onofrio, M; D'Orazio, A; Da Cunha Sargedas De Sousa, M J; Da Via, C; Dabrowski, W; Dafinca, A; Dai, T; Dallapiccola, C; Dam, M; Dameri, M; Damiani, D S; Danielsson, H O; Dao, V; Darbo, G; Darlea, G L; Dassoulas, J A; Davey, W; Davidek, T; Davidson, N; Davidson, R; Davies, E; Davies, M; Davignon, O; Davison, A R; Davygora, Y; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Castro, S; De Cecco, S; de Graat, J; De Groot, N; de Jong, P; De La Taille, C; De la Torre, H; De Lorenzi, F; de Mora, L; De Nooij, L; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Vivie De Regie, J B; De Zorzi, G; Dearnaley, W J; Debbe, R; Debenedetti, C; Dechenaux, B; Dedovich, D V; Degenhardt, J; Del Papa, C; Del Peso, J; Del Prete, T; Delemontex, T; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Della Pietra, M; della Volpe, D; Delmastro, M; Delsart, P A; Deluca, C; Demers, S; Demichev, M; Demirkoz, B; Deng, J; Denisov, S P; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Devetak, E; Deviveiros, P O; Dewhurst, A; DeWilde, B; Dhaliwal, S; Dhullipudi, R; Di Ciaccio, A; Di Ciaccio, L; Di Girolamo, A; Di Girolamo, B; Di Luise, S; Di Mattia, A; Di Micco, B; Di Nardo, R; Di Simone, A; Di Sipio, R; Diaz, M A; Diehl, E B; Dietrich, J; Dietzsch, T A; Diglio, S; Dindar Yagci, K; Dingfelder, J; Dinut, F; Dionisi, C; Dita, P; Dita, S; Dittus, F; Djama, F; Djobava, T; do Vale, M A B; Do Valle Wemans, A; Doan, T K O; Dobbs, M; Dobinson, R; Dobos, D; Dobson, E; Dodd, J; Doglioni, C; Doherty, T; Doi, Y; Dolejsi, J; Dolenc, I; Dolezal, Z; Dolgoshein, B A; Dohmae, T; Donadelli, M; Donini, J; Dopke, J; Doria, A; Dos Anjos, A; Dotti, A; Dova, M T; Doxiadis, A D; Doyle, A T; Dris, M; Dubbert, J; Dube, S; Duchovni, E; Duckeck, G; Dudarev, A; Dudziak, F; Dührssen, M; Duerdoth, I P; Duflot, L; Dufour, M-A; Duguid, L; Dunford, M; Duran Yildiz, H; Duxfield, R; Dwuznik, M; Dydak, F; Düren, M; Ebke, J; Eckweiler, S; Edmonds, K; Edson, W; Edwards, C A; Edwards, N C; Ehrenfeld, W; Eifert, T; Eigen, G; Einsweiler, K; Eisenhandler, E; Ekelof, T; El Kacimi, M; Ellert, M; Elles, S; Ellinghaus, F; Ellis, K; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Engelmann, R; Engl, A; Epp, B; Erdmann, J; Ereditato, A; Eriksson, D; Ernst, J; Ernst, M; Ernwein, J; Errede, D; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Espinal Curull, X; Esposito, B; Etienne, F; Etienvre, A I; Etzion, E; Evangelakou, D; Evans, H; Fabbri, L; Fabre, C; Fakhrutdinov, R M; Falciano, S; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farley, J; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassnacht, P; Fassouliotis, D; Fatholahzadeh, B; Favareto, A; Fayard, L; Fazio, S; Febbraro, R; Federic, P; Fedin, O L; Fedorko, W; Fehling-Kaschek, M; Feligioni, L; Fellmann, D; Feng, C; Feng, E J; Fenyuk, A B; Ferencei, J; Fernando, W; Ferrag, S; Ferrando, J; Ferrara, V; Ferrari, A; Ferrari, P; Ferrari, R; Ferreira de Lima, D E; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; Fiascaris, M; Fiedler, F; Filipčič, A; Filthaut, F; Fincke-Keeler, M; Fiolhais, M C N; Fiorini, L; Firan, A; Fischer, G; Fisher, M J; Flechl, M; Fleck, I; Fleckner, J; Fleischmann, P; Fleischmann, S; Flick, T; Floderus, A; Flores Castillo, L R; Flowerdew, M J; Fonseca Martin, T; Formica, A; Forti, A; Fortin, D; Fournier, D; Fox, H; Francavilla, P; Franchini, M; Franchino, S; Francis, D; Frank, T; Franz, S; Fraternali, M; Fratina, S; French, S T; Friedrich, C; Friedrich, F; Froeschl, R; Froidevaux, D; Frost, J A; Fukunaga, C; Fullana Torregrosa, E; Fulsom, B G; Fuster, J; Gabaldon, C; Gabizon, O; Gadfort, T; Gadomski, S; Gagliardi, G; Gagnon, P; Galea, C; Gallas, E J; Gallo, V; Gallop, B J; Gallus, P; Gan, K K; Gao, Y S; Gaponenko, A; Garberson, F; Garcia-Sciveres, M; García, C; García Navarro, J E; Gardner, R W; Garelli, N; Garitaonandia, H; Garonne, V; Gatti, C; Gaudio, G; Gaur, B; Gauthier, L; Gauzzi, P; Gavrilenko, I L; Gay, C; Gaycken, G; Gazis, E N; Ge, P; Gecse, Z; Gee, C N P; Geerts, D A A; Geich-Gimbel, Ch; Gellerstedt, K; Gemme, C; Gemmell, A; Genest, M H; Gentile, S; George, M; George, S; Gerlach, P; Gershon, A; Geweniger, C; Ghazlane, H; Ghodbane, N; Giacobbe, B; Giagu, S; Giakoumopoulou, V; Giangiobbe, V; Gianotti, F; Gibbard, B; Gibson, A; Gibson, S M; Gillberg, D; Gillman, A R; Gingrich, D M; Ginzburg, J; Giokaris, N; Giordani, M P; Giordano, R; Giorgi, F M; Giovannini, P; Giraud, P F; Giugni, D; Giunta, M; Giusti, P; Gjelsten, B K; Gladilin, L K; Glasman, C; Glatzer, J; Glazov, A; Glitza, K W; Glonti, G L; Goddard, J R; Godfrey, J; Godlewski, J; Goebel, M; Göpfert, T; Goeringer, C; Gössling, C; Goldfarb, S; Golling, T; Gomes, A; Gomez Fajardo, L S; Gonçalo, R; Goncalves Pinto Firmino Da Costa, J; Gonella, L; Gonzalez, S; González de la Hoz, S; Gonzalez Parra, G; Gonzalez Silva, M L; Gonzalez-Sevilla, S; Goodson, J J; Goossens, L; Gorbounov, P A; Gordon, H A; Gorelov, I; Gorfine, G; Gorini, B; Gorini, E; Gorišek, A; Gornicki, E; Gosdzik, B; Goshaw, A T; Gosselink, M; Gostkin, M I; Gough Eschrich, I; Gouighri, M; Goujdami, D; Goulette, M P; Goussiou, A G; Goy, C; Gozpinar, S; Grabowska-Bold, I; Grafström, P; Grahn, K-J; Grancagnolo, F; Grancagnolo, S; Grassi, V; Gratchev, V; Grau, N; Gray, H M; Gray, J A; Graziani, E; Grebenyuk, O G; Greenshaw, T; Greenwood, Z D; Gregersen, K; Gregor, I M; Grenier, P; Griffiths, J; Grigalashvili, N; Grillo, A A; Grinstein, S; Grishkevich, Y V; Grivaz, J-F; Gross, E; Grosse-Knetter, J; Groth-Jensen, J; Grybel, K; Guest, D; Guicheney, C; Guindon, S; Gul, U; Guler, H; Gunther, J; Guo, B; Guo, J; Gutierrez, P; Guttman, N; Gutzwiller, O; Guyot, C; Gwenlan, C; Gwilliam, C B; Haas, A; Haas, S; Haber, C; Hadavand, H K; Hadley, D R; Haefner, P; Hahn, F; Haider, S; Hajduk, Z; Hakobyan, H; Hall, D; Haller, J; Hamacher, K; Hamal, P; Hamer, M; Hamilton, A; Hamilton, S; Han, L; Hanagaki, K; Hanawa, K; Hance, M; Handel, C; Hanke, P; Hansen, J R; Hansen, J B; Hansen, J D; Hansen, P H; Hansson, P; Hara, K; Hare, G A; Harenberg, T; Harkusha, S; Harper, D; Harrington, R D; Harris, O M; Hartert, J; Hartjes, F; Haruyama, T; Harvey, A; Hasegawa, S; Hasegawa, Y; Hassani, S; Haug, S; Hauschild, M; Hauser, R; Havranek, M; Hawkes, C M; Hawkings, R J; Hawkins, A D; Hawkins, D; Hayakawa, T; Hayashi, T; Hayden, D; Hays, C P; Hayward, H S; Haywood, S J; He, M; Head, S J; Hedberg, V; Heelan, L; Heim, S; Heinemann, B; Heisterkamp, S; Helary, L; Heller, C; Heller, M; Hellman, S; Hellmich, D; Helsens, C; Henderson, R C W; Henke, M; Henrichs, A; Henriques Correia, A M; Henrot-Versille, S; Hensel, C; Henß, T; Hernandez, C M; Hernández Jiménez, Y; Herrberg, R; Herten, G; Hertenberger, R; Hervas, L; Hesketh, G G; Hessey, N P; Higón-Rodriguez, E; Hill, J C; Hiller, K H; Hillert, S; Hillier, S J; Hinchliffe, I; Hines, E; Hirose, M; Hirsch, F; Hirschbuehl, D; Hobbs, J; Hod, N; Hodgkinson, M C; Hodgson, P; Hoecker, A; Hoeferkamp, M R; Hoffman, J; Hoffmann, D; Hohlfeld, M; Holder, M; Holmgren, S O; Holy, T; Holzbauer, J L; Hong, T M; Hooft van Huysduynen, L; Horn, C; Horner, S; Hostachy, J-Y; Hou, S; Hoummada, A; Howard, J; Howarth, J; Hristova, I; Hrivnac, J; Hryn'ova, T; Hsu, P J; Hsu, S-C; Hubacek, Z; Hubaut, F; Huegging, F; Huettmann, A; Huffman, T B; Hughes, E W; Hughes, G; Huhtinen, M; Hurwitz, M; Husemann, U; Huseynov, N; Huston, J; Huth, J; Iacobucci, G; Iakovidis, G; Ibbotson, M; Ibragimov, I; Iconomidou-Fayard, L; Idarraga, J; Iengo, P; Igonkina, O; Ikegami, Y; Ikeno, M; Iliadis, D; Ilic, N; Ince, T; Inigo-Golfin, J; Ioannou, P; Iodice, M; Iordanidou, K; Ippolito, V; Irles Quiles, A; Isaksson, C; Ishino, M; Ishitsuka, M; Ishmukhametov, R; Issever, C; Istin, S; Ivashin, A V; Iwanski, W; Iwasaki, H; Izen, J M; Izzo, V; Jackson, B; Jackson, J N; Jackson, P; Jaekel, M R; Jain, V; Jakobs, K; Jakobsen, S; Jakoubek, T; Jakubek, J; Jana, D K; Jansen, E; Jansen, H; Jantsch, A; Janus, M; Jarlskog, G; Jeanty, L; Jen-La Plante, I; Jennens, D; Jenni, P; Jež, P; Jézéquel, S; Jha, M K; Ji, H; Ji, W; Jia, J; Jiang, Y; Jimenez Belenguer, M; Jin, S; Jinnouchi, O; Joergensen, M D; Joffe, D; Johansen, M; Johansson, K E; Johansson, P; Johnert, S; Johns, K A; Jon-And, K; Jones, G; Jones, R W L; Jones, T J; Joram, C; Jorge, P M; Joshi, K D; Jovicevic, J; Jovin, T; Ju, X; Jung, C A; Jungst, R M; Juranek, V; Jussel, P; Juste Rozas, A; Kabana, S; Kaci, M; Kaczmarska, A; Kadlecik, P; Kado, M; Kagan, H; Kagan, M; Kajomovitz, E; Kalinin, S; Kalinovskaya, L V; Kama, S; Kanaya, N; Kaneda, M; Kaneti, S; Kanno, T; Kantserov, V A; Kanzaki, J; Kaplan, B; Kapliy, A; Kaplon, J; Kar, D; Karagounis, M; Karakostas, K; Karnevskiy, M; Kartvelishvili, V; Karyukhin, A N; Kashif, L; Kasieczka, G; Kass, R D; Kastanas, A; Kataoka, M; Kataoka, Y; Katsoufis, E; Katzy, J; Kaushik, V; Kawagoe, K; Kawamoto, T; Kawamura, G; Kayl, M S; Kazama, S; Kazanin, V A; Kazarinov, M Y; Keeler, R; Kehoe, R; Keil, M; Kekelidze, G D; Keller, J S; Kenyon, M; Kepka, O; Kerschen, N; Kerševan, B P; Kersten, S; Kessoku, K; Keung, J; Khalil-Zada, F; Khandanyan, H; Khanov, A; Kharchenko, D; Khodinov, A; Khomich, A; Khoo, T J; Khoriauli, G; Khoroshilov, A; Khovanskiy, V; Khramov, E; Khubua, J; Kim, H; Kim, S H; Kimura, N; Kind, O; King, B T; King, M; King, R S B; Kirk, J; Kiryunin, A E; Kishimoto, T; Kisielewska, D; Kitamura, T; Kittelmann, T; Kladiva, E; Klein, M; Klein, U; Kleinknecht, K; Klemetti, M; Klier, A; Klimek, P; Klimentov, A; Klingenberg, R; Klinger, J A; Klinkby, E B; Klioutchnikova, T; Klok, P F; Klous, S; Kluge, E-E; Kluge, T; Kluit, P; Kluth, S; Knecht, N S; Kneringer, E; Knoops, E B F G; Knue, A; Ko, B R; Kobayashi, T; Kobel, M; Kocian, M; Kodys, P; Köneke, K; König, A C; Koenig, S; Köpke, L; Koetsveld, F; Koevesarki, P; Koffas, T; Koffeman, E; Kogan, L A; Kohlmann, S; Kohn, F; Kohout, Z; Kohriki, T; Koi, T; Kolachev, G M; Kolanoski, H; Kolesnikov, V; Koletsou, I; Koll, J; Kollefrath, M; Komar, A A; Komori, Y; Kondo, T; Kono, T; Kononov, A I; Konoplich, R; Konstantinidis, N; Koperny, S; Korcyl, K; Kordas, K; Korn, A; Korol, A; Korolkov, I; Korolkova, E V; Korotkov, V A; Kortner, O; Kortner, S; Kostyukhin, V V; Kotov, S; Kotov, V M; Kotwal, A; Kourkoumelis, C; Kouskoura, V; Koutsman, A; Kowalewski, R; Kowalski, T Z; Kozanecki, W; Kozhin, A S; Kral, V; Kramarenko, V A; Kramberger, G; Krasny, M W; Krasznahorkay, A; Kraus, J K; Kreiss, S; Krejci, F; Kretzschmar, J; Krieger, N; Krieger, P; Kroeninger, K; Kroha, H; Kroll, J; Kroseberg, J; Krstic, J; Kruchonak, U; Krüger, H; Kruker, T; Krumnack, N; Krumshteyn, Z V; Kubota, T; Kuday, S; Kuehn, S; Kugel, A; Kuhl, T; Kuhn, D; Kukhtin, V; Kulchitsky, Y; Kuleshov, S; Kummer, C; Kuna, M; Kunkle, J; Kupco, A; Kurashige, H; Kurata, M; Kurochkin, Y A; Kus, V; Kuwertz, E S; Kuze, M; Kvita, J; Kwee, R; La Rosa, A; La Rotonda, L; Labarga, L; Labbe, J; Lablak, S; Lacasta, C; Lacava, F; Lacker, H; Lacour, D; Lacuesta, V R; Ladygin, E; Lafaye, R; Laforge, B; Lagouri, T; Lai, S; Laisne, E; Lamanna, M; Lambourne, L; Lampen, C L; Lampl, W; Lancon, E; Landgraf, U; Landon, M P J; Lane, J L; Lang, V S; Lange, C; Lankford, A J; Lanni, F; Lantzsch, K; Laplace, S; Lapoire, C; Laporte, J F; Lari, T; Larner, A; Lassnig, M; Laurelli, P; Lavorini, V; Lavrijsen, W; Laycock, P; Le Dortz, O; Le Guirriec, E; Le Maner, C; Le Menedeu, E; LeCompte, T; Ledroit-Guillon, F; Lee, H; Lee, J S H; Lee, S C; Lee, L; Lefebvre, M; Legendre, M; Legger, F; Leggett, C; Lehmacher, M; Lehmann Miotto, G; Lei, X; Leite, M A L; Leitner, R; Lellouch, D; Lemmer, B; Lendermann, V; Leney, K J C; Lenz, T; Lenzen, G; Lenzi, B; Leonhardt, K; Leontsinis, S; Lepold, F; Leroy, C; Lessard, J-R; Lester, C G; Lester, C M; Levêque, J; Levin, D; Levinson, L J; Lewis, A; Lewis, G H; Leyko, A M; Leyton, M; Li, B; Li, H; Li, S; Li, X; Liang, Z; Liao, H; Liberti, B; Lichard, P; Lichtnecker, M; Lie, K; Liebig, W; Limbach, C; Limosani, A; Limper, M; Lin, S C; Linde, F; Linnemann, J T; Lipeles, E; Lipniacka, A; Liss, T M; Lissauer, D; Lister, A; Litke, A M; Liu, C; Liu, D; Liu, H; Liu, J B; Liu, L; Liu, M; Liu, Y; Livan, M; Livermore, S S A; Lleres, A; Llorente Merino, J; Lloyd, S L; Lobodzinska, E; Loch, P; Lockman, W S; Loddenkoetter, T; Loebinger, F K; Loginov, A; Loh, C W; Lohse, T; Lohwasser, K; Lokajicek, M; Lombardo, V P; Long, R E; Lopes, L; Lopez Mateos, D; Lorenz, J; Lorenzo Martinez, N; Losada, M; Loscutoff, P; Lo Sterzo, F; Losty, M J; Lou, X; Lounis, A; Loureiro, K F; Love, J; Love, P A; Lowe, A J; Lu, F; Lubatti, H J; Luci, C; Lucotte, A; Ludwig, A; Ludwig, D; Ludwig, I; Ludwig, J; Luehring, F; Luijckx, G; Lukas, W; Lumb, D; Luminari, L; Lund, E; Lund-Jensen, B; Lundberg, B; Lundberg, J; Lundberg, O; Lundquist, J; Lungwitz, M; Lynn, D; Lytken, E; Ma, H; Ma, L L; Maccarrone, G; Macchiolo, A; Maček, B; Machado Miguens, J; Mackeprang, R; Madaras, R J; Maddocks, H J; Mader, W F; Maenner, R; Maeno, T; Mättig, P; Mättig, S; Magnoni, L; Magradze, E; Mahboubi, K; Mahmoud, S; Mahout, G; Maiani, C; Maidantchik, C; Maio, A; Majewski, S; Makida, Y; Makovec, N; Mal, P; Malaescu, B; Malecki, Pa; Malecki, P; Maleev, V P; Malek, F; Mallik, U; Malon, D; Malone, C; Maltezos, S; Malyshev, V; Malyukov, S; Mameghani, R; Mamuzic, J; Manabe, A; Mandelli, L; Mandić, I; Mandrysch, R; Maneira, J; Mangeard, P S; Manhaes de Andrade Filho, L; Manjarres Ramos, J A; Mann, A; Manning, P M; Manousakis-Katsikakis, A; Mansoulie, B; Mapelli, A; Mapelli, L; March, L; Marchand, J F; Marchese, F; Marchiori, G; Marcisovsky, M; Marino, C P; Marroquim, F; Marshall, Z; Martens, F K; Marti, L F; Marti-Garcia, S; Martin, B; Martin, B; Martin, J P; Martin, T A; Martin, V J; Martin dit Latour, B; Martin-Haugh, S; Martinez, M; Martinez Outschoorn, V; Martyniuk, A C; Marx, M; Marzano, F; Marzin, A; Masetti, L; Mashimo, T; Mashinistov, R; Masik, J; Maslennikov, A L; Massa, I; Massaro, G; Massol, N; Mastrandrea, P; Mastroberardino, A; Masubuchi, T; Matricon, P; Matsunaga, H; Matsushita, T; Mattravers, C; Maurer, J; Maxfield, S J; Mayne, A; Mazini, R; Mazur, M; Mazzaferro, L; Mazzanti, M; Mc Kee, S P; McCarn, A; McCarthy, R L; McCarthy, T G; McCubbin, N A; McFarlane, K W; Mcfayden, J A; Mchedlidze, G; Mclaughlan, T; McMahon, S J; McPherson, R A; Meade, A; Mechnich, J; Mechtel, M; Medinnis, M; Meera-Lebbai, R; Meguro, T; Mehdiyev, R; Mehlhase, S; Mehta, A; Meier, K; Meirose, B; Melachrinos, C; Mellado Garcia, B R; Meloni, F; Mendoza Navas, L; Meng, Z; Mengarelli, A; Menke, S; Meoni, E; Mercurio, K M; Mermod, P; Merola, L; Meroni, C; Merritt, F S; Merritt, H; Messina, A; Metcalfe, J; Mete, A S; Meyer, C; Meyer, C; Meyer, J-P; Meyer, J; Meyer, J; Meyer, T C; Miao, J; Michal, S; Micu, L; Middleton, R P; Migas, S; Mijović, L; Mikenberg, G; Mikestikova, M; Mikuž, M; Miller, D W; Miller, R J; Mills, W J; Mills, C; Milov, A; Milstead, D A; Milstein, D; Minaenko, A A; Miñano Moya, M; Minashvili, I A; Mincer, A I; Mindur, B; Mineev, M; Ming, Y; Mir, L M; Mirabelli, G; Mitrevski, J; Mitsou, V A; Mitsui, S; Miyagawa, P S; Mjörnmark, J U; Moa, T; Moeller, V; Mönig, K; Möser, N; Mohapatra, S; Mohr, W; Moles-Valls, R; Monk, J; Monnier, E; Montejo Berlingen, J; Monticelli, F; Monzani, S; Moore, R W; Moorhead, G F; Mora Herrera, C; Moraes, A; Morange, N; Morel, J; Morello, G; Moreno, D; Moreno Llácer, M; Morettini, P; Morgenstern, M; Morii, M; Morley, A K; Mornacchi, G; Morris, J D; Morvaj, L; Moser, H G; Mosidze, M; Moss, J; Mount, R; Mountricha, E; Mouraviev, S V; Moyse, E J W; Mueller, F; Mueller, J; Mueller, K; Müller, T A; Mueller, T; Muenstermann, D; Munwes, Y; Murray, W J; Mussche, I; Musto, E; Myagkov, A G; Myska, M; Nadal, J; Nagai, K; Nagai, R; Nagano, K; Nagarkar, A; Nagasaka, Y; Nagel, M; Nairz, A M; Nakahama, Y; Nakamura, K; Nakamura, T; Nakano, I; Nanava, G; Napier, A; Narayan, R; Nash, M; Nattermann, T; Naumann, T; Navarro, G; Neal, H A; Nechaeva, P Yu; Neep, T J; Negri, A; Negri, G; Negrini, M; Nektarijevic, S; Nelson, A; Nelson, T K; Nemecek, S; Nemethy, P; Nepomuceno, A A; Nessi, M; Neubauer, M S; Neumann, M; Neusiedl, A; Neves, R M; Nevski, P; Newman, P R; Nguyen Thi Hong, V; Nickerson, R B; Nicolaidou, R; Nicquevert, B; Niedercorn, F; Nielsen, J; Nikiforou, N; Nikiforov, A; Nikolaenko, V; Nikolic-Audit, I; Nikolics, K; Nikolopoulos, K; Nilsen, H; Nilsson, P; Ninomiya, Y; Nisati, A; Nisius, R; Nobe, T; Nodulman, L; Nomachi, M; Nomidis, I; Norberg, S; Nordberg, M; Norton, P R; Novakova, J; Nozaki, M; Nozka, L; Nugent, I M; Nuncio-Quiroz, A-E; Nunes Hanninger, G; Nunnemann, T; Nurse, E; O'Brien, B J; O'Neale, S W; O'Neil, D C; O'Shea, V; Oakes, L B; Oakham, F G; Oberlack, H; Ocariz, J; Ochi, A; Oda, S; Odaka, S; Odier, J; Ogren, H; Oh, A; Oh, S H; Ohm, C C; Ohshima, T; Okawa, H; Okumura, Y; Okuyama, T; Olariu, A; Olchevski, A G; Olivares Pino, S A; Oliveira, M; Oliveira Damazio, D; Oliver Garcia, E; Olivito, D; Olszewski, A; Olszowska, J; Onofre, A; Onyisi, P U E; Oram, C J; Oreglia, M J; Oren, Y; Orestano, D; Orlando, N; Orlov, I; Oropeza Barrera, C; Orr, R S; Osculati, B; Ospanov, R; Osuna, C; Otero y Garzon, G; Ottersbach, J P; Ouchrif, M; Ouellette, E A; Ould-Saada, F; Ouraou, A; Ouyang, Q; Ovcharova, A; Owen, M; Owen, S; Ozcan, V E; Ozturk, N; Pacheco Pages, A; Padilla Aranda, C; Pagan Griso, S; Paganis, E; Pahl, C; Paige, F; Pais, P; Pajchel, K; Palacino, G; Paleari, C P; Palestini, S; Pallin, D; Palma, A; Palmer, J D; Pan, Y B; Panagiotopoulou, E; Pani, P; Panikashvili, N; Panitkin, S; Pantea, D; Papadelis, A; Papadopoulou, Th D; Paramonov, A; Paredes Hernandez, D; Park, W; Parker, M A; Parodi, F; Parsons, J A; Parzefall, U; Pashapour, S; Pasqualucci, E; Passaggio, S; Passeri, A; Pastore, F; Pastore, Fr; Pásztor, G; Pataraia, S; Patel, N; Pater, J R; Patricelli, S; Pauly, T; Pecsy, M; Pedraza Lopez, S; Pedraza Morales, M I; Peleganchuk, S V; Pelikan, D; Peng, H; Penning, B; Penson, A; Penwell, J; Perantoni, M; Perez, K; Perez Cavalcanti, T; Perez Codina, E; Pérez García-Estañ, M T; Perez Reale, V; Perini, L; Pernegger, H; Perrino, R; Perrodo, P; Peshekhonov, V D; Peters, K; Petersen, B A; Petersen, J; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petrolo, E; Petrucci, F; Petschull, D; Petteni, M; Pezoa, R; Phan, A; Phillips, P W; Piacquadio, G; Picazio, A; Piccaro, E; Piccinini, M; Piec, S M; Piegaia, R; Pignotti, D T; Pilcher, J E; Pilkington, A D; Pina, J; Pinamonti, M; Pinder, A; Pinfold, J L; Pinto, B; Pizio, C; Plamondon, M; Pleier, M-A; Plotnikova, E; Poblaguev, A; Poddar, S; Podlyski, F; Poggioli, L; Pohl, M; Polesello, G; Policicchio, A; Polini, A; Poll, J; Polychronakos, V; Pomeroy, D; Pommès, K; Pontecorvo, L; Pope, B G; Popeneciu, G A; Popovic, D S; Poppleton, A; Portell Bueso, X; Pospelov, G E; Pospisil, S; Potrap, I N; Potter, C J; Potter, C T; Poulard, G; Poveda, J; Pozdnyakov, V; Prabhu, R; Pralavorio, P; Pranko, A; Prasad, S; Pravahan, R; Prell, S; Pretzl, K; Price, D; Price, J; Price, L E; Prieur, D; Primavera, M; Prokofiev, K; Prokoshin, F; Protopopescu, S; Proudfoot, J; Prudent, X; Przybycien, M; Przysiezniak, H; Psoroulas, S; Ptacek, E; Pueschel, E; Purdham, J; Purohit, M; Puzo, P; Pylypchenko, Y; Qian, J; Quadt, A; Quarrie, D R; Quayle, W B; Quinonez, F; Raas, M; Radescu, V; Radloff, P; Rador, T; Ragusa, F; Rahal, G; Rahimi, A M; Rahm, D; Rajagopalan, S; Rammensee, M; Rammes, M; Randle-Conde, A S; Randrianarivony, K; Rauscher, F; Rave, T C; Raymond, M; Read, A L; Rebuzzi, D M; Redelbach, A; Redlinger, G; Reece, R; Reeves, K; Reinherz-Aronis, E; Reinsch, A; Reisinger, I; Rembser, C; Ren, Z L; Renaud, A; Rescigno, M; Resconi, S; Resende, B; Reznicek, P; Rezvani, R; Richter, R; Richter-Was, E; Ridel, M; Rijpstra, M; Rijssenbeek, M; Rimoldi, A; Rinaldi, L; Rios, R R; Riu, I; Rivoltella, G; Rizatdinova, F; Rizvi, E; Robertson, S H; Robichaud-Veronneau, A; Robinson, D; Robinson, J E M; Robson, A; Rocha de Lima, J G; Roda, C; Roda Dos Santos, D; Roe, A; Roe, S; Røhne, O; Rolli, S; Romaniouk, A; Romano, M; Romeo, G; Romero Adam, E; Roos, L; Ros, E; Rosati, S; Rosbach, K; Rose, A; Rose, M; Rosenbaum, G A; Rosenberg, E I; Rosendahl, P L; Rosenthal, O; Rosselet, L; Rossetti, V; Rossi, E; Rossi, L P; Rotaru, M; Roth, I; Rothberg, J; Rousseau, D; Royon, C R; Rozanov, A; Rozen, Y; Ruan, X; Rubbo, F; Rubinskiy, I; Ruckert, B; Ruckstuhl, N; Rud, V I; Rudolph, C; Rudolph, G; Rühr, F; Ruiz-Martinez, A; Rumyantsev, L; Rurikova, Z; Rusakovich, N A; Rutherfoord, J P; Ruwiedel, C; Ruzicka, P; Ryabov, Y F; Rybar, M; Rybkin, G; Ryder, N C; Saavedra, A F; Sadeh, I; Sadrozinski, H F-W; Sadykov, R; Safai Tehrani, F; Sakamoto, H; Salamanna, G; Salamon, A; Saleem, M; Salek, D; Salihagic, D; Salnikov, A; Salt, J; Salvachua Ferrando, B M; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sampsonidis, D; Samset, B H; Sanchez, A; Sanchez Martinez, V; Sandaker, H; Sander, H G; Sanders, M P; Sandhoff, M; Sandoval, T; Sandoval, C; Sandstroem, R; Sankey, D P C; Sansoni, A; Santamarina Rios, C; Santoni, C; Santonico, R; Santos, H; Saraiva, J G; Sarangi, T; Sarkisyan-Grinbaum, E; Sarri, F; Sartisohn, G; Sasaki, O; Sasaki, Y; Sasao, N; Satsounkevitch, I; Sauvage, G; Sauvan, E; Sauvan, J B; Savard, P; Savinov, V; Savu, D O; Sawyer, L; Saxon, D H; Saxon, J; Sbarra, C; Sbrizzi, A; Scannicchio, D A; Scarcella, M; Schaarschmidt, J; Schacht, P; Schaefer, D; Schäfer, U; Schaepe, S; Schaetzel, S; Schaffer, A C; Schaile, D; Schamberger, R D; Schamov, A G; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Scherzer, M I; Schiavi, C; Schieck, J; Schioppa, M; Schlenker, S; Schmidt, E; Schmieden, K; Schmitt, C; Schmitt, S; Schmitz, M; Schneider, B; Schnoor, U; Schoening, A; Schorlemmer, A L S; Schott, M; Schouten, D; Schovancova, J; Schram, M; Schroeder, C; Schroer, N; Schultens, M J; Schultes, J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, Ph; Schwanenberger, C; Schwartzman, A; Schwemling, Ph; Schwienhorst, R; Schwierz, R; Schwindling, J; Schwindt, T; Schwoerer, M; Sciolla, G; Scott, W G; Searcy, J; Sedov, G; Sedykh, E; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekula, S J; Selbach, K E; Seliverstov, D M; Sellden, B; Sellers, G; Seman, M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Seuster, R; Severini, H; Sfyrla, A; Shabalina, E; Shamim, M; Shan, L Y; Shank, J T; Shao, Q T; Shapiro, M; Shatalov, P B; Shaw, K; Sherman, D; Sherwood, P; Shibata, A; Shimizu, S; Shimojima, M; Shin, T; Shiyakova, M; Shmeleva, A; Shochet, M J; Short, D; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sidoti, A; Siegert, F; Sijacki, Dj; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simoniello, R; Simonyan, M; Sinervo, P; Sinev, N B; Sipica, V; Siragusa, G; Sircar, A; Sisakyan, A N; Sivoklokov, S Yu; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K; Skubic, P; Slater, M; Slavicek, T; Sliwa, K; Smakhtin, V; Smart, B H; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, B C; Smith, D; Smith, K M; Smizanska, M; Smolek, K; Snesarev, A A; Snow, S W; Snow, J; Snyder, S; Sobie, R; Sodomka, J; Soffer, A; Solans, C A; Solar, M; Solc, J; Soldatov, E Yu; Soldevila, U; Solfaroli Camillocci, E; Solodkov, A A; Solovyanov, O V; Solovyev, V; Soni, N; Sopko, V; Sopko, B; Sosebee, M; Soualah, R; Soukharev, A; Spagnolo, S; Spanò, F; Spighi, R; Spigo, G; Spiwoks, R; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Strube, J; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Soh, D A; Su, D; Subramania, Hs; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Swedish, S; Sykora, I; Sykora, T; Sánchez, J; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tamsett, M C; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanasijczuk, A J; Tani, K; Tannoury, N; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tatarkhanov, M; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thong, W M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tipton, P; Tisserant, S; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tomoto, M; Tompkins, L; Toms, K; Tonoyan, A; Topfel, C; Topilin, N D; Torchiani, I; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Triplett, N; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiakiris, M; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Turala, M; Turecek, D; Turk Cakir, I; Turlay, E; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Tzanakos, G; Uchida, K; Ueda, I; Ueno, R; Ugland, M; Uhlenbrock, M; Uhrmacher, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Unno, Y; Urbaniec, D; Usai, G; Uslenghi, M; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valenta, J; Valentinetti, S; Valero, A; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; Van Der Leeuw, R; van der Poel, E; van der Ster, D; van Eldik, N; van Gemmeren, P; van Vulpen, I; Vanadia, M; Vandelli, W; Vaniachine, A; Vankov, P; Vannucci, F; Vari, R; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Vegni, G; Veillet, J J; Veloso, F; Veness, R; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinek, E; Vinogradov, V B; Virchaux, M; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Radziewski, H; von Toerne, E; Vorobel, V; Vorwerk, V; Vos, M; Voss, R; Voss, T T; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vu Anh, T; Vuillermet, R; Vukotic, I; Wagner, W; Wagner, P; Wahlen, H; Wahrmund, S; Wakabayashi, J; Walch, S; Walder, J; Walker, R; Walkowiak, W; Wall, R; Waller, P; Walsh, B; Wang, C; Wang, H; Wang, H; Wang, J; Wang, J; Wang, R; Wang, S M; Wang, T; Warburton, A; Ward, C P; Warsinsky, M; Washbrook, A; Wasicki, C; Watanabe, I; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, A T; Waugh, B M; Weber, M S; Weber, P; Weidberg, A R; Weigell, P; Weingarten, J; Weiser, C; Wellenstein, H; Wells, P S; Wenaus, T; Wendland, D; Weng, Z; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Werth, M; Wessels, M; Wetter, J; Weydert, C; Whalen, K; Wheeler-Ellis, S J; White, A; White, M J; White, S; Whitehead, S R; Whiteson, D; Whittington, D; Wicek, F; Wicke, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wijeratne, P A; Wildauer, A; Wildt, M A; Wilhelm, I; Wilkens, H G; Will, J Z; Williams, E; Williams, H H; Willis, W; Willocq, S; Wilson, J A; Wilson, M G; Wilson, A; Wingerter-Seez, I; Winkelmann, S; Winklmeier, F; Wittgen, M; Wollstadt, S J; Wolter, M W; Wolters, H; Wong, W C; Wooden, G; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wraight, K; Wright, M; Wrona, B; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wynne, B M; Xella, S; Xiao, M; Xie, S; Xu, C; Xu, D; Yabsley, B; Yacoob, S; Yamada, M; Yamaguchi, H; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamaoka, J; Yamazaki, T; Yamazaki, Y; Yan, Z; Yang, H; Yang, U K; Yang, Y; Yang, Z; Yanush, S; Yao, L; Yao, Y; Yasu, Y; Ybeles Smit, G V; Ye, J; Ye, S; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Young, C; Young, C J; Youssef, S; Yu, D; Yu, J; Yu, J; Yuan, L; Yurkewicz, A; Zabinski, B; Zaidan, R; Zaitsev, A M; Zajacova, Z; Zanello, L; Zaytsev, A; Zeitnitz, C; Zeman, M; Zemla, A; Zendler, C; Zenin, O; Ženiš, T; Zinonos, Z; Zenz, S; Zerwas, D; Zevi della Porta, G; Zhan, Z; Zhang, D; Zhang, H; Zhang, J; Zhang, X; Zhang, Z; Zhao, L; Zhao, T; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, N; Zhou, Y; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhuravlov, V; Zieminska, D; Zimin, N I; Zimmermann, R; Zimmermann, S; Zimmermann, S; Ziolkowski, M; Zitoun, R; Živković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; zur Nedden, M; Zutshi, V; Zwalinski, L

2012-12-28

This Letter presents a search for magnetic monopoles with the ATLAS detector at the CERN Large Hadron Collider using an integrated luminosity of 2.0  fb(-1) of pp collisions recorded at a center-of-mass energy of sqrt[s]=7  TeV. No event is found in the signal region, leading to an upper limit on the production cross section at 95% confidence level of 1.6/ϵ  fb for Dirac magnetic monopoles with the minimum unit magnetic charge and with mass between 200 GeV and 1500 GeV, where ϵ is the monopole reconstruction efficiency. The efficiency ϵ is high and uniform in the fiducial region given by pseudorapidity |η|<1.37 and transverse kinetic energy 600-700

Real-time estimation of prostate tumor rotation and translation with a kV imaging system based on an iterative closest point algorithm.

