Clustering Categorical Data Using Community Detection Techniques
2017-01-01
With the advent of the k-modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in k-modes makes it hard to reach a good clustering without resorting to many trials. Recently proposed methods for better initialization are deterministic and reduce the clustering cost considerably. A variety of initialization methods differ in how the heuristics chooses the set of initial centers. In this paper, we address the clustering problem for categorical data from the perspective of community detection. Instead of initializing k modes and running several iterations, our scheme, CD-Clustering, builds an unweighted graph and detects highly cohesive groups of nodes using a fast community detection technique. The top-k detected communities by size will define the k modes. Evaluation on ten real categorical datasets shows that our method outperforms the existing initialization methods for k-modes in terms of accuracy, precision, and recall in most of the cases. PMID:29430249
Faint Debris Detection by Particle Based Track-Before-Detect Method
NASA Astrophysics Data System (ADS)
Uetsuhara, M.; Ikoma, N.
2014-09-01
This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired during observation campaigns dedicated to GEO breakup fragments, which would contain a sufficient number of faint debris images. The results indicate the proposed method is capable of tracking faint debris with moderate computational costs at operational level.
A Track Initiation Method for the Underwater Target Tracking Environment
NASA Astrophysics Data System (ADS)
Li, Dong-dong; Lin, Yang; Zhang, Yao
2018-04-01
A novel efficient track initiation method is proposed for the harsh underwater target tracking environment (heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method (TSEPM). Track initiation demands that the method should determine the existence and initial state of a target quickly and correctly. Heavy clutter and large measurement errors certainly pose additional difficulties and challenges, which deteriorate and complicate the track initiation in the harsh underwater target tracking environment. There are three primary shortcomings for the current track initiation methods to initialize a target: (a) they cannot eliminate the turbulences of clutter effectively; (b) there may be a high false alarm probability and low detection probability of a track; (c) they cannot estimate the initial state for a new confirmed track correctly. Based on the multiple hypotheses tracking principle and modified logic-based track initiation method, in order to increase the detection probability of a track, track splitting creates a large number of tracks which include the true track originated from the target. And in order to decrease the false alarm probability, based on the evaluation mechanism, track pruning and track merging are proposed to reduce the false tracks. TSEPM method can deal with the track initiation problems derived from heavy clutter and large measurement errors, determine the target's existence and estimate its initial state with the least squares method. What's more, our method is fully automatic and does not require any kind manual input for initializing and tuning any parameter. Simulation results indicate that our new method improves significantly the performance of the track initiation in the harsh underwater target tracking environment.
Detecting and treating occlusal caries lesions: a cost-effectiveness analysis.
Schwendicke, F; Stolpe, M; Meyer-Lueckel, H; Paris, S
2015-02-01
The health gains and costs resulting from using different caries detection strategies might not only depend on the accuracy of the used method but also the treatment emanating from its use in different populations. We compared combinations of visual-tactile, radiographic, or laser-fluorescence-based detection methods with 1 of 3 treatments (non-, micro-, and invasive treatment) initiated at different cutoffs (treating all or only dentinal lesions) in populations with low or high caries prevalence. A Markov model was constructed to follow an occlusal surface in a permanent molar in an initially 12-y-old male German patient over his lifetime. Prevalence data and transition probabilities were extracted from the literature, while validity parameters of different methods were synthesized or obtained from systematic reviews. Microsimulations were performed to analyze the model, assuming a German health care setting and a mixed public-private payer perspective. Radiographic and fluorescence-based methods led to more overtreatments, especially in populations with low prevalence. For the latter, combining visual-tactile or radiographic detection with microinvasive treatment retained teeth longest (mean 66 y) at lowest costs (329 and 332 Euro, respectively), while combining radiographic or fluorescence-based detections with invasive treatment was the least cost-effective (<60 y, >700 Euro). In populations with high prevalence, combining radiographic detection with microinvasive treatment was most cost-effective (63 y, 528 Euro), while sensitive detection methods combined with invasive treatments were again the least cost-effective (<59 y, >690 Euro). The suitability of detection methods differed significantly between populations, and the cost-effectiveness was greatly influenced by the treatment initiated after lesion detection. The accuracy of a detection method relative to a "gold standard" did not automatically convey into better health or reduced costs. Detection methods should be evaluated not only against their criterion validity but also the long-term effects resulting from their use in different populations. © International & American Associations for Dental Research 2014.
A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image
NASA Astrophysics Data System (ADS)
Barat, Christian; Phlypo, Ronald
2010-12-01
We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.
Chen, Shuo-Tsung; Wang, Tzung-Dau; Lee, Wen-Jeng; Huang, Tsai-Wei; Hung, Pei-Kai; Wei, Cheng-Yu; Chen, Chung-Ming; Kung, Woon-Man
2015-01-01
Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.
Nanostructure-initiator mass spectrometry biometrics
Leclerc, Marion; Bowen, Benjamin; Northen, Trent
2015-09-08
Several embodiments described herein are drawn to methods of identifying an analyte on a subject's skin, methods of generating a fingerprint, methods of determining a physiological change in a subject, methods of diagnosing health status of a subject, and assay systems for detecting an analyte and generating a fingerprint, by nanostructure-initiator mass spectrometry (NIMS).
Computer-aided detection of initial polyp candidates with level set-based adaptive convolution
NASA Astrophysics Data System (ADS)
Zhu, Hongbin; Duan, Chaijie; Liang, Zhengrong
2009-02-01
In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.
Cheng, Mengzhu; Wang, Lihong; Yang, Qing; Huang, Xiaohua
2018-08-30
The pollution of rare earth elements (REEs) in ecosystem is becoming more and more serious, so it is urgent to establish methods for monitoring the pollution of REEs. Monitoring environmental pollution via the response of plants to pollutants has become the most stable and accurate method compared with traditional methods, but scientists still need to find the primary response of plants to pollutants to improve the sensitivity and speed of this method. Based on the facts that the initiation of endocytosis is the primary cellular response of the plant leaf cells to REEs and the detection of endocytosis is complex and expensive, we constructed a detection method in living plant cells for rapidly monitoring the response of plants to exogenous lanthanum [La(III), a representative of REEs] by designing a new immuno-electrochemical method for detecting the content change in extracellular vitronectin-like protein (VN) that are closely related to endocytosis. Results showed that when 30 μM La(III) initiated a small amount of endocytosis, the content of extracellular VN increased by 5.46 times, but the structure and function of plasma membrane were not interfered by La(III); when 80 μM La(III) strongly initiated a large amount of endocytosis, the content of extracellular VN increased by 119 times, meanwhile, the structure and function of plasma membrane were damaged. In summary, the detection method can reflect the response of plants to La(III) via detecting the content change in extracellular VN, which provides an effective and convenient way to monitor the response of plants to exogenous REEs. Copyright © 2018. Published by Elsevier Inc.
NASA Astrophysics Data System (ADS)
Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining
2017-12-01
We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.
Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning
2012-01-01
In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464
Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning
2012-01-01
In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.
The Applications of Gold Nanoparticle-Initialed Chemiluminescence in Biomedical Detection
NASA Astrophysics Data System (ADS)
Liu, Zezhong; Zhao, Furong; Gao, Shandian; Shao, Junjun; Chang, Huiyun
2016-10-01
Chemiluminescence technique as a novel detection method has gained much attention in recent years owning to the merits of high sensitivity, wider linear ranges, and low background signal. Similarly, nanotechnology especially for gold nanoparticles has emerged as detection tools due to their unique physical and chemical properties. Recently, it has become increasingly popular to couple gold nanoparticles with chemiluminescence technique in biological agents' detection. In this review, we describe the superiority of both chemiluminescence and gold nanoparticles and conclude the different applications of gold nanoparticle-initialed chemiluminescence in biomedical detection.
An analysis of automatic human detection and tracking
NASA Astrophysics Data System (ADS)
Demuth, Philipe R.; Cosmo, Daniel L.; Ciarelli, Patrick M.
2015-12-01
This paper presents an automatic method to detect and follow people on video streams. This method uses two techniques to determine the initial position of the person at the beginning of the video file: one based on optical flow and the other one based on Histogram of Oriented Gradients (HOG). After defining the initial bounding box, tracking is done using four different trackers: Median Flow tracker, TLD tracker, Mean Shift tracker and a modified version of the Mean Shift tracker using HSV color space. The results of the methods presented in this paper are then compared at the end of the paper.
Long-term object tracking combined offline with online learning
NASA Astrophysics Data System (ADS)
Hu, Mengjie; Wei, Zhenzhong; Zhang, Guangjun
2016-04-01
We propose a simple yet effective method for long-term object tracking. Different from the traditional visual tracking method, which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion. To summarize, our algorithm can be roughly decomposed into an initialization stage and a tracking stage. In the initialization stage, an offline detector is trained to get the object appearance information at the category level, which is used for detecting the potential target and initializing the tracking stage. The tracking stage consists of three modules: the online tracking module, detection module, and decision module. A pretrained detector is used for maintaining drift of the online tracker, while the online tracker is used for filtering out false positive detections. A confidence selection mechanism is proposed to optimize the object location based on the online tracker and detection. If the target is lost, the pretrained detector is utilized to reinitialize the whole algorithm when the target is relocated. During experiments, we evaluate our method on several challenging video sequences, and it demonstrates huge improvement compared with detection and online tracking only.
Vision Sensor-Based Road Detection for Field Robot Navigation
Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen
2015-01-01
Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514
Ben Younes, Lassad; Nakajima, Yoshikazu; Saito, Toki
2014-03-01
Femur segmentation is well established and widely used in computer-assisted orthopedic surgery. However, most of the robust segmentation methods such as statistical shape models (SSM) require human intervention to provide an initial position for the SSM. In this paper, we propose to overcome this problem and provide a fully automatic femur segmentation method for CT images based on primitive shape recognition and SSM. Femur segmentation in CT scans was performed using primitive shape recognition based on a robust algorithm such as the Hough transform and RANdom SAmple Consensus. The proposed method is divided into 3 steps: (1) detection of the femoral head as sphere and the femoral shaft as cylinder in the SSM and the CT images, (2) rigid registration between primitives of SSM and CT image to initialize the SSM into the CT image, and (3) fitting of the SSM to the CT image edge using an affine transformation followed by a nonlinear fitting. The automated method provided good results even with a high number of outliers. The difference of segmentation error between the proposed automatic initialization method and a manual initialization method is less than 1 mm. The proposed method detects primitive shape position to initialize the SSM into the target image. Based on primitive shapes, this method overcomes the problem of inter-patient variability. Moreover, the results demonstrate that our method of primitive shape recognition can be used for 3D SSM initialization to achieve fully automatic segmentation of the femur.
Detection of chemical pollutants by passive LWIR hyperspectral imaging
NASA Astrophysics Data System (ADS)
Lavoie, Hugo; Thériault, Jean-Marc; Bouffard, François; Puckrin, Eldon; Dubé, Denis
2012-09-01
Toxic industrial chemicals (TICs) represent a major threat to public health and security. Their detection constitutes a real challenge to security and first responder's communities. One promising detection method is based on the passive standoff identification of chemical vapors emanating from the laboratory under surveillance. To investigate this method, the Department of National Defense and Public Safety Canada have mandated Defense Research and Development Canada (DRDC) - Valcartier to develop and test passive Long Wave Infrared (LWIR) hyperspectral imaging (HSI) sensors for standoff detection. The initial effort was focused to address the standoff detection and identification of toxic industrial chemicals (TICs) and precursors. Sensors such as the Multi-option Differential Detection and Imaging Fourier Spectrometer (MoDDIFS) and the Improved Compact ATmospheric Sounding Interferometer (iCATSI) were developed for this application. This paper describes the sensor developments and presents initial results of standoff detection and identification of TICs and precursors. The standoff sensors are based on the differential Fourier-transform infrared (FTIR) radiometric technology and are able to detect, spectrally resolve and identify small leak plumes at ranges in excess of 1 km. Results from a series of trials in asymmetric threat type scenarios will be presented. These results will serve to establish the potential of the method for standoff detection of TICs precursors and surrogates.
Hu, Qinqin; Fu, Yingchun; Xu, Xiahong; Qiao, Zhaohui; Wang, Ronghui; Zhang, Ying; Li, Yanbin
2016-02-07
Acrylamide (AA), a neurotoxin and a potential carcinogen, has been found in various thermally processed foods such as potato chips, biscuits, and coffee. Simple, cost-effective, and sensitive methods for the rapid detection of AA are needed to ensure food safety. Herein, a novel colorimetric method was proposed for the visual detection of AA based on a nucleophile-initiated thiol-ene Michael addition reaction. Gold nanoparticles (AuNPs) were aggregated by glutathione (GSH) because of a ligand-replacement, accompanied by a color change from red to purple. In the presence of AA, after the thiol-ene Michael addition reaction between GSH and AA with the catalysis of a nucleophile, the sulfhydryl group of GSH was consumed by AA, which hindered the subsequent ligand-replacement and the aggregation of AuNPs. Therefore, the concentration of AA could be determined by the visible color change caused by dispersion/aggregation of AuNPs. This new method showed high sensitivity with a linear range from 0.1 μmol L(-1) to 80 μmol L(-1) and a detection limit of 28.6 nmol L(-1), and especially revealed better selectivity than the fluorescence sensing method reported previously. Moreover, this new method was used to detect AA in potato chips with a satisfactory result in comparison with the standard methods based on chromatography, which indicated that the colorimetric method can be expanded for the rapid detection of AA in thermally processed foods.
DOT National Transportation Integrated Search
1979-01-01
The report describes the initial phase of a two-phase project on the visual, on-the-road detection of driving while intoxicated (DWI). The purpose of the overall project is to develop and test procedures for enhancing on-the-road detection of DWI. Th...
NASA Technical Reports Server (NTRS)
Hoadley, A. W.; Porter, A. J.
1991-01-01
The theory and experimental verification of a method of detecting fluid-mass loss, expansion-chamber pressure loss, or excessive vapor build-up in NASA's Airborne Information Management System (AIMS) are presented. The primary purpose of this leak-detection method is to detect the fluid-mass loss before the volume of vapor on the liquid side causes a temperature-critical part to be out of the liquid. The method detects the initial leak after the first 2.5 pct of the liquid mass has been lost, and it can be used for detecting subsequent situations including the leaking of air into the liquid chamber and the subsequent vapor build-up.
Fatigue crack detection and identification by the elastic wave propagation method
NASA Astrophysics Data System (ADS)
Stawiarski, Adam; Barski, Marek; Pająk, Piotr
2017-05-01
In this paper the elastic wave propagation phenomenon was used to detect the initiation of the fatigue damage in isotropic plate with a circular hole. The safety and reliability of structures mostly depend on the effectiveness of the monitoring methods. The Structural Health Monitoring (SHM) system based on the active pitch-catch measurement technique was proposed. The piezoelectric (PZT) elements was used as an actuators and sensors in the multipoint measuring system. The comparison of the intact and defected structures has been used by damage detection algorithm. One part of the SHM system has been responsible for detection of the fatigue crack initiation. The second part observed the evolution of the damage growth and assess the size of the defect. The numerical results of the wave propagation phenomenon has been used to present the effectiveness and accuracy of the proposed method. The preliminary experimental analysis has been carried out during the tension test of the aluminum plate with a circular hole to determine the efficiency of the measurement technique.
Monocular Vision-Based Underwater Object Detection
Zhang, Zhen; Dai, Fengzhao; Bu, Yang; Wang, Huibin
2017-01-01
In this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmission information. The global contrast of various features is used to initially identify the region of interest (ROI), which is then filtered by the image segmentation method, producing the final underwater object detection results. We test the performance of our method with diverse underwater datasets. Samples of the datasets are acquired by a monocular camera with different qualities (such as resolution and focal length) and setups (viewing distance, viewing angle, and optical environment). It is demonstrated that our ROI detection method is necessary and can largely remove the background noise and significantly increase the accuracy of our underwater object detection method. PMID:28771194
Comparison of methods to detect Pasteurella multocida in carrier waterfowl
Samuel, M.D.; Shadduck, D.J.; Goldberg, Diana R.; Johnson, W.P.
2003-01-01
We conducted laboratory challenge trials using mallard ducks (Anas platyrhynchos) to compare methods for detecting carriers of Pasteurella multocida, the bacterium that causes avian cholera, in wild birds. Birds that survived the initial infection were euthanized at 2-4 wk intervals up to 14 wk post challenge. Isolates of P. multocida were obtained at necropsy from 23% of the birds that survived initial infection. We found that swab samples (oral, cloacal, nasal, eye, and leg joint) were most effective for detecting carrier birds up to 14 wk post infection. No detectable differences in isolation were observed for samples stored in either 10% dimethysulfoxide or brain heart infusion broth. The frequency of detecting carriers in our challenge trials appeared to be related to mortality rates observed during the trial, but was not related to a number of other factors including time after challenge, time delays in collecting tissues postmortem, and route of infection. In our trials, there was little association between antibody levels and carrier status. We concluded that swabs samples collected from recently dead birds, stored in liquid nitrogen, and processed using selective broth provide a feasible field method for detecting P. multocida carriers in wild waterfowl.
van Stralen, Marijn; Bosch, Johan G; Voormolen, Marco M; van Burken, Gerard; Krenning, Boudewijn J; van Geuns, Robert-Jan M; Lancée, Charles T; de Jong, Nico; Reiber, Johan H C
2005-10-01
We propose a semiautomatic endocardial border detection method for three-dimensional (3D) time series of cardiac ultrasound (US) data based on pattern matching and dynamic programming, operating on two-dimensional (2D) slices of the 3D plus time data, for the estimation of full cycle left ventricular volume, with minimal user interaction. The presented method is generally applicable to 3D US data and evaluated on data acquired with the Fast Rotating Ultrasound (FRU-) Transducer, developed by Erasmus Medical Center (Rotterdam, the Netherlands), a conventional phased-array transducer, rotating at very high speed around its image axis. The detection is based on endocardial edge pattern matching using dynamic programming, which is constrained by a 3D plus time shape model. It is applied to an automatically selected subset of 2D images of the original data set, for typically 10 equidistant rotation angles and 16 cardiac phases (160 images). Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastole and end-systole volumes. Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastolic (ED) and end-systolic (ES) volumes. The semiautomatic border detection approach shows good correlations with MRI ED/ES volumes (r = 0.938) and low interobserver variability (y = 1.005x - 16.7, r = 0.943) over full-cycle volume estimations. It shows a high consistency in tracking the user-defined initial borders over space and time. We show that the ease of the acquisition using the FRU-transducer and the semiautomatic endocardial border detection method together can provide a way to quickly estimate the left ventricular volume over the full cardiac cycle using little user interaction.
2011-01-01
Background Fluorescence in situ hybridization (FISH) is very accurate method for measuring HER2 gene copies, as a sign of potential breast cancer. This method requires small tissue samples, and has a high sensitivity to detect abnormalities from a histological section. By using multiple colors, this method allows the detection of multiple targets simultaneously. The target parts in the cells become visible as colored dots. The HER-2 probes are visible as orange stained spots under a fluorescent microscope while probes for centromere 17 (CEP-17), the chromosome on which the gene HER-2/neu is located, are visible as green spots. Methods The conventional analysis involves the scoring of the ratio of HER-2/neu over CEP 17 dots within each cell nucleus and then averaging the scores for a number of 60 cells. A ratio of 2.0 of HER-2/neu to CEP 17 copy number denotes amplification. Several methods have been proposed for the detection and automated evaluation (dot counting) of FISH signals. In this paper the combined method based on the mathematical morphology (MM) and inverse multifractal (IMF) analysis is suggested. Similar method was applied recently in detection of microcalcifications in digital mammograms, and was very successful. Results The combined MM using top-hat and bottom-hat filters, and the IMF method was applied to FISH images from Molecular Biology Lab, Department of Pathology, Wielkoposka Cancer Center, Poznan. Initial results indicate that this method can be applied to FISH images for the evaluation of HER2/neu status. Conclusions Mathematical morphology and multifractal approach are used for colored dot detection and counting in FISH images. Initial results derived on clinical cases are promising. Note that the overlapping of colored dots, particularly red/orange dots, needs additional improvements in post-processing. PMID:21489192
Genital HSV Shedding among Kenyan Women Initiating Antiretroviral Therapy
Manguro, Griffins O.; Masese, Linnet N.; Deya, Ruth W.; Magaret, Amalia; Wald, Anna; McClelland, R. Scott; Graham, Susan M.
2016-01-01
Objectives Genital ulcer disease (GUD) prevalence increases in the first month of antiretroviral treatment (ART), followed by a return to baseline prevalence by month 3. Since most GUD is caused by herpes simplex virus type 2 (HSV-2), we hypothesized that genital HSV detection would follow a similar pattern after treatment initiation. Methods We conducted a prospective cohort study of 122 HSV-2 and HIV-1 co-infected women with advanced HIV disease who initiated ART and were followed closely with collection of genital swab specimens for the first three months of treatment. Results At baseline, the HSV detection rate was 32%, without significant increase in genital HSV detection noted during the first month or the third month of ART. HIV-1 shedding declined during this period; no association was also noted between HSV and HIV-1 shedding during this period. Conclusion Because other studies have reported increased HSV detection in women initiating ART and we have previously reported an increase in GUD during early ART, it may be prudent to counsel HIV-1 infected women initiating ART that HSV shedding in the genital tract may continue after ART initiation. PMID:27683204
Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei
2011-04-01
An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.
Initial Results in Using a Self-Coherence Method for Detecting Sustained Oscillations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, Ning; Dagle, Jeffery E.
2015-01-01
This paper develops a self-coherence method for detecting sustained oscillations using phasor measurement unit (PMU) data. Sustained oscillations decrease system performance and introduce potential reliability issues. Timely detection of the oscillations at an early stage provides the opportunity for taking remedial reaction. Using high-speed time-synchronized PMU data, this paper details a self-coherence method for detecting sustained oscillation, even when the oscillation amplitude is lower than ambient noise. Simulation and field measurement data are used to evaluate the proposed method’s performance. It is shown that the proposed method can detect sustained oscillations and estimate oscillation frequencies with a low signal-to-noise ratio.more » Comparison with a power spectral density method also shows that the proposed self-coherence method performs better. Index Terms—coherence, power spectral density, phasor measurement unit (PMU), oscillations, power system dynamics« less
Zhang, Li-rong; Zhu, Guichi; Zhang, Chun-yang
2014-07-01
MicroRNAs (miRNAs) are an emerging class of biomarkers and therapeutic targets for various diseases including cancers. Here, we develop a homogeneous and label-free method for sensitive detection of let-7a miRNA based on bifunctional strand displacement amplification (SDA)-mediated hyperbranched rolling circle amplification (HRCA). The binding of target miRNA with the linear template initiates the bifunctional SDA reaction, generating two different kinds of triggers which can hybridize with the linear template to initiate new rounds of SDA reaction for the production of more and more triggers. In the meantime, the released two different kinds of triggers can function as the first and the second primers, respectively, to initiate the HRCA reaction whose products can be simply monitored by a standard fluorometer with SYBR Green I as the fluorescent indicator. The proposed method exhibits high sensitivity with a detection limit of as low as 1.8 × 10(-13) M and a large dynamic range of 5 orders of magnitude from 0.1 pM to 10 nM, and it can even discriminate the single-base difference among the miRNA family members. Moreover, this method can be used to analyze the total RNA samples from the human lung tissues and might be further applied for sensitive detection of various proteins, small molecules, and metal ions in combination with specific aptamers.
Concurrently adjusting interrelated control parameters to achieve optimal engine performance
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2015-12-01
Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.
Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter
NASA Astrophysics Data System (ADS)
Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi
2013-03-01
Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.
Detection the nonlinear ultrasonic signals based on modified Duffing equations
NASA Astrophysics Data System (ADS)
Zhang, Yuhua; Mao, Hanling; Mao, Hanying; Huang, Zhenfeng
The nonlinear ultrasonic signals, like second harmonic generation (SHG) signals, could reflect the nonlinearity of material induced by fatigue damage in nonlinear ultrasonic technique which are weak nonlinear signals and usually submerged by strong background noise. In this paper the modified Duffing equations are applied to detect the SHG signals relating to the fatigue damage of material. Due to the Duffing equation could only detect the signal with specific frequency and initial phase, firstly the frequency transformation is carried on the Duffing equation which could detect the signal with any frequency. Then the influence of initial phases of to-be-detected signal and reference signal on the detection result is studied in detail, four modified Duffing equations are proposed to detect actual engineering signals with any initial phase. The relationship between the response amplitude and the total driving force is applied to estimate the amplitude of weak periodic signal. The detection results show the modified Duffing equations could effectively detect the second harmonic in SHG signals. When the SHG signals include strong background noise, the noise doesn't change the motion state of Duffing equation and the second harmonic signal could be detected until the SNR of noisy SHG signals are -26.3, yet the frequency spectrum method could only identify when the SNR is greater than 0.5. When estimation the amplitude of second harmonic signal, the estimation error of Duffing equation is obviously less than the frequency spectrum analysis method under the same noise level, which illustrates the Duffing equation has the noise immune capacity. The presence of the second harmonic signal in nonlinear ultrasonic experiments could provide an insight about the early fatigue damage of engineering components.
Good initialization model with constrained body structure for scene text recognition
NASA Astrophysics Data System (ADS)
Zhu, Anna; Wang, Guoyou; Dong, Yangbo
2016-09-01
Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.
Niu, Shuyan; Qu, Lijing; Zhang, Qing; Lin, Jiehua
2012-02-15
A sensitive and specific sandwich assay for the detection of thrombin is described. Two affiliative aptamers were used to increase the assay specificity through sandwich recognition. Recognition DNA loaded on gold nanoparticles (AuNPs) partially hybridized with the initiator DNA, which was displaced by surviving DNA. After the initiator DNA was released into the solution, one hairpin structure was opened, which in turn opened another hairpin structure. The initiator DNA was displaced and released into the solution again by another hairpin structure because of the hybridized reaction. Then the released initiator DNA initiated another autocatalytic strand displacement reaction. A sophisticated network of three such duplex formation cycles was designed to amplify the fluorescence signal. Other proteins, such as bovine serum albumin and lysozyme, did not interfere with the detection of thrombin. This approach enables rapid and specific thrombin detection with reduced costs and minimized material consumption compared with traditional assay processes. The detection limit of thrombin was as low as 4.3 × 10⁻¹³ M based on the AuNP amplification and the autocatalytic strand displacement cycle reaction. This method could be used in biological samples with excellent selectivity. Copyright © 2011 Elsevier Inc. All rights reserved.
Isothermal amplification detection of nucleic acids by a double-nicked beacon.
Shi, Chao; Zhou, Meiling; Pan, Mei; Zhong, Guilin; Ma, Cuiping
2016-03-01
Isothermal and rapid amplification detection of nucleic acids is an important technology in environmental monitoring, foodborne pathogen detection, and point-of-care clinical diagnostics. Here we have developed a novel method of isothermal signal amplification for single-stranded DNA (ssDNA) detection. The ssDNA target could be used as an initiator, coupled with a double-nicked molecular beacon, to originate amplification cycles, achieving cascade signal amplification. In addition, the method showed good specificity and strong anti-jamming capability. Overall, it is a one-pot and isothermal strand displacement amplification method without the requirement of a stepwise procedure, which greatly simplifies the experimental procedure and decreases the probability of contamination of samples. With its advantages, the method would be very useful to detect nucleic acids in point-of-care or field use. Copyright © 2015 Elsevier Inc. All rights reserved.
Zhu, Qing-Xia; Cao, Yong-Bing; Cao, Ying-Ying; Lu, Feng
2014-04-01
A novel facile method for on-site detection of antipertensive chemicals (e. g. nicardipine hydrochloride, doxazosin mesylate, propranolol hydrochloride, and hydrochlorothiazide) adulterated in traditional Chinese medicine for hypertension using thin layer chromatography (TLC) combined with surface enhanced Raman spectroscopy (SERS) was reported in the present paper. Analytes and pharmaceutical matrices was separated by TLC, then SERS method was used to complete qualitative identification of trace substances on TLC plate. By optimizing colloidal silver concentration and developing solvent, as well as exploring the optimal limits of detection (LOD), the initially established TLC-SERS method was used to detect real hypertension Chinese pharmaceuticals. The results showed that this method had good specificity for the four chemicals and high sensitivity with a limit of detection as lower as to 0.005 microg. Finally, two of the ten antipertensive drugs were detected to be adulterated with chemicals. This simple and fast method can realize rapid detection of chemicals illegally for doping in antipertensive Chinese pharmaceuticals, and would have good prospects in on-site detection of chemicals for doping in Chinese pharmaceuticals.
Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor.