PubMed

Tehrani, Joubin Nasehi; O'Brien, Ricky T; Poulsen, Per Rugaard; Keall, Paul

2013-12-07

Previous studies have shown that during cancer radiotherapy a small translation or rotation of the tumor can lead to errors in dose delivery. Current best practice in radiotherapy accounts for tumor translations, but is unable to address rotation due to a lack of a reliable real-time estimate. We have developed a method based on the iterative closest point (ICP) algorithm that can compute rotation from kilovoltage x-ray images acquired during radiation treatment delivery. A total of 11 748 kilovoltage (kV) images acquired from ten patients (one fraction for each patient) were used to evaluate our tumor rotation algorithm. For each kV image, the three dimensional coordinates of three fiducial markers inside the prostate were calculated. The three dimensional coordinates were used as input to the ICP algorithm to calculate the real-time tumor rotation and translation around three axes. The results show that the root mean square error was improved for real-time calculation of tumor displacement from a mean of 0.97 mm with the stand alone translation to a mean of 0.16 mm by adding real-time rotation and translation displacement with the ICP algorithm. The standard deviation (SD) of rotation for the ten patients was 2.3°, 0.89° and 0.72° for rotation around the right-left (RL), anterior-posterior (AP) and superior-inferior (SI) directions respectively. The correlation between all six degrees of freedom showed that the highest correlation belonged to the AP and SI translation with a correlation of 0.67. The second highest correlation in our study was between the rotation around RL and rotation around AP, with a correlation of -0.33. Our real-time algorithm for calculation of rotation also confirms previous studies that have shown the maximum SD belongs to AP translation and rotation around RL. ICP is a reliable and fast algorithm for estimating real-time tumor rotation which could create a pathway to investigational clinical treatment studies requiring real-time measurement and adaptation to tumor rotation.

Real-time estimation of prostate tumor rotation and translation with a kV imaging system based on an iterative closest point algorithm

NASA Astrophysics Data System (ADS)

Nasehi Tehrani, Joubin; O'Brien, Ricky T.; Rugaard Poulsen, Per; Keall, Paul

2013-12-01

Previous studies have shown that during cancer radiotherapy a small translation or rotation of the tumor can lead to errors in dose delivery. Current best practice in radiotherapy accounts for tumor translations, but is unable to address rotation due to a lack of a reliable real-time estimate. We have developed a method based on the iterative closest point (ICP) algorithm that can compute rotation from kilovoltage x-ray images acquired during radiation treatment delivery. A total of 11 748 kilovoltage (kV) images acquired from ten patients (one fraction for each patient) were used to evaluate our tumor rotation algorithm. For each kV image, the three dimensional coordinates of three fiducial markers inside the prostate were calculated. The three dimensional coordinates were used as input to the ICP algorithm to calculate the real-time tumor rotation and translation around three axes. The results show that the root mean square error was improved for real-time calculation of tumor displacement from a mean of 0.97 mm with the stand alone translation to a mean of 0.16 mm by adding real-time rotation and translation displacement with the ICP algorithm. The standard deviation (SD) of rotation for the ten patients was 2.3°, 0.89° and 0.72° for rotation around the right-left (RL), anterior-posterior (AP) and superior-inferior (SI) directions respectively. The correlation between all six degrees of freedom showed that the highest correlation belonged to the AP and SI translation with a correlation of 0.67. The second highest correlation in our study was between the rotation around RL and rotation around AP, with a correlation of -0.33. Our real-time algorithm for calculation of rotation also confirms previous studies that have shown the maximum SD belongs to AP translation and rotation around RL. ICP is a reliable and fast algorithm for estimating real-time tumor rotation which could create a pathway to investigational clinical treatment studies requiring real-time measurement and adaptation to tumor rotation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

The cross-section for the production of two jets in association with a leptonically decaying Z boson (Zjj ) is measured in proton–proton collisions at a centre-of-mass energy of 13 TeV, using data recorded with the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of 3.2 fb -1. The electroweak Zjj cross-section is extracted in a fiducial region chosen to enhance the electroweak contribution relative to the dominant Drell–Yan Zjj process, which is constrained using a data-driven approach. The measured fiducial electroweak cross-section is σmore » $$Zjj\\atop{EW}$$ 119 ± 16 (stat.) ± 20 (syst.) ± 2 (lumi.) fb for dijet invariant mass greater than 250 GeV, and 34.2 ± 5.8 (stat.) ± 5.5 (syst.) ± 0.7 (lumi.) fb for dijet invariant mass greater than 1 TeV. Standard Model predictions are in agreement with the measurements. Lastly, the inclusive Zjj cross-section is also measured in six different fiducial regions with varying contributions from electroweak and Drell–Yan Zjj production.« less

Effects of line fiducial parameters and beamforming on ultrasound calibration

PubMed Central

Ameri, Golafsoun; Baxter, John S. H.; McLeod, A. Jonathan; Peters, Terry M.; Chen, Elvis C. S.

2017-01-01

Abstract. Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the total accuracy of the interventional guidance system. Here, we investigate the effects of US image reconstruction techniques as well as phantom material and geometry on US calibration. It was shown that the FLE was reduced by 29% with synthetic transmit aperture imaging compared with conventional B-mode imaging in a Z-bar calibration, resulting in a 10% reduction of calibration error. In addition, an evaluation of a variety of calibration phantoms with different geometrical and material properties was performed. The phantoms included braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. It was shown that these properties have a significant effect on calibration error, which is a variable based on US beamforming techniques. These results would have important implications for calibration procedures and their feasibility in the context of image-guided procedures. PMID:28331886

Effects of line fiducial parameters and beamforming on ultrasound calibration.

PubMed

Ameri, Golafsoun; Baxter, John S H; McLeod, A Jonathan; Peters, Terry M; Chen, Elvis C S

2017-01-01

Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the total accuracy of the interventional guidance system. Here, we investigate the effects of US image reconstruction techniques as well as phantom material and geometry on US calibration. It was shown that the FLE was reduced by 29% with synthetic transmit aperture imaging compared with conventional B-mode imaging in a Z-bar calibration, resulting in a 10% reduction of calibration error. In addition, an evaluation of a variety of calibration phantoms with different geometrical and material properties was performed. The phantoms included braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. It was shown that these properties have a significant effect on calibration error, which is a variable based on US beamforming techniques. These results would have important implications for calibration procedures and their feasibility in the context of image-guided procedures.

Real-time analysis keratometer

NASA Technical Reports Server (NTRS)

Adachi, Iwao P. (Inventor); Adachi, Yoshifumi (Inventor); Frazer, Robert E. (Inventor)

1987-01-01

A computer assisted keratometer in which a fiducial line pattern reticle illuminated by CW or pulsed laser light is projected on a corneal surface through lenses, a prismoidal beamsplitter quarterwave plate, and objective optics. The reticle surface is curved as a conjugate of an ideal corneal curvature. The fiducial image reflected from the cornea undergoes a polarization shift through the quarterwave plate and beamsplitter whereby the projected and reflected beams are separated and directed orthogonally. The reflected beam fiducial pattern forms a moire pattern with a replica of the first recticle. This moire pattern contains transverse aberration due to differences in curvature between the cornea and the ideal corneal curvature. The moire pattern is analyzed in real time by computer which displays either the CW moire pattern or a pulsed mode analysis of the transverse aberration of the cornea under observation, in real time. With the eye focused on a plurality of fixation points in succession, a survey of the entire corneal topography is made and a contour map or three dimensional plot of the cornea can be made as a computer readout in addition to corneal radius and refractive power analysis.

Phantom study and accuracy evaluation of an image-to-world registration approach used with electro-magnetic tracking system for neurosurgery

NASA Astrophysics Data System (ADS)

Li, Senhu; Sarment, David

2015-12-01

Minimally invasive neurosurgery needs intraoperative imaging updates and high efficient image guide system to facilitate the procedure. An automatic image guided system utilized with a compact and mobile intraoperative CT imager was introduced in this work. A tracking frame that can be easily attached onto the commercially available skull clamp was designed. With known geometry of fiducial and tracking sensor arranged on this rigid frame that was fabricated through high precision 3D printing, not only was an accurate, fully automatic registration method developed in a simple and less-costly approach, but also it helped in estimating the errors from fiducial localization in image space through image processing, and in patient space through the calibration of tracking frame. Our phantom study shows the fiducial registration error as 0.348+/-0.028mm, comparing the manual registration error as 1.976+/-0.778mm. The system in this study provided a robust and accurate image-to-patient registration without interruption of routine surgical workflow and any user interactions involved through the neurosurgery.

Linear feature detection algorithm for astronomical surveys - I. Algorithm description

NASA Astrophysics Data System (ADS)

Bektešević, Dino; Vinković, Dejan

2017-11-01

Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.

An efficient parallel termination detection algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, A. H.; Crivelli, S.; Jessup, E. R.

2004-05-27

Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Ofmore » these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.« less

WE-AB-303-08: Direct Lung Tumor Tracking Using Short Imaging Arcs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shieh, C; Huang, C; Keall, P

2015-06-15

Purpose: Most current tumor tracking technologies rely on implanted markers, which suffer from potential toxicity of marker placement and mis-targeting due to marker migration. Several markerless tracking methods have been proposed: these are either indirect methods or have difficulties tracking lung tumors in most clinical cases due to overlapping anatomies in 2D projection images. We propose a direct lung tumor tracking algorithm robust to overlapping anatomies using short imaging arcs. Methods: The proposed algorithm tracks the tumor based on kV projections acquired within the latest six-degree imaging arc. To account for respiratory motion, an external motion surrogate is used tomore » select projections of the same phase within the latest arc. For each arc, the pre-treatment 4D cone-beam CT (CBCT) with tumor contours are used to estimate and remove the contribution to the integral attenuation from surrounding anatomies. The position of the tumor model extracted from 4D CBCT of the same phase is then optimized to match the processed projections using the conjugate gradient method. The algorithm was retrospectively validated on two kV scans of a lung cancer patient with implanted fiducial markers. This patient was selected as the tumor is attached to the mediastinum, representing a challenging case for markerless tracking methods. The tracking results were converted to expected marker positions and compared with marker trajectories obtained via direct marker segmentation (ground truth). Results: The root-mean-squared-errors of tracking were 0.8 mm and 0.9 mm in the superior-inferior direction for the two scans. Tracking error was found to be below 2 and 3 mm for 90% and 98% of the time, respectively. Conclusions: A direct lung tumor tracking algorithm robust to overlapping anatomies was proposed and validated on two scans of a lung cancer patient. Sub-millimeter tracking accuracy was observed, indicating the potential of this algorithm for real-time guidance applications.« less

2D-3D rigid registration to compensate for prostate motion during 3D TRUS-guided biopsy.

PubMed

De Silva, Tharindu; Fenster, Aaron; Cool, Derek W; Gardi, Lori; Romagnoli, Cesare; Samarabandu, Jagath; Ward, Aaron D

2013-02-01

Three-dimensional (3D) transrectal ultrasound (TRUS)-guided systems have been developed to improve targeting accuracy during prostate biopsy. However, prostate motion during the procedure is a potential source of error that can cause target misalignments. The authors present an image-based registration technique to compensate for prostate motion by registering the live two-dimensional (2D) TRUS images acquired during the biopsy procedure to a preacquired 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. The authors implemented an intensity-based 2D-3D rigid registration algorithm optimizing the normalized cross-correlation (NCC) metric using Powell's method. The 2D TRUS images acquired during the procedure prior to biopsy gun firing were registered to the baseline 3D TRUS image acquired at the beginning of the procedure. The accuracy was measured by calculating the target registration error (TRE) using manually identified fiducials within the prostate; these fiducials were used for validation only and were not provided as inputs to the registration algorithm. They also evaluated the accuracy when the registrations were performed continuously throughout the biopsy by acquiring and registering live 2D TRUS images every second. This measured the improvement in accuracy resulting from performing the registration, continuously compensating for motion during the procedure. To further validate the method using a more challenging data set, registrations were performed using 3D TRUS images acquired by intentionally exerting different levels of ultrasound probe pressures in order to measure the performance of our algorithm when the prostate tissue was intentionally deformed. In this data set, biopsy scenarios were simulated by extracting 2D frames from the 3D TRUS images and registering them to the baseline 3D image. A graphics processing unit (GPU)-based implementation was used to improve the registration speed. They also studied the correlation between NCC and TREs. The root-mean-square (RMS) TRE of registrations performed prior to biopsy gun firing was found to be 1.87 ± 0.81 mm. This was an improvement over 4.75 ± 2.62 mm before registration. When the registrations were performed every second during the biopsy, the RMS TRE was reduced to 1.63 ± 0.51 mm. For 3D data sets acquired under different probe pressures, the RMS TRE was found to be 3.18 ± 1.6 mm. This was an improvement from 6.89 ± 4.1 mm before registration. With the GPU based implementation, the registrations were performed with a mean time of 1.1 s. The TRE showed a weak correlation with the similarity metric. However, the authors measured a generally convex shape of the metric around the ground truth, which may explain the rapid convergence of their algorithm to accurate results. Registration to compensate for prostate motion during 3D TRUS-guided biopsy can be performed with a measured accuracy of less than 2 mm and a speed of 1.1 s, which is an important step toward improving the targeting accuracy of a 3D TRUS-guided biopsy system.

Radar Detection of Marine Mammals

DTIC Science & Technology

2011-09-30

BFT-BPT algorithm for use with our radar data. This track - before - detect algorithm had been effective in enhancing small but persistent signatures in...will be possible with the detect before track algorithm. 4 We next evaluated the track before detect algorithm, the BFT-BPT, on the CEDAR data

Performances of the New Real Time Tsunami Detection Algorithm applied to tide gauges data

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Morucci, S.

2017-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection (TDA) based on the real-time tide removal and real-time band-pass filtering of seabed pressure time series acquired by Bottom Pressure Recorders. The TDA algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability with respect to the most widely used tsunami detection algorithm, while containing the computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. In this work we present the performance of the TDA algorithm applied to tide gauge data. We have adapted the new tsunami detection algorithm and the Monte Carlo test methodology to tide gauges. Sea level data acquired by coastal tide gauges in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event generated by Tohoku earthquake on March 11th 2011, using data recorded by several tide gauges scattered all over the Pacific area.

The Large Underground Xenon (LUX) experiment

DOE PAGES

Akerib, D. S.; Bai, X.; Bedikian, S.; ...

2012-11-29

The Large Underground Xenon (LUX) collaboration has designed and constructed a dual-phase xenon detector, in order to conduct a search for Weakly Interacting Massive Particles (WIMPs), a leading dark matter candidate. The goal of the LUX detector is to clearly detect (or exclude) WIMPS with a spin independent cross section per nucleon of 2×10 -46 cm 2, equivalent to ~1 event/100 kg/month in the inner 100-kg fiducial volume (FV) of the 370-kg detector. The overall background goals are set to have <1 background events characterized as possible WIMPs in the FV in 300 days of running. This work describes themore » design and construction of the LUX detector.« less

A Novel Zero Velocity Interval Detection Algorithm for Self-Contained Pedestrian Navigation System with Inertial Sensors

PubMed Central

Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan

2016-01-01

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elmagarmid, A.K.

The availability of distributed data bases is directly affected by the timely detection and resolution of deadlocks. Consequently, mechanisms are needed to make deadlock detection algorithms resilient to failures. Presented first is a centralized algorithm that allows transactions to have multiple requests outstanding. Next, a new distributed deadlock detection algorithm (DDDA) is presented, using a global detector (GD) to detect global deadlocks and local detectors (LDs) to detect local deadlocks. This algorithm essentially identifies transaction-resource interactions that m cause global (multisite) deadlocks. Third, a deadlock detection algorithm utilizing a transaction-wait-for (TWF) graph is presented. It is a fully disjoint algorithmmore » that allows multiple outstanding requests. The proposed algorithm can achieve improved overall performance by using multiple disjoint controllers coupled with the two-phase property while maintaining the simplicity of centralized schemes. Fourth, an algorithm that combines deadlock detection and avoidance is given. This algorithm uses concurrent transaction controllers and resource coordinators to achieve maximum distribution. The language of CSP is used to describe this algorithm. Finally, two efficient deadlock resolution protocols are given along with some guidelines to be used in choosing a transaction for abortion.« less

Navigation system for flexible endoscopes

NASA Astrophysics Data System (ADS)

Hummel, Johann; Figl, Michael; Birkfellner, Wolfgang; Häfner, Michael; Kollmann, Christian; Bergmann, Helmar

2003-05-01

Endoscopic Ultrasound (EUS) features flexible endoscopes equipped with a radial or linear array scanhead allowing high resolution examination of organs adjacent to the upper gastrointestinal tract. An optical system based on fibre-glass or a CCD-chip allows additional orientation. However, 3-dimensional orientation and correct identification of the various anatomical structures may be difficult. It therefore seems desirable to merge real-time US images with high resolution CT or MR images acquired prior to EUS to simplify navigation during the intervention. The additional information provided by CT or MR images might facilitate diagnosis of tumors and, ultimately, guided puncture of suspicious lesions. We built a grid with 15 plastic spheres and measured their positions relatively to five fiducial markers placed on the top of the grid. For this measurement we used an optical tracking system (OTS) (Polaris, NDI, Can). Two sensors of an electromagnetic tracking system (EMTS) (Aurora, NDI, Can) were mounted on a flexible endoscope (Pentax GG 38 UX, USA) to enable a free hand ultrasound calibration. To determine the position of the plastic spheres in the emitter coordinate system of the EMTS we applied a point-to-point registration (Horn) using the coordinates of the fiducial markers in both coordinate systems (OTS and EMTS). For the transformation between EMTS to the CT space the Horn algorithm was adopted again using the fiducial markers. Visualization was enabled by the use of the AVW-4.0 library (Biomedical Imaging Resource, Mayo Clinic, Rochester/MN, USA). To evaluate the suitability of our new navigation system we measured the Fiducial Registration Error (FRE) of the diverse registrations and the Target Registration Error (TRE) for the complete transformation from the US space to the CT space. The FRE for the ultrasound calibration amounted to 4.3 mm +/- 4.2 mm, resulting from 10 calibration procedures. For the transformation from the OTS reference system to the EMTS emitter space we found an average FRE of 0.8 mm +/- 0.2 mm. The FRE for the CT registration was 1.0 mm +/- 0.3 mm. The TRE was found to be 3.8 mm +/- 1.3 mm if we target the same spheres which where used for the calibration procedure. A movement of the phantom results in higher TREs because of the orientation sensitivity of the sensor. In that case the TRE in the area where the biopsy is supposed to be taken place was found to be 7.9 mm +/- 3.2 mm. Our system provides the interventionist with additional information about position and orientation of the used flexible instrument. Additionally, it improves the marksmanship of biopsies. The use of the miniaturized EMTS enables for the first time the navigation of flexible instruments in this way. For the successful application of navigation systems in interventional radiology, an accuracy in the range of 5 mm is desirable. The accuracy of the localization of a point in CT space are just 3 mm too high as required. One of the possibilities to overcome this difference is to mount the two sensors in such a way that the interference of their electromagnetic fields is minimized. A considerable restraint constitutes the small characteristic volume (360mm x 600mm x 600mm), which requires for most application an additional optical system.

Image fusion pitfalls for cranial radiosurgery.

PubMed

Jonker, Benjamin P

2013-01-01

Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls.

Photogrammetry-Based Head Digitization for Rapid and Accurate Localization of EEG Electrodes and MEG Fiducial Markers Using a Single Digital SLR Camera.

PubMed

Clausner, Tommy; Dalal, Sarang S; Crespo-García, Maité

2017-01-01

The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D . Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position.

Photogrammetric Accuracy and Modeling of Rolling Shutter Cameras

NASA Astrophysics Data System (ADS)

Ye, W.; Qiao, G.; Kong, F.; Guo, S.; Ma, X.; Tong, X.; Li, R.

2016-06-01

Global climate change is one of the major challenges that all nations are commonly facing. Long-term observations of the Antarctic ice sheet have been playing a critical role in quantitatively estimating and predicting effects resulting from the global changes. The film-based ARGON reconnaissance imagery provides a remarkable data source for studying the Antarctic ice-sheet in 1960s, thus greatly extending the time period of Antarctica surface observations. To deal with the low-quality images and the unavailability of camera poses, a systematic photogrammetric approach is proposed to reconstruct the interior and exterior orientation information for further glacial mapping applications, including ice flow velocity mapping and mass balance estimation. Some noteworthy details while performing geometric modelling using the ARGON images were introduced, including methods and results for handling specific effects of film deformation, damaged or missing fiducial marks and calibration report, automatic fiducial mark detection, control point selection through Antarctic shadow and ice surface terrain analysis, and others. Several sites in East Antarctica were tested. As an example, four images in the Byrd glacier region were used to assess the accuracy of the geometric modelling. A digital elevation model (DEM) and an orthophoto map of Byrd glacier were generated. The accuracy of the ground positions estimated by using independent check points is within one nominal pixel of 140 m of ARGON imagery. Furthermore, a number of significant features, such as ice flow velocity and regional change patterns, will be extracted and analysed.

Photogrammetry-Based Head Digitization for Rapid and Accurate Localization of EEG Electrodes and MEG Fiducial Markers Using a Single Digital SLR Camera

PubMed Central

Clausner, Tommy; Dalal, Sarang S.; Crespo-García, Maité

2017-01-01

The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D. Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position. PMID:28559791

Accurate and consistent automatic seismocardiogram annotation without concurrent ECG.

PubMed

Laurin, A; Khosrow-Khavar, F; Blaber, A P; Tavakolian, Kouhyar

2016-09-01

Seismocardiography (SCG) is the measurement of vibrations in the sternum caused by the beating of the heart. Precise cardiac mechanical timings that are easily obtained from SCG are critically dependent on accurate identification of fiducial points. So far, SCG annotation has relied on concurrent ECG measurements. An algorithm capable of annotating SCG without the use any other concurrent measurement was designed. We subjected 18 participants to graded lower body negative pressure. We collected ECG and SCG, obtained R peaks from the former, and annotated the latter by hand, using these identified peaks. We also annotated the SCG automatically. We compared the isovolumic moment timings obtained by hand to those obtained using our algorithm. Mean  ±  confidence interval of the percentage of accurately annotated cardiac cycles were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for levels of negative pressure 0, -20, -30, -40, and  -50 mmHg. LF/HF ratios, the relative power of low-frequency variations to high-frequency variations in heart beat intervals, obtained from isovolumic moments were also compared to those obtained from R peaks. The mean differences  ±  confidence interval were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for increasing levels of negative pressure. The accuracy and consistency of the algorithm enables the use of SCG as a stand-alone heart monitoring tool in healthy individuals at rest, and could serve as a basis for an eventual application in pathological cases.

Intra- and inter-radiation therapist reproducibility of daily isocenter verification using prostatic fiducial markers

PubMed Central

Ullman, Karen L; Ning, Holly; Susil, Robert C; Ayele, Asna; Jocelyn, Lucresse; Havelos, Jan; Guion, Peter; Xie, Huchen; Li, Guang; Arora, Barbara C; Cannon, Angela; Miller, Robert W; Norman Coleman, C; Camphausen, Kevin; Ménard, Cynthia

2006-01-01

Background We sought to determine the intra- and inter-radiation therapist reproducibility of a previously established matching technique for daily verification and correction of isocenter position relative to intraprostatic fiducial markers (FM). Materials and methods With the patient in the treatment position, anterior-posterior and left lateral electronic images are acquired on an amorphous silicon flat panel electronic portal imaging device. After each portal image is acquired, the therapist manually translates and aligns the fiducial markers in the image to the marker contours on the digitally reconstructed radiograph. The distances between the planned and actual isocenter location is displayed. In order to determine the reproducibility of this technique, four therapists repeated and recorded this operation two separate times on 20 previously acquired portal image datasets from two patients. The data were analyzed to obtain the mean variability in the distances measured between and within observers. Results The mean and median intra-observer variability ranged from 0.4 to 0.7 mm and 0.3 to 0.6 mm respectively with a standard deviation of 0.4 to 1.0 mm. Inter-observer results were similar with a mean variability of 0.9 mm, a median of 0.6 mm, and a standard deviation of 0.7 mm. When using a 5 mm threshold, only 0.5% of treatments will undergo a table shift due to intra or inter-observer error, increasing to an error rate of 2.4% if this threshold were reduced to 3 mm. Conclusion We have found high reproducibility with a previously established method for daily verification and correction of isocenter position relative to prostatic fiducial markers using electronic portal imaging. PMID:16722575

Residual susceptibility of the red imported fire ant (Hymenoptera: Formicidae) to four agricultural insecticides.

PubMed

Seagraves, Michael P; McPherson, Robert M

2003-06-01

The red imported fire ant, Solenopsis invicta Buren, is an abundant predator in cropping systems throughout its range. It has been documented to be an important predator of numerous crop pests, as well as being an agricultural pest itself. Information on the impact of insecticides on natural enemies such as fire ants is necessary for the integration of biological and chemical control tactics in an effective pest management program. Therefore, a residual vial bioassay was developed to determine the concentration-mortality responses of S. invicta workers to four commonly used insecticides: acephate, chlorpyrifos, methomyl and lambda-cyhalothrin. Fire ant workers showed a mortality response to serial dilutions to all four chemicals. Methomyl (LC50 0.04 microg/vial, fiducial limits 0.03-0.06) was the most toxic, followed by chlorpyrifos (LC50 0.11 microg/vial, fiducial limits 0.07-0.17) and acephate (LC50 0.76 microg/vial, fiducial limits 0.50-1.04). Of the chemicals assayed, it took a much higher concentration of lambda-cyhalothrin (LC50 2.30 microg/vial, fiducial limits 1.57-3.59) to kill 50% of the workers compared with the other three chemicals. The results of this study demonstrate the wide range in responses of fire ants to four insecticides that are labeled and commonly used on numerous agricultural crops throughout the United States. These results further suggest the possibility of using a discriminating dose of lambda-cyhalothrin to control the target pest species while conserving fire ants in the agricultural systems in which their predatory behavior is beneficial to the integrated pest management program.

Magnitude of Interfractional Vaginal Cuff Movement: Implications for External Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Daniel J.; Michaletz-Lorenz, Martha; Goddu, S. Murty

2012-03-15

Purpose: To quantify the extent of interfractional vaginal cuff movement in patients receiving postoperative irradiation for cervical or endometrial cancer in the absence of bowel/bladder instruction. Methods and Materials: Eleven consecutive patients with cervical or endometrial cancer underwent placement of three gold seed fiducial markers in the vaginal cuff apex as part of standard of care before simulation. Patients subsequently underwent external irradiation and brachytherapy treatment based on institutional guidelines. Daily megavoltage CT imaging was performed during each external radiation treatment fraction. The daily positions of the vaginal apex fiducial markers were subsequently compared with the original position of themore » fiducial markers on the simulation CT. Composite dose-volume histograms were also created by summing daily target positions. Results: The average ({+-} standard deviation) vaginal cuff movement throughout daily pelvic external radiotherapy when referenced to the simulation position was 16.2 {+-} 8.3 mm. The maximum vaginal cuff movement for any patient during treatment was 34.5 mm. In the axial plane the mean vaginal cuff movement was 12.9 {+-} 6.7 mm. The maximum vaginal cuff axial movement was 30.7 mm. In the craniocaudal axis the mean movement was 10.3 {+-} 7.6 mm, with a maximum movement of 27.0 mm. Probability of cuff excursion outside of the clinical target volume steadily dropped as margin size increased (53%, 26%, 4.2%, and 1.4% for 1.0, 1.5, 2.0, and 2.5 cm, respectively.) However, rectal and bladder doses steadily increased with larger margin sizes. Conclusions: The magnitude of vaginal cuff movement is highly patient specific and can impact target coverage in patients without bowel/bladder instructions at simulation. The use of vaginal cuff fiducials can help identify patients at risk for target volume excursion.« less

Clinical determination of target registration error of an image-guided otologic surgical system using patients with bone-anchored hearing aids

NASA Astrophysics Data System (ADS)

Balachandran, Ramya; Labadie, Robert F.; Fitzpatrick, J. Michael

2007-03-01

Image guidance in otologic surgery has been thwarted by the need for a non-invasive fiducial system with target registration error (TRE) at the inner ear below 1.5mm. We previously presented a fiducial frame for this purpose that attaches to the upper dentition via patient-specific bite blocks and demonstrated a TRE of 0.73mm (+/-0.23mm) on cadaveric skulls. In that study, TRE measurement depended upon placement of bone-implanted, intracranial target fiducials-clearly impossible to repeat clinically. Using cadaveric specimens, we recently presented a validation method based on an auditory implant system (BAHA System® Cochlear Corp., Denver, CO). That system requires a skull-implanted titanium screw behind the ear upon which a bone-anchored hearing aid (BAHA) is mounted. In our validation, we replace the BAHA with a fiducial marker to permit measurement of TRE. That TRE is then used to estimate TRE at an internal point. While the method can be used to determine accuracy at any point within the head, we focus in this study on the inner ear, in particular the cochlea, and we apply the method to patients (N=5). Physical localizations were performed after varying elapsed times since bite-block fabrication, and TRE at the cochlea was estimated. We found TRE to be 0.97mm at the cochlea within one month and 2.5mm after seven months. Thus, while accuracy deteriorates considerably with delays of seven months or more, if this frame is used within one month of the fabrication of the bite-block, it achieves the goal and in fact exhibits submillimetric accuracy.

Evaluation of lung tumor motion management in radiation therapy with dynamic MRI

NASA Astrophysics Data System (ADS)

Park, Seyoun; Farah, Rana; Shea, Steven M.; Tryggestad, Erik; Hales, Russell; Lee, Junghoon

2017-03-01

Surrogate-based tumor motion estimation and tracing methods are commonly used in radiotherapy despite the lack of continuous real time 3D tumor and surrogate data. In this study, we propose a method to simultaneously track the tumor and external surrogates with dynamic MRI, which allows us to evaluate their reproducible correlation. Four MRIcompatible fiducials are placed on the patient's chest and upper abdomen, and multi-slice 2D cine MRIs are acquired to capture the lung and whole tumor, followed by two-slice 2D cine MRIs to simultaneously track the tumor and fiducials, all in sagittal orientation. A phase-binned 4D-MRI is first reconstructed from multi-slice MR images using body area as a respiratory surrogate and group-wise registration. The 4D-MRI provides 3D template volumes for different breathing phases. 3D tumor position is calculated by 3D-2D template matching in which 3D tumor templates in 4D-MRI reconstruction and the 2D cine MRIs from the two-slice tracking dataset are registered. 3D trajectories of the external surrogates are derived via matching a 3D geometrical model to the fiducial segmentations on the 2D cine MRIs. We tested our method on five lung cancer patients. Internal target volume from 4D-CT showed average sensitivity of 86.5% compared to the actual tumor motion for 5 min. 3D tumor motion correlated with the external surrogate signal, but showed a noticeable phase mismatch. The 3D tumor trajectory showed significant cycle-to-cycle variation, while the external surrogate was not sensitive enough to capture such variations. Additionally, there was significant phase mismatch between surrogate signals obtained from fiducials at different locations.

Theoretical accuracy in cosmological growth estimation

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Koyama, Kazuya; Hellwing, Wojciech A.; Zhao, Gong-Bo; Winther, Hans A.

2017-07-01

We elucidate the importance of the consistent treatment of gravity-model specific nonlinearities when estimating the growth of cosmological structures from redshift space distortions (RSD). Within the context of standard perturbation theory (SPT), we compare the predictions of two theoretical templates with redshift space data from COLA (comoving Lagrangian acceleration) simulations in the normal branch of DGP gravity (nDGP) and general relativity (GR). Using COLA for these comparisons is validated using a suite of full N-body simulations for the same theories. The two theoretical templates correspond to the standard general relativistic perturbation equations and those same equations modeled within nDGP. Gravitational clustering nonlinear effects are accounted for by modeling the power spectrum up to one-loop order and redshift space clustering anisotropy is modeled using the Taruya, Nishimichi and Saito (TNS) RSD model. Using this approach, we attempt to recover the simulation's fiducial logarithmic growth parameter f . By assigning the simulation data with errors representing an idealized survey with a volume of 10 Gpc3/h3 , we find the GR template is unable to recover fiducial f to within 1 σ at z =1 when we match the data up to kmax=0.195 h /Mpc . On the other hand, the DGP template recovers the fiducial value within 1 σ . Further, we conduct the same analysis for sets of mock data generated for generalized models of modified gravity using SPT, where again we analyze the GR template's ability to recover the fiducial value. We find that for models with enhanced gravitational nonlinearity, the theoretical bias of the GR template becomes significant for stage IV surveys. Thus, we show that for the future large data volume galaxy surveys, the self-consistent modeling of non-GR gravity scenarios will be crucial in constraining theory parameters.

Preoperative Fiducial Marker Placement in the Thoracic Spine: A Technical Report.

PubMed

Madaelil, Thomas P; Long, Jeremiah R; Wallace, Adam N; Baker, Jonathan C; Ray, Wilson Z; Santiago, Paul; Buchowski, Jacob; Zebala, Lukas P; Jennings, Jack W

2017-05-15

A retrospective review. The aim of this study was to demonstrate proof-of-concept of preoperative percutaneous intraosseous fiducial marker placement before thoracic spine surgery. Wrong-level spine surgery is defined as a never event by Center for Medicare Services, yet the strength of data supporting the implementation of Universal Protocol to limit wrong level surgery is weak. The thoracic spine is especially prone to intraoperative mislocalization, particularly in cases of morbid obesity and anatomic variations. We retrospectively reviewed all cases of preoperative percutaneous image-guided intraosseous placement of a metallic marker in the thoracic spine. Indications for surgery included degenerative disc disease (16/19), osteochondroma resection, spinal metastasis, and ligation of dural arteriovenous malformation. All metallic markers were placed from a percutaneous transpedicular approach under imaging guidance [fluoroscopy and computed tomography (CT) or CT alone]. Patient body mass index (BMI) was recorded. Overweight and obese BMI was defined greater than 25 and 30 kg/m, respectively. All 19 patients underwent fiducial marker placement and intraoperative localization successfully without complication. Twenty-two thoracic spine levels were localized. The T7, T9, T10, and T11 levels were the most often localized at rate of 18.1% for each level (4/22). The most cranial and caudal levels localized were T4 and T11. About 84.2% (16/19) of the cohort was overweight (57.9%; 11/19) or obese (26.3%; 5/19). The median BMI was 30.2 kg/m (range, 23.9-54.3 kg/m). Preoperative percutaneous thoracic fiducial marker placement under imaging guidance is a safe method for facilitating intraoperative localization of the target spinal level, especially in obese patients. Further studies are needed to quantify changes in operative time and radiation exposure. 4.

Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis.

PubMed

Yang, Chao; He, Zengyou; Yu, Weichuan

2009-01-06

In mass spectrometry (MS) based proteomic data analysis, peak detection is an essential step for subsequent analysis. Recently, there has been significant progress in the development of various peak detection algorithms. However, neither a comprehensive survey nor an experimental comparison of these algorithms is yet available. The main objective of this paper is to provide such a survey and to compare the performance of single spectrum based peak detection methods. In general, we can decompose a peak detection procedure into three consequent parts: smoothing, baseline correction and peak finding. We first categorize existing peak detection algorithms according to the techniques used in different phases. Such a categorization reveals the differences and similarities among existing peak detection algorithms. Then, we choose five typical peak detection algorithms to conduct a comprehensive experimental study using both simulation data and real MALDI MS data. The results of comparison show that the continuous wavelet-based algorithm provides the best average performance.

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

NASA Astrophysics Data System (ADS)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

Adaboost multi-view face detection based on YCgCr skin color model

NASA Astrophysics Data System (ADS)

Lan, Qi; Xu, Zhiyong

2016-09-01

Traditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors.

A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

NASA Astrophysics Data System (ADS)

Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan

2018-03-01

False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

Operation Greenhouse. Scientific Director's report of atomic-weapon tests at Eniwetok, 1951. Annex 1. 11. Timing and firing and fiducial markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grier, H.E.

1985-09-01

An automatic remote-control system armed and fired the bomb and sent out a sequence of time signals to experimental equipment on the atoll. A central station at Parry Island sent signals via submarine cables to a timer station on a shot island. The timer station controlled signals to the zero station and to experiments on the island, and through auxiliary stations, it also controlled signal distribution on adjacent islands. Light-sensitive triggering units for apparatus and for accurate standard zero-time reference were provided in the form of Blue Boxes, or fiducial markers.