Naqvi, Rizwan Ali; Arsalan, Muhammad; Batchuluun, Ganbayar; Yoon, Hyo Sik; Park, Kang Ryoung
2018-02-03
A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver's point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR)-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR) camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB). The proposed method demonstrated greater accuracy than the previous gaze classification methods.
Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor
Naqvi, Rizwan Ali; Arsalan, Muhammad; Batchuluun, Ganbayar; Yoon, Hyo Sik; Park, Kang Ryoung
2018-01-01
A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver’s point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR)-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR) camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB). The proposed method demonstrated greater accuracy than the previous gaze classification methods. PMID:29401681
Real-time method for establishing a detection map for a network of sensors
Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L
2012-09-11
A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.
Brain tumor segmentation with Vander Lugt correlator based active contour.
Essadike, Abdelaziz; Ouabida, Elhoussaine; Bouzid, Abdenbi
2018-07-01
The manual segmentation of brain tumors from medical images is an error-prone, sensitive, and time-absorbing process. This paper presents an automatic and fast method of brain tumor segmentation. In the proposed method, a numerical simulation of the optical Vander Lugt correlator is used for automatically detecting the abnormal tissue region. The tumor filter, used in the simulated optical correlation, is tailored to all the brain tumor types and especially to the Glioblastoma, which considered to be the most aggressive cancer. The simulated optical correlation, computed between Magnetic Resonance Images (MRI) and this filter, estimates precisely and automatically the initial contour inside the tumorous tissue. Further, in the segmentation part, the detected initial contour is used to define an active contour model and presenting the problematic as an energy minimization problem. As a result, this initial contour assists the algorithm to evolve an active contour model towards the exact tumor boundaries. Equally important, for a comparison purposes, we considered different active contour models and investigated their impact on the performance of the segmentation task. Several images from BRATS database with tumors anywhere in images and having different sizes, contrast, and shape, are used to test the proposed system. Furthermore, several performance metrics are computed to present an aggregate overview of the proposed method advantages. The proposed method achieves a high accuracy in detecting the tumorous tissue by a parameter returned by the simulated optical correlation. In addition, the proposed method yields better performance compared to the active contour based methods with the averages of Sensitivity=0.9733, Dice coefficient = 0.9663, Hausdroff distance = 2.6540, Specificity = 0.9994, and faster with a computational time average of 0.4119 s per image. Results reported on BRATS database reveal that our proposed system improves over the recently published state-of-the-art methods in brain tumor detection and segmentation. Copyright © 2018 Elsevier B.V. All rights reserved.
Recent advances and remaining challenges for the spectroscopic detection of explosive threats.
Fountain, Augustus W; Christesen, Steven D; Moon, Raphael P; Guicheteau, Jason A; Emmons, Erik D
2014-01-01
In 2010, the U.S. Army initiated a program through the Edgewood Chemical Biological Center to identify viable spectroscopic signatures of explosives and initiate environmental persistence, fate, and transport studies for trace residues. These studies were ultimately designed to integrate these signatures into algorithms and experimentally evaluate sensor performance for explosives and precursor materials in existing chemical point and standoff detection systems. Accurate and validated optical cross sections and signatures are critical in benchmarking spectroscopic-based sensors. This program has provided important information for the scientists and engineers currently developing trace-detection solutions to the homemade explosive problem. With this information, the sensitivity of spectroscopic methods for explosives detection can now be quantitatively evaluated before the sensor is deployed and tested.
Unwin, Richard D; Griffiths, John R; Whetton, Anthony D
2009-01-01
The application of a targeted mass spectrometric workflow to the sensitive identification of post-translational modifications is described. This protocol employs multiple reaction monitoring (MRM) to search for all putative peptides specifically modified in a target protein. Positive MRMs trigger an MS/MS experiment to confirm the nature and site of the modification. This approach, termed MIDAS (MRM-initiated detection and sequencing), is more sensitive than approaches using neutral loss scanning or precursor ion scanning methodologies, due to a more efficient use of duty cycle along with a decreased background signal associated with MRM. We describe the use of MIDAS for the identification of phosphorylation, with a typical experiment taking just a couple of hours from obtaining a peptide sample. With minor modifications, the MIDAS method can be applied to other protein modifications or unmodified peptides can be used as a MIDAS target.
Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.
Zheng, Yinfei; Zhou, Yali; Zhou, Hao; Gong, Xiaohong
2015-07-01
To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images. © The Author(s) 2014.
NASA Technical Reports Server (NTRS)
Delamorena, B. A.
1984-01-01
A method to detect stratospheric warmings using ionospheric absorption records obtained by an Absorption Meter (method A3) is introduced. The activity of the stratospheric circulation and the D region ionospheric absorption as well as other atmospheric parameters during the winter anomaly experience an abnormal variation. A simultaneity was found in the beginning of abnormal variation in the mentioned parameters, using the absorption records for detecting the initiation of the stratospheric warming. Results of this scientific experience of forecasting in the El Arenosillo Range, are presented.
Honda, Shogo; Kohama, Takeshi; Tanaka, Tatsuro; Yoshida, Hisashi
2014-01-01
It is well known that a decline of arousal level causes of poor performance of movements or judgments. Our previous study indicates that microsaccade (MS) rates and pupil fluctuations change before slow eye movements (SEMs) (Honda et al. 2013). However, SEM detection of this study was obscure and insufficient. In this study, we propose a new SEM detection method and analyze MS rates and pupil fluctuations while subjects maintain their gaze on a target. We modified Shin et al.'s method, which is optimized for EOG (electrooculography) signals, to extract the period of sustaining SEMs using a general eye tracker. After SEM detection, we analyzed MS rates and pupil fluctuations prior to the initiation of SEMs. As a result, we were able to detect SEMs more precisely than in our previous study. Moreover, the results of eye movements and pupil fluctuations analyses show that gradual rise of MS rate and longitudinal miosis are observed prior to the initiation of SEMs, which is consistent with our previous study. These findings suggest that monitoring eye movements and pupil fluctuations may evaluate the arousal level more precisely. Further, we found that these tendencies become more significant when they are restricted to the initial SEMs.
Caged Fish Studies to Detect and Monitor Contaminants of Emerging Concern in the Great Lakes
Effects-based monitoring studies were conducted in the St. Louis Harbor, Lake Superior, in support of the Great Lakes Restoration Initiative (GLRI). The overall goal of the research was to develop and validate methods using caged fish exposures to detect and monitor contaminants...
All-to-all sequenced fault detection system
Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward
2010-11-02
An apparatus, program product and method enable nodal fault detection by sequencing communications between all system nodes. A master node may coordinate communications between two slave nodes before sequencing to and initiating communications between a new pair of slave nodes. The communications may be analyzed to determine the nodal fault.
NASA Astrophysics Data System (ADS)
Chang, Chun; Huang, Benxiong; Xu, Zhengguang; Li, Bin; Zhao, Nan
2018-02-01
Three soft-input-soft-output (SISO) detection methods for dual-polarized quadrature duobinary (DP-QDB), including maximum-logarithmic-maximum-a-posteriori-probability-algorithm (Max-log-MAP)-based detection, soft-output-Viterbi-algorithm (SOVA)-based detection, and a proposed SISO detection, which can all be combined with SISO decoding, are presented. The three detection methods are investigated at 128 Gb/s in five-channel wavelength-division-multiplexing uncoded and low-density-parity-check (LDPC) coded DP-QDB systems by simulations. Max-log-MAP-based detection needs the returning-to-initial-states (RTIS) process despite having the best performance. When the LDPC code with a code rate of 0.83 is used, the detecting-and-decoding scheme with the SISO detection does not need RTIS and has better bit error rate (BER) performance than the scheme with SOVA-based detection. The former can reduce the optical signal-to-noise ratio (OSNR) requirement (at BER=10-5) by 2.56 dB relative to the latter. The application of the SISO iterative detection in LDPC-coded DP-QDB systems makes a good trade-off between requirements on transmission efficiency, OSNR requirement, and transmission distance, compared with the other two SISO methods.
A method for detecting small targets based on cumulative weighted value of target properties
NASA Astrophysics Data System (ADS)
Jin, Xing; Sun, Gang; Wang, Wei-hua; Liu, Fang; Chen, Zeng-ping
2015-03-01
Laser detection based on the "cat's eye effect" has become the hot research project for its initiative compared to the passivity of sound detection and infrared detection. And the target detection is one of the core technologies in this system. The paper puts forward a method for detecting small targets based on cumulative weighted value of target properties using given data. Firstly, we make a frame difference to the images, then make image processing based on Morphology Principles. Secondly, we segment images, and screen the targets; then find some interesting locations. Finally, comparing to a quantity of frames, we locate the target. We did an exam to 394 true frames, the experimental result shows that the mathod can detect small targets efficiently.
Automated feature detection and identification in digital point-ordered signals
Oppenlander, Jane E.; Loomis, Kent C.; Brudnoy, David M.; Levy, Arthur J.
1998-01-01
A computer-based automated method to detect and identify features in digital point-ordered signals. The method is used for processing of non-destructive test signals, such as eddy current signals obtained from calibration standards. The signals are first automatically processed to remove noise and to determine a baseline. Next, features are detected in the signals using mathematical morphology filters. Finally, verification of the features is made using an expert system of pattern recognition methods and geometric criteria. The method has the advantage that standard features can be, located without prior knowledge of the number or sequence of the features. Further advantages are that standard features can be differentiated from irrelevant signal features such as noise, and detected features are automatically verified by parameters extracted from the signals. The method proceeds fully automatically without initial operator set-up and without subjective operator feature judgement.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tang, Yanmei; Li, Xinli; Bai, Yan
The measurement of multiphase flow parameters is of great importance in a wide range of industries. In the measurement of multiphase, the signals from the sensors are extremely weak and often buried in strong background noise. It is thus desirable to develop effective signal processing techniques that can detect the weak signal from the sensor outputs. In this paper, two methods, i.e., lock-in-amplifier (LIA) and improved Duffing chaotic oscillator are compared to detect and process the weak signal. For sinusoidal signal buried in noise, the correlation detection with sinusoidal reference signal is simulated by using LIA. The improved Duffing chaoticmore » oscillator method, which based on the Wigner transformation, can restore the signal waveform and detect the frequency. Two methods are combined to detect and extract the weak signal. Simulation results show the effectiveness and accuracy of the proposed improved method. The comparative analysis shows that the improved Duffing chaotic oscillator method can restrain noise strongly since it is sensitive to initial conditions.« less
Initial study of Schroedinger eigenmaps for spectral target detection
NASA Astrophysics Data System (ADS)
Dorado-Munoz, Leidy P.; Messinger, David W.
2016-08-01
Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.
NASA Astrophysics Data System (ADS)
Zhang, Dashan; Guo, Jie; Jin, Yi; Zhu, Chang'an
2017-09-01
High-speed cameras provide full field measurement of structure motions and have been applied in nondestructive testing and noncontact structure monitoring. Recently, a phase-based method has been proposed to extract sound-induced vibrations from phase variations in videos, and this method provides insights into the study of remote sound surveillance and material analysis. An efficient singular value decomposition (SVD)-based approach is introduced to detect sound-induced subtle motions from pixel intensities in silent high-speed videos. A high-speed camera is initially applied to capture a video of the vibrating objects stimulated by sound fluctuations. Then, subimages collected from a small region on the captured video are reshaped into vectors and reconstructed to form a matrix. Orthonormal image bases (OIBs) are obtained from the SVD of the matrix; available vibration signal can then be obtained by projecting subsequent subimages onto specific OIBs. A simulation test is initiated to validate the effectiveness and efficiency of the proposed method. Two experiments are conducted to demonstrate the potential applications in sound recovery and material analysis. Results show that the proposed method efficiently detects subtle motions from the video.
Qi, Peng; Zhang, Dun; Wan, Yi
2014-11-01
Sulfate-reducing bacteria (SRB) have been extensively studied in corrosion and environmental science. However, fast enumeration of SRB population is still a difficult task. This work presents a novel specific SRB detection method based on inhibition of cysteine protease activity. The hydrolytic activity of cysteine protease was inhibited by taking advantage of sulfide, the characteristic metabolic product of SRB, to attack active cysteine thiol group in cysteine protease catalytic sites. The active thiol S-sulfhydration process could be used for SRB detection, since the amount of sulfide accumulated in culture medium was highly related with initial bacterial concentration. The working conditions of cysteine protease have been optimized to obtain better detection capability, and the SRB detection performances have been evaluated in this work. The proposed SRB detection method based on inhibition of cysteine protease activity avoided the use of biological recognition elements. In addition, compared with the widely used most probable number (MPN) method which would take up to at least 15days to accomplish whole detection process, the method based on inhibition of papain activity could detect SRB in 2 days, with a detection limit of 5.21×10(2) cfu mL(-1). The detection time for SRB population quantitative analysis was greatly shortened. Copyright © 2014 Elsevier B.V. All rights reserved.
Dziedzinska, Radka
2017-01-01
The main reasons to improve the detection of Mycobacterium avium subsp. paratuberculosis (MAP) are animal health and monitoring of MAP entering the food chain via meat, milk, and/or dairy products. Different approaches can be used for the detection of MAP, but the use of magnetic separation especially in conjunction with PCR as an end-point detection method has risen in past years. However, the extraction of DNA which is a crucial step prior to PCR detection can be complicated due to the presence of inhibitory substances. Magnetic separation methods involving either antibodies or peptides represent a powerful tool for selective separation of target bacteria from other nontarget microorganisms and inhibitory sample components. These methods enable the concentration of pathogens present in the initial matrix into smaller volume and facilitate the isolation of sufficient quantities of pure DNA. The purpose of this review was to summarize the methods based on the magnetic separation approach that are currently available for the detection of MAP in a broad range of matrices. PMID:28642876
Improved and Robust Detection of Cell Nuclei from Four Dimensional Fluorescence Images
Bashar, Md. Khayrul; Yamagata, Kazuo; Kobayashi, Tetsuya J.
2014-01-01
Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9 over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies ( 98 mean F-measure) irrespective of the large variations of filter parameters and noise levels. PMID:25020042
Li, Chen-Chen; Zhang, Yan; Tang, Bo; Zhang, Chun-Yang
2018-06-05
We combine single-molecule detection with magnetic separation for simultaneous measurement of human 8-oxoG DNA glycosylase 1 (hOGG1) and uracil DNA glycosylase (UDG) based on excision repair-initiated endonuclease IV (Endo IV)-assisted signal amplification. This method can sensitively detect multiple DNA glycosylases, and it can be further applied for the simultaneous measurement of enzyme kinetic parameters and screening of both hOGG1 and UDG inhibitors.