The Poincaré Half-Plane for Informationally-Complete POVMs

NASA Astrophysics Data System (ADS)

Planat, Michel

2017-12-01

It has been shown that classes of (minimal asymmetric) informationally complete POVMs in dimension d can be built using the multiparticle Pauli group acting on appropriate fiducial states [M. Planat and Z. Gedik, R. Soc. open sci. 4, 170387 (2017)]. The latter states may also be derived starting from the Poincar\\'e upper half-plane model H. For doing this, one translates the congruence (or non-congruence) subgroups of index d of the modular group into groups of permutation gates whose some of the eigenstates are the seeked fiducials. The structure of some IC-POVMs is found to be intimately related to the Kochen-Specker theorem.

Measurement of the cross-section for electroweak production of dijets in association with a Z boson in pp collisions at s = 13   TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-10-27

The cross-section for the production of two jets in association with a leptonically decaying Z boson (Zjj ) is measured in proton–proton collisions at a centre-of-mass energy of 13 TeV, using data recorded with the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of 3.2 fb -1. The electroweak Zjj cross-section is extracted in a fiducial region chosen to enhance the electroweak contribution relative to the dominant Drell–Yan Zjj process, which is constrained using a data-driven approach. The measured fiducial electroweak cross-section is σmore » $$Zjj\\atop{EW}$$ 119 ± 16 (stat.) ± 20 (syst.) ± 2 (lumi.) fb for dijet invariant mass greater than 250 GeV, and 34.2 ± 5.8 (stat.) ± 5.5 (syst.) ± 0.7 (lumi.) fb for dijet invariant mass greater than 1 TeV. Standard Model predictions are in agreement with the measurements. Lastly, the inclusive Zjj cross-section is also measured in six different fiducial regions with varying contributions from electroweak and Drell–Yan Zjj production.« less

Synthetic aperture imaging in ultrasound calibration

NASA Astrophysics Data System (ADS)

Ameri, Golafsoun; Baxter, John S. H.; McLeod, A. Jonathan; Jayaranthe, Uditha L.; Chen, Elvis C. S.; Peters, Terry M.

2014-03-01

Ultrasound calibration allows for ultrasound images to be incorporated into a variety of interventional applica­ tions. Traditional Z- bar calibration procedures rely on wired phantoms with an a priori known geometry. The line fiducials produce small, localized echoes which are then segmented from an array of ultrasound images from different tracked probe positions. In conventional B-mode ultrasound, the wires at greater depths appear blurred and are difficult to segment accurately, limiting the accuracy of ultrasound calibration. This paper presents a novel ultrasound calibration procedure that takes advantage of synthetic aperture imaging to reconstruct high resolution ultrasound images at arbitrary depths. In these images, line fiducials are much more readily and accu­ rately segmented, leading to decreased calibration error. The proposed calibration technique is compared to one based on B-mode ultrasound. The fiducial localization error was improved from 0.21mm in conventional B-mode images to 0.15mm in synthetic aperture images corresponding to an improvement of 29%. This resulted in an overall reduction of calibration error from a target registration error of 2.00mm to 1.78mm, an improvement of 11%. Synthetic aperture images display greatly improved segmentation capabilities due to their improved resolution and interpretability resulting in improved calibration.

Measurement of the cross-section for electroweak production of dijets in association with a Z boson in pp collisions at √{ s } = 13 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Eramo, L.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vasconcelos Corga, K.; de Vivie de Regie, J. B.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Bello, F. A.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Petrillo, K. F.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de La Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutelman, B. J.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kellermann, E.; Kempster, J. J.; Kendrick, J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-Zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kitali, V.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klingl, T.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Komar, A. A.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kourlitis, E.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kremer, J. A.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kupfer, T.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; La Ruffa, F.; Lacasta, C.; Lacava, F.; Lacey, J.; Lack, D. P. J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Langenberg, R. J.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Lau, T. S.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; Leblanc, M.; Lecompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, G. R.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Li, B.; Li, Changqiao; Li, H.; Li, L.; Li, Q.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Linck, R. A.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J. K. K.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo, C. Y.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loesle, A.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Mateos, D.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lutz, M. S.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyu, F.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; MacDonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A. S.; Magerl, V.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majersky, O.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mankinen, K. H.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchese, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin Dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; McFayden, J. A.; McHedlidze, G.; McMahon, S. J.; McNamara, P. C.; McNicol, C. J.; McPherson, R. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Mellenthin, J. D.; Melo, M.; Meloni, F.; Melzer, A.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Merlassino, C.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Millar, D. A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishu, N.; Nisius, R.; Nitsche, I.; Nitta, T.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oppen, H.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Panagoulias, I.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasner, J. M.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearson, B.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rangel-Smith, C.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, Dms; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-12-01

The cross-section for the production of two jets in association with a leptonically decaying Z boson (Zjj) is measured in proton-proton collisions at a centre-of-mass energy of 13 TeV, using data recorded with the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of 3.2 fb-1. The electroweak Zjj cross-section is extracted in a fiducial region chosen to enhance the electroweak contribution relative to the dominant Drell-Yan Zjj process, which is constrained using a data-driven approach. The measured fiducial electroweak cross-section is σEWZjj = 119 ± 16 (stat .) ± 20 (syst .) ± 2 (lumi .) fb for dijet invariant mass greater than 250 GeV, and 34.2 ± 5.8 (stat .) ± 5.5 (syst .) ± 0.7 (lumi .) fb for dijet invariant mass greater than 1 TeV. Standard Model predictions are in agreement with the measurements. The inclusive Zjj cross-section is also measured in six different fiducial regions with varying contributions from electroweak and Drell-Yan Zjj production.

A method of indirect registration of the coordinates of condylar points with a six-degree-of-freedom jaw tracker.

PubMed

Huang, B Y; Durrant, C J; Johnson, C W L; Murray, G M

2002-06-30

Previous studies have indicated that the location of a condylar point can significantly influence its trajectory. The aim of this investigation was to develop a method of registering the location of radiographically defined condylar points in the coordinate system of a six-degree-of-freedom jaw-tracking device and to determine the accuracy of this method by using a perspex model in one experiment and a dry skull in another. A direct measurement ('the gold standard') of condylar point coordinates in the coordinate system of JAWS3D was done using a three-dimensional (3D) digitizer (MicroScribe-3DX). The indirect measurement used a distributed fiducial marker as the interface between the coordinate system of MicroScribe-3DX (which was used to register the fiducial marker and the JAWS3D coordinate system) and the coordinate system of the CT scans (used to define condyle anatomy and the relation with the fiducial marker). The coordinates of condylar points could then be calculated in the coordinate system of JAWS3D. The results showed that the indirect method could register condylar point coordinates on either side to an accuracy of approximately 0.5 mm.

Fiducial marker for correlating images

DOEpatents

Miller, Lisa Marie [Rocky Point, NY; Smith, Randy J [Wading River, NY; Warren, John B [Port Jefferson, NY; Elliott, Donald [Hampton Bays, NY

2011-06-21

The invention relates to a fiducial marker having a marking grid that is used to correlate and view images produced by different imaging modalities or different imaging and viewing modalities. More specifically, the invention relates to the fiducial marking grid that has a grid pattern for producing either a viewing image and/or a first analytical image that can be overlaid with at least one other second analytical image in order to view a light path or to image different imaging modalities. Depending on the analysis, the grid pattern has a single layer of a certain thickness or at least two layers of certain thicknesses. In either case, the grid pattern is imageable by each imaging or viewing modality used in the analysis. Further, when viewing a light path, the light path of the analytical modality cannot be visualized by viewing modality (e.g., a light microscope objective). By correlating these images, the ability to analyze a thin sample that is, for example, biological in nature but yet contains trace metal ions is enhanced. Specifically, it is desired to analyze both the organic matter of the biological sample and the trace metal ions contained within the biological sample without adding or using extrinsic labels or stains.

Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

PubMed

Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

2017-07-01

Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

A QRS Detection and R Point Recognition Method for Wearable Single-Lead ECG Devices.

PubMed

Chen, Chieh-Li; Chuang, Chun-Te

2017-08-26

In the new-generation wearable Electrocardiogram (ECG) system, signal processing with low power consumption is required to transmit data when detecting dangerous rhythms and to record signals when detecting abnormal rhythms. The QRS complex is a combination of three of the graphic deflection seen on a typical ECG. This study proposes a real-time QRS detection and R point recognition method with low computational complexity while maintaining a high accuracy. The enhancement of QRS segments and restraining of P and T waves are carried out by the proposed ECG signal transformation, which also leads to the elimination of baseline wandering. In this study, the QRS fiducial point is determined based on the detected crests and troughs of the transformed signal. Subsequently, the R point can be recognized based on four QRS waveform templates and preliminary heart rhythm classification can be also achieved at the same time. The performance of the proposed approach is demonstrated using the benchmark of the MIT-BIH Arrhythmia Database, where the QRS detected sensitivity (Se) and positive prediction (+P) are 99.82% and 99.81%, respectively. The result reveals the approach's advantage of low computational complexity, as well as the feasibility of the real-time application on a mobile phone and an embedded system.

SU-E-T-754: Three-Dimensional Patient Modeling Using Photogrammetry for Collision Avoidance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Popple, R; Cardan, R

2015-06-15

Purpose: To evaluate photogrammetry for creating a three-dimensional patient model. Methods: A mannequin was configured on the couch of a CT scanner to simulate a patient setup using an indexed positioning device. A CT fiducial was placed on the indexed CT table-overlay at the reference index position. Two dimensional photogrammetry targets were placed on the table in known positions. A digital SLR camera was used to obtain 27 images from different positions around the CT table. The images were imported into a commercial photogrammetry package and a 3D model constructed. Each photogrammetry target was identified on 2 to 5 images.more » The CT DICOM metadata and the position of the CT fiducial were used to calculate the coordinates of the photogrammetry targets in the CT image frame of reference. The coordinates were transferred to the photogrammetry software to orient the 3D model. The mannequin setup was transferred to the treatment couch of a linear accelerator and positioned at isocenter using in-room lasers. The treatment couch coordinates were noted and compared with prediction. The collision free regions were measured over the full range of gantry and table motion and were compared with predictions obtained using a general purpose polygon interference algorithm. Results: The reconstructed 3D model consisted of 180000 triangles. The difference between the predicted and measured couch positions were 5 mm, 1 mm, and 1 mm for longitudinal, lateral, and vertical, respectively. The collision prediction tested 64620 gantry table combinations in 11.1 seconds. The accuracy was 96.5%, with false positive and negative results occurring at the boundaries of the collision space. Conclusion: Photogrammetry can be used as a tool for collision avoidance during treatment planning. The results indicate that a buffer zone is necessary to avoid false negatives at the boundary of the collision-free zone. Testing with human patients is underway. Research partially supported by a grant from Varian Medical Systems.« less

Development and application of pulmonary structure-function registration methods: towards pulmonary image-guidance tools for improved airway targeted therapies and outcomes

NASA Astrophysics Data System (ADS)

Guo, Fumin; Pike, Damien; Svenningsen, Sarah; Coxson, Harvey O.; Drozd, John J.; Yuan, Jing; Fenster, Aaron; Parraga, Grace

2014-03-01

Objectives: We aimed to develop a way to rapidly generate multi-modality (MRI-CT) pulmonary imaging structurefunction maps using novel non-rigid image registration methods. This objective is part of our overarching goal to provide an image processing pipeline to generate pulmonary structure-function maps and guide airway-targeted therapies. Methods: Anatomical 1H and functional 3He MRI were acquired in 5 healthy asymptomatic ex-smokers and 7 ex-smokers with chronic obstructive pulmonary disease (COPD) at inspiration breath-hold. Thoracic CT was performed within ten minutes of MRI using the same breath-hold volume. Landmark-based affine registration methods previously validated for imaging of COPD, was based on corresponding fiducial markers located in both CT and 1H MRI coronal slices and compared with shape-based CT-MRI non-rigid registration. Shape-based CT-MRI registration was developed by first identifying the shapes of the lung cavities manually, and then registering the two shapes using affine and thin-plate spline algorithms. We compared registration accuracy using the fiducial localization error (FLE) and target registration error (TRE). Results: For landmark-based registration, the TRE was 8.4±5.3 mm for whole lung and 7.8±4.6 mm for the R and L lungs registered independently (p=0.4). For shape-based registration, the TRE was 8.0±4.6 mm for whole lung as compared to 6.9±4.4 mm for the R and L lung registered independently and this difference was significant (p=0.01). The difference for shape-based (6.9±4.4 mm) and landmark-based R and L lung registration (7.8±4.6 mm) was also significant (p=.04) Conclusion: Shape-based registration TRE was significantly improved compared to landmark-based registration when considering L and R lungs independently.

Low-complexity R-peak detection in ECG signals: a preliminary step towards ambulatory fetal monitoring.

PubMed

Rooijakkers, Michiel; Rabotti, Chiara; Bennebroek, Martijn; van Meerbergen, Jef; Mischi, Massimo

2011-01-01

Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, while increasing the R-peak detection quality compared to existing R-peak detection schemes. Validation of the algorithm is performed on two manually annotated datasets, the MIT/BIH Arrhythmia database and an in-house abdominal database. Both R-peak detection quality and computational complexity are compared to state-of-the-art algorithms as described in the literature. With a detection error rate of 0.22% and 0.12% on the MIT/BIH Arrhythmia and in-house databases, respectively, the quality of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

NASA airborne radar wind shear detection algorithm and the detection of wet microbursts in the vicinity of Orlando, Florida

NASA Technical Reports Server (NTRS)

Britt, Charles L.; Bracalente, Emedio M.

1992-01-01

The algorithms used in the NASA experimental wind shear radar system for detection, characterization, and determination of windshear hazard are discussed. The performance of the algorithms in the detection of wet microbursts near Orlando is presented. Various suggested algorithms that are currently being evaluated using the flight test results from Denver and Orlando are reviewed.

ECG-derived respiration based on iterated Hilbert transform and Hilbert vibration decomposition.

PubMed

Sharma, Hemant; Sharma, K K

2018-06-01

Monitoring of the respiration using the electrocardiogram (ECG) is desirable for the simultaneous study of cardiac activities and the respiration in the aspects of comfort, mobility, and cost of the healthcare system. This paper proposes a new approach for deriving the respiration from single-lead ECG based on the iterated Hilbert transform (IHT) and the Hilbert vibration decomposition (HVD). The ECG signal is first decomposed into the multicomponent sinusoidal signals using the IHT technique. Afterward, the lower order amplitude components obtained from the IHT are filtered using the HVD to extract the respiration information. Experiments are performed on the Fantasia and Apnea-ECG datasets. The performance of the proposed ECG-derived respiration (EDR) approach is compared with the existing techniques including the principal component analysis (PCA), R-peak amplitudes (RPA), respiratory sinus arrhythmia (RSA), slopes of the QRS complex, and R-wave angle. The proposed technique showed the higher median values of correlation (first and third quartile) for both the Fantasia and Apnea-ECG datasets as 0.699 (0.55, 0.82) and 0.57 (0.40, 0.73), respectively. Also, the proposed algorithm provided the lowest values of the mean absolute error and the average percentage error computed from the EDR and reference (recorded) respiration signals for both the Fantasia and Apnea-ECG datasets as 1.27 and 9.3%, and 1.35 and 10.2%, respectively. In the experiments performed over different age group subjects of the Fantasia dataset, the proposed algorithm provided effective results in the younger population but outperformed the existing techniques in the case of elderly subjects. The proposed EDR technique has the advantages over existing techniques in terms of the better agreement in the respiratory rates and specifically, it reduces the need for an extra step required for the detection of fiducial points in the ECG for the estimation of respiration which makes the process effective and less-complex. The above performance results obtained from two different datasets validate that the proposed approach can be used for monitoring of the respiration using single-lead ECG.

MRI Signal Intensity Based B-Spline Nonrigid Registration for Pre- and Intraoperative Imaging During Prostate Brachytherapy

PubMed Central

Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M.C.; Hata, Nobuhiko

2009-01-01

Purpose To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. Materials and Methods A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts’ visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. Results All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was −0.19 ± 0.07 and FRE presented a value of 2.3 ± 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. Conclusion The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy. PMID:19856437

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

PubMed

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

Machine Learning Methods for Attack Detection in the Smart Grid.

PubMed

Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent

2016-08-01

Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

Low-complexity R-peak detection for ambulatory fetal monitoring.

PubMed

Rooijakkers, Michael J; Rabotti, Chiara; Oei, S Guid; Mischi, Massimo

2012-07-01

Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

NASA Astrophysics Data System (ADS)

Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

2014-11-01

In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

A new real-time tsunami detection algorithm

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Pignagnoli, L.

2016-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection based on the real-time tide removal and real-time band-pass filtering of sea-bed pressure recordings. The algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability, at low computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. Pressure data sets acquired by Bottom Pressure Recorders in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event which occurred at Haida Gwaii on October 28th, 2012 using data recorded by the Bullseye underwater node of Ocean Networks Canada. The algorithm successfully ran for test purpose in year-long missions onboard the GEOSTAR stand-alone multidisciplinary abyssal observatory, deployed in the Gulf of Cadiz during the EC project NEAREST and on NEMO-SN1 cabled observatory deployed in the Western Ionian Sea, operational node of the European research infrastructure EMSO.

Automated batch fiducial-less tilt-series alignment in Appion using Protomo

PubMed Central

Noble, Alex J.; Stagg, Scott M.

2015-01-01

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy. PMID:26455557

Robust registration in case of different scaling

NASA Astrophysics Data System (ADS)

Gluhchev, Georgi J.; Shalev, Shlomo

1993-09-01

The problem of robust registration in the case of anisotropic scaling has been investigated. Registration of two images using corresponding sets of fiducial points is sensitive to inaccuracies in point placement due to poor image quality or non-rigid distortions, including possible out-of-plane rotations. An approach aimed at the detection of the most unreliable points has been developed. It is based on the a priori knowledge of the sequential ordering of rotation and scaling. A measure of guilt derived from the anomalous geometric relationships is introduced. A heuristic decision rule allowing for deletion of the most guilty points is proposed. The approach allows for more precise evaluation of the translation vector. It has been tested on phantom images with known parameters and has shown satisfactory results.

First Results of the LUX Dark Matter Experiment

NASA Astrophysics Data System (ADS)

Carmona-Benitez, M. C.; Akerib, D. S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E.; Bernstein, A.; Bradley, A.; Byram, D.; Cahn, S. B.; Chan, C.; Chapman, J. J.; Chiller, A. A.; Chiller, C.; Currie, A.; de Viveiros, L.; Dobi, A.; Dobson, J.; Druszkiewicz, E.; Edwards, B.; Faham, C. H.; Fiorucci, S.; Flores, C.; Gaitskell, R. J.; Gehman, V. M.; Ghag, C.; Gibson, K. R.; Gilchriese, M. G. D.; Hall, C.; Hanhardt, M.; Haselschwardt, S.; Hertel, S. A.; Horn, M.; Huang, D. Q.; Ihm, M.; Jacobsen, R. G.; Kazkaz, K.; Knoche, R.; Larsen, N. A.; Lee, C.; Lenardo, B.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Malling, D. C.; Manalaysay, A.; Mannino, R.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H.; Neves, F.; Ott, R. A.; Pangilinan, M.; Parker, P. D.; Pease, E. K.; Pech, K.; Phelps, P.; Reichhart, L.; Shutt, T.; Silva, C.; Solovov, V. N.; Sorensen, P.; O'Sullivan, K.; Sumner, T. J.; Szydagis, M.; Taylor, D.; Tennyson, B.; Tiedt, D. R.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Verbus, J. R.; Walsh, N.; Webb, R.; White, J. T.; Witherell, M. S.; Wolfs, F. L. H.; Woods, M.; Zhang, C.; LUX Collaboration

2016-04-01

LUX (Large Underground Xenon) is a dark matter direct detection experiment deployed at the 4850' level of the Sanford Underground Research Facility (SURF) in Lead, SD, operating a 370 kg dual-phase xenon TPC. Results of the first WIMP search run were presented in late 2013, for the analysis of 85.3 live-days with a fiducial volume of 118 kg, taken during the period of April to August 2013. The experiment exhibited a sensitivity to spin-independent WIMP-nucleon elastic scattering with a minimum upper limit on the cross section of 7.6 ×10-46cm2 at a WIMP mass of 33 GeV/c2, becoming the world's leading WIMP search result, in conflict with several previous claimed hints of discovery.

A hardware-algorithm co-design approach to optimize seizure detection algorithms for implantable applications.

PubMed

Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P

2010-10-30

Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.

An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform

DTIC Science & Technology

2018-01-01

ARL-TR-8270 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform by Kwok F Tom Sensors and Electron...1 October 2016–30 September 2017 4. TITLE AND SUBTITLE An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a

Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. II. Experiment.

PubMed

Choi, Jang-Hwan; Maier, Andreas; Keil, Andreas; Pal, Saikat; McWalter, Emily J; Beaupré, Gary S; Gold, Garry E; Fahrig, Rebecca

2014-06-01

A C-arm CT system has been shown to be capable of scanning a single cadaver leg under loaded conditions by virtue of its highly flexible acquisition trajectories. In Part I of this study, using the 4D XCAT-based numerical simulation, the authors predicted that the involuntary motion in the lower body of subjects in weight-bearing positions would seriously degrade image quality and the authors suggested three motion compensation methods by which the reconstructions could be corrected to provide diagnostic image quality. Here, the authors demonstrate that a flat-panel angiography system is appropriate for scanning both legs of subjects in vivo under weight-bearing conditions and further evaluate the three motion-correction algorithms using in vivo data. The geometry of a C-arm CT system for a horizontal scan trajectory was calibrated using the PDS-2 phantom. The authors acquired images of two healthy volunteers while lying supine on a table, standing, and squatting at several knee flexion angles. In order to identify the involuntary motion of the lower body, nine 1-mm-diameter tantalum fiducial markers were attached around the knee. The static mean marker position in 3D, a reference for motion compensation, was estimated by back-projecting detected markers in multiple projections using calibrated projection matrices and identifying the intersection points in 3D of the back-projected rays. Motion was corrected using three different methods (described in detail previously): (1) 2D projection shifting, (2) 2D deformable projection warping, and (3) 3D rigid body warping. For quantitative image quality analysis, SSIM indices for the three methods were compared using the supine data as a ground truth. A 2D Euclidean distance-based metric of subjects' motion ranged from 0.85 mm (±0.49 mm) to 3.82 mm (±2.91 mm) (corresponding to 2.76 to 12.41 pixels) resulting in severe motion artifacts in 3D reconstructions. Shifting in 2D, 2D warping, and 3D warping improved the SSIM in the central slice by 20.22%, 16.83%, and 25.77% in the data with the largest motion among the five datasets (SCAN5); improvement in off-center slices was 18.94%, 29.14%, and 36.08%, respectively. The authors showed that C-arm CT control can be implemented for nonstandard horizontal trajectories which enabled us to scan and successfully reconstruct both legs of volunteers in weight-bearing positions. As predicted using theoretical models, the proposed motion correction methods improved image quality by reducing motion artifacts in reconstructions; 3D warping performed better than the 2D methods, especially in off-center slices.

Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. II. Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Jang-Hwan; Maier, Andreas; Keil, Andreas

2014-06-15

Purpose: A C-arm CT system has been shown to be capable of scanning a single cadaver leg under loaded conditions by virtue of its highly flexible acquisition trajectories. In Part I of this study, using the 4D XCAT-based numerical simulation, the authors predicted that the involuntary motion in the lower body of subjects in weight-bearing positions would seriously degrade image quality and the authors suggested three motion compensation methods by which the reconstructions could be corrected to provide diagnostic image quality. Here, the authors demonstrate that a flat-panel angiography system is appropriate for scanning both legs of subjectsin vivo undermore » weight-bearing conditions and further evaluate the three motion-correction algorithms using in vivo data. Methods: The geometry of a C-arm CT system for a horizontal scan trajectory was calibrated using the PDS-2 phantom. The authors acquired images of two healthy volunteers while lying supine on a table, standing, and squatting at several knee flexion angles. In order to identify the involuntary motion of the lower body, nine 1-mm-diameter tantalum fiducial markers were attached around the knee. The static mean marker position in 3D, a reference for motion compensation, was estimated by back-projecting detected markers in multiple projections using calibrated projection matrices and identifying the intersection points in 3D of the back-projected rays. Motion was corrected using three different methods (described in detail previously): (1) 2D projection shifting, (2) 2D deformable projection warping, and (3) 3D rigid body warping. For quantitative image quality analysis, SSIM indices for the three methods were compared using the supine data as a ground truth. Results: A 2D Euclidean distance-based metric of subjects’ motion ranged from 0.85 mm (±0.49 mm) to 3.82 mm (±2.91 mm) (corresponding to 2.76 to 12.41 pixels) resulting in severe motion artifacts in 3D reconstructions. Shifting in 2D, 2D warping, and 3D warping improved the SSIM in the central slice by 20.22%, 16.83%, and 25.77% in the data with the largest motion among the five datasets (SCAN5); improvement in off-center slices was 18.94%, 29.14%, and 36.08%, respectively. Conclusions: The authors showed that C-arm CT control can be implemented for nonstandard horizontal trajectories which enabled us to scan and successfully reconstruct both legs of volunteers in weight-bearing positions. As predicted using theoretical models, the proposed motion correction methods improved image quality by reducing motion artifacts in reconstructions; 3D warping performed better than the 2D methods, especially in off-center slices.« less

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOEpatents

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2015-07-28

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

Error detection method

DOEpatents

Olson, Eric J.

2013-06-11

An apparatus, program product, and method that run an algorithm on a hardware based processor, generate a hardware error as a result of running the algorithm, generate an algorithm output for the algorithm, compare the algorithm output to another output for the algorithm, and detect the hardware error from the comparison. The algorithm is designed to cause the hardware based processor to heat to a degree that increases the likelihood of hardware errors to manifest, and the hardware error is observable in the algorithm output. As such, electronic components may be sufficiently heated and/or sufficiently stressed to create better conditions for generating hardware errors, and the output of the algorithm may be compared at the end of the run to detect a hardware error that occurred anywhere during the run that may otherwise not be detected by traditional methodologies (e.g., due to cooling, insufficient heat and/or stress, etc.).

Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

NASA Astrophysics Data System (ADS)

Ren, Shengwei; Zhang, Li; Zhang, Shibing

2016-10-01

Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

Lining seam elimination algorithm and surface crack detection in concrete tunnel lining

NASA Astrophysics Data System (ADS)

Qu, Zhong; Bai, Ling; An, Shi-Quan; Ju, Fang-Rong; Liu, Ling

2016-11-01

Due to the particularity of the surface of concrete tunnel lining and the diversity of detection environments such as uneven illumination, smudges, localized rock falls, water leakage, and the inherent seams of the lining structure, existing crack detection algorithms cannot detect real cracks accurately. This paper proposed an algorithm that combines lining seam elimination with the improved percolation detection algorithm based on grid cell analysis for surface crack detection in concrete tunnel lining. First, check the characteristics of pixels within the overlapping grid to remove the background noise and generate the percolation seed map (PSM). Second, cracks are detected based on the PSM by the accelerated percolation algorithm so that the fracture unit areas can be scanned and connected. Finally, the real surface cracks in concrete tunnel lining can be obtained by removing the lining seam and performing percolation denoising. Experimental results show that the proposed algorithm can accurately, quickly, and effectively detect the real surface cracks. Furthermore, it can fill the gap in the existing concrete tunnel lining surface crack detection by removing the lining seam.

A community detection algorithm based on structural similarity

NASA Astrophysics Data System (ADS)

Guo, Xuchao; Hao, Xia; Liu, Yaqiong; Zhang, Li; Wang, Lu

2017-09-01

In order to further improve the efficiency and accuracy of community detection algorithm, a new algorithm named SSTCA (the community detection algorithm based on structural similarity with threshold) is proposed. In this algorithm, the structural similarities are taken as the weights of edges, and the threshold k is considered to remove multiple edges whose weights are less than the threshold, and improve the computational efficiency. Tests were done on the Zachary’s network, Dolphins’ social network and Football dataset by the proposed algorithm, and compared with GN and SSNCA algorithm. The results show that the new algorithm is superior to other algorithms in accuracy for the dense networks and the operating efficiency is improved obviously.

Detection of dominant flow and abnormal events in surveillance video

NASA Astrophysics Data System (ADS)

Kwak, Sooyeong; Byun, Hyeran

2011-02-01

We propose an algorithm for abnormal event detection in surveillance video. The proposed algorithm is based on a semi-unsupervised learning method, a kind of feature-based approach so that it does not detect the moving object individually. The proposed algorithm identifies dominant flow without individual object tracking using a latent Dirichlet allocation model in crowded environments. It can also automatically detect and localize an abnormally moving object in real-life video. The performance tests are taken with several real-life databases, and their results show that the proposed algorithm can efficiently detect abnormally moving objects in real time. The proposed algorithm can be applied to any situation in which abnormal directions or abnormal speeds are detected regardless of direction.

Quantum machine learning for quantum anomaly detection

NASA Astrophysics Data System (ADS)

Liu, Nana; Rebentrost, Patrick

2018-04-01

Anomaly detection is used for identifying data that deviate from "normal" data patterns. Its usage on classical data finds diverse applications in many important areas such as finance, fraud detection, medical diagnoses, data cleaning, and surveillance. With the advent of quantum technologies, anomaly detection of quantum data, in the form of quantum states, may become an important component of quantum applications. Machine-learning algorithms are playing pivotal roles in anomaly detection using classical data. Two widely used algorithms are the kernel principal component analysis and the one-class support vector machine. We find corresponding quantum algorithms to detect anomalies in quantum states. We show that these two quantum algorithms can be performed using resources that are logarithmic in the dimensionality of quantum states. For pure quantum states, these resources can also be logarithmic in the number of quantum states used for training the machine-learning algorithm. This makes these algorithms potentially applicable to big quantum data applications.

A Formally Verified Conflict Detection Algorithm for Polynomial Trajectories

NASA Technical Reports Server (NTRS)

Narkawicz, Anthony; Munoz, Cesar

2015-01-01

In air traffic management, conflict detection algorithms are used to determine whether or not aircraft are predicted to lose horizontal and vertical separation minima within a time interval assuming a trajectory model. In the case of linear trajectories, conflict detection algorithms have been proposed that are both sound, i.e., they detect all conflicts, and complete, i.e., they do not present false alarms. In general, for arbitrary nonlinear trajectory models, it is possible to define detection algorithms that are either sound or complete, but not both. This paper considers the case of nonlinear aircraft trajectory models based on polynomial functions. In particular, it proposes a conflict detection algorithm that precisely determines whether, given a lookahead time, two aircraft flying polynomial trajectories are in conflict. That is, it has been formally verified that, assuming that the aircraft trajectories are modeled as polynomial functions, the proposed algorithm is both sound and complete.

Health management system for rocket engines

NASA Technical Reports Server (NTRS)

Nemeth, Edward

1990-01-01

The functional framework of a failure detection algorithm for the Space Shuttle Main Engine (SSME) is developed. The basic algorithm is based only on existing SSME measurements. Supplemental measurements, expected to enhance failure detection effectiveness, are identified. To support the algorithm development, a figure of merit is defined to estimate the likelihood of SSME criticality 1 failure modes and the failure modes are ranked in order of likelihood of occurrence. Nine classes of failure detection strategies are evaluated and promising features are extracted as the basis for the failure detection algorithm. The failure detection algorithm provides early warning capabilities for a wide variety of SSME failure modes. Preliminary algorithm evaluation, using data from three SSME failures representing three different failure types, demonstrated indications of imminent catastrophic failure well in advance of redline cutoff in all three cases.

Measurement of differential cross-sections of a single top quark produced in association with a W boson at $$\\sqrt{s}={13}{\\text {TeV}}$$ with ATLAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

The differential cross-section for the production of a W boson in association with a top quark is measured for several particle-level observables. The measurements are performed using 36.1fb -1 of pp collision data collected with the ATLAS detector at the LHC in 2015 and 2016. Differential cross-sections are then measured in a fiducial phase space defined by the presence of two charged leptons and exactly one jet matched to a b-hadron, and are normalised with the fiducial cross-section. Results are found to be in good agreement with predictions from several Monte Carlo event generators.

Fiducial marker application method for position alignment of in situ multimodal X-ray experiments and reconstructions

DOE PAGES

Shade, Paul A.; Menasche, David B.; Bernier, Joel V.; ...

2016-03-01

An evolving suite of X-ray characterization methods are presently available to the materials community, providing a great opportunity to gain new insight into material behavior and provide critical validation data for materials models. Two critical and related issues are sample repositioning during anin situexperiment and registration of multiple data sets after the experiment. To address these issues, a method is described which utilizes a focused ion-beam scanning electron microscope equipped with a micromanipulator to apply gold fiducial markers to samples for X-ray measurements. The method is demonstrated with a synchrotron X-ray experiment involvingin situloading of a titanium alloy tensile specimen.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

Tmore » his paper presents the extended results of measurements of W ± W ± j j production and limits on anomalous quartic gauge couplings using 20.3 fb -1 of proton–proton collision data at $$\\sqrt{s}$$ = 8 eV recorded by the ALAS detector at the Large Hadron Collider. Events with two leptons (e or μ) with the same electric charge and at least two jets are analyzed. Production cross sections are determined in two fiducial regions, with different sensitivities to the electroweak and strong production mechanisms. Lastly, an additional fiducial region, particularly sensitive to anomalous quartic gauge coupling parameters α 4 and α 5 , is introduced, which allows more stringent limits on these parameters compared to the previous ALAS measurement.« less

Measurement of differential cross-sections of a single top quark produced in association with a W boson at √{s}={13}{ {TeV}} with ATLAS

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bauer, K. T.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Bergsten, L. J.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Betti, A.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozson, A. J.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Büscher, D.; Büscher, V.; Buschmann, E.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Li, C.-Q.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; CapeansGarrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casha, A. F.; Casolino, M.; Casper, D. W.; Castelijn, R.; CastilloGimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corrigan, E. E.; Corriveau, F.; Cortes-Gonzalez, A.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; CuhadarDonszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Dann, N. S.; Danninger, M.; DanoHoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; DiValentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Dickinson, J.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobre, M.; Dodsworth, D.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubinin, F.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dulsen, C.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duperrin, A.; DuranYildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Ennis, J. S.; Epland, M. B.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; FaucciGiannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, M.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; FloresCastillo, L. R.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; Gonnella, F.; Gonski, J. L.; González de laHoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Grabowska-Bold, I.; Gradin, P. O. J.; Graham, E. C.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gurbuz, S.; Gustavino, G.; Gutelman, B. J.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, K.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Handl, D. M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hlaluku, D. R.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Holzbock, M.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hostiuc, A.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Huhtinen, M.; Hunter, R. F. H.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Hyneman, R.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Iltzsche, F.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kellermann, E.; Kempster, J. J.; Kendrick, J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kiehn, M.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kitali, V.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klingl, T.; Klioutchnikova, T.; Klitzner, F. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Konya, B.; Kopeliansky, R.; Koperny, S.; Korcyl, K.; Kordas, K.; Korn, A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kourlitis, E.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kremer, J. A.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kupfer, T.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; Navarro, J. L. La Rosa; La Rotonda, L.; La Ruffa, F.; Lacasta, C.; Lacava, F.; Lacey, J.; Lack, D. P. J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Langenberg, R. J.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Lau, T. S.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, G. R.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Les, R.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Li, B.; Li, H.; Li, L.; Li, Q.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Limosani, A.; Lin, C. Y.; Lin, K.; Lin, S. C.; Lin, T. H.; Linck, R. A.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J. K. K.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; LlorenteMerino, J.; Lloyd, S. L.; Lo, C. Y.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loesle, A.; Loew, K. M.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lund-Jensen, B.; Lutz, M. S.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyu, F.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Mader, W. F.; Madsen, A.; Madysa, N.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A. S.; Magerl, V.; Maiani, C.; Maidantchik, C.; Maier, T.; Maio, A.; Majersky, O.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mankinen, K. H.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchese, L.; Marchiori, G.; Marcisovsky, M.; Marin Tobon, C. A.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Mason, L. H.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McNamara, P. C.; McNicol, C. J.; McPherson, R. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meirose, B.; Melini, D.; MelladoGarcia, B. R.; Mellenthin, J. D.; Melo, M.; Meloni, F.; Melzer, A.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Merlassino, C.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Millar, D. A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mirto, A.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, M.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Mwewa, C.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Ng, Y. S.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforou, N.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishu, N.; Nisius, R.; Nitsche, I.; Nitta, T.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olsson, M. J. R.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oppen, H.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orgill, E. C.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Panagoulias, I.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasner, J. M.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearson, B.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Pokharel, I.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Portillo Quintero, D. M.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potti, H.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; RomanoSaez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, D.; Roy, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Rüttinger, E. M.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; SanchezPineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaeffer, J.; Schaepe, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schenck, F.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Šfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherman, A. D.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, L.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Sottocornola, S.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, T. J.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeda, K.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Thais, S. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tian, Y.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; ValdesSanturio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von Buddenbrock, S. E.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakamiya, K.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, A. M.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, A.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Woods, N. L.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Xu, W.; Yabsley, B.; Yacoob, S.; Yajima, K.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; YauWong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2018-03-01

The differential cross-section for the production of a W boson in association with a top quark is measured for several particle-level observables. The measurements are performed using {36.1} {fb}^{-1} of pp collision data collected with the ATLAS detector at the LHC in 2015 and 2016. Differential cross-sections are measured in a fiducial phase space defined by the presence of two charged leptons and exactly one jet matched to a b-hadron, and are normalised with the fiducial cross-section. Results are found to be in good agreement with predictions from several Monte Carlo event generators.

Measurement of differential cross-sections of a single top quark produced in association with a W boson at $$\\sqrt{s}={13}{\\text {TeV}}$$ with ATLAS

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2018-03-06

The differential cross-section for the production of a W boson in association with a top quark is measured for several particle-level observables. The measurements are performed using 36.1fb -1 of pp collision data collected with the ATLAS detector at the LHC in 2015 and 2016. Differential cross-sections are then measured in a fiducial phase space defined by the presence of two charged leptons and exactly one jet matched to a b-hadron, and are normalised with the fiducial cross-section. Results are found to be in good agreement with predictions from several Monte Carlo event generators.

Clustering analysis of moving target signatures

NASA Astrophysics Data System (ADS)

Martone, Anthony; Ranney, Kenneth; Innocenti, Roberto

2010-04-01

Previously, we developed a moving target indication (MTI) processing approach to detect and track slow-moving targets inside buildings, which successfully detected moving targets (MTs) from data collected by a low-frequency, ultra-wideband radar. Our MTI algorithms include change detection, automatic target detection (ATD), clustering, and tracking. The MTI algorithms can be implemented in a real-time or near-real-time system; however, a person-in-the-loop is needed to select input parameters for the clustering algorithm. Specifically, the number of clusters to input into the cluster algorithm is unknown and requires manual selection. A critical need exists to automate all aspects of the MTI processing formulation. In this paper, we investigate two techniques that automatically determine the number of clusters: the adaptive knee-point (KP) algorithm and the recursive pixel finding (RPF) algorithm. The KP algorithm is based on a well-known heuristic approach for determining the number of clusters. The RPF algorithm is analogous to the image processing, pixel labeling procedure. Both algorithms are used to analyze the false alarm and detection rates of three operational scenarios of personnel walking inside wood and cinderblock buildings.

DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D.

PubMed

Shuvaev, Sergey A; Lazutkin, Alexander A; Kedrov, Alexander V; Anokhin, Konstantin V; Enikolopov, Grigori N; Koulakov, Alexei A

2017-01-01

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.

Multi-object Detection and Discrimination Algorithms

DTIC Science & Technology

2015-03-26

with  an   algorithm  similar  to  a  depth-­‐first   search .   This  stage  of  the   algorithm  is  O(CN).  From...Multi-object Detection and Discrimination Algorithms This document contains an overview of research and work performed and published at the University...of Florida from October 1, 2009 to October 31, 2013 pertaining to proposal 57306CS: Multi-object Detection and Discrimination Algorithms

Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection

NASA Astrophysics Data System (ADS)

Amiri, Ali; Fathy, Mahmood

2010-12-01

This article explores the problem of video shot boundary detection and examines a novel shot boundary detection algorithm by using QR-decomposition and modeling of gradual transitions by Gaussian functions. Specifically, the authors attend to the challenges of detecting gradual shots and extracting appropriate spatiotemporal features that affect the ability of algorithms to efficiently detect shot boundaries. The algorithm utilizes the properties of QR-decomposition and extracts a block-wise probability function that illustrates the probability of video frames to be in shot transitions. The probability function has abrupt changes in hard cut transitions, and semi-Gaussian behavior in gradual transitions. The algorithm detects these transitions by analyzing the probability function. Finally, we will report the results of the experiments using large-scale test sets provided by the TRECVID 2006, which has assessments for hard cut and gradual shot boundary detection. These results confirm the high performance of the proposed algorithm.

Autonomous detection of indoor and outdoor signs

NASA Astrophysics Data System (ADS)

Holden, Steven; Snorrason, Magnus; Goodsell, Thomas; Stevens, Mark R.

2005-05-01

Most goal-oriented mobile robot tasks involve navigation to one or more known locations. This is generally done using GPS coordinates and landmarks outdoors, or wall-following and fiducial marks indoors. Such approaches ignore the rich source of navigation information that is already in place for human navigation in all man-made environments: signs. A mobile robot capable of detecting and reading arbitrary signs could be tasked using directions that are intuitive to hu-mans, and it could report its location relative to intuitive landmarks (a street corner, a person's office, etc.). Such ability would not require active marking of the environment and would be functional in the absence of GPS. In this paper we present an updated version of a system we call Sign Understanding in Support of Autonomous Navigation (SUSAN). This system relies on cues common to most signs, the presence of text, vivid color, and compact shape. By not relying on templates, SUSAN can detect a wide variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. In this paper we focus on the text detection capability. We present results summarizing probability of detection and false alarm rate across many scenes containing signs of very different designs and in a variety of lighting conditions.

Image fusion pitfalls for cranial radiosurgery

PubMed Central

Jonker, Benjamin P.

2013-01-01

Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls. PMID:23682338

Fast and accurate image recognition algorithms for fresh produce food safety sensing

NASA Astrophysics Data System (ADS)

Yang, Chun-Chieh; Kim, Moon S.; Chao, Kuanglin; Kang, Sukwon; Lefcourt, Alan M.

2011-06-01

This research developed and evaluated the multispectral algorithms derived from hyperspectral line-scan fluorescence imaging under violet LED excitation for detection of fecal contamination on Golden Delicious apples. The algorithms utilized the fluorescence intensities at four wavebands, 680 nm, 684 nm, 720 nm, and 780 nm, for computation of simple functions for effective detection of contamination spots created on the apple surfaces using four concentrations of aqueous fecal dilutions. The algorithms detected more than 99% of the fecal spots. The effective detection of feces showed that a simple multispectral fluorescence imaging algorithm based on violet LED excitation may be appropriate to detect fecal contamination on fast-speed apple processing lines.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using amore » combinatorial algorithm.« less

Gas leak detection in infrared video with background modeling

NASA Astrophysics Data System (ADS)

Zeng, Xiaoxia; Huang, Likun

2018-03-01

Background modeling plays an important role in the task of gas detection based on infrared video. VIBE algorithm is a widely used background modeling algorithm in recent years. However, the processing speed of the VIBE algorithm sometimes cannot meet the requirements of some real time detection applications. Therefore, based on the traditional VIBE algorithm, we propose a fast prospect model and optimize the results by combining the connected domain algorithm and the nine-spaces algorithm in the following processing steps. Experiments show the effectiveness of the proposed method.

Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

NASA Astrophysics Data System (ADS)

Salamatova, T.; Zhukov, V.

2017-02-01

The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.

Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

NASA Astrophysics Data System (ADS)

Zhu, Zhe

2017-08-01

The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

Measurement of inclusive and differential cross sections in the H → ZZ * → 4 ℓ decay channel in pp collisions at √{s}=13 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Sola, J. D. Bossio; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de la Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gupta, S.; Gurbuz, S.; Gustavino, G.; Gutelman, B. J.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Hyneman, R.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kellermann, E.; Kempster, J. J.; Kendrick, J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kitali, V.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klingl, T.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Komar, A. A.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kourlitis, E.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kremer, J. A.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kupfer, T.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; La Ruffa, F.; Lacasta, C.; Lacava, F.; Lacey, J.; Lack, D. P. J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Langenberg, R. J.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Lau, T. S.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, G. R.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Li, B.; Li, Changqiao; Li, H.; Li, L.; Li, Q.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, K.; Lin, S. C.; Lin, T. H.; Linck, R. A.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J. K. K.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo, C. Y.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loesle, A.; Loew, K. M.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Mateos, D.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lutz, M. S.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyu, F.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A. S.; Magerl, V.; Maiani, C.; Maidantchik, C.; Maier, T.; Maio, A.; Majersky, O.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mankinen, K. H.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchese, L.; Marchiori, G.; Marcisovsky, M.; Marin Tobon, C. A.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Mason, L. H.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McNamara, P. C.; McNicol, C. J.; McPherson, R. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Mellenthin, J. D.; Melo, M.; Meloni, F.; Melzer, A.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Merlassino, C.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Millar, D. A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mirto, A.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforou, N.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishu, N.; Nisius, R.; Nitsche, I.; Nitta, T.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oppen, H.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Panagoulias, I.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasner, J. M.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearson, B.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Pokharel, I.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potti, H.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rangel-Smith, C.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2017-10-01

Inclusive and differential fiducial cross sections of Higgs boson production in proton-proton collisions are measured in the H → ZZ * → 4 ℓ decay channel. The proton-proton collision data were produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb-1. The inclusive fiducial cross section in the H → ZZ * → 4ℓ decay channel is measured to be 3.62 ± 0.50(stat) - 0.20 + 0.25 (sys) fb, in agreement with the Standard Model prediction of 2 .91 ± 0 .13 fb. The cross section is also extrapolated to the total phase space including all Standard Model Higgs boson decays. Several differential fiducial cross sections are measured for observables sensitive to the Higgs boson production and decay, including kinematic distributions of jets produced in association with the Higgs boson. Good agreement is found between data and Standard Model predictions. The results are used to put constraints on anomalous Higgs boson interactions with Standard Model particles, using the pseudo-observable extension to the kappa-framework. [Figure not available: see fulltext.

Measurement of fiducial differential cross sections of gluon-fusion production of Higgs bosons decaying to WW* → eνμν with the ATLAS detector at $$ \\sqrt{s}=8 $$ TeV

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2016-08-17

Here, this paper describes a measurement of fiducial and differential cross sections of gluon-fusion Higgs boson production in the H → WW *→ eνμν channel, using 20.3 fb –1 of proton-proton collision data. The data were produced at a centre-of-mass energy of √s = 8 TeV at the CERN Large Hadron Collider and recorded by the ATLAS detector in 2012. Cross sections are measured from the observed H→ W W*→ eνμν signal yield in categories distinguished by the number of associated jets. The total cross section is measured in a fiducial region defined by the kinematic properties of the chargedmore » leptons and neutrinos. Differential cross sections are reported as a function of the number of jets, the Higgs boson transverse momentum, the dilepton rapidity, and the transverse momentum of the leading jet. The jet-veto efficiency, or fraction of events with no jets above a given transverse momentum threshold, is also reported. All measurements are compared to QCD predictions from Monte Carlo generators and fixed-order calculations, and are in agreement with the Standard Model predictions.« less

A method for improving the accuracy of stereotaxic procedures in monkeys using implanted fiducial markers in CT scans that also serve as anchor points in a stereotaxic frame.

PubMed

Risher, D W; Zhang, X; Kostarczyk, E; Gokin, A P; Honda, C N; Giesler, G J

1997-04-25

We developed a relatively inexpensive method for stereotaxic placement of electrodes or needles in the brains of monkeys. Steel balls were affixed to the skulls of monkeys. These balls served as fiducial markers and were also used as points at which the monkey's skull was held in a modified stereotaxic apparatus. Computed tomography (CT) was used to establish the location of an injection target with respect to the fiducial markers. A computer program related the CT coordinates to stereotaxic coordinates. These were used to direct an electrode marker toward a target in the hypothalamus. With the marker left in place, the monkey was removed from the stereotaxic frame and a second CT scan was performed. Corrections for errors in marker placement were made and retrograde tracers were injected. This procedure was found to be more accurate and reliable than conventional stereotaxic procedures. The accuracy and repeatability of the technique were also established using a phantom model of a monkey's skull. Two important advantages of this method are that animals can be repeatedly placed into the stereotaxic frame in precisely the same position and that there are many opportunities during the procedure to check for and correct errors.

The Gould's Belt Very Large Array Survey. II. The Serpens Region

NASA Astrophysics Data System (ADS)

Ortiz-León, Gisela N.; Loinard, Laurent; Mioduszewski, Amy J.; Dzib, Sergio A.; Rodríguez, Luis F.; Pech, Gerardo; Rivera, Juana L.; Torres, Rosa M.; Boden, Andrew F.; Hartmann, Lee; Evans, Neal J., II; Briceño, Cesar; Tobin, John; Kounkel, Marina A.; González-Lópezlira, Rosa A.

2015-05-01

We present deep (∼17 μJy) radio continuum observations of the Serpens molecular cloud, the Serpens south cluster, and the W40 region obtained using the Very Large Array in its A configuration. We detect a total of 146 sources, 29 of which are young stellar objects (YSOs), 2 of which are BV stars, and 5 more of which are associated with phenomena related to YSOs. Based on their radio variability and spectral index, we propose that about 16 of the remaining 110 unclassified sources are also YSOs. For approximately 65% of the known YSOs detected here as radio sources, the emission is most likely non-thermal and related to stellar coronal activity. As also recently observed in Ophiuchus, our sample of YSOs with X-ray counterparts lies below the fiducial Güdel & Benz relation. Finally, we analyze the proper motions of nine sources in the W40 region. This allows us to better constrain the membership of the radio sources in the region.

Comparison of human observer and algorithmic target detection in nonurban forward-looking infrared imagery

NASA Astrophysics Data System (ADS)

Weber, Bruce A.

2005-07-01

We have performed an experiment that compares the performance of human observers with that of a robust algorithm for the detection of targets in difficult, nonurban forward-looking infrared imagery. Our purpose was to benchmark the comparison and document performance differences for future algorithm improvement. The scale-insensitive detection algorithm, used as a benchmark by the Night Vision Electronic Sensors Directorate for algorithm evaluation, employed a combination of contrastlike features to locate targets. Detection receiver operating characteristic curves and observer-confidence analyses were used to compare human and algorithmic responses and to gain insight into differences. The test database contained ground targets, in natural clutter, whose detectability, as judged by human observers, ranged from easy to very difficult. In general, as compared with human observers, the algorithm detected most of the same targets, but correlated confidence with correct detections poorly and produced many more false alarms at any useful level of performance. Though characterizing human performance was not the intent of this study, results suggest that previous observational experience was not a strong predictor of human performance, and that combining individual human observations by majority vote significantly reduced false-alarm rates.

Enhancement of image contrast by fluorescence in microtechnology

NASA Astrophysics Data System (ADS)

Berndt, Michael; Tutsch, Rainer

2005-06-01

New developments in production technology increasingly focus on hybrid microsystems. Especially for systems with movable components, the process step of assembly is mandatory. In general, the accuracy of positioning of the parts has to be better than 1 μm. This makes specialized and automated production equipment necessary, which can lead to a conflict with the aim of flexibility of the range of products. Design for manufacturing is a well known remedy. Assembly aids are common practice today. These features of the workpieces bear no functionality for the end product but considerably ease certain process steps. By standardization of assembly aids generalized production equipment free from product-specific features could be developed. In our contribution, we demonstrate the photogrammetric determination of the positions of workpieces without reference to their exterior shape, using circular fiducial marks of 150 μm in diameter. The surface properties of the workpieces, however, still have an influence on image formation. As an example, the marks may be hidden by local specular reflections. A solution to this problem is to add an exclusive optical property to the fiducial marks to get an image with high contrast against the surface of the workpiece. In biology and medicine samples are stained with fluorescing dyes to enhance the contrast in optical microscopy. In fluorochromes, light of a characteristic wavelength is emitted after the absorption of light with a shorter wavelength. In our experiments we added a fluorochrome to a common photoresist and coated the surface of the workpiece with a thin layer thereof. Using photolithography as a patterning technique we generated fiducial marks with structures down to 25 μm. These marks can be identified by their characteristic emission wavelength under short-wavelength illumination. Only the fiducial marks remain visible in the images and processing these images is straightforward. The generation of fluorescing patterns by photolithography opens new possibilities for testing and process control in many fields of microtechnology.

A line fiducial method for geometric calibration of cone-beam CT systems with diverse scan trajectories

NASA Astrophysics Data System (ADS)

Jacobson, M. W.; Ketcha, M. D.; Capostagno, S.; Martin, A.; Uneri, A.; Goerres, J.; De Silva, T.; Reaungamornrat, S.; Han, R.; Manbachi, A.; Stayman, J. W.; Vogt, S.; Kleinszig, G.; Siewerdsen, J. H.

2018-01-01

Modern cone-beam CT systems, especially C-arms, are capable of diverse source-detector orbits. However, geometric calibration of these systems using conventional configurations of spherical fiducials (BBs) may be challenged for novel source-detector orbits and system geometries. In part, this is because the BB configurations are designed with careful forethought regarding the intended orbit so that BB marker projections do not overlap in projection views. Examples include helical arrangements of BBs (Rougee et al 1993 Proc. SPIE 1897 161-9) such that markers do not overlap in projections acquired from a circular orbit and circular arrangements of BBs (Cho et al 2005 Med. Phys. 32 968-83). As a more general alternative, this work proposes a calibration method based on an array of line-shaped, radio-opaque wire segments. With this method, geometric parameter estimation is accomplished by relating the 3D line equations representing the wires to the 2D line equations of their projections. The use of line fiducials simplifies many challenges with fiducial recognition and extraction in an orbit-independent manner. For example, their projections can overlap only mildly, for any gantry pose, as long as the wires are mutually non-coplanar in 3D. The method was tested in application to circular and non-circular trajectories in simulation and in real orbits executed using a mobile C-arm prototype for cone-beam CT. Results indicated high calibration accuracy, as measured by forward and backprojection/triangulation error metrics. Triangulation errors on the order of microns and backprojected ray deviations uniformly less than 0.2 mm were observed in both real and simulated orbits. Mean forward projection errors less than 0.1 mm were observed in a comprehensive sweep of different C-arm gantry angulations. Finally, successful integration of the method into a CT imaging chain was demonstrated in head phantom scans.

Simultaneous tumor and surrogate motion tracking with dynamic MRI for radiation therapy planning

NASA Astrophysics Data System (ADS)

Park, Seyoun; Farah, Rana; Shea, Steven M.; Tryggestad, Erik; Hales, Russell; Lee, Junghoon

2018-01-01

Respiration-induced tumor motion is a major obstacle for achieving high-precision radiotherapy of cancers in the thoracic and abdominal regions. Surrogate-based estimation and tracking methods are commonly used in radiotherapy, but with limited understanding of quantified correlation to tumor motion. In this study, we propose a method to simultaneously track the lung tumor and external surrogates to evaluate their spatial correlation in a quantitative way using dynamic MRI, which allows real-time acquisition without ionizing radiation exposure. To capture the lung and whole tumor, four MRI-compatible fiducials are placed on the patient’s chest and upper abdomen. Two different types of acquisitions are performed in the sagittal orientation including multi-slice 2D cine MRIs to reconstruct 4D-MRI and two-slice 2D cine MRIs to simultaneously track the tumor and fiducials. A phase-binned 4D-MRI is first reconstructed from multi-slice MR images using body area as a respiratory surrogate and groupwise registration. The 4D-MRI provides 3D template volumes for different breathing phases. 3D tumor position is calculated by 3D-2D template matching in which 3D tumor templates in the 4D-MRI reconstruction and the 2D cine MRIs from the two-slice tracking dataset are registered. 3D trajectories of the external surrogates are derived via matching a 3D geometrical model of the fiducials to their segmentations on the 2D cine MRIs. We tested our method on ten lung cancer patients. Using a correlation analysis, the 3D tumor trajectory demonstrates a noticeable phase mismatch and significant cycle-to-cycle motion variation, while the external surrogate was not sensitive enough to capture such variations. Additionally, there was significant phase mismatch between surrogate signals obtained from the fiducials at different locations.

SU-F-T-636: Comprehensive Approach to Motion Assessment for Liver and Pancreas SBRT Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halvorsen, P; Iftimia, I; Hunter, K

2016-06-15

Purpose: Our past practice for liver and pancreas SBRT consisted of free breathing (FB) with gated treatment delivery using a 30-70% phase window. We have recently adopted an assessment method leading to individualized motion management to minimize target motion. We present our results from 47 patients treated with this new approach. Methods: We perform an initial patient coaching and assessment session in our conventional simulator suite to observe the motion of the implanted fiducials with FB anterior and lateral 20-second cine acquisitions. The physician decides whether to attempt inhale or exhale breath-hold (BH). The patient is coached while observing withmore » cine to ascertain their ability to achieve the desired BH mode for long periods as needed for treatment delivery. If the patient cannot comply, a FB approach is adopted using gating or simple ITV method (for patients without fiducials). After achieving a patient-specific motion management mode, we perform CT-simulation using the Varian RPM system to reproduce the chosen mode and record a reference session for treatment delivery. For pre-treatment imaging, the fiducials are observed under fluoro while coaching the patient. Results: Of 47 SBRT cases analyzed, 32 were liver and 15 were pancreas. The chosen techniques were: 32 exhale BH (12 with abdominal compression), 7 FB gated, 4 inhale BH, and 4 FB ITV. Maximum fiducial motion amplitude was 5 mm for the FB gated patients, and less than 5 mm for all BH patients with most able to achieve a maximum amplitude of 3 mm. Conclusion: This study showed that an individualized motion management approach can reduce the target volume and, therefore, the volume of irradiated healthy tissue from liver or pancreas SBRT. Effective coaching is essential in achieving consistent BH with 3 mm amplitude. The fluoro/cine session is helpful in establishing the right coaching approach for each patient.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanabe, S; Utsunomiya, S; Abe, E

Purpose: To assess an accuracy of fiducial maker-based setup using ExacTrac (ExT-based setup) as compared with soft tissue-based setup using Cone-beam CT (CBCT-based setup) for patients with prostate cancer receiving intensity-modulated radiation therapy (IMRT) for the purpose of investigating whether ExT-based setup can be an alternative to CBCT-based setup. Methods: The setup accuracy was analyzed prospectively for 7 prostate cancer patients with implanted three fiducial markers received IMRT. All patients were treated after CBCT-based setup was performed and corresponding shifts were recorded. ExacTrac images were obtained before and after CBCT-based setup. The fiducial marker-based shifts were calculated based on thosemore » two images and recorded on the assumption that the setup correction was carried out by fiducial marker-based auto correction. Mean and standard deviation of absolute differences and the correlation between CBCT and ExT shifts were estimated. Results: A total of 178 image dataset were analyzed. On the differences between CBCT and ExT shifts, 133 (75%) of 178 image dataset resulted in smaller differences than 3 mm in all dimensions. Mean differences in the anterior-posterior (AP), superior-inferior (SI), and left-right (LR) dimensions were 1.8 ± 1.9 mm, 0.7 ± 1.9 mm, and 0.6 ± 0.8 mm, respectively. The percentages of shift agreements within ±3 mm were 76% for AP, 90% for SI, and 100% for LR. The Pearson coefficient of correlation for CBCT and ExT shifts were 0.80 for AP, 0.80 for SI, and 0.65 for LR. Conclusion: This work showed that the accuracy of ExT-based setup was correlated with that of CBCT-based setup, implying that ExT-based setup has a potential ability to be an alternative to CBCT-based setup. The further work is to specify the conditions that ExT-based setup can provide the accuracy comparable to CBCT-based setup.« less

SU-E-J-49: Design and Fabrication of Custom 3D Printed Phantoms for Radiation Therapy Research and Quality Assurance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jenkins, C; Xing, L

2015-06-15

Purpose The rapid proliferation of affordable 3D printing techniques has enabled the custom fabrication of items ranging from paper weights to medical implants. This study investigates the feasibility of utilizing the technology for developing novel phantoms for use in radiation therapy quality assurance (QA) procedures. Methods A phantom for measuring the geometric parameters of linear accelerator (LINAC) on-board imaging (OBI) systems was designed using SolidWorks. The design was transferred to a 3D printer and fabricated using a fused deposition modeling (FDM) technique. Fiducials were embedded in the phantom by placing 1.6 mm diameter steel balls in predefined holes and securingmore » them with silicone. Several MV and kV images of the phantom were collected and the visibility and geometric accuracy were evaluated. A second phantom, for use in the experimental evaluation of a high dose rate (HDR) brachytherapy dosimeter, was designed to secure several applicator needles in water. The applicator was fabricated in the same 3D printer and used for experiments. Results The general accuracy of printed parts was determined to be 0.1 mm. The cost of materials for the imaging and QA phantoms were $22 and $5 respectively. Both the plastic structure and fiducial markers of the imaging phantom were visible in MV and kV images. Fiducial marker locations were determined to be within 1mm of desired locations, with the discrepancy being attributed to the fiducial attachment process. The HDR phantom secured the applicators within 0.5 mm of the desired locations. Conclusion 3D printing offers an inexpensive method for fabricating custom phantoms for use in radiation therapy quality assurance. While the geometric accuracy of such parts is limited compared to more expensive methods, the phantoms are still highly functional and provide a unique opportunity for rapid fabrication of custom phantoms for use in radiation therapy QA and research.« less

Image to physical space registration of supine breast MRI for image guided breast surgery

NASA Astrophysics Data System (ADS)

Conley, Rebekah H.; Meszoely, Ingrid M.; Pheiffer, Thomas S.; Weis, Jared A.; Yankeelov, Thomas E.; Miga, Michael I.

2014-03-01

Breast conservation therapy (BCT) is a desirable option for many women diagnosed with early stage breast cancer and involves a lumpectomy followed by radiotherapy. However, approximately 50% of eligible women will elect for mastectomy over BCT despite equal survival benefit (provided margins of excised tissue are cancer free) due to uncertainty in outcome with regards to complete excision of cancerous cells, risk of local recurrence, and cosmesis. Determining surgical margins intraoperatively is difficult and achieving negative margins is not as robust as it needs to be, resulting in high re-operation rates and often mastectomy. Magnetic resonance images (MRI) can provide detailed information about tumor margin extents, however diagnostic images are acquired in a fundamentally different patient presentation than that used in surgery. Therefore, the high quality diagnostic MRIs taken in the prone position with pendant breast are not optimal for use in surgical planning/guidance due to the drastic shape change between preoperative images and the common supine surgical position. This work proposes to investigate the value of supine MRI in an effort to localize tumors intraoperatively using image-guidance. Mock intraoperative setups (realistic patient positioning in non-sterile environment) and preoperative imaging data were collected from a patient scheduled for a lumpectomy. The mock intraoperative data included a tracked laser range scan of the patient's breast surface, tracked center points of MR visible fiducials on the patient's breast, and tracked B-mode ultrasound and strain images. The preoperative data included a supine MRI with visible fiducial markers. Fiducial markers localized in the MRI were rigidly registered to their mock intraoperative counterparts using an optically tracked stylus. The root mean square (RMS) fiducial registration error using the tracked markers was 3.4mm. Following registration, the average closest point distance between the MR generated surface nodes and the LRS point cloud was 1.76±0.502 mm.

SA-SOM algorithm for detecting communities in complex networks

NASA Astrophysics Data System (ADS)

Chen, Luogeng; Wang, Yanran; Huang, Xiaoming; Hu, Mengyu; Hu, Fang

2017-10-01

Currently, community detection is a hot topic. This paper, based on the self-organizing map (SOM) algorithm, introduced the idea of self-adaptation (SA) that the number of communities can be identified automatically, a novel algorithm SA-SOM of detecting communities in complex networks is proposed. Several representative real-world networks and a set of computer-generated networks by LFR-benchmark are utilized to verify the accuracy and the efficiency of this algorithm. The experimental findings demonstrate that this algorithm can identify the communities automatically, accurately and efficiently. Furthermore, this algorithm can also acquire higher values of modularity, NMI and density than the SOM algorithm does.

A novel adaptive, real-time algorithm to detect gait events from wearable sensors.

PubMed

Chia Bejarano, Noelia; Ambrosini, Emilia; Pedrocchi, Alessandra; Ferrigno, Giancarlo; Monticone, Marco; Ferrante, Simona

2015-05-01

A real-time, adaptive algorithm based on two inertial and magnetic sensors placed on the shanks was developed for gait-event detection. For each leg, the algorithm detected the Initial Contact (IC), as the minimum of the flexion/extension angle, and the End Contact (EC) and the Mid-Swing (MS), as minimum and maximum of the angular velocity, respectively. The algorithm consisted of calibration, real-time detection, and step-by-step update. Data collected from 22 healthy subjects (21 to 85 years) walking at three self-selected speeds were used to validate the algorithm against the GaitRite system. Comparable levels of accuracy and significantly lower detection delays were achieved with respect to other published methods. The algorithm robustness was tested on ten healthy subjects performing sudden speed changes and on ten stroke subjects (43 to 89 years). For healthy subjects, F1-scores of 1 and mean detection delays lower than 14 ms were obtained. For stroke subjects, F1-scores of 0.998 and 0.944 were obtained for IC and EC, respectively, with mean detection delays always below 31 ms. The algorithm accurately detected gait events in real time from a heterogeneous dataset of gait patterns and paves the way for the design of closed-loop controllers for customized gait trainings and/or assistive devices.

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Corner detection and sorting method based on improved Harris algorithm in camera calibration

NASA Astrophysics Data System (ADS)

Xiao, Ying; Wang, Yonghong; Dan, Xizuo; Huang, Anqi; Hu, Yue; Yang, Lianxiang

2016-11-01

In traditional Harris corner detection algorithm, the appropriate threshold which is used to eliminate false corners is selected manually. In order to detect corners automatically, an improved algorithm which combines Harris and circular boundary theory of corners is proposed in this paper. After detecting accurate corner coordinates by using Harris algorithm and Forstner algorithm, false corners within chessboard pattern of the calibration plate can be eliminated automatically by using circular boundary theory. Moreover, a corner sorting method based on an improved calibration plate is proposed to eliminate false background corners and sort remaining corners in order. Experiment results show that the proposed algorithms can eliminate all false corners and sort remaining corners correctly and automatically.

QRS Detection Algorithm for Telehealth Electrocardiogram Recordings.

PubMed

Khamis, Heba; Weiss, Robert; Xie, Yang; Chang, Chan-Wei; Lovell, Nigel H; Redmond, Stephen J

2016-07-01

QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a "UNSW" QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG. The UNSW algorithm generates a feature signal containing information about ECG amplitude and derivative, which is filtered according to its frequency content and an adaptive threshold is applied. The algorithm was tested on clinical and telehealth ECG and the QRS detection performance is compared to the Pan-Tompkins (PT) and Gutiérrez-Rivas (GR) algorithm. For the MIT-BIH Arrhythmia database (virtually artifact free, clinical ECG), the overall sensitivity (Se) and positive predictivity (+P) of the UNSW algorithm was >99%, which was comparable to PT and GR. When applied to the MIT-BIH noise stress test database (clinical ECG with added calibrated noise) after artifact masking, all three algorithms had overall Se >99%, and the UNSW algorithm had higher +P (98%, p < 0.05) than PT and GR. For 250 telehealth ECG records (unsupervised recordings; dry metal electrodes), the UNSW algorithm had 98% Se and 95% +P which was superior to PT (+P: p < 0.001) and GR (Se and +P: p < 0.001). This is the first study to describe a QRS detection algorithm for telehealth data and evaluate it on clinical and telehealth ECG with superior results to published algorithms. The UNSW algorithm could be used to manage increasing telehealth ECG analysis workloads.

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shepard, A; Bednarz, B

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localizedmore » block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA190298.« less

TH-E-17A-06: Anatomical-Adaptive Compressed Sensing (AACS) Reconstruction for Thoracic 4-Dimensional Cone-Beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shieh, C; Kipritidis, J; OBrien, R

2014-06-15

Purpose: The Feldkamp-Davis-Kress (FDK) algorithm currently used for clinical thoracic 4-dimensional (4D) cone-beam CT (CBCT) reconstruction suffers from noise and streaking artifacts due to projection under-sampling. Compressed sensing theory enables reconstruction of under-sampled datasets via total-variation (TV) minimization, but TV-minimization algorithms such as adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS) often converge slowly and are prone to over-smoothing anatomical details. These disadvantages can be overcome by incorporating general anatomical knowledge via anatomy segmentation. Based on this concept, we have developed an anatomical-adaptive compressed sensing (AACS) algorithm for thoracic 4D-CBCT reconstruction. Methods: AACS is based on the ASD-POCS framework, where each iteration consists of a TV-minimizationmore » step and a data fidelity constraint step. Prior to every AACS iteration, four major thoracic anatomical structures - soft tissue, lungs, bony anatomy, and pulmonary details - were segmented from the updated solution image. Based on the segmentation, an anatomical-adaptive weighting was applied to the TV-minimization step, so that TV-minimization was enhanced at noisy/streaky regions and suppressed at anatomical structures of interest. The image quality and convergence speed of AACS was compared to conventional ASD-POCS using an XCAT digital phantom and a patient scan. Results: For the XCAT phantom, the AACS image represented the ground truth better than the ASD-POCS image, giving a higher structural similarity index (0.93 vs. 0.84) and lower absolute difference (1.1*10{sup 4} vs. 1.4*10{sup 4}). For the patient case, while both algorithms resulted in much less noise and streaking than FDK, the AACS image showed considerably better contrast and sharpness of the vessels, tumor, and fiducial marker than the ASD-POCS image. In addition, AACS converged over 50% faster than ASD-POCS in both cases. Conclusions: The proposed AACS algorithm was shown to reconstruct thoracic 4D-CBCT images more accurately and with faster convergence compared to ASD-POCS. The superior image quality and rapid convergence makes AACS promising for future clinical use.« less

Comparative analysis of peak-detection techniques for comprehensive two-dimensional chromatography.

PubMed

Latha, Indu; Reichenbach, Stephen E; Tao, Qingping

2011-09-23

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful technology for separating complex samples. The typical goal of GC×GC peak detection is to aggregate data points of analyte peaks based on their retention times and intensities. Two techniques commonly used for two-dimensional peak detection are the two-step algorithm and the watershed algorithm. A recent study [4] compared the performance of the two-step and watershed algorithms for GC×GC data with retention-time shifts in the second-column separations. In that analysis, the peak retention-time shifts were corrected while applying the two-step algorithm but the watershed algorithm was applied without shift correction. The results indicated that the watershed algorithm has a higher probability of erroneously splitting a single two-dimensional peak than the two-step approach. This paper reconsiders the analysis by comparing peak-detection performance for resolved peaks after correcting retention-time shifts for both the two-step and watershed algorithms. Simulations with wide-ranging conditions indicate that when shift correction is employed with both algorithms, the watershed algorithm detects resolved peaks with greater accuracy than the two-step method. Copyright © 2011 Elsevier B.V. All rights reserved.

Bio-ALIRT biosurveillance detection algorithm evaluation.

PubMed

Siegrist, David; Pavlin, J

2004-09-24

Early detection of disease outbreaks by a medical biosurveillance system relies on two major components: 1) the contribution of early and reliable data sources and 2) the sensitivity, specificity, and timeliness of biosurveillance detection algorithms. This paper describes an effort to assess leading detection algorithms by arranging a common challenge problem and providing a common data set. The objectives of this study were to determine whether automated detection algorithms can reliably and quickly identify the onset of natural disease outbreaks that are surrogates for possible terrorist pathogen releases, and do so at acceptable false-alert rates (e.g., once every 2-6 weeks). Historic de-identified data were obtained from five metropolitan areas over 23 months; these data included International Classification of Diseases, Ninth Revision (ICD-9) codes related to respiratory and gastrointestinal illness syndromes. An outbreak detection group identified and labeled two natural disease outbreaks in these data and provided them to analysts for training of detection algorithms. All outbreaks in the remaining test data were identified but not revealed to the detection groups until after their analyses. The algorithms established a probability of outbreak for each day's counts. The probability of outbreak was assessed as an "actual" alert for different false-alert rates. The best algorithms were able to detect all of the outbreaks at false-alert rates of one every 2-6 weeks. They were often able to detect for the same day human investigators had identified as the true start of the outbreak. Because minimal data exists for an actual biologic attack, determining how quickly an algorithm might detect such an attack is difficult. However, application of these algorithms in combination with other data-analysis methods to historic outbreak data indicates that biosurveillance techniques for analyzing syndrome counts can rapidly detect seasonal respiratory and gastrointestinal illness outbreaks. Further research is needed to assess the value of electronic data sources for predictive detection. In addition, simulations need to be developed and implemented to better characterize the size and type of biologic attack that can be detected by current methods by challenging them under different projected operational conditions.

A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm.

PubMed

Pandit, Diptangshu; Zhang, Li; Liu, Chengyu; Chattopadhyay, Samiran; Aslam, Nauman; Lim, Chee Peng

2017-06-01

Detection of the R-peak pertaining to the QRS complex of an ECG signal plays an important role for the diagnosis of a patient's heart condition. To accurately identify the QRS locations from the acquired raw ECG signals, we need to handle a number of challenges, which include noise, baseline wander, varying peak amplitudes, and signal abnormality. This research aims to address these challenges by developing an efficient lightweight algorithm for QRS (i.e., R-peak) detection from raw ECG signals. A lightweight real-time sliding window-based Max-Min Difference (MMD) algorithm for QRS detection from Lead II ECG signals is proposed. Targeting to achieve the best trade-off between computational efficiency and detection accuracy, the proposed algorithm consists of five key steps for QRS detection, namely, baseline correction, MMD curve generation, dynamic threshold computation, R-peak detection, and error correction. Five annotated databases from Physionet are used for evaluating the proposed algorithm in R-peak detection. Integrated with a feature extraction technique and a neural network classifier, the proposed ORS detection algorithm has also been extended to undertake normal and abnormal heartbeat detection from ECG signals. The proposed algorithm exhibits a high degree of robustness in QRS detection and achieves an average sensitivity of 99.62% and an average positive predictivity of 99.67%. Its performance compares favorably with those from the existing state-of-the-art models reported in the literature. In regards to normal and abnormal heartbeat detection, the proposed QRS detection algorithm in combination with the feature extraction technique and neural network classifier achieves an overall accuracy rate of 93.44% based on an empirical evaluation using the MIT-BIH Arrhythmia data set with 10-fold cross validation. In comparison with other related studies, the proposed algorithm offers a lightweight adaptive alternative for R-peak detection with good computational efficiency. The empirical results indicate that it not only yields a high accuracy rate in QRS detection, but also exhibits efficient computational complexity at the order of O(n), where n is the length of an ECG signal. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of Coronal Mass Ejections Using Multiple Features and Space-Time Continuity

NASA Astrophysics Data System (ADS)

Zhang, Ling; Yin, Jian-qin; Lin, Jia-ben; Feng, Zhi-quan; Zhou, Jin

2017-07-01

Coronal Mass Ejections (CMEs) release tremendous amounts of energy in the solar system, which has an impact on satellites, power facilities and wireless transmission. To effectively detect a CME in Large Angle Spectrometric Coronagraph (LASCO) C2 images, we propose a novel algorithm to locate the suspected CME regions, using the Extreme Learning Machine (ELM) method and taking into account the features of the grayscale and the texture. Furthermore, space-time continuity is used in the detection algorithm to exclude the false CME regions. The algorithm includes three steps: i) define the feature vector which contains textural and grayscale features of a running difference image; ii) design the detection algorithm based on the ELM method according to the feature vector; iii) improve the detection accuracy rate by using the decision rule of the space-time continuum. Experimental results show the efficiency and the superiority of the proposed algorithm in the detection of CMEs compared with other traditional methods. In addition, our algorithm is insensitive to most noise.