Surveillance for vancomycin-resistant enterococci: type, rates, costs, and implications.
Shadel, Brooke N; Puzniak, Laura A; Gillespie, Kathleen N; Lawrence, Steven J; Kollef, Marin; Mundy, Linda M
2006-10-01
To evaluate 2 active surveillance strategies for detection of enteric vancomycin-resistant enterococci (VRE) in an intensive care unit (ICU). Thirty-month prospective observational study. ICU at a university-affiliated referral center. All patients with an ICU stay of 24 hours or more were eligible for the study. Clinical active surveillance (CAS), involving culture of a rectal swab specimen for detection of VRE, was performed on admission, weekly while the patient was in the ICU, and at discharge. Laboratory-based active surveillance (LAS), involving culture of a stool specimen for detection of VRE, was performed on stool samples submitted for Clostridium difficile toxin detection. Enteric colonization with VRE was detected in 309 (17%) of 1,872 patients. The CAS method initially detected 280 (91%) of the 309 patients colonized with VRE, compared with 25 patients (8%) detected by LAS; colonization in 4 patients (1%) was initially detected by analysis of other clinical specimens. Most patients with colonization (76%) would have gone undetected by LAS alone, whereas use of the CAS method exclusively would have missed only 3 patients (1%) who were colonized. CAS cost Dollars 1,913 per month, or Dollars 57,395 for the 30-month study period. Cost savings of CAS from preventing cases of VRE colonization and bacteremia were estimated to range from Dollars 56,258 to Dollars 303,334 per month. A patient-based CAS strategy for detection of enteric colonization with VRE was superior to LAS. In this high-risk setting, CAS appeared to be the most efficient and cost-effective surveillance method. The modest costs of CAS were offset by the averted costs associated with the prevention of VRE colonization and bacteremia.
NASA Astrophysics Data System (ADS)
Hoell, Simon; Omenzetter, Piotr
2018-02-01
To advance the concept of smart structures in large systems, such as wind turbines (WTs), it is desirable to be able to detect structural damage early while using minimal instrumentation. Data-driven vibration-based damage detection methods can be competitive in that respect because global vibrational responses encompass the entire structure. Multivariate damage sensitive features (DSFs) extracted from acceleration responses enable to detect changes in a structure via statistical methods. However, even though such DSFs contain information about the structural state, they may not be optimised for the damage detection task. This paper addresses the shortcoming by exploring a DSF projection technique specialised for statistical structural damage detection. High dimensional initial DSFs are projected onto a low-dimensional space for improved damage detection performance and simultaneous computational burden reduction. The technique is based on sequential projection pursuit where the projection vectors are optimised one by one using an advanced evolutionary strategy. The approach is applied to laboratory experiments with a small-scale WT blade under wind-like excitations. Autocorrelation function coefficients calculated from acceleration signals are employed as DSFs. The optimal numbers of projection vectors are identified with the help of a fast forward selection procedure. To benchmark the proposed method, selections of original DSFs as well as principal component analysis scores from these features are additionally investigated. The optimised DSFs are tested for damage detection on previously unseen data from the healthy state and a wide range of damage scenarios. It is demonstrated that using selected subsets of the initial and transformed DSFs improves damage detectability compared to the full set of features. Furthermore, superior results can be achieved by projecting autocorrelation coefficients onto just a single optimised projection vector.
Fast object reconstruction in block-based compressive low-light-level imaging
NASA Astrophysics Data System (ADS)
Ke, Jun; Sui, Dong; Wei, Ping
2014-11-01
In this paper we propose a simply yet effective and efficient method for long-term object tracking. Different from traditional visual tracking method which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion problem. To summarize, our algorithm can be roughly decomposed in a initialization stage and a tracking stage. In the initialization stage, an offline classifier is trained to get the object appearance information in category level. When the video stream is coming, the pre-trained offline classifier is used for detecting the potential target and initializing the tracking stage. In the tracking stage, it consists of three parts which are online tracking part, offline tracking part and confidence judgment part. Online tracking part captures the specific target appearance information while detection part localizes the object based on the pre-trained offline classifier. Since there is no data dependence between online tracking and offline detection, these two parts are running in parallel to significantly improve the processing speed. A confidence selection mechanism is proposed to optimize the object location. Besides, we also propose a simple mechanism to judge the absence of the object. If the target is lost, the pre-trained offline classifier is utilized to re-initialize the whole algorithm as long as the target is re-located. During experiment, we evaluate our method on several challenging video sequences and demonstrate competitive results.
Adaptive local thresholding for robust nucleus segmentation utilizing shape priors
NASA Astrophysics Data System (ADS)
Wang, Xiuzhong; Srinivas, Chukka
2016-03-01
This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.
BMI and BMI SDS in childhood: annual increments and conditional change.
Brannsether, Bente; Eide, Geir Egil; Roelants, Mathieu; Bjerknes, Robert; Júlíusson, Pétur Benedikt
2017-02-01
Background Early detection of abnormal weight gain in childhood may be important for preventive purposes. It is still debated which annual changes in BMI should warrant attention. Aim To analyse 1-year increments of Body Mass Index (BMI) and standardised BMI (BMI SDS) in childhood and explore conditional change in BMI SDS as an alternative method to evaluate 1-year changes in BMI. Subjects and methods The distributions of 1-year increments of BMI (kg/m 2 ) and BMI SDS are summarised by percentiles. Differences according to sex, age, height, weight, initial BMI and weight status on the BMI and BMI SDS increments were assessed with multiple linear regression. Conditional change in BMI SDS was based on the correlation between annual BMI measurements converted to SDS. Results BMI increments depended significantly on sex, height, weight and initial BMI. Changes in BMI SDS depended significantly only on the initial BMI SDS. The distribution of conditional change in BMI SDS using a two-correlation model was close to normal (mean = 0.11, SD = 1.02, n = 1167), with 3.2% (2.3-4.4%) of the observations below -2 SD and 2.8% (2.0-4.0%) above +2 SD. Conclusion Conditional change in BMI SDS can be used to detect unexpected large changes in BMI SDS. Although this method requires the use of a computer, it may be clinically useful to detect aberrant weight development.
Automatic characterization of sleep need dissipation dynamics using a single EEG signal.
Garcia-Molina, Gary; Bellesi, Michele; Riedner, Brady; Pastoor, Sander; Pfundtner, Stefan; Tononi, Giulio
2015-01-01
In the two-process model of sleep regulation, slow-wave activity (SWA, i.e. the EEG power in the 0.5-4 Hz frequency band) is considered a direct indicator of sleep need. SWA builds up during non-rapid eye movement (NREM) sleep, declines before the onset of rapid-eye-movement (REM) sleep, remains low during REM and the level of increase in successive NREM episodes gets progressively lower. Sleep need dissipates with a speed that is proportional to SWA and can be characterized in terms of the initial sleep need, and the decay rate. The goal in this paper is to automatically characterize sleep need from a single EEG signal acquired at a frontal location. To achieve this, a highly specific and reasonably sensitive NREM detection algorithm is proposed that leverages the concept of a single-class Kernel-based classifier. Using automatic NREM detection, we propose a method to estimate the decay rate and the initial sleep need. This method was tested on experimental data from 8 subjects who recorded EEG during three nights at home. We found that on average the estimates of the decay rate and the initial sleep need have higher values when automatic NREM detection was used as compared to manual NREM annotation. However, the average variability of these estimates across multiple nights of the same subject was lower when the automatic NREM detection classifier was used. While this method slightly over estimates the sleep need parameters, the reduced variability across subjects makes it more effective for within subject statistical comparisons of a given sleep intervention.
NASA Astrophysics Data System (ADS)
Takakura, T.; Yanagi, I.; Goto, Y.; Ishige, Y.; Kohara, Y.
2016-03-01
We developed a resistive-pulse sensor with a solid-state pore and measured the latex agglutination of submicron particles induced by antigen-antibody interaction for single-molecule detection of proteins. We fabricated the pore based on numerical simulation to clearly distinguish between monomer and dimer latex particles. By measuring single dimers agglutinated in the single-molecule regime, we detected single human alpha-fetoprotein molecules. Adjusting the initial particle concentration improves the limit of detection (LOD) to 95 fmol/l. We established a theoretical model of the LOD by combining the reaction kinetics and the counting statistics to explain the effect of initial particle concentration on the LOD. The theoretical model shows how to improve the LOD quantitatively. The single-molecule detection studied here indicates the feasibility of implementing a highly sensitive immunoassay by a simple measurement method using resistive-pulse sensing.
Lette, Manon; Stoop, Annerieke; Lemmens, Lidwien C; Buist, Yvette; Baan, Caroline A; de Bruin, Simone R
2017-06-23
A wide range of initiatives on early detection and intervention have been developed to proactively identify problems related to health and wellbeing in (frail) older people, with the aim of supporting them to live independently for as long as possible. Nevertheless, it remains unclear what the best way is to design such initiatives and how older people's needs and preferences can be best addressed. This study aimed to address this gap in the literature by exploring: 1) older people's perspectives on health and living environment in relation to living independently at home; 2) older people's needs and preferences in relation to initiating and receiving care and support; and 3) professionals' views on what would be necessary to enable the alignment of early detection initiatives with older people's own needs and preferences. In this qualitative study, we conducted semi-structured interviews with 36 older people and 19 professionals in proactive elderly care. Data were analysed using the framework analysis method. From the interviews with older people important themes in relation to health and living environment emerged, such as maintaining independence, appropriate housing, social relationships, a supporting network and a sense of purpose and autonomy. Older people preferred to remain self-sufficient, and they would rather not ask for help for psychological or social problems. However, the interviews also highlighted that they were not always able or willing to anticipate future needs, which can hinder early detection or early intervention. At the same time, professionals indicated that older people tend to over-estimate their self-reliance and therefore advocated for early detection and intervention, including social and psychological issues. Older people have a broad range of needs in different domains of life. Discrepancies exist between older people and professionals with regard to their views on timing and scope of early detection initiatives. This study aimed to reveal starting-points for better alignment between initiatives and older people's needs and preferences. Such starting points may support policy makers and care professionals involved in early detection initiatives to make more informed decisions.
Fujita, Hiroto; Kataoka, Yuka; Tobita, Seiji; Kuwahara, Masayasu; Sugimoto, Naoki
2016-07-19
We have developed a novel RNA detection method, termed signal amplification by ternary initiation complexes (SATIC), in which an analyte sample is simply mixed with the relevant reagents and allowed to stand for a short time under isothermal conditions (37 °C). The advantage of the technique is that there is no requirement for (i) heat annealing, (ii) thermal cycling during the reaction, (iii) a reverse transcription step, or (iv) enzymatic or mechanical fragmentation of the target RNA. SATIC involves the formation of a ternary initiation complex between the target RNA, a circular DNA template, and a DNA primer, followed by rolling circle amplification (RCA) to generate multiple copies of G-quadruplex (G4) on a long DNA strand like beads on a string. The G4s can be specifically fluorescence-stained with N(3)-hydroxyethyl thioflavin T (ThT-HE), which emits weakly with single- and double-stranded RNA/DNA but strongly with parallel G4s. An improved dual SATIC system, which involves the formation of two different ternary initiation complexes in the RCA process, exhibited a wide quantitative detection range of 1-5000 pM. Furthermore, this enabled visual observation-based RNA detection, which is more rapid and convenient than conventional isothermal methods, such as reverse transcription-loop-mediated isothermal amplification, signal mediated amplification of RNA technology, and RNA-primed rolling circle amplification. Thus, SATIC methodology may serve as an on-site and real-time measurement technique for transcriptomic biomarkers for various diseases.
Schacherer, Lindsey J; Xie, Weiping; Owens, Michaela A; Alarcon, Clara; Hu, Tiger X
2016-09-01
Liquid chromatography coupled with tandem mass spectrometry is increasingly used for protein detection for transgenic crops research. Currently this is achieved with protein reference standards which may take a significant time or efforts to obtain and there is a need for rapid protein detection without protein reference standards. A sensitive and specific method was developed to detect target proteins in transgenic maize leaf crude extract at concentrations as low as ∼30 ng mg(-1) dry leaf without the need of reference standards or any sample enrichment. A hybrid Q-TRAP mass spectrometer was used to monitor all potential tryptic peptides of the target proteins in both transgenic and non-transgenic samples. The multiple reaction monitoring-initiated detection and sequencing (MIDAS) approach was used for initial peptide/protein identification via Mascot database search. Further confirmation was achieved by direct comparison between transgenic and non-transgenic samples. Definitive confirmation was provided by running the same experiments of synthetic peptides or protein standards, if available. A targeted proteomic mass spectrometry method using MIDAS approach is an ideal methodology for detection of new proteins in early stages of transgenic crop research and development when neither protein reference standards nor antibodies are available. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.
Heap/stack guard pages using a wakeup unit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gooding, Thomas M; Satterfield, David L; Steinmacher-Burow, Burkhard
A method and system for providing a memory access check on a processor including the steps of detecting accesses to a memory device including level-1 cache using a wakeup unit. The method includes invalidating level-1 cache ranges corresponding to a guard page, and configuring a plurality of wakeup address compare (WAC) registers to allow access to selected WAC registers. The method selects one of the plurality of WAC registers, and sets up a WAC register related to the guard page. The method configures the wakeup unit to interrupt on access of the selected WAC register. The method detects access ofmore » the memory device using the wakeup unit when a guard page is violated. The method generates an interrupt to the core using the wakeup unit, and determines the source of the interrupt. The method detects the activated WAC registers assigned to the violated guard page, and initiates a response.« less
Application of ultrasonic signature analysis for fatigue detection in complex structures
NASA Technical Reports Server (NTRS)
Zuckerwar, A. J.
1974-01-01
Ultrasonic signature analysis shows promise of being a singularly well-suited method for detecting fatigue in structures as complex as aircraft. The method employs instrumentation centered about a Fourier analyzer system, which features analog-to-digital conversion, digital data processing, and digital display of cross-correlation functions and cross-spectra. These features are essential to the analysis of ultrasonic signatures according to the procedure described here. In order to establish the feasibility of the method, the initial experiments were confined to simple plates with simulated and fatigue-induced defects respectively. In the first test the signature proved sensitive to the size of a small hole drilled into the plate. In the second test, performed on a series of fatigue-loaded plates, the signature proved capable of indicating both the initial appearance and subsequent growth of a fatigue crack. In view of these encouraging results it is concluded that the method has reached a sufficiently advanced stage of development to warrant application to small-scale structures or even actual aircraft.