STREAMFINDER - I. A new algorithm for detecting stellar streams

NASA Astrophysics Data System (ADS)

Malhan, Khyati; Ibata, Rodrigo A.

2018-07-01

We have designed a powerful new algorithm to detect stellar streams in an automated and systematic way. The algorithm, which we call the STREAMFINDER, is well suited for finding dynamically cold and thin stream structures that may lie along any simple or complex orbits in Galactic stellar surveys containing any combination of positional and kinematic information. In the present contribution, we introduce the algorithm, lay out the ideas behind it, explain the methodology adopted to detect streams, and detail its workings by running it on a suite of simulations of mock Galactic survey data of similar quality to that expected from the European Space Agency/Gaia mission. We show that our algorithm is able to detect even ultra-faint stream features lying well below previous detection limits. Tests show that our algorithm will be able to detect distant halo stream structures >10° long containing as few as ˜15 members (ΣG ˜ 33.6 mag arcsec-2) in the Gaia data set.

Distributed learning automata-based algorithm for community detection in complex networks

NASA Astrophysics Data System (ADS)

Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza

2016-03-01

Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.

An Improved Harmonic Current Detection Method Based on Parallel Active Power Filter

NASA Astrophysics Data System (ADS)

Zeng, Zhiwu; Xie, Yunxiang; Wang, Yingpin; Guan, Yuanpeng; Li, Lanfang; Zhang, Xiaoyu

2017-05-01

Harmonic detection technology plays an important role in the applications of active power filter. The accuracy and real-time performance of harmonic detection are the precondition to ensure the compensation performance of Active Power Filter (APF). This paper proposed an improved instantaneous reactive power harmonic current detection algorithm. The algorithm uses an improved ip -iq algorithm which is combined with the moving average value filter. The proposed ip -iq algorithm can remove the αβ and dq coordinate transformation, decreasing the cost of calculation, simplifying the extraction process of fundamental components of load currents, and improving the detection speed. The traditional low-pass filter is replaced by the moving average filter, detecting the harmonic currents more precisely and quickly. Compared with the traditional algorithm, the THD (Total Harmonic Distortion) of the grid currents is reduced from 4.41% to 3.89% for the simulations and from 8.50% to 4.37% for the experiments after the improvement. The results show the proposed algorithm is more accurate and efficient.

A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Becker, D.; Cain, S.

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

Effect of Non-rigid Registration Algorithms on Deformation Based Morphometry: A Comparative Study with Control and Williams Syndrome Subjects

PubMed Central

Han, Zhaoying; Thornton-Wells, Tricia A.; Dykens, Elisabeth M.; Gore, John C.; Dawant, Benoit M.

2014-01-01

Deformation Based Morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared non-rigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established non-rigid registration algorithms using thirteen subjects with Williams Syndrome (WS) and thirteen Normal Control (NC) subjects. The five non-rigid registration algorithms include: (1) The Adaptive Bases Algorithm (ABA); (2) The Image Registration Toolkit (IRTK); (3) The FSL Nonlinear Image Registration Tool (FSL); (4) The Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. The unique nature of the data set used in this study also permits comparison of visible anatomical differences between the groups and regions of difference detected by each algorithm. Results show that the interpretation of DBM results is difficult. Four out of the five algorithms we have evaluated detect bilateral differences between the two groups in the insular cortex, the basal ganglia, orbitofrontal cortex, as well as in the cerebellum. These correspond to differences that have been reported in the literature and that are visible in our samples. But our results also show that some algorithms detect regions that are not detected by the others and that the extent of the detected regions varies from algorithm to algorithm. These results suggest that using more than one algorithm when performing DBM studies would increase confidence in the results. Properties of the algorithms such as the similarity measure they maximize and the regularity of the deformation fields, as well as the location of differences detected with DBM, also need to be taken into account in the interpretation process. PMID:22459439

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

PubMed Central

Wang, Jianqiang; Sun, Xiaoyan; Guo, Junbin

2013-01-01

The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS). This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR) of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

Expert system constant false alarm rate processor

NASA Astrophysics Data System (ADS)

Baldygo, William J., Jr.; Wicks, Michael C.

1993-10-01

The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.

Toward an Objective Enhanced-V Detection Algorithm

NASA Technical Reports Server (NTRS)

Moses, John F.; Brunner,Jason C.; Feltz, Wayne F.; Ackerman, Steven A.; Moses, John F.; Rabin, Robert M.

2007-01-01

The area of coldest cloud tops above thunderstorms sometimes has a distinct V or U shape. This pattern, often referred to as an "enhanced-V signature, has been observed to occur during and preceding severe weather. This study describes an algorithmic approach to objectively detect overshooting tops, temperature couplets, and enhanced-V features with observations from the Geostationary Operational Environmental Satellite and Low Earth Orbit data. The methodology consists of temperature, temperature difference, and distance thresholds for the overshooting top and temperature couplet detection parts of the algorithm and consists of cross correlation statistics of pixels for the enhanced-V detection part of the algorithm. The effectiveness of the overshooting top and temperature couplet detection components of the algorithm is examined using GOES and MODIS image data for case studies in the 2003-2006 seasons. The main goal is for the algorithm to be useful for operations with future sensors, such as GOES-R.

Evaluating the utility of syndromic surveillance algorithms for screening to detect potentially clonal hospital infection outbreaks

PubMed Central

Talbot, Thomas R; Schaffner, William; Bloch, Karen C; Daniels, Titus L; Miller, Randolph A

2011-01-01

Objective The authors evaluated algorithms commonly used in syndromic surveillance for use as screening tools to detect potentially clonal outbreaks for review by infection control practitioners. Design Study phase 1 applied four aberrancy detection algorithms (CUSUM, EWMA, space-time scan statistic, and WSARE) to retrospective microbiologic culture data, producing a list of past candidate outbreak clusters. In phase 2, four infectious disease physicians categorized the phase 1 algorithm-identified clusters to ascertain algorithm performance. In phase 3, project members combined the algorithms to create a unified screening system and conducted a retrospective pilot evaluation. Measurements The study calculated recall and precision for each algorithm, and created precision-recall curves for various methods of combining the algorithms into a unified screening tool. Results Individual algorithm recall and precision ranged from 0.21 to 0.31 and from 0.053 to 0.29, respectively. Few candidate outbreak clusters were identified by more than one algorithm. The best method of combining the algorithms yielded an area under the precision-recall curve of 0.553. The phase 3 combined system detected all infection control-confirmed outbreaks during the retrospective evaluation period. Limitations Lack of phase 2 reviewers' agreement indicates that subjective expert review was an imperfect gold standard. Less conservative filtering of culture results and alternate parameter selection for each algorithm might have improved algorithm performance. Conclusion Hospital outbreak detection presents different challenges than traditional syndromic surveillance. Nevertheless, algorithms developed for syndromic surveillance have potential to form the basis of a combined system that might perform clinically useful hospital outbreak screening. PMID:21606134

Evaluation schemes for video and image anomaly detection algorithms

NASA Astrophysics Data System (ADS)

Parameswaran, Shibin; Harguess, Josh; Barngrover, Christopher; Shafer, Scott; Reese, Michael

2016-05-01

Video anomaly detection is a critical research area in computer vision. It is a natural first step before applying object recognition algorithms. There are many algorithms that detect anomalies (outliers) in videos and images that have been introduced in recent years. However, these algorithms behave and perform differently based on differences in domains and tasks to which they are subjected. In order to better understand the strengths and weaknesses of outlier algorithms and their applicability in a particular domain/task of interest, it is important to measure and quantify their performance using appropriate evaluation metrics. There are many evaluation metrics that have been used in the literature such as precision curves, precision-recall curves, and receiver operating characteristic (ROC) curves. In order to construct these different metrics, it is also important to choose an appropriate evaluation scheme that decides when a proposed detection is considered a true or a false detection. Choosing the right evaluation metric and the right scheme is very critical since the choice can introduce positive or negative bias in the measuring criterion and may favor (or work against) a particular algorithm or task. In this paper, we review evaluation metrics and popular evaluation schemes that are used to measure the performance of anomaly detection algorithms on videos and imagery with one or more anomalies. We analyze the biases introduced by these by measuring the performance of an existing anomaly detection algorithm.

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms.

PubMed

Andersson, Richard; Larsson, Linnea; Holmqvist, Kenneth; Stridh, Martin; Nyström, Marcus

2017-04-01

Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484-2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

SU-D-207-05: Real-Time Intrafractional Motion Tracking During VMAT Delivery Using a Conventional Elekta CBCT System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Yang-Kyun; Sharp, Gregory C.; Gierga, David P.

2015-06-15

Purpose: Real-time kV projection streaming capability has become recently available for Elekta XVI version 5.0. This study aims to investigate the feasibility and accuracy of real-time fiducial marker tracking during CBCT acquisition with or without simultaneous VMAT delivery using a conventional Elekta linear accelerator. Methods: A client computer was connected to an on-board kV imaging system computer, and receives and processes projection images immediately after image acquisition. In-house marker tracking software based on FFT normalized cross-correlation was developed and installed in the client computer. Three gold fiducial markers with 3 mm length were implanted in a pelvis-shaped phantom with 36more » cm width. The phantom was placed on a programmable motion platform oscillating in anterior-posterior and superior-inferior directions simultaneously. The marker motion was tracked in real-time for (1) a kV-only CBCT scan with treatment beam off and (2) a kV CBCT scan during a 6-MV VMAT delivery. The exposure parameters per projection were 120 kVp and 1.6 mAs. Tracking accuracy was assessed by comparing superior-inferior positions between the programmed and tracked trajectories. Results: The projection images were successfully transferred to the client computer at a frequency of about 5 Hz. In the kV-only scan, highly accurate marker tracking was achieved over the entire range of cone-beam projection angles (detection rate / tracking error were 100.0% / 0.6±0.5 mm). In the kV-VMAT scan, MV-scatter degraded image quality, particularly for lateral projections passing through the thickest part of the phantom (kV source angle ranging 70°-110° and 250°-290°), resulting in a reduced detection rate (90.5%). If the lateral projections are excluded, tracking performance was comparable to the kV-only case (detection rate / tracking error were 100.0% / 0.8±0.5 mm). Conclusion: Our phantom study demonstrated a promising Result for real-time motion tracking using a conventional Elekta linear accelerator. MV-scatter suppression is needed to improve tracking accuracy during MV delivery. This research is funded by Motion Management Research Grant from Elekta.« less

Search for the appearance of atmospheric tau neutrinos in Super-Kamiokande

NASA Astrophysics Data System (ADS)

Li, Zepeng; Super-Kamiokande Collaboration

2016-03-01

Super-K is a 50 kiloton Water Cherenkov detector with 22.5 kiloton of fiducial volume located at a depth of 2700 meters water equivalent. The large target mass in the fiducial volume offers an opportunity to search for rare tau neutrino appearance from oscillations of atmospheric neutrinos. Events after reduction are classified by a particle identification, based on a neural network (Multilayer Perceptrons), that is optimized to distinguish tau leptons produced by charged-current tau neutrino interactions from electron and muon neutrino interactions in the detector. Super-K atmospheric neutrino data are fit with an unbinned maximum likelihood method to search for tau neutrino appearance. The talk presented results with data taken between 1996 and 2014, comprising 4582 days of live time.

Integrated fiducial sample mount and software for correlated microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timothy R McJunkin; Jill R. Scott; Tammy L. Trowbridge

2014-02-01

A novel design sample mount with integrated fiducials and software for assisting operators in easily and efficiently locating points of interest established in previous analytical sessions is described. The sample holder and software were evaluated with experiments to demonstrate the utility and ease of finding the same points of interest in two different microscopy instruments. Also, numerical analysis of expected errors in determining the same position with errors unbiased by a human operator was performed. Based on the results, issues related to acquiring reproducibility and best practices for using the sample mount and software were identified. Overall, the sample mountmore » methodology allows data to be efficiently and easily collected on different instruments for the same sample location.« less

Design and preliminary accuracy studies of an MRI-guided transrectal prostate intervention system.

PubMed

Krieger, Axel; Csoma, Csaba; Iordachital, Iulian I; Guion, Peter; Singh, Anurag K; Fichtinger, Gabor; Whitcomb, Louis L

2007-01-01

This paper reports a novel system for magnetic resonance imaging (MRI) guided transrectal prostate interventions, such as needle biopsy, fiducial marker placement, and therapy delivery. The system utilizes a hybrid tracking method, comprised of passive fiducial tracking for initial registration and subsequent incremental motion measurement along the degrees of freedom using fiber-optical encoders and mechanical scales. Targeting accuracy of the system is evaluated in prostate phantom experiments. Achieved targeting accuracy and procedure times were found to compare favorably with existing systems using passive and active tracking methods. Moreover, the portable design of the system using only standard MRI image sequences and minimal custom scanner interfacing allows the system to be easily used on different MRI scanners.

Development and validation of a dual sensing scheme to improve accuracy of bradycardia and pause detection in an insertable cardiac monitor.

PubMed

Passman, Rod S; Rogers, John D; Sarkar, Shantanu; Reiland, Jerry; Reisfeld, Erin; Koehler, Jodi; Mittal, Suneet

2017-07-01

Undersensing of premature ventricular beats and low-amplitude R waves are primary causes for inappropriate bradycardia and pause detections in insertable cardiac monitors (ICMs). The purpose of this study was to develop and validate an enhanced algorithm to reduce inappropriately detected bradycardia and pause episodes. Independent data sets to develop and validate the enhanced algorithm were derived from a database of ICM-detected bradycardia and pause episodes in de-identified patients monitored for unexplained syncope. The original algorithm uses an auto-adjusting sensitivity threshold for R-wave sensing to detect tachycardia and avoid T-wave oversensing. In the enhanced algorithm, a second sensing threshold is used with a long blanking and fixed lower sensitivity threshold, looking for evidence of undersensed signals. Data reported includes percent change in appropriate and inappropriate bradycardia and pause detections as well as changes in episode detection sensitivity and positive predictive value with the enhanced algorithm. The validation data set, from 663 consecutive patients, consisted of 4904 (161 patients) bradycardia and 2582 (133 patients) pause episodes, of which 2976 (61%) and 996 (39%) were appropriately detected bradycardia and pause episodes. The enhanced algorithm reduced inappropriate bradycardia and pause episodes by 95% and 47%, respectively, with 1.7% and 0.6% reduction in appropriate episodes, respectively. The average episode positive predictive value improved by 62% (P < .001) for bradycardia detection and by 26% (P < .001) for pause detection, with an average relative sensitivity of 95% (P < .001) and 99% (P = .5), respectively. The enhanced dual sense algorithm for bradycardia and pause detection in ICMs substantially reduced inappropriate episode detection with a minimal reduction in true episode detection. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Adapting detection sensitivity based on evidence of irregular sinus arrhythmia to improve atrial fibrillation detection in insertable cardiac monitors.

PubMed

Pürerfellner, Helmut; Sanders, Prashanthan; Sarkar, Shantanu; Reisfeld, Erin; Reiland, Jerry; Koehler, Jodi; Pokushalov, Evgeny; Urban, Luboš; Dekker, Lukas R C

2017-10-03

Intermittent change in p-wave discernibility during periods of ectopy and sinus arrhythmia is a cause of inappropriate atrial fibrillation (AF) detection in insertable cardiac monitors (ICM). To address this, we developed and validated an enhanced AF detection algorithm. Atrial fibrillation detection in Reveal LINQ ICM uses patterns of incoherence in RR intervals and absence of P-wave evidence over a 2-min period. The enhanced algorithm includes P-wave evidence during RR irregularity as evidence of sinus arrhythmia or ectopy to adaptively optimize sensitivity for AF detection. The algorithm was developed and validated using Holter data from the XPECT and LINQ Usability studies which collected surface electrocardiogram (ECG) and continuous ICM ECG over a 24-48 h period. The algorithm detections were compared with Holter annotations, performed by multiple reviewers, to compute episode and duration detection performance. The validation dataset comprised of 3187 h of valid Holter and LINQ recordings from 138 patients, with true AF in 37 patients yielding 108 true AF episodes ≥2-min and 449 h of AF. The enhanced algorithm reduced inappropriately detected episodes by 49% and duration by 66% with <1% loss in true episodes or duration. The algorithm correctly identified 98.9% of total AF duration and 99.8% of total sinus or non-AF rhythm duration. The algorithm detected 97.2% (99.7% per-patient average) of all AF episodes ≥2-min, and 84.9% (95.3% per-patient average) of detected episodes involved AF. An enhancement that adapts sensitivity for AF detection reduced inappropriately detected episodes and duration with minimal reduction in sensitivity. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Cardiology

Automated batch fiducial-less tilt-series alignment in Appion using Protomo.

PubMed

Noble, Alex J; Stagg, Scott M

2015-11-01

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy. Copyright © 2015 Elsevier Inc. All rights reserved.

First Results of the LUX Dark Matter Experiment

DOE PAGES

Carmona-Benitez, M. C.; Akerib, D. S.; Araújo, H. M.; ...

2016-05-31

LUX (Large Underground Xenon) is a dark matter direct detection experiment deployed at the 4850' level of the Sanford Underground Research Facility (SURF) in Lead, SD, operating a 370 kg dual-phase xenon TPC. Results of the first WIMP search run were presented in late 2013, for the analysis of 85.3 live-days with a fiducial volume of 118 kg, taken during the period of April to August 2013. The experiment exhibited a sensitivity to spin-independent WIMP-nucleon elastic scattering with a minimum upper limit on the cross section of 7.6×10 -46 cm 2 at a WIMP mass of 33 GeV/c 2, thusmore » becoming the world's leading WIMP search result, in conflict with several previous claimed hints of discovery.« less

First Results of the LUX Dark Matter Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carmona-Benitez, M. C.; Akerib, D. S.; Araújo, H. M.

LUX (Large Underground Xenon) is a dark matter direct detection experiment deployed at the 4850' level of the Sanford Underground Research Facility (SURF) in Lead, SD, operating a 370 kg dual-phase xenon TPC. Results of the first WIMP search run were presented in late 2013, for the analysis of 85.3 live-days with a fiducial volume of 118 kg, taken during the period of April to August 2013. The experiment exhibited a sensitivity to spin-independent WIMP-nucleon elastic scattering with a minimum upper limit on the cross section of 7.6×10 -46 cm 2 at a WIMP mass of 33 GeV/c 2, thusmore » becoming the world's leading WIMP search result, in conflict with several previous claimed hints of discovery.« less

Limits on spin-dependent WIMP-nucleon cross sections from the XENON10 experiment.

PubMed

Angle, J; Aprile, E; Arneodo, F; Baudis, L; Bernstein, A; Bolozdynya, A; Coelho, L C C; Dahl, C E; DeViveiros, L; Ferella, A D; Fernandes, L M P; Fiorucci, S; Gaitskell, R J; Giboni, K L; Gomez, R; Hasty, R; Kastens, L; Kwong, J; Lopes, J A M; Madden, N; Manalaysay, A; Manzur, A; McKinsey, D N; Monzani, M E; Ni, K; Oberlack, U; Orboeck, J; Plante, G; Santorelli, R; dos Santos, J M F; Shagin, P; Shutt, T; Sorensen, P; Schulte, S; Winant, C; Yamashita, M

2008-08-29

XENON10 is an experiment to directly detect weakly interacting massive particles (WIMPs), which may comprise the bulk of the nonbaryonic dark matter in our Universe. We report new results for spin-dependent WIMP-nucleon interactions with 129Xe and 131Xe from 58.6 live days of operation at the Laboratori Nazionali del Gran Sasso. Based on the nonobservation of a WIMP signal in 5.4 kg of fiducial liquid xenon mass, we exclude previously unexplored regions in the theoretically allowed parameter space for neutralinos. We also exclude a heavy Majorana neutrino with a mass in the range of approximately 10 GeV/c2-2 TeV/c2 as a dark matter candidate under standard assumptions for its density and distribution in the galactic halo.

Stride search: A general algorithm for storm detection in high resolution climate data

DOE PAGES

Bosler, Peter Andrew; Roesler, Erika Louise; Taylor, Mark A.; ...

2015-09-08

This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared. The commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. Stride Search is designed to work at all latitudes, while grid point searches may fail in polar regions. Results from the two algorithms are compared for the application of tropicalmore » cyclone detection, and shown to produce similar results for the same set of storm identification criteria. The time required for both algorithms to search the same data set is compared. Furthermore, Stride Search's ability to search extreme latitudes is demonstrated for the case of polar low detection.« less

A scale-invariant keypoint detector in log-polar space

NASA Astrophysics Data System (ADS)

Tao, Tao; Zhang, Yun

2017-02-01

The scale-invariant feature transform (SIFT) algorithm is devised to detect keypoints via the difference of Gaussian (DoG) images. However, the DoG data lacks the high-frequency information, which can lead to a performance drop of the algorithm. To address this issue, this paper proposes a novel log-polar feature detector (LPFD) to detect scale-invariant blubs (keypoints) in log-polar space, which, in contrast, can retain all the image information. The algorithm consists of three components, viz. keypoint detection, descriptor extraction and descriptor matching. Besides, the algorithm is evaluated in detecting keypoints from the INRIA dataset by comparing with the SIFT algorithm and one of its fast versions, the speed up robust features (SURF) algorithm in terms of three performance measures, viz. correspondences, repeatability, correct matches and matching score.

CONEDEP: COnvolutional Neural network based Earthquake DEtection and Phase Picking

NASA Astrophysics Data System (ADS)

Zhou, Y.; Huang, Y.; Yue, H.; Zhou, S.; An, S.; Yun, N.

2017-12-01

We developed an automatic local earthquake detection and phase picking algorithm based on Fully Convolutional Neural network (FCN). The FCN algorithm detects and segments certain features (phases) in 3 component seismograms to realize efficient picking. We use STA/LTA algorithm and template matching algorithm to construct the training set from seismograms recorded 1 month before and after the Wenchuan earthquake. Precise P and S phases are identified and labeled to construct the training set. Noise data are produced by combining back-ground noise and artificial synthetic noise to form the equivalent scale of noise set as the signal set. Training is performed on GPUs to achieve efficient convergence. Our algorithm has significantly improved performance in terms of the detection rate and precision in comparison with STA/LTA and template matching algorithms.

Improvement and implementation for Canny edge detection algorithm

NASA Astrophysics Data System (ADS)

Yang, Tao; Qiu, Yue-hong

2015-07-01

Edge detection is necessary for image segmentation and pattern recognition. In this paper, an improved Canny edge detection approach is proposed due to the defect of traditional algorithm. A modified bilateral filter with a compensation function based on pixel intensity similarity judgment was used to smooth image instead of Gaussian filter, which could preserve edge feature and remove noise effectively. In order to solve the problems of sensitivity to the noise in gradient calculating, the algorithm used 4 directions gradient templates. Finally, Otsu algorithm adaptively obtain the dual-threshold. All of the algorithm simulated with OpenCV 2.4.0 library in the environments of vs2010, and through the experimental analysis, the improved algorithm has been proved to detect edge details more effectively and with more adaptability.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Automatic target detection using binary template matching

NASA Astrophysics Data System (ADS)

Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook

2005-03-01

This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

Frequency hopping signal detection based on wavelet decomposition and Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Zheng, Yang; Chen, Xihao; Zhu, Rui

2017-07-01

Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert-Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert-Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

Robust automatic line scratch detection in films.

PubMed

Newson, Alasdair; Almansa, Andrés; Gousseau, Yann; Pérez, Patrick

2014-03-01

Line scratch detection in old films is a particularly challenging problem due to the variable spatiotemporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This step's robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture, and slanted or partial scratches. Comparisons show significant advantages over previous work.

Image based book cover recognition and retrieval

NASA Astrophysics Data System (ADS)

Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine

2017-11-01

In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

Hazardous gas detection for FTIR-based hyperspectral imaging system using DNN and CNN

NASA Astrophysics Data System (ADS)

Kim, Yong Chan; Yu, Hyeong-Geun; Lee, Jae-Hoon; Park, Dong-Jo; Nam, Hyun-Woo

2017-10-01

Recently, a hyperspectral imaging system (HIS) with a Fourier Transform InfraRed (FTIR) spectrometer has been widely used due to its strengths in detecting gaseous fumes. Even though numerous algorithms for detecting gaseous fumes have already been studied, it is still difficult to detect target gases properly because of atmospheric interference substances and unclear characteristics of low concentration gases. In this paper, we propose detection algorithms for classifying hazardous gases using a deep neural network (DNN) and a convolutional neural network (CNN). In both the DNN and CNN, spectral signal preprocessing, e.g., offset, noise, and baseline removal, are carried out. In the DNN algorithm, the preprocessed spectral signals are used as feature maps of the DNN with five layers, and it is trained by a stochastic gradient descent (SGD) algorithm (50 batch size) and dropout regularization (0.7 ratio). In the CNN algorithm, preprocessed spectral signals are trained with 1 × 3 convolution layers and 1 × 2 max-pooling layers. As a result, the proposed algorithms improve the classification accuracy rate by 1.5% over the existing support vector machine (SVM) algorithm for detecting and classifying hazardous gases.

A Motion Detection Algorithm Using Local Phase Information

PubMed Central

Lazar, Aurel A.; Ukani, Nikul H.; Zhou, Yiyin

2016-01-01

Previous research demonstrated that global phase alone can be used to faithfully represent visual scenes. Here we provide a reconstruction algorithm by using only local phase information. We also demonstrate that local phase alone can be effectively used to detect local motion. The local phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector. The local phase-based motion detection algorithm introduced here consists of two building blocks. The first building block measures/evaluates the temporal change of the local phase. The temporal derivative of the local phase is shown to exhibit the structure of a second order Volterra kernel with two normalized inputs. We provide an efficient, FFT-based algorithm for implementing the change of the local phase. The second processing building block implements the detector; it compares the maximum of the Radon transform of the local phase derivative with a chosen threshold. We demonstrate examples of applying the local phase-based motion detection algorithm on several video sequences. We also show how the locally detected motion can be used for segmenting moving objects in video scenes and compare our local phase-based algorithm to segmentation achieved with a widely used optic flow algorithm. PMID:26880882

Detection of dechallenge in spontaneous reporting systems: a comparison of Bayes methods.

PubMed

Banu, A Bazila; Alias Balamurugan, S Appavu; Thirumalaikolundusubramanian, Ponniah

2014-01-01

Dechallenge is a response observed for the reduction or disappearance of adverse drug reactions (ADR) on withdrawal of a drug from a patient. Currently available algorithms to detect dechallenge have limitations. Hence, there is a need to compare available new methods. To detect dechallenge in Spontaneous Reporting Systems, data-mining algorithms like Naive Bayes and Improved Naive Bayes were applied for comparing the performance of the algorithms in terms of accuracy and error. Analyzing the factors of dechallenge like outcome and disease category will help medical practitioners and pharmaceutical industries to determine the reasons for dechallenge in order to take essential steps toward drug safety. Adverse drug reactions of the year 2011 and 2012 were downloaded from the United States Food and Drug Administration's database. The outcome of classification algorithms showed that Improved Naive Bayes algorithm outperformed Naive Bayes with accuracy of 90.11% and error of 9.8% in detecting the dechallenge. Detecting dechallenge for unknown samples are essential for proper prescription. To overcome the issues exposed by Naive Bayes algorithm, Improved Naive Bayes algorithm can be used to detect dechallenge in terms of higher accuracy and minimal error.

Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

NASA Astrophysics Data System (ADS)

Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

2017-05-01

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

Research on improved edge extraction algorithm of rectangular piece

NASA Astrophysics Data System (ADS)

He, Yi-Bin; Zeng, Ya-Jun; Chen, Han-Xin; Xiao, San-Xia; Wang, Yan-Wei; Huang, Si-Yu

Traditional edge detection operators such as Prewitt operator, LOG operator and Canny operator, etc. cannot meet the requirements of the modern industrial measurement. This paper proposes a kind of image edge detection algorithm based on improved morphological gradient. It can be detect the image using structural elements, which deals with the characteristic information of the image directly. Choosing different shapes and sizes of structural elements to use together, the ideal image edge information can be detected. The experimental result shows that the algorithm can well extract image edge with noise, which is clearer, and has more detailed edges compared with the previous edge detection algorithm.

Heterogeneous Vision Data Fusion for Independently Moving Cameras

DTIC Science & Technology

2010-03-01

target detection , tracking , and identification over a large terrain. The goal of the project is to investigate and evaluate the existing image...fusion algorithms, develop new real-time algorithms for Category-II image fusion, and apply these algorithms in moving target detection and tracking . The...moving target detection and classification. 15. SUBJECT TERMS Image Fusion, Target Detection , Moving Cameras, IR Camera, EO Camera 16. SECURITY

An Automated Energy Detection Algorithm Based on Consecutive Mean Excision

DTIC Science & Technology

2018-01-01

present in the RF spectrum. 15. SUBJECT TERMS RF spectrum, detection threshold algorithm, consecutive mean excision, rank order filter , statistical...Median 4 3.1.9 Rank Order Filter (ROF) 4 3.1.10 Crest Factor (CF) 5 3.2 Statistical Summary 6 4. Algorithm 7 5. Conclusion 8 6. References 9...energy detection algorithm based on morphological filter processing with a semi- disk structure. Adelphi (MD): Army Research Laboratory (US); 2018 Jan

A frameless stereotaxic operating microscope for neurosurgery.

PubMed

Friets, E M; Strohbehn, J W; Hatch, J F; Roberts, D W

1989-06-01

A new system, which we call the frameless stereotaxic operating microscope, is discussed. Its purpose is to display CT or other image data in the operating microscope in the correct scale, orientation, and position without the use of a stereotaxic frame. A nonimaging ultrasonic rangefinder allows the position of the operating microscope and the position of the patient to be determined. Discrete fiducial points on the patient's external anatomy are located in both image space and operating room space, linking the image data and the operating room. Physician-selected image information, e.g., tumor contours or guidance to predetermined targets, is projected through the optics of the operating microscope using a miniature cathode ray tube and a beam splitter. Projected images superpose the surgical field, reconstructed from image data to match the focal plane of the operating microscope. The algorithms on which the system is based are described, and the sources and effects of errors are discussed. The system's performance is simulated, providing an estimate of accuracy. Two phantoms are used to measure accuracy experimentally. Clinical results and observations are given.

Improved Limits on Scattering of Weakly Interacting Massive Particles from Reanalysis of 2013 LUX Data.

PubMed

Akerib, D S; Araújo, H M; Bai, X; Bailey, A J; Balajthy, J; Beltrame, P; Bernard, E P; Bernstein, A; Biesiadzinski, T P; Boulton, E M; Bradley, A; Bramante, R; Cahn, S B; Carmona-Benitez, M C; Chan, C; Chapman, J J; Chiller, A A; Chiller, C; Currie, A; Cutter, J E; Davison, T J R; de Viveiros, L; Dobi, A; Dobson, J E Y; Druszkiewicz, E; Edwards, B N; Faham, C H; Fiorucci, S; Gaitskell, R J; Gehman, V M; Ghag, C; Gibson, K R; Gilchriese, M G D; Hall, C R; Hanhardt, M; Haselschwardt, S J; Hertel, S A; Hogan, D P; Horn, M; Huang, D Q; Ignarra, C M; Ihm, M; Jacobsen, R G; Ji, W; Kazkaz, K; Khaitan, D; Knoche, R; Larsen, N A; Lee, C; Lenardo, B G; Lesko, K T; Lindote, A; Lopes, M I; Malling, D C; Manalaysay, A; Mannino, R L; Marzioni, M F; McKinsey, D N; Mei, D-M; Mock, J; Moongweluwan, M; Morad, J A; Murphy, A St J; Nehrkorn, C; Nelson, H N; Neves, F; O'Sullivan, K; Oliver-Mallory, K C; Ott, R A; Palladino, K J; Pangilinan, M; Pease, E K; Phelps, P; Reichhart, L; Rhyne, C; Shaw, S; Shutt, T A; Silva, C; Solovov, V N; Sorensen, P; Stephenson, S; Sumner, T J; Szydagis, M; Taylor, D J; Taylor, W; Tennyson, B P; Terman, P A; Tiedt, D R; To, W H; Tripathi, M; Tvrznikova, L; Uvarov, S; Verbus, J R; Webb, R C; White, J T; Whitis, T J; Witherell, M S; Wolfs, F L H; Yazdani, K; Young, S K; Zhang, C

2016-04-22

We present constraints on weakly interacting massive particles (WIMP)-nucleus scattering from the 2013 data of the Large Underground Xenon dark matter experiment, including 1.4×10^{4}  kg day of search exposure. This new analysis incorporates several advances: single-photon calibration at the scintillation wavelength, improved event-reconstruction algorithms, a revised background model including events originating on the detector walls in an enlarged fiducial volume, and new calibrations from decays of an injected tritium β source and from kinematically constrained nuclear recoils down to 1.1 keV. Sensitivity, especially to low-mass WIMPs, is enhanced compared to our previous results which modeled the signal only above a 3 keV minimum energy. Under standard dark matter halo assumptions and in the mass range above 4  GeV c^{-2}, these new results give the most stringent direct limits on the spin-independent WIMP-nucleon cross section. The 90% C.L. upper limit has a minimum of 0.6 zb at 33  GeV c^{-2} WIMP mass.

Search for continuous gravitational waves from neutron stars in globular cluster NGC 6544

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Bejger, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Creighton, T.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; De, S.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fenyvesi, E.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gehrels, N.; Gemme, G.; Geng, P.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jian, L.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kapadia, S. J.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chi-Woong; Kim, Chunglee; Kim, J.; Kim, K.; Kim, N.; Kim, W.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Laxen, M.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Lewis, J. B.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Nedkova, K.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patel, P.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Perri, L. M.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Saulson, P. R.; Sauter, O. E. S.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T.; Shahriar, M. S.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yu, H.; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; Sigurdsson, S.; LIGO Scientific Collaboration; Virgo Collaboration

2017-04-01

We describe a directed search for continuous gravitational waves in data from the sixth initial LIGO science run. The target was the nearby globular cluster NGC 6544 at a distance of ≈2.7 kpc . The search covered a broad band of frequencies along with first and second frequency derivatives for a fixed sky position. The search coherently integrated data from the two LIGO interferometers over a time span of 9.2 days using the matched-filtering F -statistic. We found no gravitational-wave signals and set 95% confidence upper limits as stringent as 6.0 ×10-25 on intrinsic strain and 8.5 ×10-6 on fiducial ellipticity. These values beat the indirect limits from energy conservation for stars with characteristic spin-down ages older than 300 years and are within the range of theoretical predictions for possible neutron-star ellipticities. An important feature of this search was use of a barycentric resampling algorithm which substantially reduced computational cost; this method is used extensively in searches of Advanced LIGO and Virgo detector data.

Improved limits on scattering of weakly interacting massive particles from reanalysis of 2013 LUX data

DOE PAGES

Akerib, D. S.

2016-04-20

Here, we present constraints on weakly interacting massive particles (WIMP)-nucleus scattering from the 2013 data of the Large Underground Xenon dark matter experiment, including 1.4 × 10 4 kg day of search exposure. This new analysis incorporates several advances: single-photon calibration at the scintillation wavelength, improved event-reconstruction algorithms, a revised background model including events originating on the detector walls in an enlarged fiducial volume, and new calibrations from decays of an injected tritium β source and from kinematically constrained nuclear recoils down to 1.1 keV. Sensitivity, especially to low-mass WIMPs, is enhanced compared to our previous results which modeled themore » signal only above a 3 keV minimum energy. Under standard dark matter halo assumptions and in the mass range above 4 GeV c –2, these new results give the most stringent direct limits on the spin-independent WIMP-nucleon cross section. The 90% C.L. upper limit has a minimum of 0.6 zb at 33 GeV c –2 WIMP mass.« less

Improved Limits on Scattering of Weakly Interacting Massive Particles from Reanalysis of 2013 LUX Data

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Bradley, A.; Bramante, R.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Chapman, J. J.; Chiller, A. A.; Chiller, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; de Viveiros, L.; Dobi, A.; Dobson, J. E. Y.; Druszkiewicz, E.; Edwards, B. N.; Faham, C. H.; Fiorucci, S.; Gaitskell, R. J.; Gehman, V. M.; Ghag, C.; Gibson, K. R.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Ihm, M.; Jacobsen, R. G.; Ji, W.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lee, C.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Malling, D. C.; Manalaysay, A.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O'Sullivan, K.; Oliver-Mallory, K. C.; Ott, R. A.; Palladino, K. J.; Pangilinan, M.; Pease, E. K.; Phelps, P.; Reichhart, L.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Solovov, V. N.; Sorensen, P.; Stephenson, S.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Yazdani, K.; Young, S. K.; Zhang, C.; LUX Collaboration

2016-04-01

We present constraints on weakly interacting massive particles (WIMP)-nucleus scattering from the 2013 data of the Large Underground Xenon dark matter experiment, including 1.4 ×104 kg day of search exposure. This new analysis incorporates several advances: single-photon calibration at the scintillation wavelength, improved event-reconstruction algorithms, a revised background model including events originating on the detector walls in an enlarged fiducial volume, and new calibrations from decays of an injected tritium β source and from kinematically constrained nuclear recoils down to 1.1 keV. Sensitivity, especially to low-mass WIMPs, is enhanced compared to our previous results which modeled the signal only above a 3 keV minimum energy. Under standard dark matter halo assumptions and in the mass range above 4 GeV c-2 , these new results give the most stringent direct limits on the spin-independent WIMP-nucleon cross section. The 90% C.L. upper limit has a minimum of 0.6 zb at 33 GeV c-2 WIMP mass.