Evidential analysis of difference images for change detection of multitemporal remote sensing images
NASA Astrophysics Data System (ADS)
Chen, Yin; Peng, Lijuan; Cremers, Armin B.
2018-03-01
In this article, we develop two methods for unsupervised change detection in multitemporal remote sensing images based on Dempster-Shafer's theory of evidence (DST). In most unsupervised change detection methods, the probability of difference image is assumed to be characterized by mixture models, whose parameters are estimated by the expectation maximization (EM) method. However, the main drawback of the EM method is that it does not consider spatial contextual information, which may entail rather noisy detection results with numerous spurious alarms. To remedy this, we firstly develop an evidence theory based EM method (EEM) which incorporates spatial contextual information in EM by iteratively fusing the belief assignments of neighboring pixels to the central pixel. Secondly, an evidential labeling method in the sense of maximizing a posteriori probability (MAP) is proposed in order to further enhance the detection result. It first uses the parameters estimated by EEM to initialize the class labels of a difference image. Then it iteratively fuses class conditional information and spatial contextual information, and updates labels and class parameters. Finally it converges to a fixed state which gives the detection result. A simulated image set and two real remote sensing data sets are used to evaluate the two evidential change detection methods. Experimental results show that the new evidential methods are comparable to other prevalent methods in terms of total error rate.
Caries Detection Methods Based on Changes in Optical Properties between Healthy and Carious Tissue
Karlsson, Lena
2010-01-01
A conservative, noninvasive or minimally invasive approach to clinical management of dental caries requires diagnostic techniques capable of detecting and quantifying lesions at an early stage, when progression can be arrested or reversed. Objective evidence of initiation of the disease can be detected in the form of distinct changes in the optical properties of the affected tooth structure. Caries detection methods based on changes in a specific optical property are collectively referred to as optically based methods. This paper presents a simple overview of the feasibility of three such technologies for quantitative or semiquantitative assessment of caries lesions. Two of the techniques are well-established: quantitative light-induced fluorescence, which is used primarily in caries research, and laser-induced fluorescence, a commercially available method used in clinical dental practice. The third technique, based on near-infrared transillumination of dental enamel is in the developmental stages. PMID:20454579
NASA Astrophysics Data System (ADS)
Shi, Aiye; Wang, Chao; Shen, Shaohong; Huang, Fengchen; Ma, Zhenli
2016-10-01
Chi-squared transform (CST), as a statistical method, can describe the difference degree between vectors. The CST-based methods operate directly on information stored in the difference image and are simple and effective methods for detecting changes in remotely sensed images that have been registered and aligned. However, the technique does not take spatial information into consideration, which leads to much noise in the result of change detection. An improved unsupervised change detection method is proposed based on spatial constraint CST (SCCST) in combination with a Markov random field (MRF) model. First, the mean and variance matrix of the difference image of bitemporal images are estimated by an iterative trimming method. In each iteration, spatial information is injected to reduce scattered changed points (also known as "salt and pepper" noise). To determine the key parameter confidence level in the SCCST method, a pseudotraining dataset is constructed to estimate the optimal value. Then, the result of SCCST, as an initial solution of change detection, is further improved by the MRF model. The experiments on simulated and real multitemporal and multispectral images indicate that the proposed method performs well in comprehensive indices compared with other methods.
Assessment of an Automated Touchdown Detection Algorithm for the Orion Crew Module
NASA Technical Reports Server (NTRS)
Gay, Robert S.
2011-01-01
Orion Crew Module (CM) touchdown detection is critical to activating the post-landing sequence that safe?s the Reaction Control Jets (RCS), ensures that the vehicle remains upright, and establishes communication with recovery forces. In order to accommodate safe landing of an unmanned vehicle or incapacitated crew, an onboard automated detection system is required. An Orion-specific touchdown detection algorithm was developed and evaluated to differentiate landing events from in-flight events. The proposed method will be used to initiate post-landing cutting of the parachute riser lines, to prevent CM rollover, and to terminate RCS jet firing prior to submersion. The RCS jets continue to fire until touchdown to maintain proper CM orientation with respect to the flight path and to limit impact loads, but have potentially hazardous consequences if submerged while firing. The time available after impact to cut risers and initiate the CM Up-righting System (CMUS) is measured in minutes, whereas the time from touchdown to RCS jet submersion is a function of descent velocity, sea state conditions, and is often less than one second. Evaluation of the detection algorithms was performed for in-flight events (e.g. descent under chutes) using hi-fidelity rigid body analyses in the Decelerator Systems Simulation (DSS), whereas water impacts were simulated using a rigid finite element model of the Orion CM in LS-DYNA. Two touchdown detection algorithms were evaluated with various thresholds: Acceleration magnitude spike detection, and Accumulated velocity changed (over a given time window) spike detection. Data for both detection methods is acquired from an onboard Inertial Measurement Unit (IMU) sensor. The detection algorithms were tested with analytically generated in-flight and landing IMU data simulations. The acceleration spike detection proved to be faster while maintaining desired safety margin. Time to RCS jet submersion was predicted analytically across a series of simulated Orion landing conditions. This paper details the touchdown detection method chosen and the analysis used to support the decision.
NASA Astrophysics Data System (ADS)
Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.
2014-06-01
This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.
Method and apparatus for detecting explosives
Moore, David Steven [Santa Fe, NM
2011-05-10
A method and apparatus is provided for detecting explosives by thermal imaging. The explosive material is subjected to a high energy wave which can be either a sound wave or an electromagnetic wave which will initiate a chemical reaction in the explosive material which chemical reaction will produce heat. The heat is then sensed by a thermal imaging device which will provide a signal to a computing device which will alert a user of the apparatus to the possibility of an explosive device being present.
Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG
Westover, M. Brandon; Cole, Andrew J.; Kilbride, Ronan D.; Hoch, Daniel B.; Cash, Sydney S.
2012-01-01
Objective: To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. Methods: We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Results: Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. Conclusions: In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary. PMID:23054233
Multi person detection and tracking based on hierarchical level-set method
NASA Astrophysics Data System (ADS)
Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid
2018-04-01
In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.
Fuel cell flooding detection and correction
DiPierno Bosco, Andrew; Fronk, Matthew Howard
2000-08-15
Method and apparatus for monitoring an H.sub.2 -O.sub.2 PEM fuel cells to detect and correct flooding. The pressure drop across a given H.sub.2 or O.sub.2 flow field is monitored and compared to predetermined thresholds of unacceptability. If the pressure drop exists a threshold of unacceptability corrective measures are automatically initiated.
Assessing the Ability of Ground-Penetrating Radar to Detect Fungal Decay in Douglas-Fir Beams
Christopher Adam Senalik; James Wacker; Xiping Wang; F. Jalinoos
2016-01-01
This paper describes the testing plan and current progress for assessing the efficacy of using ground-penetrating radar (GPR) to detect fungal decay within Douglas-fir beams. Initially, the beams were assessed using a variety of physical, mechanical, and nondestructive evaluation (NDE) test methods including micro-resistance drilling, Janka hardness, ultrasonic...
A Novel Approach to Rotorcraft Damage Tolerance
NASA Technical Reports Server (NTRS)
Forth, Scott C.; Everett, Richard A.; Newman, John A.
2002-01-01
Damage-tolerance methodology is positioned to replace safe-life methodologies for designing rotorcraft structures. The argument for implementing a damage-tolerance method comes from the fundamental fact that rotorcraft structures typically fail by fatigue cracking. Therefore, if technology permits prediction of fatigue-crack growth in structures, a damage-tolerance method should deliver the most accurate prediction of component life. Implementing damage-tolerance (DT) into high-cycle-fatigue (HCF) components will require a shift from traditional DT methods that rely on detecting an initial flaw with nondestructive inspection (NDI) methods. The rapid accumulation of cycles in a HCF component will result in a design based on a traditional DT method that is either impractical because of frequent inspections, or because the design will be too heavy to operate efficiently. Furthermore, once a HCF component develops a detectable propagating crack, the remaining fatigue life is short, sometimes less than one flight hour, which does not leave sufficient time for inspection. Therefore, designing a HCF component will require basing the life analysis on an initial flaw that is undetectable with current NDI technology.
Soda, Paolo; Mazzoleni, Stefano; Cavallo, Giuseppe; Guglielmelli, Eugenio; Iannello, Giulio
2010-09-01
Recent research has successfully introduced the application of robotics and mechatronics to functional assessment and motor therapy. Measurements of movement initiation in isometric conditions are widely used in clinical rehabilitation and their importance in functional assessment has been demonstrated for specific parts of the human body. The determination of the voluntary movement initiation time, also referred to as onset time, represents a challenging issue since the time window characterizing the movement onset is of particular relevance for the understanding of recovery mechanisms after a neurological damage. Establishing it manually as well as a troublesome task may also introduce oversight errors and loss of information. The most commonly used methods for automatic onset time detection compare the raw signal, or some extracted measures such as its derivatives (i.e., velocity and acceleration) with a chosen threshold. However, they suffer from high variability and systematic errors because of the weakness of the signal, the abnormality of response profiles as well as the variability of movement initiation times among patients. In this paper, we introduce a technique to optimise onset detection according to each input signal. It is based on a classification system that enables us to establish which deterministic method provides the most accurate onset time on the basis of information directly derived from the raw signal. The approach was tested on annotated force and torque datasets. Each dataset is constituted by 768 signals acquired from eight anatomical districts in 96 patients who carried out six tasks related to common daily activities. The results show that the proposed technique improves not only on the performance achieved by each of the deterministic methods, but also on that attained by a group of clinical experts. The paper describes a classification system detecting the voluntary movement initiation time and adaptable to different signals. By using a set of features directly derived from raw data, we obtained promising results. Furthermore, although the technique has been developed within the scope of isometric force and torque signal analysis, it can be applied to other detection problems where several simple detectors are available. Copyright (c) 2010 Elsevier B.V. All rights reserved.
Lu, Huanhuan; Wang, Fuzhong; Zhang, Huichun
2016-04-01
Traditional speech detection methods regard the noise as a jamming signal to filter,but under the strong noise background,these methods lost part of the original speech signal while eliminating noise.Stochastic resonance can use noise energy to amplify the weak signal and suppress the noise.According to stochastic resonance theory,a new method based on adaptive stochastic resonance to extract weak speech signals is proposed.This method,combined with twice sampling,realizes the detection of weak speech signals from strong noise.The parameters of the systema,b are adjusted adaptively by evaluating the signal-to-noise ratio of the output signal,and then the weak speech signal is optimally detected.Experimental simulation analysis showed that under the background of strong noise,the output signal-to-noise ratio increased from the initial value-7dB to about 0.86 dB,with the gain of signalto-noise ratio is 7.86 dB.This method obviously raises the signal-to-noise ratio of the output speech signals,which gives a new idea to detect the weak speech signals in strong noise environment.
Model Based Inference for Wire Chafe Diagnostics
NASA Technical Reports Server (NTRS)
Schuet, Stefan R.; Wheeler, Kevin R.; Timucin, Dogan A.; Wysocki, Philip F.; Kowalski, Marc Edward
2009-01-01
Presentation for Aging Aircraft conference covering chafing fault diagnostics using Time Domain Reflectometry. Laboratory setup and experimental methods are presented, along with initial results that summarize fault modeling and detection capabilities.
Checklist and "Pollard Walk" butterfly survey methods on public lands
Royer, Ronald A.; Austin, Jane E.; Newton, Wesley E.
1998-01-01
Checklist and “Pollard Walk” butterfly survey methods were contemporaneously applied to seven public sites in North Dakota during the summer of 1995. Results were compared for effect of method and site on total number of butterflies and total number of species detected per hour. Checklist searching produced significantly more butterfly detections per hour than Pollard Walks at all sites. Number of species detected per hour did not differ significantly either among sites or between methods. Many species were detected by only one method, and at most sites generalist and invader species were more likely to be observed during checklist searches than during Pollard Walks. Results indicate that checklist surveys are a more efficient means for initial determination of a species list for a site, whereas for long-term monitoring the Pollard Walk is more practical and statistically manageable. Pollard Walk transects are thus recommended once a prairie butterfly fauna has been defined for a site by checklist surveys.
Hoppe, Cindy C; Nguyen, Lida T; Kirsch, Lee E; Wiencek, John M
2008-01-01
Background Glucagon is a peptide hormone with many uses as a therapeutic agent, including the emergency treatment of hypoglycemia. Physical instability of glucagon in solution leads to problems with the manufacture, formulation, and delivery of this pharmaceutical product. Glucagon has been shown to aggregate and form fibrils and gels in vitro. Small oligomeric precursors serve to initiate and nucleate the aggregation process. In this study, these initial aggregates, or seed nuclei, are characterized in bulk solution using light scattering methods and field-flow fractionation. Results High molecular weight aggregates of glucagon were detected in otherwise monomeric solutions using light scattering techniques. These aggregates were detected upon initial mixing of glucagon powder in dilute HCl and NaOH. In the pharmaceutically relevant case of acidic glucagon, the removal of aggregates by filtration significantly slowed the aggregation process. Field-flow fractionation was used to separate aggregates from monomeric glucagon and determine relative mass. The molar mass of the large aggregates was shown to grow appreciably over time as the glucagon solutions gelled. Conclusion The results of this study indicate that initial glucagon solutions are predominantly monomeric, but contain small quantities of large aggregates. These results suggest that the initial aggregates are seed nuclei, or intermediates which catalyze the aggregation process, even at low concentrations. PMID:18613970
Vasconcelos, Karla Anacleto de; Frota, Silvana Maria Monte Coelho; Ruffino-Netto, Antonio; Kritski, Afrânio Lineu
2018-04-01
To investigate early detection of amikacin-induced ototoxicity in a population treated for multidrug-resistant tuberculosis (MDR-TB), by means of three different tests: pure-tone audiometry (PTA); high-frequency audiometry (HFA); and distortion-product otoacoustic emission (DPOAE) testing. This was a longitudinal prospective cohort study involving patients aged 18-69 years with a diagnosis of MDR-TB who had to receive amikacin for six months as part of their antituberculosis drug regimen for the first time. Hearing was assessed before treatment initiation and at two and six months after treatment initiation. Sequential statistics were used to analyze the results. We included 61 patients, but the final population consisted of 10 patients (7 men and 3 women) because of sequential analysis. Comparison of the test results obtained at two and six months after treatment initiation with those obtained at baseline revealed that HFA at two months and PTA at six months detected hearing threshold shifts consistent with ototoxicity. However, DPOAE testing did not detect such shifts. The statistical method used in this study makes it possible to conclude that, over the six-month period, amikacin-associated hearing threshold shifts were detected by HFA and PTA, and that DPOAE testing was not efficient in detecting such shifts.