3D-2D registration for surgical guidance: effect of projection view angles on registration accuracy

NASA Astrophysics Data System (ADS)

Uneri, A.; Otake, Y.; Wang, A. S.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Siewerdsen, J. H.

2014-01-01

An algorithm for intensity-based 3D-2D registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ˜0°-180° at variable C-arm magnification. Registration accuracy was assessed in terms of 2D projection distance error and 3D target registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ˜10°-20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual registration.

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.

PubMed

Li, Qi; Melton, Kristin; Lingren, Todd; Kirkendall, Eric S; Hall, Eric; Zhai, Haijun; Ni, Yizhao; Kaiser, Megan; Stoutenborough, Laura; Solti, Imre

2014-01-01

Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Texture orientation-based algorithm for detecting infrared maritime targets.

PubMed

Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

2015-05-20

Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

Investigating prior probabilities in a multiple hypothesis test for use in space domain awareness

NASA Astrophysics Data System (ADS)

Hardy, Tyler J.; Cain, Stephen C.

2016-05-01

The goal of this research effort is to improve Space Domain Awareness (SDA) capabilities of current telescope systems through improved detection algorithms. Ground-based optical SDA telescopes are often spatially under-sampled, or aliased. This fact negatively impacts the detection performance of traditionally proposed binary and correlation-based detection algorithms. A Multiple Hypothesis Test (MHT) algorithm has been previously developed to mitigate the effects of spatial aliasing. This is done by testing potential Resident Space Objects (RSOs) against several sub-pixel shifted Point Spread Functions (PSFs). A MHT has been shown to increase detection performance for the same false alarm rate. In this paper, the assumption of a priori probability used in a MHT algorithm is investigated. First, an analysis of the pixel decision space is completed to determine alternate hypothesis prior probabilities. These probabilities are then implemented into a MHT algorithm, and the algorithm is then tested against previous MHT algorithms using simulated RSO data. Results are reported with Receiver Operating Characteristic (ROC) curves and probability of detection, Pd, analysis.

A wavelet transform algorithm for peak detection and application to powder x-ray diffraction data.

PubMed

Gregoire, John M; Dale, Darren; van Dover, R Bruce

2011-01-01

Peak detection is ubiquitous in the analysis of spectral data. While many noise-filtering algorithms and peak identification algorithms have been developed, recent work [P. Du, W. Kibbe, and S. Lin, Bioinformatics 22, 2059 (2006); A. Wee, D. Grayden, Y. Zhu, K. Petkovic-Duran, and D. Smith, Electrophoresis 29, 4215 (2008)] has demonstrated that both of these tasks are efficiently performed through analysis of the wavelet transform of the data. In this paper, we present a wavelet-based peak detection algorithm with user-defined parameters that can be readily applied to the application of any spectral data. Particular attention is given to the algorithm's resolution of overlapping peaks. The algorithm is implemented for the analysis of powder diffraction data, and successful detection of Bragg peaks is demonstrated for both low signal-to-noise data from theta-theta diffraction of nanoparticles and combinatorial x-ray diffraction data from a composition spread thin film. These datasets have different types of background signals which are effectively removed in the wavelet-based method, and the results demonstrate that the algorithm provides a robust method for automated peak detection.

Robust crop and weed segmentation under uncontrolled outdoor illumination.

PubMed

Jeon, Hong Y; Tian, Lei F; Zhu, Heping

2011-01-01

An image processing algorithm for detecting individual weeds was developed and evaluated. Weed detection processes included were normalized excessive green conversion, statistical threshold value estimation, adaptive image segmentation, median filter, morphological feature calculation and Artificial Neural Network (ANN). The developed algorithm was validated for its ability to identify and detect weeds and crop plants under uncontrolled outdoor illuminations. A machine vision implementing field robot captured field images under outdoor illuminations and the image processing algorithm automatically processed them without manual adjustment. The errors of the algorithm, when processing 666 field images, ranged from 2.1 to 2.9%. The ANN correctly detected 72.6% of crop plants from the identified plants, and considered the rest as weeds. However, the ANN identification rates for crop plants were improved up to 95.1% by addressing the error sources in the algorithm. The developed weed detection and image processing algorithm provides a novel method to identify plants against soil background under the uncontrolled outdoor illuminations, and to differentiate weeds from crop plants. Thus, the proposed new machine vision and processing algorithm may be useful for outdoor applications including plant specific direct applications (PSDA).

Superior Rhythm Discrimination With the SmartShock Technology Algorithm　- Results of the Implantable Defibrillator With Enhanced Features and Settings for Reduction of Inaccurate Detection (DEFENSE) Trial.

PubMed

Oginosawa, Yasushi; Kohno, Ritsuko; Honda, Toshihiro; Kikuchi, Kan; Nozoe, Masatsugu; Uchida, Takayuki; Minamiguchi, Hitoshi; Sonoda, Koichiro; Ogawa, Masahiro; Ideguchi, Takeshi; Kizaki, Yoshihisa; Nakamura, Toshihiro; Oba, Kageyuki; Higa, Satoshi; Yoshida, Keiki; Tsunoda, Soichi; Fujino, Yoshihisa; Abe, Haruhiko

2017-08-25

Shocks delivered by implanted anti-tachyarrhythmia devices, even when appropriate, lower the quality of life and survival. The new SmartShock Technology ® (SST) discrimination algorithm was developed to prevent the delivery of inappropriate shock. This prospective, multicenter, observational study compared the rate of inaccurate detection of ventricular tachyarrhythmia using the SST vs. a conventional discrimination algorithm.Methods and Results:Recipients of implantable cardioverter defibrillators (ICD) or cardiac resynchronization therapy defibrillators (CRT-D) equipped with the SST algorithm were enrolled and followed up every 6 months. The tachycardia detection rate was set at ≥150 beats/min with the SST algorithm. The primary endpoint was the time to first inaccurate detection of ventricular tachycardia (VT) with conventional vs. the SST discrimination algorithm, up to 2 years of follow-up. Between March 2012 and September 2013, 185 patients (mean age, 64.0±14.9 years; men, 74%; secondary prevention indication, 49.5%) were enrolled at 14 Japanese medical centers. Inaccurate detection was observed in 32 patients (17.6%) with the conventional, vs. in 19 patients (10.4%) with the SST algorithm. SST significantly lowered the rate of inaccurate detection by dual chamber devices (HR, 0.50; 95% CI: 0.263-0.950; P=0.034). Compared with previous algorithms, the SST discrimination algorithm significantly lowered the rate of inaccurate detection of VT in recipients of dual-chamber ICD or CRT-D.

Data-driven approach of CUSUM algorithm in temporal aberrant event detection using interactive web applications.

PubMed

Li, Ye; Whelan, Michael; Hobbs, Leigh; Fan, Wen Qi; Fung, Cecilia; Wong, Kenny; Marchand-Austin, Alex; Badiani, Tina; Johnson, Ian

2016-06-27

In 2014/2015, Public Health Ontario developed disease-specific, cumulative sum (CUSUM)-based statistical algorithms for detecting aberrant increases in reportable infectious disease incidence in Ontario. The objective of this study was to determine whether the prospective application of these CUSUM algorithms, based on historical patterns, have improved specificity and sensitivity compared to the currently used Early Aberration Reporting System (EARS) algorithm, developed by the US Centers for Disease Control and Prevention. A total of seven algorithms were developed for the following diseases: cyclosporiasis, giardiasis, influenza (one each for type A and type B), mumps, pertussis, invasive pneumococcal disease. Historical data were used as baseline to assess known outbreaks. Regression models were used to model seasonality and CUSUM was applied to the difference between observed and expected counts. An interactive web application was developed allowing program staff to directly interact with data and tune the parameters of CUSUM algorithms using their expertise on the epidemiology of each disease. Using these parameters, a CUSUM detection system was applied prospectively and the results were compared to the outputs generated by EARS. The outcome was the detection of outbreaks, or the start of a known seasonal increase and predicting the peak in activity. The CUSUM algorithms detected provincial outbreaks earlier than the EARS algorithm, identified the start of the influenza season in advance of traditional methods, and had fewer false positive alerts. Additionally, having staff involved in the creation of the algorithms improved their understanding of the algorithms and improved use in practice. Using interactive web-based technology to tune CUSUM improved the sensitivity and specificity of detection algorithms.

Text Extraction from Scene Images by Character Appearance and Structure Modeling

PubMed Central

Yi, Chucai; Tian, Yingli

2012-01-01

In this paper, we propose a novel algorithm to detect text information from natural scene images. Scene text classification and detection are still open research topics. Our proposed algorithm is able to model both character appearance and structure to generate representative and discriminative text descriptors. The contributions of this paper include three aspects: 1) a new character appearance model by a structure correlation algorithm which extracts discriminative appearance features from detected interest points of character samples; 2) a new text descriptor based on structons and correlatons, which model character structure by structure differences among character samples and structure component co-occurrence; and 3) a new text region localization method by combining color decomposition, character contour refinement, and string line alignment to localize character candidates and refine detected text regions. We perform three groups of experiments to evaluate the effectiveness of our proposed algorithm, including text classification, text detection, and character identification. The evaluation results on benchmark datasets demonstrate that our algorithm achieves the state-of-the-art performance on scene text classification and detection, and significantly outperforms the existing algorithms for character identification. PMID:23316111

Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

PubMed

Ang, Li Minn; Seng, Kah Phooi; Ge, Feng Lu

2017-05-23

This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively.

Research on Abnormal Detection Based on Improved Combination of K - means and SVDD

NASA Astrophysics Data System (ADS)

Hao, Xiaohong; Zhang, Xiaofeng

2018-01-01

In order to improve the efficiency of network intrusion detection and reduce the false alarm rate, this paper proposes an anomaly detection algorithm based on improved K-means and SVDD. The algorithm first uses the improved K-means algorithm to cluster the training samples of each class, so that each class is independent and compact in class; Then, according to the training samples, the SVDD algorithm is used to construct the minimum superspheres. The subordinate relationship of the samples is determined by calculating the distance of the minimum superspheres constructed by SVDD. If the test sample is less than the center of the hypersphere, the test sample belongs to this class, otherwise it does not belong to this class, after several comparisons, the final test of the effective detection of the test sample.In this paper, we use KDD CUP99 data set to simulate the proposed anomaly detection algorithm. The results show that the algorithm has high detection rate and low false alarm rate, which is an effective network security protection method.

Detecting an atomic clock frequency anomaly using an adaptive Kalman filter algorithm

NASA Astrophysics Data System (ADS)

Song, Huijie; Dong, Shaowu; Wu, Wenjun; Jiang, Meng; Wang, Weixiong

2018-06-01

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. The Kalman filter algorithm, as a linear optimal algorithm, has been widely used in real-time detection for abnormal frequency. In order to obtain an optimal state estimation, the observation model and dynamic model of the Kalman filter algorithm should satisfy Gaussian white noise conditions. The detection performance is degraded if anomalies affect the observation model or dynamic model. The idea of the adaptive Kalman filter algorithm, applied to clock frequency anomaly detection, uses the residuals given by the prediction for building ‘an adaptive factor’ the prediction state covariance matrix is real-time corrected by the adaptive factor. The results show that the model error is reduced and the detection performance is improved. The effectiveness of the algorithm is verified by the frequency jump simulation, the frequency drift jump simulation and the measured data of the atomic clock by using the chi-square test.

Reducing false-positive detections by combining two stage-1 computer-aided mass detection algorithms

NASA Astrophysics Data System (ADS)

Bedard, Noah D.; Sampat, Mehul P.; Stokes, Patrick A.; Markey, Mia K.

2006-03-01

In this paper we present a strategy for reducing the number of false-positives in computer-aided mass detection. Our approach is to only mark "consensus" detections from among the suspicious sites identified by different "stage-1" detection algorithms. By "stage-1" we mean that each of the Computer-aided Detection (CADe) algorithms is designed to operate with high sensitivity, allowing for a large number of false positives. In this study, two mass detection methods were used: (1) Heath and Bowyer's algorithm based on the average fraction under the minimum filter (AFUM) and (2) a low-threshold bi-lateral subtraction algorithm. The two methods were applied separately to a set of images from the Digital Database for Screening Mammography (DDSM) to obtain paired sets of mass candidates. The consensus mass candidates for each image were identified by a logical "and" operation of the two CADe algorithms so as to eliminate regions of suspicion that were not independently identified by both techniques. It was shown that by combining the evidence from the AFUM filter method with that obtained from bi-lateral subtraction, the same sensitivity could be reached with fewer false-positives per image relative to using the AFUM filter alone.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

PubMed Central

Xu, Songhua; Krauthammer, Michael

2010-01-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper’s key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manually labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. In this paper, we demonstrate that a projection histogram-based text detection approach is well suited for text detection in biomedical images, with a performance of F score of .60. The approach performs better than comparable approaches for text detection. Further, we show that the iterative application of the algorithm is boosting overall detection performance. A C++ implementation of our algorithm is freely available through email request for academic use. PMID:20887803

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

PubMed

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Measurement of the inclusive and fiducial t\\bar{t} production cross-sections in the lepton+jets channel in pp collisions at √{s} = 8 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Bergsten, L. J.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Betti, A.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blumenschein, U.; Blunier, Dr.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozson, A. J.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casha, A. F.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioară, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Dickinson, J.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Dodsworth, D.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubinin, F.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dulsen, C.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duperrin, A.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Ennis, J. S.; Epland, M. B.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; Gonski, J. L.; González de la Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gurbuz, S.; Gustavino, G.; Gutelman, B. J.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Handl, D. M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hlaluku, D. R.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Holzbock, M.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hostiuc, A.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Huhtinen, M.; Hunter, R. F. H.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Hyneman, R.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Iltzsche, F.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kellermann, E.; Kempster, J. J.; Kendrick, J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kitali, V.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klingl, T.; Klioutchnikova, T.; Klitzner, F. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Komar, A. A.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Konya, B.; Kopeliansky, R.; Koperny, S.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kourlitis, E.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kremer, J. A.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kupfer, T.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; Navarro, J. L. La Rosa; La Rotonda, L.; La Ruffa, F.; Lacasta, C.; Lacava, F.; Lacey, J.; Lack, D. P. J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Langenberg, R. J.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Lau, T. S.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, G. R.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Les, R.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Li, B.; Li, C.-Q.; Li, H.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, C. Y.; Lin, K.; Lin, S. C.; Lin, T. H.; Linck, R. A.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J. K. K.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo, C. Y.; Sterzo, F. Lo; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loesle, A.; Loew, K. M.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lutz, M. S.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyu, F.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Mader, W. F.; Madsen, A.; Madysa, N.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A. S.; Magerl, V.; Maiani, C.; Maidantchik, C.; Maier, T.; Maio, A.; Majersky, O.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mankinen, K. H.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchese, L.; Marchiori, G.; Marcisovsky, M.; Marin Tobon, C. A.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Mason, L. H.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McNamara, P. C.; McNicol, C. J.; McPherson, R. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Mellenthin, J. D.; Melo, M.; Meloni, F.; Melzer, A.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Merlassino, C.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Millar, D. A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mirto, A.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Ng, Y. S.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforou, N.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishu, N.; Nisius, R.; Nitsche, I.; Nitta, T.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olsson, M. J. R.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oppen, H.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; St. Panagiotopoulou, E.; Panagoulias, I.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasner, J. M.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearson, B.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Pokharel, I.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Portillo Quintero, D. M.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potti, H.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rangel-Smith, C.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, D.; Roy, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Rüttinger, E. M.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schenck, F.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Šfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherman, A. D.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, L.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Sottocornola, S.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, T. J.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeda, K.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Thais, S. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tian, Y.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakamiya, K.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, A.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Woods, N. L.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Xu, W.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2018-06-01

The inclusive and fiducial t\\bar{t} production cross-sections are measured in the lepton+jets channel using 20.2 fb^{-1} of proton-proton collision data at a centre-of-mass energy of 8 TeV recorded with the ATLAS detector at the LHC. Major systematic uncertainties due to the modelling of the jet energy scale and b-tagging efficiency are constrained by separating selected events into three disjoint regions. In order to reduce systematic uncertainties in the most important background, the W {+ jets} process is modelled using Z+ jets events in a data-driven approach. The inclusive t\\bar{t} cross-section is measured with a precision of 5.7% to be σ _{ {inc}}(t\\bar{t}) = 248.3 ± 0.7 ({stat.}) ± 13.4 ({syst.}) ± 4.7 ({lumi.}) {pb}, assuming a top-quark mass of 172.5 GeV. The result is in agreement with the Standard Model prediction. The cross-section is also measured in a phase space close to that of the selected data. The fiducial cross-section is σ _{ {fid}}(t\\bar{t}) = 48.8 ± 0.1 ({stat.}) ± 2.0 ({syst.}) ± 0.9 ({lumi.}) {pb} with a precision of 4.5%.

Influence of the number of elongated fiducial markers on the localization accuracy of the prostate

NASA Astrophysics Data System (ADS)

de Boer, Johan; de Bois, Josien; van Herk, Marcel; Sonke, Jan-Jakob

2012-10-01

Implanting fiducial markers for localization purposes has become an accepted practice in radiotherapy for prostate cancer. While many correction strategies correct for translations only, advanced correction protocols also require knowledge of the rotation of the prostate. For this purpose, typically, three or more markers are implanted. Elongated fiducial markers provide more information about their orientation than traditional round or cylindrical markers. Potentially, fewer markers are required. In this study, we evaluate the effect of the number of elongated markers on the localization accuracy of the prostate. To quantify the localization error, we developed a model that estimates, at arbitrary locations in the prostate, the registration error caused by translational and rotational uncertainties of the marker registration. Every combination of one, two and three markers was analysed for a group of 24 patients. The average registration errors at the prostate surface were 0.3-0.8 mm and 0.4-1 mm for registrations on, respectively, three markers and two markers located on different sides of the prostate. Substantial registration errors (2.0-2.2 mm) occurred at the prostate surface contralateral to the markers when two markers were implanted on the same side of the prostate or only one marker was used. In conclusion, there is no benefit in using three elongated markers: two markers accurately localize the prostate if they are implanted at some distance from each other.

Fiducial, total and differential cross-section measurements of t-channel single top-quark production in pp collisions at 8 TeV using data collected by the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Navarro, L. Barranco; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bylund, O. Bessidskaia; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; De Mendizabal, J. Bilbao; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Sola, J. D. Bossio; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Madden, W. D. Breaden; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Urbán, S. Cabrera; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Lopez, S. Calvente; Calvet, D.; Calvet, S.; Calvet, T. P.; Toro, R. Camacho; Camarda, S.; Camarri, P.; Cameron, D.; Armadans, R. Caminal; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Bret, M. Cano; Cantero, J.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Alberich, L. Cerda; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Barajas, C. A. Chavez; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Moursli, R. Cherkaoui El; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Muiño, P. Conde; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Ortuzar, M. Crispin; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'Onofrio, M.; De Sousa, M. J. Da Cunha Sargedas; Via, C. Da; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Regie, J. B. De Vivie; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Cornell, S. Díez; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Duncan, A. K.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; Kacimi, M. El; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Giannelli, M. Faucci; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Martinez, P. Fernandez; Perez, S. Fernandez; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; de Lima, D. E. Ferreira; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Castillo, L. R. Flores; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Torregrosa, E. Fullana; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, J.; Gao, Y.; Gao, Y. S.; Walls, F. M. Garay; García, C.; Navarro, J. E. García; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Bravo, A. Gascon; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Costa, J. Goncalves Pinto Firmino Da; Gonella, G.; Gonella, L.; Gongadze, A.; de la Hoz, S. González; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Grafström, P.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Ortiz, N. G. Gutierrez; Gutschow, C.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Hellman, S.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Correia, A. M. Henriques; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Jiménez, Y. Hernández; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hladik, O.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Ponce, J. M. Iturbe; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, B.; Jackson, P.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jeng, G.-Y.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Pena, J. Jimenez; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Rozas, A. Juste; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneti, S.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kapliy, A.; Kar, D.; Karakostas, K.; Karamaoun, A.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; King, M.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klapdor-kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolanoski, H.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Kravchenko, A.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunigo, T.; Kupco, A.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; Rosa, A. La; Navarro, J. L. La Rosa; Rotonda, L. La; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Manghi, F. Lasagni; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Dortz, O. Le; Guirriec, E. Le; Quilleuc, E. P. Le; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Miotto, G. Lehmann; Lei, X.; Leight, W. A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Leontsinis, S.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Leyton, M.; Li, B.; Li, C.; Li, H.; Li, L.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, H.; Liu, H.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Merino, J. Llorente; Lloyd, S. L.; Sterzo, F. Lo; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A. Lopez; Mateos, D. Lopez; Paredes, B. Lopez; Paz, I. Lopez; Solis, A. Lopez; Lorenz, J.; Martinez, N. Lorenzo; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Miguens, J. Machado; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, L.; Mandić, I.; Maneira, J.; Filho, L. Manhaes de Andrade; Ramos, J. Manjarres; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti-Garcia, S.; Martin, B.; Martin, T. A.; Martin, V. J.; Latour, B. Martin dit; Martinez, M.; Outschoorn, V. I. Martinez; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Fadden, N. C. Mc; Goldrick, G. Mc; Kee, S. P. Mc; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McPherson, R. A.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melini, D.; Garcia, B. R. Mellado; Melo, M.; Meloni, F.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Theenhausen, H. Meyer Zu; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Berlingen, J. Montejo; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Llácer, M. Moreno; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Mortensen, S. S.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Mueller, T.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Sanchez, F. J. Munoz; Quijada, J. A. Murillo; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Garcia, R. F. Naranjo; Narayan, R.; Villar, D. I. Narrias; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Manh, T. Nguyen; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'grady, F.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Seabra, L. F. Oleiro; Pino, S. A. Olivares; Damazio, D. Oliveira; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Garzon, G. Otero y.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pages, A. Pacheco; Rodriguez, L. Pacheco; Aranda, C. Padilla; Pagáčová, M.; Griso, S. Pagan; Paganini, M.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Pandini, C. E.; Vazquez, J. G. Panduro; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Hernandez, D. Paredes; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Lopez, S. Pedraza; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Codina, E. Perez; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Astigarraga, M. E. Pozo; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Perez, A. Rodriguez; Rodriguez, D. Rodriguez; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Saez, S. M. Romano; Adam, E. Romero; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Tehrani, F. Safai; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Loyola, J. E. Salazar; Salek, D.; De Bruin, P. H. Sales; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sánchez, J.; Martinez, V. Sanchez; Pineda, A. Sanchez; Sandaker, H.; Sandbach, R. L.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Castillo, I. Santoyo; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shirabe, S.; Shiyakova, M.; Shmeleva, A.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Haddad, E. Sideras; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Sanchez, C. A. Solans; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Kate, H. Ten; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Santurio, E. Valdes; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Ferrer, J. A. Valls; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yeletskikh, I.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Nedden, M. zur; Zwalinski, L.

2017-08-01

Detailed measurements of t-channel single top-quark production are presented. They use 20.2 fb^{-1} of data collected by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of 8 TeV at the LHC. Total, fiducial and differential cross-sections are measured for both top-quark and top-antiquark production. The fiducial cross-section is measured with a precision of 5.8% (top quark) and 7.8% (top antiquark), respectively. The total cross-sections are measured to be σ _{ {tot}} (tq) = 56.7^{+4.3}_{-3.8}pb for top-quark production and σ _{ {tot}} (\\bar{t} q) = 32.9^{+3.0}_{-2.7}pb for top-antiquark production, in agreement with the Standard Model prediction. In addition, the ratio of top-quark to top-antiquark production cross-sections is determined to be R_t=1.72 ± 0.09. The differential cross-sections as a function of the transverse momentum and rapidity of both the top quark and the top antiquark are measured at both the parton and particle levels. The transverse momentum and rapidity differential cross-sections of the accompanying jet from the t-channel scattering are measured at particle level. All measurements are compared to various Monte Carlo predictions as well as to fixed-order QCD calculations where available.

Measurement of inclusive and differential cross sections in the H → ZZ * → 4ℓ decay channel in pp collisions at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

Inclusive and differential fiducial cross sections of Higgs boson production in proton-proton collisions are measured in the H → ZZ* → 4ℓ decay channel. The proton-proton collision data were produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb –1. The inclusive fiducial cross section in the H → ZZ* → 4ℓ decay channel is measured to be 3.62±0.50(stat) –0.20 +0.25 (sys) fb, in agreement with the Standard Model prediction of 2.91 ± 0.13 fb. The cross section ismore » also extrapolated to the total phase space including all Standard Model Higgs boson decays. Several differential fiducial cross sections are measured for observables sensitive to the Higgs boson production and decay, including kinematic distributions of jets produced in association with the Higgs boson. Good agreement is found between data and Standard Model predictions. The results are used to put constraints on anomalous Higgs boson interactions with Standard Model particles, using the pseudo-observable extension to the kappa-framework.« less

Next-to-leading-order electroweak corrections to the production of three charged leptons plus missing energy at the LHC

NASA Astrophysics Data System (ADS)

Biedermann, Benedikt; Denner, Ansgar; Hofer, Lars

2017-10-01

The production of a neutral and a charged vector boson with subsequent decays into three charged leptons and a neutrino is a very important process for precision tests of the Standard Model of elementary particles and in searches for anomalous triple-gauge-boson couplings. In this article, the first computation of next-to-leading-order electroweak corrections to the production of the four-lepton final states μ + μ -e+ ν e, {μ}+{μ}-{e}-{\\overline{ν}}e , μ + μ - μ + ν μ , and {μ}+{μ}-{μ}-{\\overline{ν}}_{μ } at the Large Hadron Collider is presented. We use the complete matrix elements at leading and next-to-leading order, including all off-shell effects of intermediate massive vector bosons and virtual photons. The relative electroweak corrections to the fiducial cross sections from quark-induced partonic processes vary between -3% and -6%, depending significantly on the event selection. At the level of differential distributions, we observe large negative corrections of up to -30% in the high-energy tails of distributions originating from electroweak Sudakov logarithms. Photon-induced contributions at next-to-leading order raise the leading-order fiducial cross section by +2%. Interference effects in final states with equal-flavour leptons are at the permille level for the fiducial cross section, but can lead to sizeable effects in off-shell sensitive phase-space regions.

Fiducial, total and differential cross-section measurements of t-channel single top-quark production in pp collisions at 8 TeV using data collected by the ATLAS detector.

PubMed

Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adachi, S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Verzini, M J Alconada; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alshehri, A A; Alstaty, M; Gonzalez, B Alvarez; Piqueras, D Álvarez; Alviggi, M G; Amadio, B T; Coutinho, Y Amaral; Amelung, C; Amidei, D; Santos, S P Amor Dos; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antel, C; Antonelli, M; Antonov, A; Antrim, D J; Anulli, F; Aoki, M; Bella, L Aperio; Arabidze, G; Arai, Y; Araque, J P; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Armitage, L J; Arnaez, O; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Artz, S; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Augsten, K; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Baca, M J; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Bagiacchi, P; Bagnaia, P; Bai, Y; Baines, J T; Bajic, M; Baker, O K; Baldin, E M; Balek, P; Balestri, T; Balli, F; Balunas, W K; Banas, E; Banerjee, Sw; Bannoura, A A E; Barak, L; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisits, M-S; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska-Blenessy, Z; Baroncelli, A; Barone, G; Barr, A J; Navarro, L Barranco; Barreiro, F; da Costa, J Barreiro Guimarães; Bartoldus, R; Barton, A E; Bartos, P; Basalaev, A; Bassalat, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Bechtle, P; Beck, H P; Becker, K; Becker, M; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bedognetti, M; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Bell, A S; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Belyaev, N L; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Noccioli, E Benhar; Benitez, J; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Kuutmann, E Bergeaas; Berger, N; Beringer, J; Berlendis, S; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertram, I A; Bertsche, C; Bertsche, D; Besjes, G J; Bylund, O Bessidskaia; Bessner, M; Besson, N; Betancourt, C; Bethani, A; Bethke, S; Bevan, A J; Bianchi, R M; Bianco, M; Biebel, O; Biedermann, D; Bielski, R; Biesuz, N V; Biglietti, M; De Mendizabal, J Bilbao; Billoud, T R V; Bilokon, H; Bindi, M; Bingul, A; Bini, C; Biondi, S; Bisanz, T; Bjergaard, D M; Black, C W; Black, J E; Black, K M; Blackburn, D; Blair, R E; Blazek, T; Bloch, I; Blocker, C; Blue, A; Blum, W; Blumenschein, U; Blunier, S; Bobbink, G J; Bobrovnikov, V S; Bocchetta, S S; Bocci, A; Bock, C; Boehler, M; Boerner, D; Bogaerts, J A; Bogavac, D; Bogdanchikov, A G; Bohm, C; Boisvert, V; Bokan, P; Bold, T; Boldyrev, A S; Bomben, M; Bona, M; Boonekamp, M; Borisov, A; Borissov, G; Bortfeldt, J; Bortoletto, D; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Sola, J D Bossio; Boudreau, J; Bouffard, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Boutle, S K; Boveia, A; Boyd, J; Boyko, I R; Bracinik, J; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Madden, W D Breaden; Brendlinger, K; Brennan, A J; Brenner, L; Brenner, R; Bressler, S; Bristow, T M; Britton, D; Britzger, D; Brochu, F M; Brock, I; Brock, R; Brooijmans, G; Brooks, T; Brooks, W K; Brosamer, J; Brost, E; Broughton, J H; de Renstrom, P A Bruckman; Bruncko, D; Bruneliere, R; Bruni, A; Bruni, G; Bruni, L S; Brunt, B H; Bruschi, M; Bruscino, N; Bryant, P; Bryngemark, L; Buanes, T; Buat, Q; Buchholz, P; Buckley, A G; Budagov, I A; Buehrer, F; Bugge, M K; Bulekov, O; Bullock, D; Burckhart, H; Burdin, S; Burgard, C D; Burger, A M; Burghgrave, B; Burka, K; Burke, S; Burmeister, I; Burr, J T P; Busato, E; Büscher, D; Büscher, V; Bussey, P; Butler, J M; Buttar, C M; Butterworth, J M; Butti, P; Buttinger, W; Buzatu, A; Buzykaev, A R; Urbán, S Cabrera; Caforio, D; Cairo, V M; Cakir, O; Calace, N; Calafiura, P; Calandri, A; Calderini, G; Calfayan, P; Callea, G; Caloba, L P; Lopez, S Calvente; Calvet, D; Calvet, S; Calvet, T P; Toro, R Camacho; Camarda, S; Camarri, P; Cameron, D; Armadans, R Caminal; Camincher, C; Campana, S; Campanelli, M; Camplani, A; Campoverde, A; Canale, V; Canepa, A; Bret, M Cano; Cantero, J; Cao, T; Garrido, M D M Capeans; Caprini, I; Caprini, M; Capua, M; Carbone, R M; Cardarelli, R; Cardillo, F; Carli, I; Carli, T; Carlino, G; Carlson, B T; Carminati, L; Carney, R M D; Caron, S; Carquin, E; Carrillo-Montoya, G D; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Casolino, M; Casper, D W; Castaneda-Miranda, E; Castelijn, R; Castelli, A; Gimenez, V Castillo; Castro, N F; Catinaccio, A; Catmore, J R; Cattai, A; Caudron, J; Cavaliere, V; Cavallaro, E; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Alberich, L Cerda; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cervelli, A; Cetin, S A; Chafaq, A; Chakraborty, D; Chan, S K; Chan, Y L; Chang, P; Chapman, J D; Charlton, D G; Chatterjee, A; Chau, C C; Barajas, C A Chavez; Che, S; Cheatham, S; Chegwidden, A; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, S; Chen, S; Chen, X; Chen, Y; Cheng, H C; Cheng, H J; Cheng, Y; Cheplakov, A; Cheremushkina, E; Moursli, R Cherkaoui El; Chernyatin, V; Cheu, E; Chevalier, L; Chiarella, V; Chiarelli, G; Chiodini, G; Chisholm, A S; Chitan, A; Chizhov, M V; Choi, K; Chomont, A R; Chouridou, S; Chow, B K B; Christodoulou, V; Chromek-Burckhart, D; Chudoba, J; Chuinard, A J; Chwastowski, J J; Chytka, L; Ciapetti, G; Ciftci, A K; Cinca, D; Cindro, V; Cioara, I A; Ciocca, C; Ciocio, A; Cirotto, F; Citron, Z H; Citterio, M; Ciubancan, M; Clark, A; Clark, B L; Clark, M R; Clark, P J; Clarke, R N; Clement, C; Coadou, Y; Cobal, M; Coccaro, A; Cochran, J; Colasurdo, L; Cole, B; Colijn, A P; Collot, J; Colombo, T; Muiño, P Conde; Coniavitis, E; Connell, S H; Connelly, I A; Consorti, V; Constantinescu, S; Conti, G; Conventi, F; Cooke, M; Cooper, B D; Cooper-Sarkar, A M; Cormier, F; Cormier, K J R; Cornelissen, T; Corradi, M; Corriveau, F; Cortes-Gonzalez, A; Cortiana, G; Costa, G; Costa, M J; Costanzo, D; Cottin, G; Cowan, G; Cox, B E; Cranmer, K; Crawley, S J; Cree, G; Crépé-Renaudin, S; Crescioli, F; Cribbs, W A; Ortuzar, M Crispin; Cristinziani, M; Croft, V; Crosetti, G; Cueto, A; Donszelmann, T Cuhadar; Cummings, J; Curatolo, M; Cúth, J; Czirr, H; Czodrowski, P; D'amen, G; D'Auria, S; D'Onofrio, M; De Sousa, M J Da Cunha Sargedas; Via, C Da; Dabrowski, W; Dado, T; Dai, T; Dale, O; Dallaire, F; Dallapiccola, C; Dam, M; Dandoy, J R; Dang, N P; Daniells, A C; Dann, N S; Danninger, M; Hoffmann, M Dano; Dao, V; Darbo, G; Darmora, S; Dassoulas, J; Dattagupta, A; Davey, W; David, C; Davidek, T; Davies, M; Davison, P; Dawe, E; Dawson, I; De, K; de Asmundis, R; De Benedetti, A; De Castro, S; De Cecco, S; De Groot, N; de Jong, P; De la Torre, H; De Lorenzi, F; De Maria, A; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Regie, J B De Vivie; Dearnaley, W J; Debbe, R; Debenedetti, C; Dedovich, D V; Dehghanian, N; Deigaard, I; Del Gaudio, M; Del Peso, J; Del Prete, T; Delgove, D; Deliot, F; Delitzsch, C M; Dell'Acqua, A; Dell'Asta, L; Dell'Orso, M; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; DeMarco, D A; Demers, S; Demichev, M; Demilly, A; Denisov, S P; Denysiuk, D; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Deterre, C; Dette, K; Deviveiros, P O; Dewhurst, A; Dhaliwal, S; Di Ciaccio, A; Di Ciaccio, L; Di Clemente, W K; Di Donato, C; Di Girolamo, A; Di Girolamo, B; Di Micco, B; Di Nardo, R; Di Petrillo, K F; Di Simone, A; Di Sipio, R; Di Valentino, D; Diaconu, C; Diamond, M; Dias, F A; Diaz, M A; Diehl, E B; Dietrich, J; Cornell, S Díez; Dimitrievska, A; Dingfelder, J; Dita, P; Dita, S; Dittus, F; Djama, F; Djobava, T; Djuvsland, J I; do Vale, M A B; Dobos, D; Dobre, M; Doglioni, C; Dolejsi, J; Dolezal, Z; Donadelli, M; Donati, S; Dondero, P; Donini, J; Dopke, J; Doria, A; Dova, M T; Doyle, A T; Drechsler, E; Dris, M; Du, Y; Duarte-Campderros, J; Duchovni, E; Duckeck, G; Ducu, O A; Duda, D; Dudarev, A; Dudder, A Chr; Duffield, E M; Duflot, L; Dührssen, M; Dumancic, M; Duncan, A K; Dunford, M; Yildiz, H Duran; Düren, M; Durglishvili, A; Duschinger, D; Dutta, B; Dyndal, M; Eckardt, C; Ecker, K M; Edgar, R C; Edwards, N C; Eifert, T; Eigen, G; Einsweiler, K; Ekelof, T; Kacimi, M El; Ellajosyula, V; Ellert, M; Elles, S; Ellinghaus, F; Elliot, A A; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Enari, Y; Endner, O C; Ennis, J S; Erdmann, J; Ereditato, A; Ernis, G; Ernst, J; Ernst, M; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Esposito, B; Etienvre, A I; Etzion, E; Evans, H; Ezhilov, A; Ezzi, M; Fabbri, F; Fabbri, L; Facini, G; Fakhrutdinov, R M; Falciano, S; Falla, R J; Faltova, J; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farina, C; Farina, E M; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassi, F; Fassnacht, P; Fassouliotis, D; Giannelli, M Faucci; Favareto, A; Fawcett, W J; Fayard, L; Fedin, O L; Fedorko, W; Feigl, S; Feligioni, L; Feng, C; Feng, E J; Feng, H; Fenyuk, A B; Feremenga, L; Martinez, P Fernandez; Perez, S Fernandez; Ferrando, J; Ferrari, A; Ferrari, P; Ferrari, R; de Lima, D E Ferreira; Ferrer, A; Ferrere, D; Ferretti, C; Fiedler, F; Filipčič, A; Filipuzzi, M; Filthaut, F; Fincke-Keeler, M; Finelli, K D; Fiolhais, M C N; Fiorini, L; Fischer, A; Fischer, C; Fischer, J; Fisher, W C; Flaschel, N; Fleck, I; Fleischmann, P; Fletcher, G T; Fletcher, R R M; Flick, T; Flierl, B M; Castillo, L R Flores; Flowerdew, M J; Forcolin, G T; Formica, A; Forti, A; Foster, A G; Fournier, D; Fox, H; Fracchia, S; Francavilla, P; Franchini, M; Francis, D; Franconi, L; Franklin, M; Frate, M; Fraternali, M; Freeborn, D; Fressard-Batraneanu, S M; Friedrich, F; Froidevaux, D; Frost, J A; Fukunaga, C; Torregrosa, E Fullana; Fusayasu, T; Fuster, J; Gabaldon, C; Gabizon, O; Gabrielli, A; Gabrielli, A; Gach, G P; Gadatsch, S; Gagliardi, G; Gagnon, L G; Gagnon, P; Galea, C; Galhardo, B; Gallas, E J; Gallop, B J; Gallus, P; Galster, G; Gan, K K; Ganguly, S; Gao, J; Gao, Y; Gao, Y S; Walls, F M Garay; García, C; Navarro, J E García; Garcia-Sciveres, M; Gardner, R W; Garelli, N; Garonne, V; Bravo, A Gascon; Gasnikova, K; Gatti, C; Gaudiello, A; Gaudio, G; Gauthier, L; Gavrilenko, I L; Gay, C; Gaycken, G; Gazis, E N; Gecse, Z; Gee, C N P; Geich-Gimbel, Ch; Geisen, M; Geisler, M P; Gellerstedt, K; Gemme, C; Genest, M H; Geng, C; Gentile, S; Gentsos, C; George, S; Gerbaudo, D; Gershon, A; Ghasemi, S; Ghneimat, M; Giacobbe, B; Giagu, S; Giannetti, P; Gibson, S M; Gignac, M; Gilchriese, M; Gillam, T P S; Gillberg, D; Gilles, G; Gingrich, D M; Giokaris, N; Giordani, M P; Giorgi, F M; Giraud, P F; Giromini, P; Giugni, D; Giuli, F; Giuliani, C; Giulini, M; Gjelsten, B K; Gkaitatzis, S; Gkialas, I; Gkougkousis, E L; Gladilin, L K; Glasman, C; Glatzer, J; Glaysher, P C F; Glazov, A; Goblirsch-Kolb, M; Godlewski, J; Goldfarb, S; Golling, T; Golubkov, D; Gomes, A; Gonçalo, R; Costa, J Goncalves Pinto Firmino Da; Gonella, G; Gonella, L; Gongadze, A; de la Hoz, S González; Gonzalez-Sevilla, S; Goossens, L; Gorbounov, P A; Gordon, H A; Gorelov, I; Gorini, B; Gorini, E; Gorišek, A; Goshaw, A T; Gössling, C; Gostkin, M I; Goudet, C R; Goujdami, D; Goussiou, A G; Govender, N; Gozani, E; Graber, L; Grabowska-Bold, I; Gradin, P O J; Grafström, P; Gramling, J; Gramstad, E; Grancagnolo, S; Gratchev, V; Gravila, P M; Gray, H M; Graziani, E; Greenwood, Z D; Grefe, C; Gregersen, K; Gregor, I M; Grenier, P; Grevtsov, K; Griffiths, J; Grillo, A A; Grimm, K; Grinstein, S; Gris, Ph; Grivaz, J-F; Groh, S; Gross, E; Grosse-Knetter, J; Grossi, G C; Grout, Z J; Guan, L; Guan, W; Guenther, J; Guescini, F; Guest, D; Gueta, O; Gui, B; Guido, E; Guillemin, T; Guindon, S; Gul, U; Gumpert, C; Guo, J; Guo, W; Guo, Y; Gupta, R; Gupta, S; Gustavino, G; Gutierrez, P; Ortiz, N G Gutierrez; Gutschow, C; Guyot, C; Gwenlan, C; Gwilliam, C B; Haas, A; Haber, C; Hadavand, H K; Haddad, N; Hadef, A; Hageböck, S; Hagihara, M; Hakobyan, H; Haleem, M; Haley, J; Halladjian, G; Hallewell, G D; Hamacher, K; Hamal, P; Hamano, K; Hamilton, A; Hamity, G N; Hamnett, P G; Han, L; Han, S; Hanagaki, K; Hanawa, K; Hance, M; Haney, B; Hanke, P; Hanna, R; Hansen, J B; Hansen, J D; Hansen, M C; Hansen, P H; Hara, K; Hard, A S; Harenberg, T; Hariri, F; Harkusha, S; Harrington, R D; Harrison, P F; Hartjes, F; Hartmann, N M; Hasegawa, M; Hasegawa, Y; Hasib, A; Hassani, S; Haug, S; Hauser, R; Hauswald, L; Havranek, M; Hawkes, C M; Hawkings, R J; Hayakawa, D; Hayden, D; Hays, C P; Hays, J M; Hayward, H S; Haywood, S J; Head, S J; Heck, T; Hedberg, V; Heelan, L; Heim, S; Heim, T; Heinemann, B; Heinrich, J J; Heinrich, L; Heinz, C; Hejbal, J; Helary, L; Hellman, S; Helsens, C; Henderson, J; Henderson, R C W; Heng, Y; Henkelmann, S; Correia, A M Henriques; Henrot-Versille, S; Herbert, G H; Herde, H; Herget, V; Jiménez, Y Hernández; Herten, G; Hertenberger, R; Hervas, L; Hesketh, G G; Hessey, N P; Hetherly, J W; Higón-Rodriguez, E; Hill, E; Hill, J C; Hiller, K H; Hillier, S J; Hinchliffe, I; Hines, E; Hirose, M; Hirschbuehl, D; Hladik, O; Hoad, X; Hobbs, J; Hod, N; Hodgkinson, M C; Hodgson, P; Hoecker, A; Hoeferkamp, M R; Hoenig, F; Hohn, D; Holmes, T R; Homann, M; Honda, S; Honda, T; Hong, T M; Hooberman, B H; Hopkins, W H; Horii, Y; Horton, A J; Hostachy, J-Y; Hou, S; Hoummada, A; Howarth, J; Hoya, J; Hrabovsky, M; Hristova, I; Hrivnac, J; Hryn'ova, T; Hrynevich, A; Hsu, P J; Hsu, S-C; Hu, Q; Hu, S; Huang, Y; Hubacek, Z; Hubaut, F; Huegging, F; Huffman, T B; Hughes, E W; Hughes, G; Huhtinen, M; Huo, P; Huseynov, N; Huston, J; Huth, J; Iacobucci, G; Iakovidis, G; Ibragimov, I; Iconomidou-Fayard, L; Ideal, E; Idrissi, Z; Iengo, P; Igonkina, O; Iizawa, T; Ikegami, Y; Ikeno, M; Ilchenko, Y; Iliadis, D; Ilic, N; Introzzi, G; Ioannou, P; Iodice, M; Iordanidou, K; Ippolito, V; Ishijima, N; Ishino, M; Ishitsuka, M; Issever, C; Istin, S; Ito, F; Ponce, J M Iturbe; Iuppa, R; Iwasaki, H; Izen, J M; Izzo, V; Jabbar, S; Jackson, B; Jackson, P; Jain, V; Jakobi, K B; Jakobs, K; Jakobsen, S; Jakoubek, T; Jamin, D O; Jana, D K; Jansky, R; Janssen, J; Janus, M; Janus, P A; Jarlskog, G; Javadov, N; Javůrek, T; Jeanneau, F; Jeanty, L; Jejelava, J; Jeng, G-Y; Jenni, P; Jeske, C; Jézéquel, S; Ji, H; Jia, J; Jiang, H; Jiang, Y; Jiang, Z; Jiggins, S; Pena, J Jimenez; Jin, S; Jinaru, A; Jinnouchi, O; Jivan, H; Johansson, P; Johns, K A; Johnson, C A; Johnson, W J; Jon-And, K; Jones, G; Jones, R W L; Jones, S; Jones, T J; Jongmanns, J; Jorge, P M; Jovicevic, J; Ju, X; Rozas, A Juste; Köhler, M K; Kaczmarska, A; Kado, M; Kagan, H; Kagan, M; Kahn, S J; Kaji, T; Kajomovitz, E; Kalderon, C W; Kaluza, A; Kama, S; Kamenshchikov, A; Kanaya, N; Kaneti, S; Kanjir, L; Kantserov, V A; Kanzaki, J; Kaplan, B; Kaplan, L S; Kapliy, A; Kar, D; Karakostas, K; Karamaoun, A; Karastathis, N; Kareem, M J; Karentzos, E; Karnevskiy, M; Karpov, S N; Karpova, Z M; Karthik, K; Kartvelishvili, V; Karyukhin, A N; Kasahara, K; Kashif, L; Kass, R D; Kastanas, A; Kataoka, Y; Kato, C; Katre, A; Katzy, J; Kawade, K; Kawagoe, K; Kawamoto, T; Kawamura, G; Kazanin, V F; Keeler, R; Kehoe, R; Keller, J S; Kempster, J J; Keoshkerian, H; Kepka, O; Kerševan, B P; Kersten, S; Keyes, R A; Khader, M; Khalil-Zada, F; Khanov, A; Kharlamov, A G; Kharlamova, T; Khoo, T J; Khovanskiy, V; Khramov, E; Khubua, J; Kido, S; Kilby, C R; Kim, H Y; Kim, S H; Kim, Y K; Kimura, N; Kind, O M; King, B T; King, M; Kirk, J; Kiryunin, A E; Kishimoto, T; Kisielewska, D; Kiss, F; Kiuchi, K; Kivernyk, O; Kladiva, E; Klapdor-Kleingrothaus, T; Klein, M H; Klein, M; Klein, U; Kleinknecht, K; Klimek, P; Klimentov, A; Klingenberg, R; Klioutchnikova, T; Kluge, E-E; Kluit, P; Kluth, S; Knapik, J; Kneringer, E; Knoops, E B F G; Knue, A; Kobayashi, A; Kobayashi, D; Kobayashi, T; Kobel, M; Kocian, M; Kodys, P; Koffas, T; Koffeman, E; Köhler, N M; Koi, T; Kolanoski, H; Kolb, M; Koletsou, I; Komar, A A; Komori, Y; Kondo, T; Kondrashova, N; Köneke, K; König, A C; Kono, T; Konoplich, R; Konstantinidis, N; Kopeliansky, R; Koperny, S; Kopp, A K; Korcyl, K; Kordas, K; Korn, A; Korol, A A; Korolkov, I; Korolkova, E V; Kortner, O; Kortner, S; Kosek, T; Kostyukhin, V V; Kotwal, A; Koulouris, A; Kourkoumeli-Charalampidi, A; Kourkoumelis, C; Kouskoura, V; Kowalewska, A B; Kowalewski, R; Kowalski, T Z; Kozakai, C; Kozanecki, W; Kozhin, A S; Kramarenko, V A; Kramberger, G; Krasnopevtsev, D; Krasny, M W; Krasznahorkay, A; Kravchenko, A; Kretz, M; Kretzschmar, J; Kreutzfeldt, K; Krieger, P; Krizka, K; Kroeninger, K; Kroha, H; Kroll, J; Kroseberg, J; Krstic, J; Kruchonak, U; Krüger, H; Krumnack, N; Kruse, M C; Kruskal, M; Kubota, T; Kucuk, H; Kuday, S; Kuechler, J T; Kuehn, S; Kugel, A; Kuger, F; Kuhl, T; Kukhtin, V; Kukla, R; Kulchitsky, Y; Kuleshov, S; Kuna, M; Kunigo, T; Kupco, A; Kuprash, O; Kurashige, H; Kurchaninov, L L; Kurochkin, Y A; Kurth, M G; Kus, V; Kuwertz, E S; Kuze, M; Kvita, J; Kwan, T; Kyriazopoulos, D; Rosa, A La; Navarro, J L La Rosa; Rotonda, L La; Lacasta, C; Lacava, F; Lacey, J; Lacker, H; Lacour, D; Ladygin, E; Lafaye, R; Laforge, B; Lagouri, T; Lai, S; Lammers, S; Lampl, W; Lançon, E; Landgraf, U; Landon, M P J; Lanfermann, M C; Lang, V S; Lange, J C; Lankford, A J; Lanni, F; Lantzsch, K; Lanza, A; Laplace, S; Lapoire, C; Laporte, J F; Lari, T; Manghi, F Lasagni; Lassnig, M; Laurelli, P; Lavrijsen, W; Law, A T; Laycock, P; Lazovich, T; Lazzaroni, M; Le, B; Dortz, O Le; Guirriec, E Le; Quilleuc, E P Le; LeBlanc, M; LeCompte, T; Ledroit-Guillon, F; Lee, C A; Lee, S C; Lee, L; Lefebvre, B; Lefebvre, G; Lefebvre, M; Legger, F; Leggett, C; Lehan, A; Miotto, G Lehmann; Lei, X; Leight, W A; Leister, A G; Leite, M A L; Leitner, R; Lellouch, D; Lemmer, B; Leney, K J C; Lenz, T; Lenzi, B; Leone, R; Leone, S; Leonidopoulos, C; Leontsinis, S; Lerner, G; Leroy, C; Lesage, A A J; Lester, C G; Levchenko, M; Levêque, J; Levin, D; Levinson, L J; Levy, M; Lewis, D; Leyton, M; Li, B; Li, C; Li, H; Li, L; Li, L; Li, Q; Li, S; Li, X; Li, Y; Liang, Z; Liberti, B; Liblong, A; Lichard, P; Lie, K; Liebal, J; Liebig, W; Limosani, A; Lin, S C; Lin, T H; Lindquist, B E; Lionti, A E; Lipeles, E; Lipniacka, A; Lisovyi, M; Liss, T M; Lister, A; Litke, A M; Liu, B; Liu, D; Liu, H; Liu, H; Liu, J; Liu, J B; Liu, K; Liu, L; Liu, M; Liu, Y L; Liu, Y; Livan, M; Lleres, A; Merino, J Llorente; Lloyd, S L; Sterzo, F Lo; Lobodzinska, E M; Loch, P; Loebinger, F K; Loew, K M; Loginov, A; Lohse, T; Lohwasser, K; Lokajicek, M; Long, B A; Long, J D; Long, R E; Longo, L; Looper, K A; Lopez, J A Lopez; Mateos, D Lopez; Paredes, B Lopez; Paz, I Lopez; Solis, A Lopez; Lorenz, J; Martinez, N Lorenzo; Losada, M; Lösel, P J; Lou, X; Lounis, A; Love, J; Love, P A; Lu, H; Lu, N; Lubatti, H J; Luci, C; Lucotte, A; Luedtke, C; Luehring, F; Lukas, W; Luminari, L; Lundberg, O; Lund-Jensen, B; Luzi, P M; Lynn, D; Lysak, R; Lytken, E; Lyubushkin, V; Ma, H; Ma, L L; Ma, Y; Maccarrone, G; Macchiolo, A; Macdonald, C M; Maček, B; Miguens, J Machado; Madaffari, D; Madar, R; Maddocks, H J; Mader, W F; Madsen, A; Maeda, J; Maeland, S; Maeno, T; Maevskiy, A; Magradze, E; Mahlstedt, J; Maiani, C; Maidantchik, C; Maier, A A; Maier, T; Maio, A; Majewski, S; Makida, Y; Makovec, N; Malaescu, B; Malecki, Pa; Maleev, V P; Malek, F; Mallik, U; Malon, D; Malone, C; Maltezos, S; Malyukov, S; Mamuzic, J; Mancini, G; Mandelli, L; Mandić, I; Maneira, J; Filho, L Manhaes de Andrade; Ramos, J Manjarres; Mann, A; Manousos, A; Mansoulie, B; Mansour, J D; Mantifel, R; Mantoani, M; Manzoni, S; Mapelli, L; Marceca, G; March, L; Marchiori, G; Marcisovsky, M; Marjanovic, M; Marley, D E; Marroquim, F; Marsden, S P; Marshall, Z; Marti-Garcia, S; Martin, B; Martin, T A; Martin, V J; Latour, B Martin Dit; Martinez, M; Outschoorn, V I Martinez; Martin-Haugh, S; Martoiu, V S; Martyniuk, A C; Marzin, A; Masetti, L; Mashimo, T; Mashinistov, R; Masik, J; Maslennikov, A L; Massa, I; Massa, L; Mastrandrea, P; Mastroberardino, A; Masubuchi, T; Mättig, P; Mattmann, J; Maurer, J; Maxfield, S J; Maximov, D A; Mazini, R; Maznas, I; Mazza, S M; Fadden, N C Mc; Goldrick, G Mc; Kee, S P Mc; McCarn, A; McCarthy, R L; McCarthy, T G; McClymont, L I; McDonald, E F; Mcfayden, J A; Mchedlidze, G; McMahon, S J; McPherson, R A; Medinnis, M; Meehan, S; Mehlhase, S; Mehta, A; Meier, K; Meineck, C; Meirose, B; Melini, D; Garcia, B R Mellado; Melo, M; Meloni, F; Menary, S B; Meng, L; Meng, X T; Mengarelli, A; Menke, S; Meoni, E; Mergelmeyer, S; Mermod, P; Merola, L; Meroni, C; Merritt, F S; Messina, A; Metcalfe, J; Mete, A S; Meyer, C; Meyer, C; Meyer, J-P; Meyer, J; Theenhausen, H Meyer Zu; Miano, F; Middleton, R P; Miglioranzi, S; Mijović, L; Mikenberg, G; Mikestikova, M; Mikuž, M; Milesi, M; Milic, A; Miller, D W; Mills, C; Milov, A; Milstead, D A; Minaenko, A A; Minami, Y; Minashvili, I A; Mincer, A I; Mindur, B; Mineev, M; Minegishi, Y; Ming, Y; Mir, L M; Mistry, K P; Mitani, T; Mitrevski, J; Mitsou, V A; Miucci, A; Miyagawa, P S; Mizukami, A; Mjörnmark, J U; Mlynarikova, M; Moa, T; Mochizuki, K; Mogg, P; Mohapatra, S; Molander, S; Moles-Valls, R; Monden, R; Mondragon, M C; Mönig, K; Monk, J; Monnier, E; Montalbano, A; Berlingen, J Montejo; Monticelli, F; Monzani, S; Moore, R W; Morange, N; Moreno, D; Llácer, M Moreno; Morettini, P; Morgenstern, S; Mori, D; Mori, T; Morii, M; Morinaga, M; Morisbak, V; Moritz, S; Morley, A K; Mornacchi, G; Morris, J D; Mortensen, S S; Morvaj, L; Moschovakos, P; Mosidze, M; Moss, H J; Moss, J; Motohashi, K; Mount, R; Mountricha, E; Moyse, E J W; Muanza, S; Mudd, R D; Mueller, F; Mueller, J; Mueller, R S P; Mueller, T; Muenstermann, D; Mullen, P; Mullier, G A; Sanchez, F J Munoz; Quijada, J A Murillo; Murray, W J; Musheghyan, H; Muškinja, M; Myagkov, A G; Myska, M; Nachman, B P; Nackenhorst, O; Nagai, K; Nagai, R; Nagano, K; Nagasaka, Y; Nagata, K; Nagel, M; Nagy, E; Nairz, A M; Nakahama, Y; Nakamura, K; Nakamura, T; Nakano, I; Garcia, R F Naranjo; Narayan, R; Villar, D I Narrias; Naryshkin, I; Naumann, T; Navarro, G; Nayyar, R; Neal, H A; Nechaeva, P Yu; Neep, T J; Negri, A; Negrini, M; Nektarijevic, S; Nellist, C; Nelson, A; Nemecek, S; Nemethy, P; Nepomuceno, A A; Nessi, M; Neubauer, M S; Neumann, M; Neves, R M; Nevski, P; Newman, P R; Nguyen, D H; Manh, T Nguyen; Nickerson, R B; Nicolaidou, R; Nielsen, J; Nikolaenko, V; Nikolic-Audit, I; Nikolopoulos, K; Nilsen, J K; Nilsson, P; Ninomiya, Y; Nisati, A; Nisius, R; Nobe, T; Nomachi, M; Nomidis, I; Nooney, T; Norberg, S; Nordberg, M; Norjoharuddeen, N; Novgorodova, O; Nowak, S; Nozaki, M; Nozka, L; Ntekas, K; Nurse, E; Nuti, F; O'grady, F; O'Neil, D C; O'Rourke, A A; O'Shea, V; Oakham, F G; Oberlack, H; Obermann, T; Ocariz, J; Ochi, A; Ochoa, I; Ochoa-Ricoux, J P; Oda, S; Odaka, S; Ogren, H; Oh, A; Oh, S H; Ohm, C C; Ohman, H; Oide, H; Okawa, H; Okumura, Y; Okuyama, T; Olariu, A; Seabra, L F Oleiro; Pino, S A Olivares; Damazio, D Oliveira; Olszewski, A; Olszowska, J; Onofre, A; Onogi, K; Onyisi, P U E; Oreglia, M J; Oren, Y; Orestano, D; Orlando, N; Orr, R S; Osculati, B; Ospanov, R; Garzon, G Otero Y; Otono, H; Ouchrif, M; Ould-Saada, F; Ouraou, A; Oussoren, K P; Ouyang, Q; Owen, M; Owen, R E; Ozcan, V E; Ozturk, N; Pachal, K; Pages, A Pacheco; Rodriguez, L Pacheco; Aranda, C Padilla; Pagáčová, M; Griso, S Pagan; Paganini, M; Paige, F; Pais, P; Pajchel, K; Palacino, G; Palazzo, S; Palestini, S; Palka, M; Pallin, D; Panagiotopoulou, E St; Pandini, C E; Vazquez, J G Panduro; Pani, P; Panitkin, S; Pantea, D; Paolozzi, L; Papadopoulou, Th D; Papageorgiou, K; Paramonov, A; Hernandez, D Paredes; Parker, A J; Parker, M A; Parker, K A; Parodi, F; Parsons, J A; Parzefall, U; Pascuzzi, V R; Pasqualucci, E; Passaggio, S; Pastore, Fr; Pásztor, G; Pataraia, S; Pater, J R; Pauly, T; Pearce, J; Pearson, B; Pedersen, L E; Pedersen, M; Lopez, S Pedraza; Pedro, R; Peleganchuk, S V; Penc, O; Peng, C; Peng, H; Penwell, J; Peralva, B S; Perego, M M; Perepelitsa, D V; Codina, E Perez; Perini, L; Pernegger, H; Perrella, S; Peschke, R; Peshekhonov, V D; Peters, K; Peters, R F Y; Petersen, B A; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petroff, P; Petrolo, E; Petrov, M; Petrucci, F; Pettersson, N E; Peyaud, A; Pezoa, R; Phillips, P W; Piacquadio, G; Pianori, E; Picazio, A; Piccaro, E; Piccinini, M; Pickering, M A; Piegaia, R; Pilcher, J E; Pilkington, A D; Pin, A W J; Pinamonti, M; Pinfold, J L; Pingel, A; Pires, S; Pirumov, H; Pitt, M; Plazak, L; Pleier, M-A; Pleskot, V; Plotnikova, E; Pluth, D; Poettgen, R; Poggioli, L; Pohl, D; Polesello, G; Poley, A; Policicchio, A; Polifka, R; Polini, A; Pollard, C S; Polychronakos, V; Pommès, K; Pontecorvo, L; Pope, B G; Popeneciu, G A; Poppleton, A; Pospisil, S; Potamianos, K; Potrap, I N; Potter, C J; Potter, C T; Poulard, G; Poveda, J; Pozdnyakov, V; Astigarraga, M E Pozo; Pralavorio, P; Pranko, A; Prell, S; Price, D; Price, L E; Primavera, M; Prince, S; Prokofiev, K; Prokoshin, F; Protopopescu, S; Proudfoot, J; Przybycien, M; Puddu, D; Purohit, M; Puzo, P; Qian, J; Qin, G; Qin, Y; Quadt, A; Quayle, W B; Queitsch-Maitland, M; Quilty, D; Raddum, S; Radeka, V; Radescu, V; Radhakrishnan, S K; Radloff, P; Rados, P; Ragusa, F; Rahal, G; Raine, J A; Rajagopalan, S; Rammensee, M; Rangel-Smith, C; Ratti, M G; Rauch, D M; Rauscher, F; Rave, S; Ravenscroft, T; Ravinovich, I; Raymond, M; Read, A L; Readioff, N P; Reale, M; Rebuzzi, D M; Redelbach, A; Redlinger, G; Reece, R; Reed, R G; Reeves, K; Rehnisch, L; Reichert, J; Reiss, A; Rembser, C; Ren, H; Rescigno, M; Resconi, S; Resseguie, E D; Rezanova, O L; Reznicek, P; Rezvani, R; Richter, R; Richter, S; Richter-Was, E; Ricken, O; Ridel, M; Rieck, P; Riegel, C J; Rieger, J; Rifki, O; Rijssenbeek, M; Rimoldi, A; Rimoldi, M; Rinaldi, L; Ristić, B; Ritsch, E; Riu, I; Rizatdinova, F; Rizvi, E; Rizzi, C; Roberts, R T; Robertson, S H; Robichaud-Veronneau, A; Robinson, D; Robinson, J E M; Robson, A; Roda, C; Rodina, Y; Perez, A Rodriguez; Rodriguez, D Rodriguez; Roe, S; Rogan, C S; Røhne, O; Roloff, J; Romaniouk, A; Romano, M; Saez, S M Romano; Adam, E Romero; Rompotis, N; Ronzani, M; Roos, L; Ros, E; Rosati, S; Rosbach, K; Rose, P; Rosien, N-A; Rossetti, V; Rossi, E; Rossi, L P; Rosten, J H N; Rosten, R; Rotaru, M; Roth, I; Rothberg, J; Rousseau, D; Rozanov, A; Rozen, Y; Ruan, X; Rubbo, F; Rudolph, M S; Rühr, F; Ruiz-Martinez, A; Rurikova, Z; Rusakovich, N A; Ruschke, A; Russell, H L; Rutherfoord, J P; Ruthmann, N; Ryabov, Y F; Rybar, M; Rybkin, G; Ryu, S; Ryzhov, A; Rzehorz, G F; Saavedra, A F; Sabato, G; Sacerdoti, S; Sadrozinski, H F-W; Sadykov, R; Tehrani, F Safai; Saha, P; Sahinsoy, M; Saimpert, M; Saito, T; Sakamoto, H; Sakurai, Y; Salamanna, G; Salamon, A; Loyola, J E Salazar; Salek, D; De Bruin, P H Sales; Salihagic, D; Salnikov, A; Salt, J; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sammel, D; Sampsonidis, D; Sánchez, J; Martinez, V Sanchez; Pineda, A Sanchez; Sandaker, H; Sandbach, R L; Sandhoff, M; Sandoval, C; Sankey, D P C; Sannino, M; Sansoni, A; Santoni, C; Santonico, R; Santos, H; Castillo, I Santoyo; Sapp, K; Sapronov, A; Saraiva, J G; Sarrazin, B; Sasaki, O; Sato, K; Sauvan, E; Savage, G; Savard, P; Savic, N; Sawyer, C; Sawyer, L; Saxon, J; Sbarra, C; Sbrizzi, A; Scanlon, T; Scannicchio, D A; Scarcella, M; Scarfone, V; Schaarschmidt, J; Schacht, P; Schachtner, B M; Schaefer, D; Schaefer, L; Schaefer, R; Schaeffer, J; Schaepe, S; Schaetzel, S; Schäfer, U; Schaffer, A C; Schaile, D; Schamberger, R D; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Schiavi, C; Schier, S; Schillo, C; Schioppa, M; Schlenker, S; Schmidt-Sommerfeld, K R; Schmieden, K; Schmitt, C; Schmitt, S; Schmitz, S; Schneider, B; Schnoor, U; Schoeffel, L; Schoening, A; Schoenrock, B D; Schopf, E; Schott, M; Schouwenberg, J F P; Schovancova, J; Schramm, S; Schreyer, M; Schuh, N; Schulte, A; Schultens, M J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, Ph; Schwartzman, A; Schwarz, T A; Schweiger, H; Schwemling, Ph; Schwienhorst, R; Schwindling, J; Schwindt, T; Sciolla, G; Scuri, F; Scutti, F; Searcy, J; Seema, P; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekhon, K; Sekula, S J; Seliverstov, D M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Sessa, M; Seuster, R; Severini, H; Sfiligoj, T; Sforza, F; Sfyrla, A; Shabalina, E; Shaikh, N W; Shan, L Y; Shang, R; Shank, J T; Shapiro, M; Shatalov, P B; Shaw, K; Shaw, S M; Shcherbakova, A; Shehu, C Y; Sherwood, P; Shi, L; Shimizu, S; Shimmin, C O; Shimojima, M; Shirabe, S; Shiyakova, M; Shmeleva, A; Saadi, D Shoaleh; Shochet, M J; Shojaii, S; Shope, D R; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sickles, A M; Sidebo, P E; Haddad, E Sideras; Sidiropoulou, O; Sidorov, D; Sidoti, A; Siegert, F; Sijacki, Dj; Silva, J; Silverstein, S B; Simak, V; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simon, D; Simon, M; Sinervo, P; Sinev, N B; Sioli, M; Siragusa, G; Siral, I; Sivoklokov, S Yu; Sjölin, J; Skinner, M B; Skottowe, H P; Skubic, P; Slater, M; Slavicek, T; Slawinska, M; Sliwa, K; Slovak, R; Smakhtin, V; Smart, B H; Smestad, L; Smiesko, J; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, J W; Smith, M N K; Smith, R W; Smizanska, M; Smolek, K; Snesarev, A A; Snyder, I M; Snyder, S; Sobie, R; Socher, F; Soffer, A; Soh, D A; Sokhrannyi, G; Sanchez, C A Solans; Solar, M; Soldatov, E Yu; Soldevila, U; Solodkov, A A; Soloshenko, A; Solovyanov, O V; Solovyev, V; Sommer, P; Son, H; Song, H Y; Sood, A; Sopczak, A; Sopko, V; Sorin, V; Sosa, D; Sotiropoulou, C L; Soualah, R; Soukharev, A M; South, D; Sowden, B C; Spagnolo, S; Spalla, M; Spangenberg, M; Spanò, F; Sperlich, D; Spettel, F; Spighi, R; Spigo, G; Spiller, L A; Spousta, M; Denis, R D St; Stabile, A; Stamen, R; Stamm, S; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stanitzki, M M; Stapnes, S; Starchenko, E A; Stark, G H; Stark, J; Staroba, P; Starovoitov, P; Stärz, S; Staszewski, R; Steinberg, P; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoicea, G; Stolte, P; Stonjek, S; Stradling, A R; Straessner, A; Stramaglia, M E; Strandberg, J; Strandberg, S; Strandlie, A; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Strubig, A; Stucci, S A; Stugu, B; Styles, N A; Su, D; Su, J; Suchek, S; Sugaya, Y; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, S; Sun, X; Sundermann, J E; Suruliz, K; Suster, C J E; Sutton, M R; Suzuki, S; Svatos, M; Swiatlowski, M; Swift, S P; Sykora, I; Sykora, T; Ta, D; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tanaka, J; Tanaka, M; Tanaka, R; Tanaka, S; Tanioka, R; Tannenwald, B B; Araya, S Tapia; Tapprogge, S; Tarem, S; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Delgado, A Tavares; Tayalati, Y; Taylor, A C; Taylor, G N; Taylor, P T E; Taylor, W; Teischinger, F A; Teixeira-Dias, P; Temming, K K; Temple, D; Kate, H Ten; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Tibbetts, M J; Torres, R E Ticse; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tipton, P; Tisserant, S; Todome, K; Todorov, T; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Tong, B; Tornambe, P; Torrence, E; Torres, H; Pastor, E Torró; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Trofymov, A; Troncon, C; Trottier-McDonald, M; Trovatelli, M; Truong, L; Trzebinski, M; Trzupek, A; Tseng, J C-L; Tsiareshka, P V; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsui, K M; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tu, Y; Tudorache, A; Tudorache, V; Tulbure, T T; Tuna, A N; Tupputi, S A; Turchikhin, S; Turgeman, D; Cakir, I Turk; Turra, R; Tuts, P M; Ucchielli, G; Ueda, I; Ughetto, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usui, J; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Santurio, E Valdes; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Ferrer, J A Valls; Van Den Wollenberg, W; Van Der Deijl, P C; van der Graaf, H; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vanguri, R; Vaniachine, A; Vankov, P; Vardanyan, G; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vasquez, J G; Vasquez, G A; Vazeille, F; Schroeder, T Vazquez; Veatch, J; Veeraraghavan, V; Veloce, L M; Veloso, F; Veneziano, S; Ventura, A; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Boeriu, O E Vickey; Viehhauser, G H A; Viel, S; Vigani, L; Villa, M; Perez, M Villaplana; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vittori, C; Vivarelli, I; Vlachos, S; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; Volpi, M; von der Schmitt, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Milosavljevic, M Vranjes; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wallangen, V; Wang, C; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, W; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Watkins, P M; Watson, A T; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Weber, S A; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M D; Werner, P; Wessels, M; Wetter, J; Whalen, K; Whallon, N L; Wharton, A M; White, A; White, M J; White, R; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilk, F; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winston, O J; Winter, B T; Wittgen, M; Wobisch, M; Wolf, T M H; Wolff, R; Wolter, M W; Wolters, H; Worm, S D; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xi, Z; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yang, Z; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Wong, K H Yau; Ye, J; Ye, S; Yeletskikh, I; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zakharchuk, N; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, J C; Zeng, Q; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, L; Zhang, M; Zhang, R; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Nedden, M Zur; Zwalinski, L

2017-01-01

Detailed measurements of t -channel single top-quark production are presented. They use 20.2 fb[Formula: see text] of data collected by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of 8 TeV at the LHC. Total, fiducial and differential cross-sections are measured for both top-quark and top-antiquark production. The fiducial cross-section is measured with a precision of 5.8% (top quark) and 7.8% (top antiquark), respectively. The total cross-sections are measured to be [Formula: see text] for top-quark production and [Formula: see text] for top-antiquark production, in agreement with the Standard Model prediction. In addition, the ratio of top-quark to top-antiquark production cross-sections is determined to be [Formula: see text]. The differential cross-sections as a function of the transverse momentum and rapidity of both the top quark and the top antiquark are measured at both the parton and particle levels. The transverse momentum and rapidity differential cross-sections of the accompanying jet from the t -channel scattering are measured at particle level. All measurements are compared to various Monte Carlo predictions as well as to fixed-order QCD calculations where available.

Sea Temperature Fiducial Reference Measurements for the Validation and Data Gap Bridging of Satellite SST Data Products

NASA Astrophysics Data System (ADS)

Wimmer, Werenfrid

2016-08-01

The Infrared Sea surface temperature Autonomous Radiometer (ISAR) was developed to provide reference data for the validation of satellite Sea Surface Temperature at the Skin interface (SSTskin) temperature data products, particularly the Advanced Along Track Scanning Radiometer (AATSR). Since March 2004 ISAR instruments have been deployed nearly continuously on ferries crossing the English Channel and the Bay of Biscay, between Portsmouth (UK) and Bilbao/Santander (Spain). The resulting twelve years of ISAR data, including an individual uncertainty estimate for each SST record, are calibrated with traceability to national standards (National Institute of Standards and Technology, USA (NIST) and National Physical Laboratory, Teddigton, UK (NPL), Fiducial Reference Measurements for satellite derived surface temperature product validation (FRM4STS)). They provide a unique independent in situ reference dataset against which to validate satellite derived products. We present results of the AATSR validation, and show the use of ISAR fiducial reference measurements as a common traceable validation data source for both AATSR and Sea and Land Surface Temperature Radiometer (SLSTR). ISAR data were also used to review performance of the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature (SST) analysis before and after the demise of ESA Environmental Satellite (Envisat) when AATSR inputs ceased This demonstrates use of the ISAR reference data set for validating the SST climatologies that will bridge the data gap between AATSR and SLSTR.

Tailoring four-dimensional cone-beam CT acquisition settings for fiducial marker-based image guidance in radiation therapy.

PubMed

Jin, Peng; van Wieringen, Niek; Hulshof, Maarten C C M; Bel, Arjan; Alderliesten, Tanja

2018-04-01

Use of four-dimensional cone-beam CT (4D-CBCT) and fiducial markers for image guidance during radiation therapy (RT) of mobile tumors is challenging due to the trade-off among image quality, imaging dose, and scanning time. This study aimed to investigate different 4D-CBCT acquisition settings for good visibility of fiducial markers in 4D-CBCT. Using these 4D-CBCTs, the feasibility of marker-based 4D registration for RT setup verification and manual respiration-induced motion quantification was investigated. For this, we applied a dynamic phantom with three different breathing motion amplitudes and included two patients with implanted markers. Irrespective of the motion amplitude, for a medium field of view (FOV), marker visibility was improved by reducing the imaging dose per projection and increasing the number of projection images; however, the scanning time was 4 to 8 min. For a small FOV, the total imaging dose and the scanning time were reduced (62.5% of the dose using a medium FOV, 2.5 min) without losing marker visibility. However, the body contour could be missing for a small FOV, which is not preferred in RT. The marker-based 4D setup verification was feasible for both the phantom and patient data. Moreover, manual marker motion quantification can achieve a high accuracy with a mean error of [Formula: see text].