Kilpatrick, David R.; Nakamura, Tomofumi; Burns, Cara C.; Bukbuk, David; Oderinde, Soji B.; Oberste, M. Steven; Kew, Olen M.; Pallansch, Mark A.; Shimizu, Hiroyuki
2014-01-01
Laboratory diagnosis has played a critical role in the Global Polio Eradication Initiative since 1988, by isolating and identifying poliovirus (PV) from stool specimens by using cell culture as a highly sensitive system to detect PV. In the present study, we aimed to develop a molecular method to detect PV directly from stool extracts, with a high efficiency comparable to that of cell culture. We developed a method to efficiently amplify the entire capsid coding region of human enteroviruses (EVs) including PV. cDNAs of the entire capsid coding region (3.9 kb) were obtained from as few as 50 copies of PV genomes. PV was detected from the cDNAs with an improved PV-specific real-time reverse transcription-PCR system and nucleotide sequence analysis of the VP1 coding region. For assay validation, we analyzed 84 stool extracts that were positive for PV in cell culture and detected PV genomes from 100% of the extracts (84/84 samples) with this method in combination with a PV-specific extraction method. PV could be detected in 2/4 stool extract samples that were negative for PV in cell culture. In PV-positive samples, EV species C viruses were also detected with high frequency (27% [23/86 samples]). This method would be useful for direct detection of PV from stool extracts without using cell culture. PMID:25339406
Wu, Yuhua; Wang, Yulei; Li, Jun; Li, Wei; Zhang, Li; Li, Yunjing; Li, Xiaofei; Li, Jun; Zhu, Li; Wu, Gang
2014-01-01
The Cauliflower mosaic virus (CaMV) 35S promoter (P35S) is a commonly used target for detection of genetically modified organisms (GMOs). There are currently 24 reported detection methods, targeting different regions of the P35S promoter. Initial assessment revealed that due to the absence of primer binding sites in the P35S sequence, 19 of the 24 reported methods failed to detect P35S in MON88913 cotton, and the other two methods could only be applied to certain GMOs. The rest three reported methods were not suitable for measurement of P35S in some testing events, because SNPs in binding sites of the primer/probe would result in abnormal amplification plots and poor linear regression parameters. In this study, we discovered a conserved region in the P35S sequence through sequencing of P35S promoters from multiple transgenic events, and developed new qualitative and quantitative detection systems targeting this conserved region. The qualitative PCR could detect the P35S promoter in 23 unique GMO events with high specificity and sensitivity. The quantitative method was suitable for measurement of P35S promoter, exhibiting good agreement between the amount of template and Ct values for each testing event. This study provides a general P35S screening method, with greater coverage than existing methods. PMID:25483893
Jarmusch, Alan K; Pirro, Valentina; Kerian, Kevin S; Cooks, R Graham
2014-10-07
Strep throat causing Streptococcus pyogenes was detected in vitro and in simulated clinical samples by performing touch spray ionization-mass spectrometry. MS analysis took only seconds to reveal characteristic bacterial and human lipids. Medical swabs were used as the substrate for ambient ionization. This work constitutes the initial step in developing a non-invasive MS-based test for clinical diagnosis of strep throat. It is limited to the single species, S. pyogenes, which is responsible for the vast majority of cases. The method is complementary to and, with further testing, a potential alternative to current methods of point-of-care detection of S. pyogenes.
Dark matter directional detection: comparison of the track direction determination
DOE Office of Scientific and Technical Information (OSTI.GOV)
Couturier, C.; Zopounidis, J.P.; Sauzet, N.
Several directional techniques have been proposed for a directional detection of Dark matter, among others anisotropic crystal detectors, nuclear emulsion plates, and low-pressure gaseous TPCs. The key point is to get access to the initial direction of the nucleus recoiling due to the elastic scattering by a WIMP. In this article, we aim at estimating, for each method, how the information of the recoil track initial direction is preserved in different detector materials. We use the SRIM simulation code to emulate the motion of the first recoiling nucleus in each material. We propose the use of a new observable, Dmore » , to quantify the preservation of the initial direction of the recoiling nucleus in the detector. We show that in an emulsion mix and an anisotropic crystal, the initial direction is lost very early, while in a typical TPC gas mix, the direction is well preserved.« less
The Low Energy Neutrino Spectrometry (LENS) Experiment and LENS prototype, μLENS, initial results
NASA Astrophysics Data System (ADS)
Yokley, Zachary
2012-03-01
LENS is a low energy solar neutrino detector that will measure the solar neutrino spectrum above 115 keV, >95% of the solar neutrino flux, in real time. The fundamental neutrino reaction in LENS is charged-current based capture on 115-In detected in a liquid scintillator medium. The reaction yields the prompt emission of an electron and the delayed emission of 2 gamma rays that serve as a time & space coincidence tag. Sufficient spatial resolution is used to exploit this signature and suppress background, particularly due to 115-In beta decay. A novel design of optical segmentation (Scintillation Lattice or SL) channels the signal light along the three primary axes. The channeling is achieved via total internal reflection by suitable low index gaps in the segmentation. The spatial resolution of a nuclear event is obtained digitally, much more precisely than possible by common time of flight methods. Advanced Geant4 analysis methods have been developed to suppress adequately the severe background due to 115-In beta decay, achieving at the same time high detection efficiency. LENS physics and detection methods along with initial results characterizing light transport in the as built μLENS prototype will be presented.
Vision based speed breaker detection for autonomous vehicle
NASA Astrophysics Data System (ADS)
C. S., Arvind; Mishra, Ritesh; Vishal, Kumar; Gundimeda, Venugopal
2018-04-01
In this paper, we are presenting a robust and real-time, vision-based approach to detect speed breaker in urban environments for autonomous vehicle. Our method is designed to detect the speed breaker using visual inputs obtained from a camera mounted on top of a vehicle. The method performs inverse perspective mapping to generate top view of the road and segment out region of interest based on difference of Gaussian and median filter images. Furthermore, the algorithm performs RANSAC line fitting to identify the possible speed breaker candidate region. This initial guessed region via RANSAC, is validated using support vector machine. Our algorithm can detect different categories of speed breakers on cement, asphalt and interlock roads at various conditions and have achieved a recall of 0.98.
Wang, Li-Juan; Ren, Ming; Zhang, Qianyi; Tang, Bo; Zhang, Chun-Yang
2017-04-18
Uracil-DNA glycosylase (UDG) is an important base excision repair (BER) enzyme responsible for the repair of uracil-induced DNA lesion and the maintenance of genomic integrity, while the aberrant expression of UDG is associated with a variety of cancers. Thus, the accurate detection of UDG activity is essential to biomedical research and clinical diagnosis. Here, we develop a fluorescent method for ultrasensitive detection of UDG activity using excision repair-initiated enzyme-assisted bicyclic cascade signal amplification. This assay involves (1) UDG-actuated uracil-excision repair, (2) excision repair-initiated nicking enzyme-mediated isothermal exponential amplification, (3) ribonuclease H (RNase H)-induced hydrolysis of signal probes for generating fluorescence signal. The presence of UDG enables the removal of uracil from U·A pairs and generates an apurinic/apyrimidinic (AP) site. Endonuclease IV (Endo IV) subsequently cleaves the AP site, resulting in the break of DNA substrate. The cleaved DNA substrate functions as both a primer and a template to initiate isothermal exponential amplification, producing a large number of triggers. The resultant trigger may selectively hybridize with the signal probe which is modified with FAM and BHQ1, forming a RNA-DNA heterogeneous duplex. The subsequent hydrolysis of RNA-DNA duplex by RNase H leads to the generation of fluorescence signal. This assay exhibits ultrahigh sensitivity with a detection limit of 0.0001 U/mL, and it can even measure UDG activity at the single-cell level. Moreover, this method can be applied for the measurement of kinetic parameters and the screening of inhibitors, thereby providing a powerful tool for DNA repair enzyme-related biomedical research and clinical diagnosis.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramuhalli, P.; Meyer, R.M.; Fricke, J.M.
2012-09-01
The overall objective of this project was to investigate the effectiveness of nondestructive examination (NDE) technology in detecting material degradation precursors by initiating and growing cracks in selected materials and using NDE methods to measure crack precursors prior to the onset of cracking. Nuclear reactor components are subject to stresses over time that are not precisely known and that make the life expectancy of components difficult to determine. To prevent future issues with the operation of these plants because of unforeseen failure of components, NDE technology is needed that can be used to identify and quantify precursors to macroscopic degradationmore » of materials. Some of the NDE methods being researched as possible solutions to the precursor detection problem are magnetic Barkhausen noise, nonlinear ultrasonics, acoustic emission, eddy current measurements, and guided wave technology. In FY12, the objective was to complete preliminary assessment of advanced NDE techniques for sensitivity to degradation precursors, using prototypical degradation mechanisms in laboratory-scale measurements. This present document reports on the deliverable that meets the following milestone: M3LW-12OR0402143 – Report detailing an initial demonstration on samples from the crack-initiation tests will be provided (demonstrating acceleration of the work).« less
Luo, Qiaohui; Yu, Neng; Shi, Chunfei; Wang, Xiaoping; Wu, Jianmin
2016-12-01
A surface plasmon resonance (SPR) sensor combined with nanoscale molecularly imprinted polymer (MIP) film as recognition element was developed for selective detection of the antibiotic ciprofloxacin (CIP). The MIP film on SPR sensor chip was prepared by in situ photo-initiated polymerization method which has the advantages of short polymerization time, controllable thickness and good uniformity. The surface wettability and thickness of MIP film on SPR sensor chip were characterized by static contact angle measurement and stylus profiler. The MIP-SPR sensor exhibited high selectivity, sensitivity and good stability for ciprofloxacin. The imprinting factors of the MIP-SPR sensor to ciprofloxacin and its structural analogue ofloxacin were 2.63 and 3.80, which is much higher than those to azithromycin, dopamine and penicillin. The SPR response had good linear relation with CIP concentration over the range 10 -11 -10 -7 molL -1 . The MIP-SPR sensor also showed good repeatability and stability during cyclic detections. On the basis of the photo-initiated polymerization method, a surface plasmon resonance imaging (SPRi) chip modified with three types of MIP sensing spots was fabricated. The MIPs-SPRi sensor shows different response patterns to ciprofloxacin and azithromycin, revealing the ability to recognize different antibiotic molecules. Copyright © 2016 Elsevier B.V. All rights reserved.
Online Bridge Crack Monitoring with Smart Film
Wang, Shuliang; Li, Xingxing; Zhou, Zhixiang; Zhang, Xu; Yang, Guang; Qiu, Minfeng
2013-01-01
Smart film crack monitoring method, which can be used for detecting initiation, length, width, shape, location, and propagation of cracks on real bridges, is proposed. Firstly, the fabrication of the smart film is developed. Then the feasibility of the method is analyzed and verified by the mechanical sensing character of the smart film under the two conditions of normal strain and crack initiation. Meanwhile, the coupling interference between parallel enameled wires of the smart film is discussed, and then low-frequency detecting signal and the custom communication protocol are used to decrease interference. On this basis, crack monitoring system with smart film is designed, where the collected crack data is sent to the remote monitoring center and the cracks are simulated and recurred. Finally, the monitoring system is applied to six bridges, and the effects are discussed. PMID:24489496
Preliminary Results of Cleaning Process for Lubricant Contamination
NASA Astrophysics Data System (ADS)
Eisenmann, D.; Brasche, L.; Lopez, R.
2006-03-01
Fluorescent penetrant inspection (FPI) is widely used for aviation and other components for surface-breaking crack detection. As with all inspection methods, adherence to the process parameters is critical to the successful detection of defects. Prior to FPI, components are cleaned using a variety of cleaning methods which are selected based on the alloy and the soil types which must be removed. It is also important that the cleaning process not adversely affect the FPI process. There are a variety of lubricants and surface coatings used in the aviation industry which must be removed prior to FPI. To assess the effectiveness of typical cleaning processes on removal of these contaminants, a study was initiated at an airline overhaul facility. Initial results of the cleaning study for lubricant contamination in nickel, titanium and aluminum alloys will be presented.
Azim, Riyasat; Li, Fangxing; Xue, Yaosuo; ...
2017-07-14
Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Azim, Riyasat; Li, Fangxing; Xue, Yaosuo
Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less
Vision-based method for detecting driver drowsiness and distraction in driver monitoring system
NASA Astrophysics Data System (ADS)
Jo, Jaeik; Lee, Sung Joo; Jung, Ho Gi; Park, Kang Ryoung; Kim, Jaihie
2011-12-01
Most driver-monitoring systems have attempted to detect either driver drowsiness or distraction, although both factors should be considered for accident prevention. Therefore, we propose a new driver-monitoring method considering both factors. We make the following contributions. First, if the driver is looking ahead, drowsiness detection is performed; otherwise, distraction detection is performed. Thus, the computational cost and eye-detection error can be reduced. Second, we propose a new eye-detection algorithm that combines adaptive boosting, adaptive template matching, and blob detection with eye validation, thereby reducing the eye-detection error and processing time significantly, which is hardly achievable using a single method. Third, to enhance eye-detection accuracy, eye validation is applied after initial eye detection, using a support vector machine based on appearance features obtained by principal component analysis (PCA) and linear discriminant analysis (LDA). Fourth, we propose a novel eye state-detection algorithm that combines appearance features obtained using PCA and LDA, with statistical features such as the sparseness and kurtosis of the histogram from the horizontal edge image of the eye. Experimental results showed that the detection accuracies of the eye region and eye states were 99 and 97%, respectively. Both driver drowsiness and distraction were detected with a success rate of 98%.
Long-term detection of Parkinsonian tremor activity from subthalamic nucleus local field potentials.
Houston, Brady; Blumenfeld, Zack; Quinn, Emma; Bronte-Stewart, Helen; Chizeck, Howard
2015-01-01
Current deep brain stimulation paradigms deliver continuous stimulation to deep brain structures to ameliorate the symptoms of Parkinson's disease. This continuous stimulation has undesirable side effects and decreases the lifespan of the unit's battery, necessitating earlier replacement. A closed-loop deep brain stimulator that uses brain signals to determine when to deliver stimulation based on the occurrence of symptoms could potentially address these drawbacks of current technology. Attempts to detect Parkinsonian tremor using brain signals recorded during the implantation procedure have been successful. However, the ability of these methods to accurately detect tremor over extended periods of time is unknown. Here we use local field potentials recorded during a deep brain stimulation clinical follow-up visit 1 month after initial programming to build a tremor detection algorithm and use this algorithm to detect tremor in subsequent visits up to 8 months later. Using this method, we detected the occurrence of tremor with accuracies between 68-93%. These results demonstrate the potential of tremor detection methods for efficacious closed-loop deep brain stimulation over extended periods of time.