Measurement of inclusive and differential cross sections in the H → ZZ * → 4ℓ decay channel in pp collisions at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-10-19

Inclusive and differential fiducial cross sections of Higgs boson production in proton-proton collisions are measured in the H → ZZ * → 4ℓ decay channel. The proton-proton collision data were produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb –1. The inclusive fiducial cross section in the H → ZZ * → 4ℓ decay channel is measured to be 3.62±0.50(stat) –0.20 +0.25 (sys) fb, in agreement with the Standard Model prediction of 2.91 ± 0.13 fb. The crossmore » section is also extrapolated to the total phase space including all Standard Model Higgs boson decays. Several differential fiducial cross sections are measured for observables sensitive to the Higgs boson production and decay, including kinematic distributions of jets produced in association with the Higgs boson. Good agreement is found between data and Standard Model predictions. Here, the results are used to put constraints on anomalous Higgs boson interactions with Standard Model particles, using the pseudo-observable extension to the kappa-framework.« less

Measurement of inclusive and differential cross sections in the H → ZZ * → 4ℓ decay channel in pp collisions at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-10-19

Inclusive and differential fiducial cross sections of Higgs boson production in proton-proton collisions are measured in the H → ZZ* → 4ℓ decay channel. The proton-proton collision data were produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb –1. The inclusive fiducial cross section in the H → ZZ* → 4ℓ decay channel is measured to be 3.62±0.50(stat) –0.20 +0.25 (sys) fb, in agreement with the Standard Model prediction of 2.91 ± 0.13 fb. The cross section ismore » also extrapolated to the total phase space including all Standard Model Higgs boson decays. Several differential fiducial cross sections are measured for observables sensitive to the Higgs boson production and decay, including kinematic distributions of jets produced in association with the Higgs boson. Good agreement is found between data and Standard Model predictions. The results are used to put constraints on anomalous Higgs boson interactions with Standard Model particles, using the pseudo-observable extension to the kappa-framework.« less

Measurement of inclusive and differential cross sections in the H → ZZ * → 4ℓ decay channel in pp collisions at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

Inclusive and differential fiducial cross sections of Higgs boson production in proton-proton collisions are measured in the H → ZZ * → 4ℓ decay channel. The proton-proton collision data were produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb –1. The inclusive fiducial cross section in the H → ZZ * → 4ℓ decay channel is measured to be 3.62±0.50(stat) –0.20 +0.25 (sys) fb, in agreement with the Standard Model prediction of 2.91 ± 0.13 fb. The crossmore » section is also extrapolated to the total phase space including all Standard Model Higgs boson decays. Several differential fiducial cross sections are measured for observables sensitive to the Higgs boson production and decay, including kinematic distributions of jets produced in association with the Higgs boson. Good agreement is found between data and Standard Model predictions. Here, the results are used to put constraints on anomalous Higgs boson interactions with Standard Model particles, using the pseudo-observable extension to the kappa-framework.« less

Acoustic change detection algorithm using an FM radio

NASA Astrophysics Data System (ADS)

Goldman, Geoffrey H.; Wolfe, Owen

2012-06-01

The U.S. Army is interested in developing low-cost, low-power, non-line-of-sight sensors for monitoring human activity. One modality that is often overlooked is active acoustics using sources of opportunity such as speech or music. Active acoustics can be used to detect human activity by generating acoustic images of an area at different times, then testing for changes among the imagery. A change detection algorithm was developed to detect physical changes in a building, such as a door changing positions or a large box being moved using acoustics sources of opportunity. The algorithm is based on cross correlating the acoustic signal measured from two microphones. The performance of the algorithm was shown using data generated with a hand-held FM radio as a sound source and two microphones. The algorithm could detect a door being opened in a hallway.

An Algorithm for Pedestrian Detection in Multispectral Image Sequences

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Fedorenko, V. V.

2017-05-01

The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-05-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-09-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States

Treesearch

Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu; William T. Sommers

2006-01-01

Traditional fire detection algorithms mainly rely on hot spot detection using thermal infrared (TIR) channels with fixed or contextual thresholds. Three solar reflectance channels (0.65 μm, 0.86 μm, and 2.1 μm) were recently adopted into the MODIS version 4 contextual algorithm to improve the active fire detection. In the southeastern United...

Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008-2012.

PubMed

Spreco, A; Eriksson, O; Dahlström, Ö; Timpka, T

2017-07-01

Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for 'nowcasting' (integrated detection and prediction) of influenza activity are warranted.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Songhua; Krauthammer, Prof. Michael

2010-01-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper's key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manuallymore » labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. We demonstrate that our projection histogram-based text detection approach is well suited for text detection in biomedical images, and that the iterative application of the algorithm boosts performance to an F score of .60. We provide a C++ implementation of our algorithm freely available for academic use.« less

Breadth-First Search-Based Single-Phase Algorithms for Bridge Detection in Wireless Sensor Networks

PubMed Central

Akram, Vahid Khalilpour; Dagdeviren, Orhan

2013-01-01

Wireless sensor networks (WSNs) are promising technologies for exploring harsh environments, such as oceans, wild forests, volcanic regions and outer space. Since sensor nodes may have limited transmission range, application packets may be transmitted by multi-hop communication. Thus, connectivity is a very important issue. A bridge is a critical edge whose removal breaks the connectivity of the network. Hence, it is crucial to detect bridges and take preventions. Since sensor nodes are battery-powered, services running on nodes should consume low energy. In this paper, we propose energy-efficient and distributed bridge detection algorithms for WSNs. Our algorithms run single phase and they are integrated with the Breadth-First Search (BFS) algorithm, which is a popular routing algorithm. Our first algorithm is an extended version of Milic's algorithm, which is designed to reduce the message length. Our second algorithm is novel and uses ancestral knowledge to detect bridges. We explain the operation of the algorithms, analyze their proof of correctness, message, time, space and computational complexities. To evaluate practical importance, we provide testbed experiments and extensive simulations. We show that our proposed algorithms provide less resource consumption, and the energy savings of our algorithms are up by 5.5-times. PMID:23845930

An exact computational method for performance analysis of sequential test algorithms for detecting network intrusions

NASA Astrophysics Data System (ADS)

Chen, Xinjia; Lacy, Fred; Carriere, Patrick

2015-05-01

Sequential test algorithms are playing increasingly important roles for quick detecting network intrusions such as portscanners. In view of the fact that such algorithms are usually analyzed based on intuitive approximation or asymptotic analysis, we develop an exact computational method for the performance analysis of such algorithms. Our method can be used to calculate the probability of false alarm and average detection time up to arbitrarily pre-specified accuracy.

Performance of 12 DIR algorithms in low-contrast regions for mass and density conserving deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yeo, U. J.; Supple, J. R.; Franich, R. D.

2013-10-15

Purpose: Deformable image registration (DIR) has become a key tool for adaptive radiotherapy to account for inter- and intrafraction organ deformation. Of contemporary interest, the application to deformable dose accumulation requires accurate deformation even in low contrast regions where dose gradients may exist within near-uniform tissues. One expects high-contrast features to generally be deformed more accurately by DIR algorithms. The authors systematically assess the accuracy of 12 DIR algorithms and quantitatively examine, in particular, low-contrast regions, where accuracy has not previously been established.Methods: This work investigates DIR algorithms in three dimensions using deformable gel (DEFGEL) [U. J. Yeo, M. L.more » Taylor, L. Dunn, R. L. Smith, T. Kron, and R. D. Franich, “A novel methodology for 3D deformable dosimetry,” Med. Phys. 39, 2203–2213 (2012)], for application to mass- and density-conserving deformations. CT images of DEFGEL phantoms with 16 fiducial markers (FMs) implanted were acquired in deformed and undeformed states for three different representative deformation geometries. Nonrigid image registration was performed using 12 common algorithms in the public domain. The optimum parameter setup was identified for each algorithm and each was tested for deformation accuracy in three scenarios: (I) original images of the DEFGEL with 16 FMs; (II) images with eight of the FMs mathematically erased; and (III) images with all FMs mathematically erased. The deformation vector fields obtained for scenarios II and III were then applied to the original images containing all 16 FMs. The locations of the FMs estimated by the algorithms were compared to actual locations determined by CT imaging. The accuracy of the algorithms was assessed by evaluation of three-dimensional vectors between true marker locations and predicted marker locations.Results: The mean magnitude of 16 error vectors per sample ranged from 0.3 to 3.7, 1.0 to 6.3, and 1.3 to 7.5 mm across algorithms for scenarios I to III, respectively. The greatest accuracy was exhibited by the original Horn and Schunck optical flow algorithm. In this case, for scenario III (erased FMs not contributing to driving the DIR calculation), the mean error was half that of the modified demons algorithm (which exhibited the greatest error), across all deformations. Some algorithms failed to reproduce the geometry at all, while others accurately deformed high contrast features but not low-contrast regions—indicating poor interpolation between landmarks.Conclusions: The accuracy of DIR algorithms was quantitatively evaluated using a tissue equivalent, mass, and density conserving DEFGEL phantom. For the model studied, optical flow algorithms performed better than demons algorithms, with the original Horn and Schunck performing best. The degree of error is influenced more by the magnitude of displacement than the geometric complexity of the deformation. As might be expected, deformation is estimated less accurately for low-contrast regions than for high-contrast features, and the method presented here allows quantitative analysis of the differences. The evaluation of registration accuracy through observation of the same high contrast features that drive the DIR calculation is shown to be circular and hence misleading.« less

A robust human face detection algorithm

NASA Astrophysics Data System (ADS)

Raviteja, Thaluru; Karanam, Srikrishna; Yeduguru, Dinesh Reddy V.

2012-01-01

Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.

Detection of suspicious pain regions on a digital infrared thermal image using the multimodal function optimization.

PubMed

Lee, Junghoon; Lee, Joosung; Song, Sangha; Lee, Hyunsook; Lee, Kyoungjoung; Yoon, Youngro

2008-01-01

Automatic detection of suspicious pain regions is very useful in the medical digital infrared thermal imaging research area. To detect those regions, we use the SOFES (Survival Of the Fitness kind of the Evolution Strategy) algorithm which is one of the multimodal function optimization methods. We apply this algorithm to famous diseases, such as a foot of the glycosuria, the degenerative arthritis and the varicose vein. The SOFES algorithm is available to detect some hot spots or warm lines as veins. And according to a hundred of trials, the algorithm is very fast to converge.

Biased normalized cuts for target detection in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Xuewen; Dorado-Munoz, Leidy P.; Messinger, David W.; Cahill, Nathan D.

2016-05-01

The Biased Normalized Cuts (BNC) algorithm is a useful technique for detecting targets or objects in RGB imagery. In this paper, we propose modifying BNC for the purpose of target detection in hyperspectral imagery. As opposed to other target detection algorithms that typically encode target information prior to dimensionality reduction, our proposed algorithm encodes target information after dimensionality reduction, enabling a user to detect different targets in interactive mode. To assess the proposed BNC algorithm, we utilize hyperspectral imagery (HSI) from the SHARE 2012 data campaign, and we explore the relationship between the number and the position of expert-provided target labels and the precision/recall of the remaining targets in the scene.

Algorithmic detectability threshold of the stochastic block model

NASA Astrophysics Data System (ADS)

Kawamoto, Tatsuro

2018-03-01

The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.

Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

2016-01-01

This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. PMID:27347978

Detection of spontaneous vesicle release at individual synapses using multiple wavelets in a CWT-based algorithm.

PubMed

Sokoll, Stefan; Tönnies, Klaus; Heine, Martin

2012-01-01

In this paper we present an algorithm for the detection of spontaneous activity at individual synapses in microscopy images. By employing the optical marker pHluorin, we are able to visualize synaptic vesicle release with a spatial resolution in the nm range in a non-invasive manner. We compute individual synaptic signals from automatically segmented regions of interest and detect peaks that represent synaptic activity using a continuous wavelet transform based algorithm. As opposed to standard peak detection algorithms, we employ multiple wavelets to match all relevant features of the peak. We evaluate our multiple wavelet algorithm (MWA) on real data and assess the performance on synthetic data over a wide range of signal-to-noise ratios.

Automated detection of hospital outbreaks: A systematic review of methods.

PubMed

Leclère, Brice; Buckeridge, David L; Boëlle, Pierre-Yves; Astagneau, Pascal; Lepelletier, Didier

2017-01-01

Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results. We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies. Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%. Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results.

A service relation model for web-based land cover change detection

NASA Astrophysics Data System (ADS)

Xing, Huaqiao; Chen, Jun; Wu, Hao; Zhang, Jun; Li, Songnian; Liu, Boyu

2017-10-01

Change detection with remotely sensed imagery is a critical step in land cover monitoring and updating. Although a variety of algorithms or models have been developed, none of them can be universal for all cases. The selection of appropriate algorithms and construction of processing workflows depend largely on the expertise of experts about the "algorithm-data" relations among change detection algorithms and the imagery data used. This paper presents a service relation model for land cover change detection by integrating the experts' knowledge about the "algorithm-data" relations into the web-based geo-processing. The "algorithm-data" relations are mapped into a set of web service relations with the analysis of functional and non-functional service semantics. These service relations are further classified into three different levels, i.e., interface, behavior and execution levels. A service relation model is then established using the Object and Relation Diagram (ORD) approach to represent the multi-granularity services and their relations for change detection. A set of semantic matching rules are built and used for deriving on-demand change detection service chains from the service relation model. A web-based prototype system is developed in .NET development environment, which encapsulates nine change detection and pre-processing algorithms and represents their service relations as an ORD. Three test areas from Shandong and Hebei provinces, China with different imagery conditions are selected for online change detection experiments, and the results indicate that on-demand service chains can be generated according to different users' demands.

Mathematical detection of aortic valve opening (B point) in impedance cardiography: A comparison of three popular algorithms.

PubMed

Árbol, Javier Rodríguez; Perakakis, Pandelis; Garrido, Alba; Mata, José Luis; Fernández-Santaella, M Carmen; Vila, Jaime

2017-03-01

The preejection period (PEP) is an index of left ventricle contractility widely used in psychophysiological research. Its computation requires detecting the moment when the aortic valve opens, which coincides with the B point in the first derivative of impedance cardiogram (ICG). Although this operation has been traditionally made via visual inspection, several algorithms based on derivative calculations have been developed to enable an automatic performance of the task. However, despite their popularity, data about their empirical validation are not always available. The present study analyzes the performance in the estimation of the aortic valve opening of three popular algorithms, by comparing their performance with the visual detection of the B point made by two independent scorers. Algorithm 1 is based on the first derivative of the ICG, Algorithm 2 on the second derivative, and Algorithm 3 on the third derivative. Algorithm 3 showed the highest accuracy rate (78.77%), followed by Algorithm 1 (24.57%) and Algorithm 2 (13.82%). In the automatic computation of PEP, Algorithm 2 resulted in significantly more missed cycles (48.57%) than Algorithm 1 (6.3%) and Algorithm 3 (3.5%). Algorithm 2 also estimated a significantly lower average PEP (70 ms), compared with the values obtained by Algorithm 1 (119 ms) and Algorithm 3 (113 ms). Our findings indicate that the algorithm based on the third derivative of the ICG performs significantly better. Nevertheless, a visual inspection of the signal proves indispensable, and this article provides a novel visual guide to facilitate the manual detection of the B point. © 2016 Society for Psychophysiological Research.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Constraints on a scale-dependent bias from galaxy clustering

NASA Astrophysics Data System (ADS)

Amendola, L.; Menegoni, E.; Di Porto, C.; Corsi, M.; Branchini, E.

2017-01-01

We forecast the future constraints on scale-dependent parametrizations of galaxy bias and their impact on the estimate of cosmological parameters from the power spectrum of galaxies measured in a spectroscopic redshift survey. For the latter we assume a wide survey at relatively large redshifts, similar to the planned Euclid survey, as the baseline for future experiments. To assess the impact of the bias we perform a Fisher matrix analysis, and we adopt two different parametrizations of scale-dependent bias. The fiducial models for galaxy bias are calibrated using mock catalogs of H α emitting galaxies mimicking the expected properties of the objects that will be targeted by the Euclid survey. In our analysis we have obtained two main results. First of all, allowing for a scale-dependent bias does not significantly increase the errors on the other cosmological parameters apart from the rms amplitude of density fluctuations, σ8 , and the growth index γ , whose uncertainties increase by a factor up to 2, depending on the bias model adopted. Second, we find that the accuracy in the linear bias parameter b0 can be estimated to within 1%-2% at various redshifts regardless of the fiducial model. The nonlinear bias parameters have significantly large errors that depend on the model adopted. Despite this, in the more realistic scenarios departures from the simple linear bias prescription can be detected with a ˜2 σ significance at each redshift explored. Finally, we use the Fisher matrix formalism to assess the impact od assuming an incorrect bias model and find that the systematic errors induced on the cosmological parameters are similar or even larger than the statistical ones.

Four-dimensional measurement of the displacement of internal fiducial and skin markers during 320-multislice computed tomography scanning of breast cancer.

PubMed

Yamashita, Hideomi; Okuma, Kae; Tada, Keiichiro; Shiraishi, Kenshiro; Takahashi, Wataru; Shibata-Mobayashi, Shino; Sakumi, Akira; Saotome, Naoya; Haga, Akihiro; Onoe, Tsuyoshi; Ino, Kenji; Akahane, Masaaki; Ohtomo, Kuni; Nakagawa, Keiichi

2012-10-01

To study the three-dimensional movement of internal tumor bed fiducial and breast skin markers, using 320-multislice computed tomography (CT); and to analyze intrafractional errors for breast cancer patients undergoing breast irradiation. This study examined 280 markers on the skin of the breast (200 markers) and on the primary tumor bed (80 markers) of 20 patients treated by external-beam photon radiotherapy. Motion assessment was analyzed in 41 respiratory phases during 20 s of cine CT in the radiotherapy position. To assess intrafractional errors resulting from respiratory motion, four-dimensional CT scans were acquired for 20 patients. Motion in the anterior-posterior (A/P) and superior-inferior (S/I) directions showed a strong correlation (|r| > 0.7) with the respiratory curve for most markers (79% and 70%, respectively). The average marker displacements between maximum and minimum value during 20 s for the 200 breast skin metal markers were 1.1 ± 0.3 mm, 2.1 ± 0.6 mm, and 1.6 ± 0.4 mm in the left-right, A/P, and S/I directions, respectively. For the 80 tumor bed clips, displacements were 0.9 ± 0.2 mm in left-right, 1.7 ± 0.5 mm in A/P, and 1.1 ± 0.3 mm in S/I. There was no significant difference in the motion between breast quadrant regions or between the primary site and the other regions. Motion in primary breast tumors was evaluated with 320-multislice CT. Very little change was detected during individual radiation treatment fractions. Copyright © 2012 Elsevier Inc. All rights reserved.

Prospects for Chemically Tagging Stars in the Galaxy

NASA Astrophysics Data System (ADS)

Ting, Yuan-Sen; Conroy, Charlie; Goodman, Alyssa

2015-07-01

It is now well-established that the elemental abundance patterns of stars hold key clues not only to their formation, but also to the assembly histories of galaxies. One of the most exciting possibilities is the use of stellar abundance patterns as “chemical tags” to identify stars that were born in the same molecular cloud. In this paper, we assess the prospects of chemical tagging as a function of several key underlying parameters. We show that in the fiducial case of 104 distinct cells in chemical space and {10}5-{10}6 stars in the survey, one can expect to detect ∼ {10}2-{10}3 groups that are ≥slant 5σ overdensities in the chemical space. However, we find that even very large overdensities in chemical space do not guarantee that the overdensity is due to a single set of stars from a common birth cloud. In fact, for our fiducial model parameters, the typical 5σ overdensity is comprised of stars from a wide range of clusters with the most dominant cluster contributing only 25% of the stars. The most important factors limiting the identification of disrupted clusters via chemical tagging are the number of chemical cells in the chemical space and the survey sampling rate of the underlying stellar population. Both of these factors can be improved through strategic observational plans. While recovering individual clusters through chemical tagging may prove challenging, we show, in agreement with previous work, that different CMFs imprint different degrees of clumpiness in chemical space. These differences provide the opportunity to statistically reconstruct the slope and high-mass cutoff of CMF and its evolution through cosmic time.

An Application of Multi-band Forced Photometry to One Square Degree of SERVS: Accurate Photometric Redshifts and Implications for Future Science

NASA Astrophysics Data System (ADS)

Nyland, Kristina; Lacy, Mark; Sajina, Anna; Pforr, Janine; Farrah, Duncan; Wilson, Gillian; Surace, Jason; Häußler, Boris; Vaccari, Mattia; Jarvis, Matt

2017-05-01

We apply The Tractor image modeling code to improve upon existing multi-band photometry for the Spitzer Extragalactic Representative Volume Survey (SERVS). SERVS consists of post-cryogenic Spitzer observations at 3.6 and 4.5 μm over five well-studied deep fields spanning 18 deg2. In concert with data from ground-based near-infrared (NIR) and optical surveys, SERVS aims to provide a census of the properties of massive galaxies out to z ≈ 5. To accomplish this, we are using The Tractor to perform “forced photometry.” This technique employs prior measurements of source positions and surface brightness profiles from a high-resolution fiducial band from the VISTA Deep Extragalactic Observations survey to model and fit the fluxes at lower-resolution bands. We discuss our implementation of The Tractor over a square-degree test region within the XMM Large Scale Structure field with deep imaging in 12 NIR/optical bands. Our new multi-band source catalogs offer a number of advantages over traditional position-matched catalogs, including (1) consistent source cross-identification between bands, (2) de-blending of sources that are clearly resolved in the fiducial band but blended in the lower resolution SERVS data, (3) a higher source detection fraction in each band, (4) a larger number of candidate galaxies in the redshift range 5 < z < 6, and (5) a statistically significant improvement in the photometric redshift accuracy as evidenced by the significant decrease in the fraction of outliers compared to spectroscopic redshifts. Thus, forced photometry using The Tractor offers a means of improving the accuracy of multi-band extragalactic surveys designed for galaxy evolution studies. We will extend our application of this technique to the full SERVS footprint in the future.

Leveraging disjoint communities for detecting overlapping community structure

NASA Astrophysics Data System (ADS)

Chakraborty, Tanmoy

2015-05-01

Network communities represent mesoscopic structure for understanding the organization of real-world networks, where nodes often belong to multiple communities and form overlapping community structure in the network. Due to non-triviality in finding the exact boundary of such overlapping communities, this problem has become challenging, and therefore huge effort has been devoted to detect overlapping communities from the network. In this paper, we present PVOC (Permanence based Vertex-replication algorithm for Overlapping Community detection), a two-stage framework to detect overlapping community structure. We build on a novel observation that non-overlapping community structure detected by a standard disjoint community detection algorithm from a network has high resemblance with its actual overlapping community structure, except the overlapping part. Based on this observation, we posit that there is perhaps no need of building yet another overlapping community finding algorithm; but one can efficiently manipulate the output of any existing disjoint community finding algorithm to obtain the required overlapping structure. We propose a new post-processing technique that by combining with any existing disjoint community detection algorithm, can suitably process each vertex using a new vertex-based metric, called permanence, and thereby finds out overlapping candidates with their community memberships. Experimental results on both synthetic and large real-world networks show that PVOC significantly outperforms six state-of-the-art overlapping community detection algorithms in terms of high similarity of the output with the ground-truth structure. Thus our framework not only finds meaningful overlapping communities from the network, but also allows us to put an end to the constant effort of building yet another overlapping community detection algorithm.

Indoor localization using pedestrian dead reckoning updated with RFID-based fiducials.

PubMed

House, Samuel; Connell, Sean; Milligan, Ian; Austin, Daniel; Hayes, Tamara L; Chiang, Patrick

2011-01-01

We describe a low-cost wearable system that tracks the location of individuals indoors using commonly available inertial navigation sensors fused with radio frequency identification (RFID) tags placed around the smart environment. While conventional pedestrian dead reckoning (PDR) calculated with an inertial measurement unit (IMU) is susceptible to sensor drift inaccuracies, the proposed wearable prototype fuses the drift-sensitive IMU with a RFID tag reader. Passive RFID tags placed throughout the smart-building then act as fiducial markers that update the physical locations of each user, thereby correcting positional errors and sensor inaccuracy. Experimental measurements taken for a 55 m × 20 m 2D floor space indicate an over 1200% improvement in average error rate of the proposed RFID-fused system over dead reckoning alone.

Test of the Chevallier-Polarski-Linder parametrization for rapid dark energy equation of state transitions

NASA Astrophysics Data System (ADS)

Linden, Sebastian; Virey, Jean-Marc

2008-07-01

We test the robustness and flexibility of the Chevallier-Polarski-Linder (CPL) parametrization of the dark energy equation of state w(z)=w0+wa(z)/(1+z) in recovering a four-parameter steplike fiducial model. We constrain the parameter space region of the underlying fiducial model where the CPL parametrization offers a reliable reconstruction. It turns out that non-negligible biases leak into the results for recent (z<2.5) rapid transitions, but that CPL yields a good reconstruction in all other cases. The presented analysis is performed with supernova Ia data as forecasted for a space mission like SNAP/JDEM, combined with future expectations for the cosmic microwave background shift parameter R and the baryonic acoustic oscillation parameter A.

Measurement of W±W± vector-boson scattering and limits on anomalous quartic gauge couplings with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao de Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisen, M.; Geisler, M. P.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghazlane, H.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de La Hoz, S.; Gonzalez Parra, G.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Grafström, P.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Grohs, J. P.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Hadef, A.; Hageböck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Hellman, S.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herget, V.; Hernández Jiménez, Y.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Hickling, R.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hinman, R. R.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Ince, T.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, B.; Jackson, P.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansky, R.; Janssen, J.; Janus, M.; Jarlskog, G.; Javadov, N.; Javå¯Rek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, W. J.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneti, S.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kapliy, A.; Kar, D.; Karakostas, K.; Karamaoun, A.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-Zada, F.; Khanov, A.; Kharlamov, A. G.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; King, M.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolanoski, H.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Kravchenko, A.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunigo, T.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; Leblanc, M.; Lecompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Leontsinis, S.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Leyko, A. M.; Leyton, M.; Li, B.; Li, C.; Li, H.; Li, H. L.; Li, L.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, H.; Liu, H.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Lockman, W. S.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopes, L.; Lopez Mateos, D.; Lopez Paredes, B.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; MacDonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, B.; Mandelli, L.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti-Garcia, S.; Martin, B.; Martin, T. A.; Martin, V. J.; Martin Dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marx, M.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; McFayden, J. A.; McHedlidze, G.; McMahon, S. J.; McPherson, R. A.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Melo, M.; Meloni, F.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Mochizuki, K.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Mosidze, M.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Mueller, T.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murillo Quijada, J. A.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Grady, F.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosenthal, O.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sandhoff, M.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-07-01

This paper presents the extended results of measurements of W±W±j j production and limits on anomalous quartic gauge couplings using 20.3 fb-1 of proton-proton collision data at √{s }=8 TeV recorded by the ATLAS detector at the Large Hadron Collider. Events with two leptons (e or μ ) with the same electric charge and at least two jets are analyzed. Production cross sections are determined in two fiducial regions, with different sensitivities to the electroweak and strong production mechanisms. An additional fiducial region, particularly sensitive to anomalous quartic gauge coupling parameters α4 and α5, is introduced, which allows more stringent limits on these parameters compared to the previous ATLAS measurement.

Cross-instrument Analysis Correlation Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

McJunkin, Timothy R.

This program has been designed to assist with the tracking of a sample from one analytical instrument to another such as SEM, microscopes, micro x-ray diffraction and other instruments where particular positions/locations on the sample are examined, photographed, etc. The software is designed to easily enter the position of fiducials and locations of interest such that in a future session in the same of different instrument the positions of interest can be re-found through using the known location fiducials in the current and reference session to transform the point into the current sessions coordinate system. The software is dialog boxmore » driven guiding the user through the necessary data entry and program choices. Information is stored in a series of text based extensible markup language (XML) files.« less

High reliability - low noise radionuclide signature identification algorithms for border security applications

NASA Astrophysics Data System (ADS)

Lee, Sangkyu

Illicit trafficking and smuggling of radioactive materials and special nuclear materials (SNM) are considered as one of the most important recent global nuclear threats. Monitoring the transport and safety of radioisotopes and SNM are challenging due to their weak signals and easy shielding. Great efforts worldwide are focused at developing and improving the detection technologies and algorithms, for accurate and reliable detection of radioisotopes of interest in thus better securing the borders against nuclear threats. In general, radiation portal monitors enable detection of gamma and neutron emitting radioisotopes. Passive or active interrogation techniques, present and/or under the development, are all aimed at increasing accuracy, reliability, and in shortening the time of interrogation as well as the cost of the equipment. Equally important efforts are aimed at advancing algorithms to process the imaging data in an efficient manner providing reliable "readings" of the interiors of the examined volumes of various sizes, ranging from cargos to suitcases. The main objective of this thesis is to develop two synergistic algorithms with the goal to provide highly reliable - low noise identification of radioisotope signatures. These algorithms combine analysis of passive radioactive detection technique with active interrogation imaging techniques such as gamma radiography or muon tomography. One algorithm consists of gamma spectroscopy and cosmic muon tomography, and the other algorithm is based on gamma spectroscopy and gamma radiography. The purpose of fusing two detection methodologies per algorithm is to find both heavy-Z radioisotopes and shielding materials, since radionuclides can be identified with gamma spectroscopy, and shielding materials can be detected using muon tomography or gamma radiography. These combined algorithms are created and analyzed based on numerically generated images of various cargo sizes and materials. In summary, the three detection methodologies are fused into two algorithms with mathematical functions providing: reliable identification of radioisotopes in gamma spectroscopy; noise reduction and precision enhancement in muon tomography; and the atomic number and density estimation in gamma radiography. It is expected that these new algorithms maybe implemented at portal scanning systems with the goal to enhance the accuracy and reliability in detecting nuclear materials inside the cargo containers.

Searching Information Sources in Networks

DTIC Science & Technology

2017-06-14

SECURITY CLASSIFICATION OF: During the course of this project, we made significant progresses in multiple directions of the information detection...result on information source detection on non-tree networks; (2) The development of information source localization algorithms to detect multiple... information sources. The algorithms have provable performance guarantees and outperform existing algorithms in 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND

LPA-CBD an improved label propagation algorithm based on community belonging degree for community detection

NASA Astrophysics Data System (ADS)

Gui, Chun; Zhang, Ruisheng; Zhao, Zhili; Wei, Jiaxuan; Hu, Rongjing

In order to deal with stochasticity in center node selection and instability in community detection of label propagation algorithm, this paper proposes an improved label propagation algorithm named label propagation algorithm based on community belonging degree (LPA-CBD) that employs community belonging degree to determine the number and the center of community. The general process of LPA-CBD is that the initial community is identified by the nodes with the maximum degree, and then it is optimized or expanded by community belonging degree. After getting the rough structure of network community, the remaining nodes are labeled by using label propagation algorithm. The experimental results on 10 real-world networks and three synthetic networks show that LPA-CBD achieves reasonable community number, better algorithm accuracy and higher modularity compared with other four prominent algorithms. Moreover, the proposed algorithm not only has lower algorithm complexity and higher community detection quality, but also improves the stability of the original label propagation algorithm.

QuateXelero: An Accelerated Exact Network Motif Detection Algorithm

PubMed Central

Khakabimamaghani, Sahand; Sharafuddin, Iman; Dichter, Norbert; Koch, Ina; Masoudi-Nejad, Ali

2013-01-01

Finding motifs in biological, social, technological, and other types of networks has become a widespread method to gain more knowledge about these networks’ structure and function. However, this task is very computationally demanding, because it is highly associated with the graph isomorphism which is an NP problem (not known to belong to P or NP-complete subsets yet). Accordingly, this research is endeavoring to decrease the need to call NAUTY isomorphism detection method, which is the most time-consuming step in many existing algorithms. The work provides an extremely fast motif detection algorithm called QuateXelero, which has a Quaternary Tree data structure in the heart. The proposed algorithm is based on the well-known ESU (FANMOD) motif detection algorithm. The results of experiments on some standard model networks approve the overal superiority of the proposed algorithm, namely QuateXelero, compared with two of the fastest existing algorithms, G-Tries and Kavosh. QuateXelero is especially fastest in constructing the central data structure of the algorithm from scratch based on the input network. PMID:23874498

Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences

NASA Technical Reports Server (NTRS)

Budalakoti, Suratna; Srivastava, Ashok N.; Akella, Ram; Turkov, Eugene

2006-01-01

This paper addresses the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. The approach taken uses unsupervised clustering of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by detailed analysis of outliers to detect anomalies. As the LCS measure is expensive to compute, the first part of the paper discusses existing algorithms, such as the Hunt-Szymanski algorithm, that have low time-complexity. We then discuss why these algorithms often do not work well in practice and present a new hybrid algorithm for computing the LCS that, in our tests, outperforms the Hunt-Szymanski algorithm by a factor of five. The second part of the paper presents new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. The algorithms provide a coherent description to an analyst of the anomalies in the sequence, compared to more normal sequences. The algorithms we present are general and domain-independent, so we discuss applications in related areas such as anomaly detection.

Robust Kalman filter design for predictive wind shear detection

NASA Technical Reports Server (NTRS)

Stratton, Alexander D.; Stengel, Robert F.

1991-01-01

Severe, low-altitude wind shear is a threat to aviation safety. Airborne sensors under development measure the radial component of wind along a line directly in front of an aircraft. In this paper, optimal estimation theory is used to define a detection algorithm to warn of hazardous wind shear from these sensors. To achieve robustness, a wind shear detection algorithm must distinguish threatening wind shear from less hazardous gustiness, despite variations in wind shear structure. This paper presents statistical analysis methods to refine wind shear detection algorithm robustness. Computational methods predict the ability to warn of severe wind shear and avoid false warning. Comparative capability of the detection algorithm as a function of its design parameters is determined, identifying designs that provide robust detection of severe wind shear.

Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices.

PubMed

Gradl, Stefan; Kugler, Patrick; Lohmuller, Clemens; Eskofier, Bjoern

2012-01-01

We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the Pan-Tompkins algorithm for QRS-detection and contains further algorithm blocks to detect abnormal heartbeats. The algorithm was validated using the MIT-BIH Arrhythmia and MIT-BIH Supraventricular Arrhythmia databases. More than 99% of all QRS complexes were detected correctly by the algorithm. Overall sensitivity for abnormal beat detection was 89.5% with a specificity of 80.6%. The application is available for download and may be used for real-time ECG-monitoring on mobile devices.

Accurate derivation of heart rate variability signal for detection of sleep disordered breathing in children.

PubMed

Chatlapalli, S; Nazeran, H; Melarkod, V; Krishnam, R; Estrada, E; Pamula, Y; Cabrera, S

2004-01-01

The electrocardiogram (ECG) signal is used extensively as a low cost diagnostic tool to provide information concerning the heart's state of health. Accurate determination of the QRS complex, in particular, reliable detection of the R wave peak, is essential in computer based ECG analysis. ECG data from Physionet's Sleep-Apnea database were used to develop, test, and validate a robust heart rate variability (HRV) signal derivation algorithm. The HRV signal was derived from pre-processed ECG signals by developing an enhanced Hilbert transform (EHT) algorithm with built-in missing beat detection capability for reliable QRS detection. The performance of the EHT algorithm was then compared against that of a popular Hilbert transform-based (HT) QRS detection algorithm. Autoregressive (AR) modeling of the HRV power spectrum for both EHT- and HT-derived HRV signals was achieved and different parameters from their power spectra as well as approximate entropy were derived for comparison. Poincare plots were then used as a visualization tool to highlight the detection of the missing beats in the EHT method After validation of the EHT algorithm on ECG data from the Physionet, the algorithm was further tested and validated on a dataset obtained from children undergoing polysomnography for detection of sleep disordered breathing (SDB). Sensitive measures of accurate HRV signals were then derived to be used in detecting and diagnosing sleep disordered breathing in children. All signal processing algorithms were implemented in MATLAB. We present a description of the EHT algorithm and analyze pilot data for eight children undergoing nocturnal polysomnography. The pilot data demonstrated that the EHT method provides an accurate way of deriving the HRV signal and plays an important role in extraction of reliable measures to distinguish between periods of normal and sleep disordered breathing (SDB) in children.

Algorithm for detection the QRS complexes based on support vector machine

NASA Astrophysics Data System (ADS)

Van, G. V.; Podmasteryev, K. V.

2017-11-01

The efficiency of computer ECG analysis depends on the accurate detection of QRS-complexes. This paper presents an algorithm for QRS complex detection based of support vector machine (SVM). The proposed algorithm is evaluated on annotated standard databases such as MIT-BIH Arrhythmia database. The QRS detector obtained a sensitivity Se = 98.32% and specificity Sp = 95.46% for MIT-BIH Arrhythmia database. This algorithm can be used as the basis for the software to diagnose electrical activity of the heart.

Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.

PubMed

Sabherwal, Pooja; Singh, Latika; Agrawal, Monika

2018-03-30

In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.

Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees

NASA Astrophysics Data System (ADS)

Khryashchev, V. V.; Lebedev, A. A.; Priorov, A. L.

2017-05-01

Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.