Devaja, Omer; Mehra, Gautam; Coutts, Michael; Montalto, Stephen Attard; Donaldson, John; Kodampur, Mallikarjun; Papadopoulos, Andreas John
2012-07-01
To establish the accuracy of sentinel lymph node (SLN) detection in early cervical cancer. Sentinel lymph node detection was performed prospectively over a 6-year period in 86 women undergoing surgery for cervical carcinoma by the combined method (Tc-99m and methylene blue dye). Further ultrastaging was performed on a subgroup of 26 patients who had benign SLNs on initial routine histological examination. The SLN was detected in 84 (97.7%) of 86 women by the combined method. Blue dye uptake was not seen in 8 women (90.7%). Sentinel lymph nodes were detected bilaterally in 63 women (73.3%), and the external iliac region was the most common anatomic location (48.8%). The median SLN count was 3 nodes (range, 1-7). Of the 84 women with sentinel node detection, 65 also underwent bilateral pelvic lymph node dissection, and in none of these cases was a benign SLN associated with a malignant non-SLN (100% negative predictive value). The median non-SLN count for all patients was 19 nodes (range, 8-35). Eighteen patients underwent removal of the SLN without bilateral pelvic lymph node dissection. Nine women (10.5%) had positive lymph nodes on final histology. One patient had bulky pelvic nodes on preoperative imaging and underwent removal of the negative bulky malignant lymph nodes and a benign SLN on the contralateral side. This latter case confirms the unreliability of the SLN method with bulky nodes. The remaining 8 patients had positive SLNs with negative nonsentinel lymph nodes. Fifty-nine SLNs from 26 patients, which were benign on initial routine histology, underwent ultrastaging, but no further disease was identified. Four patients (5%) relapsed after a median follow-up of 28 months (range, 8-80 months). Sentinel lymph node detection is an accurate and safe method in the assessment of nodal status in early cervical carcinoma.
Qi, Xiaoquan; Bakht, Saleha; Devos, Katrien M.; Gale, Mike D.; Osbourn, Anne
2001-01-01
A flexible, non-gel-based single nucleotide polymorphism (SNP) detection method is described. The method adopts thermostable ligation for allele discrimination and rolling circle amplification (RCA) for signal enhancement. Clear allelic discrimination was achieved after staining of the final reaction mixtures with Cybr-Gold and visualisation by UV illumination. The use of a compatible buffer system for all enzymes allows the reaction to be initiated and detected in the same tube or microplate well, so that the experiment can be scaled up easily for high-throughput detection. Only a small amount of DNA (i.e. 50 ng) is required per assay, and use of carefully designed short padlock probes coupled with generic primers and probes make the SNP detection cost effective. Biallelic assay by hybridisation of the RCA products with fluorescence dye-labelled probes is demonstrated, indicating that ligation-RCA (L-RCA) has potential for multiplexed assays. PMID:11713336
Historical Techniques of Lie Detection
Vicianova, Martina
2015-01-01
Since time immemorial, lying has been a part of everyday life. For this reason, it has become a subject of interest in several disciplines, including psychology. The purpose of this article is to provide a general overview of the literature and thinking to date about the evolution of lie detection techniques. The first part explores ancient methods recorded circa 1000 B.C. (e.g., God’s judgment in Europe). The second part describes technical methods based on sciences such as phrenology, polygraph and graphology. This is followed by an outline of more modern-day approaches such as FACS (Facial Action Coding System), functional MRI, and Brain Fingerprinting. Finally, after the familiarization with the historical development of techniques for lie detection, we discuss the scope for new initiatives not only in the area of designing new methods, but also for the research into lie detection itself, such as its motives and regulatory issues related to deception. PMID:27247675
Engström, Anna
2016-01-01
Tuberculosis (TB) is an ancient disease, but not a disease of the past. The increasing prevalence of drug-resistant strains of Mycobacterium tuberculosis, the causative agent of TB, demands new measures to combat the situation. Rapid and accurate detection of the pathogen, and its drug susceptibility pattern, is essential for timely initiation of treatment, and ultimately, control of the disease. Molecular-based methods offer a great chance to improve detection of drug-resistant TB; however, their development and usage should be accompanied with a profound understanding of drug resistance mechanisms and circulating M. tuberculosis strains in specific settings, as otherwise, the usefulness of such tests may be limited. This review gives an overview of the history of TB treatment and drug resistance, drug resistance mechanisms for the most commonly used drugs and molecular methods designed to detect drug-resistant strains.
A novel orthoimage mosaic method using the weighted A* algorithm for UAV imagery
NASA Astrophysics Data System (ADS)
Zheng, Maoteng; Zhou, Shunping; Xiong, Xiaodong; Zhu, Junfeng
2017-12-01
A weighted A* algorithm is proposed to select optimal seam-lines in orthoimage mosaic for UAV (Unmanned Aircraft Vehicle) imagery. The whole workflow includes four steps: the initial seam-line network is firstly generated by standard Voronoi Diagram algorithm; an edge diagram is then detected based on DSM (Digital Surface Model) data; the vertices (conjunction nodes) of initial network are relocated since some of them are on the high objects (buildings, trees and other artificial structures); and, the initial seam-lines are finally refined using the weighted A* algorithm based on the edge diagram and the relocated vertices. The method was tested with two real UAV datasets. Preliminary results show that the proposed method produces acceptable mosaic images in both the urban and mountainous areas, and is better than the result of the state-of-the-art methods on the datasets.
Chen, Xinguang
2014-01-01
Objectives. Guided by the life-course perspective, we examined whether there were subgroups with different likelihood curves of smoking onset associated with specific developmental periods. Methods. Using 12 waves of panel data from 4088 participants in the National Longitudinal Survey of Youth 1997, we detected subgroups with distinctive risk patterns by employing developmental trajectory modeling analysis. Results. From birth to age 29 years, 72% of female and 74% of US males initiated smoking. We detected 4 exclusive groups with distinctive risk patterns for both genders: the Pre-Teen Risk Group initiated smoking by age 12 years, the Teenage Risk Group initiated smoking by age 18 years, the Young Adult Risk Group initiated smoking by age 25 years, and the Low Risk Group experienced little or no risk over time. Groups differed on several etiological and outcome variables. Conclusions. The process of smoking initiation from birth to young adulthood is nonhomogeneous, with distinct subgroups whose risk of smoking onset is linked to specific stages in the life course. PMID:24328611
Lette, Manon; Baan, Caroline A; van den Berg, Matthijs; de Bruin, Simone R
2015-10-30
Over the last years, several initiatives on early detection and intervention have been put in place to proactively identify health and social problems in (frail) older people. An overview of the initiatives currently available in the Netherlands is lacking, and it is unknown whether they meet the preferences and needs of older people. Therefore, the objectives of this study were threefold: 1. To identify initiatives on early detection and intervention for older people in the Netherlands and compare their characteristics; 2. To explore the experiences of professionals with these initiatives; and 3. To explore to what extent existing initiatives meet the preferences and needs of older people. We performed a qualitative descriptive study in which we conducted semi-structured interviews with seventeen experts in preventive elderly care and three group interviews with volunteer elderly advisors. Data were analysed using the framework analysis method. We identified eight categories of initiatives based on the setting (e.g. general practitioner practice, hospital, municipality) in which they were offered. Initiatives differed in their aims and target groups. The utilization of peers to identify problems and risks, as was done by some initiatives, was seen as a strength. Difficulties were experienced with identifying the target group that would benefit from proactive delivery of care and support most, and with addressing prevalent issues among older people (e.g. psychosocial issues, self-reliance issues). Although there is a broad array of initiatives available, there is a discrepancy between supply and demand. Current initiatives insufficiently address needs of (frail) older people. More insight is needed in "what should be done by whom, for which target group and at what moment", in order to improve current practice in preventive elderly care.
Detecting Gear Tooth Fatigue Cracks in Advance of Complete Fracture
NASA Technical Reports Server (NTRS)
Zakrajsek, James J.; Lewicki, David G.
1996-01-01
Results of using vibration-based methods to detect gear tooth fatigue cracks are presented. An experimental test rig was used to fail a number of spur gear specimens through bending fatigue. The gear tooth fatigue crack in each test was initiated through a small notch in the fillet area of a tooth on the gear. The primary purpose of these tests was to verify analytical predictions of fatigue crack propagation direction and rate as a function of gear rim thickness. The vibration signal from a total of three tests was monitored and recorded for gear fault detection research. The damage consisted of complete rim fracture on the two thin rim gears and single tooth fracture on the standard full rim test gear. Vibration-based fault detection methods were applied to the vibration signal both on-line and after the tests were completed. The objectives of this effort were to identify methods capable of detecting the fatigue crack and to determine how far in advance of total failure positive detection was given. Results show that the fault detection methods failed to respond to the fatigue crack prior to complete rim fracture in the thin rim gear tests. In the standard full rim gear test all of the methods responded to the fatigue crack in advance of tooth fracture; however, only three of the methods responded to the fatigue crack in the early stages of crack propagation.
Distribution, pharmacokinetics and primary metabolism model of tramadol in zebrafish.
Zhuo, Huiqin; Jin, Hongwei; Peng, Huifang; Huang, Heqing
2016-12-01
The current study aimed to develop a rapid, robust and adequately sensitive method for simultaneous determination of the concentration of tramadol and its active metabolites in zebrafish. The pharmacokinetic and elimination pattern of tramadol and its major phase I metabolites following oral or intramuscular administration in zebrafish tissues was achieved using electrospray ionization‑quadrupole‑time of flight/mass spectrometry (ESI‑Q‑TOF/MS) and gas chromatography/mass spectrometry (GC‑MS). Following administration, the metabolisms were detected in the brain, eyes, muscle and gill tissues within 1 h. Two tramadol metabolites, O‑ and N‑desmethyltramadol, were detected in brain tissue, with N‑desmethyltramadol detected at a higher level. Following GC‑MS detection the curve indicated an initial rapid phase, corresponding to the detection of the tramadol within 1 min, and reached peak value in the brain at 5 min. Faster drug clearance was detected in low‑dose groups, and concentration had dropped around the to initial level (1.11 µg) at 20 min, but was detectable for up to 3 h. However, it took 80 min to fall back to the initial value (1.73 µg) in the high‑dose groups, and tramadol was detectable for up to 4 h. This study developed and validated a simple and high throughput analytical procedure to determine the distribution and pharmacokinetic profiles of tramadol, and its primary metabolites in tissues of zebrafish.
Fully automatic detection of salient features in 3-d transesophageal images.
Curiale, Ariel H; Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Ren, Ben; Aja-Fernández, Santiago; Bosch, Johan G
2014-12-01
Most automated segmentation approaches to the mitral valve and left ventricle in 3-D echocardiography require a manual initialization. In this article, we propose a fully automatic scheme to initialize a multicavity segmentation approach in 3-D transesophageal echocardiography by detecting the left ventricle long axis, the mitral valve and the aortic valve location. Our approach uses a probabilistic and structural tissue classification to find structures such as the mitral and aortic valves; the Hough transform for circles to find the center of the left ventricle; and multidimensional dynamic programming to find the best position for the left ventricle long axis. For accuracy and agreement assessment, the proposed method was evaluated in 19 patients with respect to manual landmarks and as initialization of a multicavity segmentation approach for the left ventricle, the right ventricle, the left atrium, the right atrium and the aorta. The segmentation results revealed no statistically significant differences between manual and automated initialization in a paired t-test (p > 0.05). Additionally, small biases between manual and automated initialization were detected in the Bland-Altman analysis (bias, variance) for the left ventricle (-0.04, 0.10); right ventricle (-0.07, 0.18); left atrium (-0.01, 0.03); right atrium (-0.04, 0.13); and aorta (-0.05, 0.14). These results indicate that the proposed approach provides robust and accurate detection to initialize a multicavity segmentation approach without any user interaction. Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
Automatic tracking of wake vortices using ground-wind sensor data
DOT National Transportation Integrated Search
1977-01-03
Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...
Thermographic techniques and adapted algorithms for automatic detection of foreign bodies in food
NASA Astrophysics Data System (ADS)
Meinlschmidt, Peter; Maergner, Volker
2003-04-01
At the moment foreign substances in food are detected mainly by using mechanical and optical methods as well as ultrasonic technique and than they are removed from the further process. These techniques detect a large portion of the foreign substances due to their different mass (mechanical sieving), their different colour (optical method) and their different surface density (ultrasonic detection). Despite the numerous different methods a considerable portion of the foreign substances remain undetected. In order to recognise materials still undetected, a complementary detection method would be desirable removing the foreign substances not registered by the a.m. methods from the production process. In a project with 13 partner from the food industry, the Fraunhofer - Institut für Holzforschung (WKI) and the Technische Unsiversität are trying to adapt thermography for the detection of foreign bodies in the food industry. After the initial tests turned out to be very promising for the differentiation of food stuffs and foreign substances, more and detailed investigation were carried out to develop suitable algorithms for automatic detection of foreign bodies. In order to achieve -besides the mere visual detection of foreign substances- also an automatic detection under production conditions, numerous experiences in image processing and pattern recognition are exploited. Results for the detection of foreign bodies will be presented at the conference showing the different advantages and disadvantages of using grey - level, statistical and morphological image processing techniques.
Collision Avoidance for Airport Traffic Concept Evaluation
NASA Technical Reports Server (NTRS)
Jones, Denise R.; Prinzel, Lawrence J., III; Otero, Sharon D.; Barker, Glover D.
2009-01-01
An initial Collision Avoidance for Airport Traffic (CAAT) concept for the Terminal Maneuvering Area (TMA) was evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. CAAT is being designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The purpose of the study was to evaluate the initial concept for an aircraft-based method of conflict detection and resolution (CD&R) in the TMA focusing on conflict detection algorithms and alerting display concepts. This paper gives an overview of the CD&R concept, simulation study, and test results.
Detection and monitoring of shear crack growth using S-P conversion of seismic waves
NASA Astrophysics Data System (ADS)
Modiriasari, A.; Bobet, A.; Pyrak-Nolte, L. J.
2017-12-01
A diagnostic method for monitoring shear crack initiation, propagation, and coalescence in rock is key for the detection of major rupture events, such as slip along a fault. Active ultrasonic monitoring was used in this study to determine the precursory signatures to shear crack initiation in pre-cracked rock. Prismatic specimens of Indiana limestone (203x2101x638x1 mm) with two pre-existing parallel flaws were subjected to uniaxial compression. The flaws were cut through the thickness of the specimen using a scroll saw. The length of the flaws was 19.05 mm and had an inclination angle with respect to the loading direction of 30o. Shear wave transducers were placed on each side of the specimen, with polarization parallel to the loading direction. The shear waves, given the geometry of the flaws, were normally incident to the shear crack forming between the two flaws during loading. Shear crack initiation and propagation was detected on the specimen surface using digital image correlation (DIC), while initiation inside the rock was monitored by measuring full waveforms of the transmitted and reflected shear (S) waves across the specimen. Prior to the detection of a shear crack on the specimen surface using DIC, transmitted S waves were converted to compressional (P) waves. The emergence of converted S-P wave occurs because of the presence of oriented microcracks inside the rock. The microcracks coalesce and form the shear crack observed on the specimen surface. Up to crack coalescence, the amplitude of the converted waves increased with shear crack propagation. However, the amplitude of the transmitted shear waves between the two flaws did not change with shear crack initiation and propagation. This is in agreement with the conversion of elastic waves (P- to S-wave or S- to P-wave) observed by Nakagawa et al., (2000) for normal incident waves. Elastic wave conversions are attributed to the formation of an array of oriented microcracks that dilate under shear stress, which causes energy partitioning into P, S, and P-to-S or S-to-P waves. This finding provides a diagnostic method for detecting shear crack initiation and growth using seismic wave conversions. Acknowledgments: This material is based upon work supported by the National Science Foundation, Geomechanics and Geotechnical Systems Program (award No. CMMI-1162082).
Early detection and progression of decay in L-joints and lap-joints in a moderate decay hazard zone
Carol A. Clausen; Terry L. Highley; Daniel L. Lindner
2006-01-01
Accelerated test methods are needed to evaluate the initiation and progression of decay in wood exposed aboveground. The relationship between test conditions and initiation of decay, however, is poorly understood. Southern pine and maple L-joints and lap-joints were exposed aboveground in a configuration that encouraged water entrapment at the Valley View Experimental...
Momose, Wataru; Yoshino, Hiroyuki; Katakawa, Yoshifumi; Yamashita, Kazunari; Imai, Keiji; Sako, Kazuhiro; Kato, Eiji; Irisawa, Akiyoshi; Yonemochi, Etsuo; Terada, Katsuhide
2012-01-01
Here, we describe a nondestructive approach using terahertz wave to detect crack initiation in a film-coated layer on a drug tablet. During scale-up and scale-down of the film coating process, differences in film density and gaps between the film-coated layer and the uncoated tablet were generated due to differences in film coating process parameters, such as the tablet-filling rate in the coating machine, spray pressure, and gas–liquid ratio etc. Tablets using the PEO/PEG formulation were employed as uncoated tablets. We found that heat and humidity caused tablets to swell, thereby breaking the film-coated layer. Using our novel approach with terahertz wave nondestructively detect film surface density (FSD) and interface density differences (IDDs) between the film-coated layer and an uncoated tablet. We also found that a reduced FSD and IDD between the film-coated layer and uncoated tablet increased the risk of crack initiation in the film-coated layer, thereby enabling us to nondestructively predict initiation of cracks in the film-coated layer. Using this method, crack initiation can be nondestructively assessed in swelling tablets after the film coating process without conducting accelerated stability tests, and film coating process parameters during scale-up and scale-down studies can be appropriately established. PMID:25755992
Arita, Minetaro; Kilpatrick, David R; Nakamura, Tomofumi; Burns, Cara C; Bukbuk, David; Oderinde, Soji B; Oberste, M Steven; Kew, Olen M; Pallansch, Mark A; Shimizu, Hiroyuki
2015-01-01
Laboratory diagnosis has played a critical role in the Global Polio Eradication Initiative since 1988, by isolating and identifying poliovirus (PV) from stool specimens by using cell culture as a highly sensitive system to detect PV. In the present study, we aimed to develop a molecular method to detect PV directly from stool extracts, with a high efficiency comparable to that of cell culture. We developed a method to efficiently amplify the entire capsid coding region of human enteroviruses (EVs) including PV. cDNAs of the entire capsid coding region (3.9 kb) were obtained from as few as 50 copies of PV genomes. PV was detected from the cDNAs with an improved PV-specific real-time reverse transcription-PCR system and nucleotide sequence analysis of the VP1 coding region. For assay validation, we analyzed 84 stool extracts that were positive for PV in cell culture and detected PV genomes from 100% of the extracts (84/84 samples) with this method in combination with a PV-specific extraction method. PV could be detected in 2/4 stool extract samples that were negative for PV in cell culture. In PV-positive samples, EV species C viruses were also detected with high frequency (27% [23/86 samples]). This method would be useful for direct detection of PV from stool extracts without using cell culture. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
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
Valente-Campos, Simone; Yonamine, Mauricio; de Moraes Moreau, Regina Lucia; Silva, Ovandir Alves
2006-06-02
The objective of the present work was to compare previously published methods and provide validation data to detect simultaneously cocaine (COC), benzoylecgonine (BE) and norcocaine (NCOC) in nail. Finger and toenail samples (5mg) were cut in very small pieces and submitted to an initial procedure for external decontamination. Methanol (3 ml) was used to release analytes from the matrix. A cleanup step was performed simultaneously by solid-phase extraction (SPE) and the residue was derivatized with pentafluoropropionic anhydride/pentafluoropropanol (PFPA/PFP). Gas chromatography-mass spectrometry (GC-MS) was used to detect the analytes in selected ion monitoring mode (SIM). Confidence parameters of validation of the method were: recovery, intra- and inter-assay precision, as well as limit of detection (LOD) of the analytes. The limits of detection were: 3.5 ng/mg for NCOC and 3.0 ng/mg for COC and BE. Good intra-assay precision was observed for all detected substances (coefficient of variation (CV)<11%). The inter-assay precision for norcocaine and benzoylecgonine were <4%. For intra- and inter-assay precision deuterated internal standards were used. Toenail and fingernail samples from eight declared cocaine users were submitted to the validated method.
Gheit, Tarik; Tommasino, Massimo
2011-01-01
Epidemiological and functional studies have clearly demonstrated that certain types of human papillomavirus (HPV) from the genus alpha of the HPV phylogenetic tree, referred to as high-risk (HR) types, are the etiological cause of cervical cancer. Several methods for HPV detection and typing have been developed, and their importance in clinical and epidemiological studies has been well demonstrated. However, comparative studies have shown that several assays have different sensitivities for the detection of specific HPV types, particularly in the case of multiple infections. In this chapter, we describe a novel one-shot method for the detection and typing of 19 mucosal HR HPV types (types 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 70, 73, and 82). The assay combines the advantages of the multiplex PCR methods, i.e., high sensitivity and the possibility to perform multiple amplifications in a single reaction, with an array primer extension (APEX) assay. The latter method offers the benefits of Sanger dideoxy sequencing with the high-throughput potential of the microarray. Initial studies have revealed that the assay is very sensitive in detecting multiple HPV infections.
Jarmusch, Alan K.; Pirro, Valentina; Kerian, Kevin S.; Cooks, Graham
2014-01-01
Strep throat causing Streptococcus pyogenes was detected in vitro and in simulated clinical samples by performing touch spray ionization - mass spectrometry. MS analysis took only seconds to reveal characteristic bacterial and human lipids. Medical swabs were used as the substrate for ambient ionization. This work constitutes the initial step in developing a noninvasive MS-based test for clinical diagnosis of strep throat. It is limited to the single species, S. pyogenes, which is responsible for the vast majority of cases. The method is complementary to and, with further testing, a potential alternative to current methods of point-of-care detection of S. pyogenes. PMID:25102079
Efficient airport detection using region-based fully convolutional neural networks
NASA Astrophysics Data System (ADS)
Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao
2018-04-01
This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.
Road traffic sign detection and classification from mobile LiDAR point clouds
NASA Astrophysics Data System (ADS)
Weng, Shengxia; Li, Jonathan; Chen, Yiping; Wang, Cheng
2016-03-01
Traffic signs are important roadway assets that provide valuable information of the road for drivers to make safer and easier driving behaviors. Due to the development of mobile mapping systems that can efficiently acquire dense point clouds along the road, automated detection and recognition of road assets has been an important research issue. This paper deals with the detection and classification of traffic signs in outdoor environments using mobile light detection and ranging (Li- DAR) and inertial navigation technologies. The proposed method contains two main steps. It starts with an initial detection of traffic signs based on the intensity attributes of point clouds, as the traffic signs are always painted with highly reflective materials. Then, the classification of traffic signs is achieved based on the geometric shape and the pairwise 3D shape context. Some results and performance analyses are provided to show the effectiveness and limits of the proposed method. The experimental results demonstrate the feasibility and effectiveness of the proposed method in detecting and classifying traffic signs from mobile LiDAR point clouds.
Gerwin, Philip M; Arbona, Rodolfo J Ricart; Riedel, Elyn R; Lepherd, Michelle L; Henderson, Ken S; Lipman, Neil S
2017-01-01
There is no consensus regarding the best practice for detecting murine pinworm infections. Initially, we evaluated 7 fecal concentration methods by using feces containing Aspiculuris tetraptera (AT) eggs (n = 20 samples per method). Sodium nitrate flotation, sodium nitrate centrifugation, Sheather sugar centrifugation, and zinc sulfate centrifugation detected eggs in 100% of samples; zinc sulfate flotation and water sedimentation detected eggs in 90%. All had better detection rates than Sheather sugar flotation (50%). To determine optimal detection methods, Swiss Webster mice were exposed to Syphacia obvelata (SO; n = 60) or AT (n = 60). We compared the following methods at days 0, 30, and 90, beginning 21 or 28 d after SO and AT exposure, respectively: fecal concentration (AT only), anal tape test (SO only), direct examination of intestinal contents (cecum and colon), Swiss roll histology (cecum and colon), and PCR analysis (pooled fur swab and feces). Detection rates for SO-exposed mice were: PCR analysis, 45%; Swiss roll histology, 30%; intestinal content exam, 27%; and tape test, 27%. The SO detection rate for PCR analysis was significantly greater than that for the tape test. Detection rates for AT-exposed mice were: intestinal content exam, 53%; PCR analysis, 33%; fecal flotation, 22%; and Swiss roll histology, 17%. The AT detection rate of PCR analysis combined with intestinal content examination was greater than for PCR analysis only and the AT detection rate of intestinal content examination was greater than for Swiss roll histology. Combining PCR analysis with intestinal content examination detected 100% of infected animals. No single test detected all positive animals. We recommend combining PCR analysis with intestinal content examination for optimal pinworm detection. PMID:28905712
Le Govic, Y; Guyot, K; Certad, G; Deschildre, A; Novo, R; Mary, C; Sendid, B; Viscogliosi, E; Favennec, L; Dei-Cas, E; Fréalle, E; Dutoit, E
2016-01-01
Cryptosporidiosis is an important though underreported public health concern. Molecular tools might be helpful in improving its diagnosis. In this study, ZR Fecal DNA MiniPrep™ Kit (ZR) and NucliSens® easyMAG® (EM) were compared using four Cryptosporidium-seeded feces and 29 Cryptosporidium-positive stools. Thereafter, ZR was selected for prospective evaluation of Cryptosporidium detection by 18S rDNA and LAXER quantitative PCR (qPCR) in 69 stools from 56 patients after Cryptosporidium detection by glycerin, modified Ziehl-Neelsen (ZN) and auramine-phenol (AP) stainings. The combination of any of the two extraction methods with 18S qPCR yielded adequate detection of Cryptosporidium in seeded stools, but the ZR kit showed the best performance. All 29 Cryptosporidium-positive samples were positive with 18S qPCR, after both ZR and EM extraction. However, false-negative results were found with LAXER qPCR or nested PCR. Cryptosporidiosis was diagnosed in 7/56 patients. All the microscopic methods enabled the initial diagnosis, but Cryptosporidium was detected in 12, 13, and 14 samples from these seven patients after glycerin, ZN, and AP staining respectively. Among these samples, 14 and 12 were positive with 18S and LAXER qPCR respectively. In two patients, Cryptosporidium DNA loads were found to be correlated with clinical evolution. Although little known, glycerin is a sensitive method for the initial detection of Cryptosporidium. When combined with 18S qPCR, ZR extraction, which had not been evaluated so far for Cryptosporidium, was an accurate tool for detecting Cryptosporidium and estimating the oocyst shedding in the course of infection.
Villamizar-Rodríguez, Germán; Fernández, Javier; Marín, Laura; Muñiz, Juan; González, Isabel; Lombó, Felipe
2015-01-01
Routine microbiological quality analyses in food samples require, in some cases, an initial incubation in pre-enrichment medium. This is necessary in order to ensure that small amounts of pathogenic strains are going to be detected. In this work, a universal pre-enrichment medium has been developed for the simultaneous growth of Bacillus cereus, Campylobacter jejuni, Clostridium perfringens, Cronobacter sakazakii, Escherichia coli, Enterobacteriaceae family (38 species, 27 genera), Listeria monocytogenes, Staphylococcus aureus, Salmonella spp. (two species, 13 strains). Growth confirmation for all these species was achieved in all cases, with excellent enrichments. This was confirmed by plating on the corresponding selective agar media for each bacterium. This GVUM universal pre-enrichment medium could be useful in food microbiological analyses, where different pathogenic bacteria must be detected after a pre-enrichment step. Following, a mPCR reaction for detection of all these pathogens was developed, after designing a set of nine oligonucleotide pairs from specific genetic targets on gDNA from each of these bacteria, covering all available strains already sequenced in GenBank for each pathogen type. The detection limits have been 1 Genome Equivalent (GE), with the exception of the Fam. Enterobacteriaceae (5 GEs). We obtained amplification for all targets (from 70 to 251 bp, depending on the bacteria type), showing the capability of this method to detect the most important industrial and sanitary food-borne pathogens from a universal pre-enrichment medium. This method includes an initial pre-enrichment step (18 h), followed by a mPCR (2 h) and a capillary electrophoresis (30 min); avoiding the tedious and long lasting growing on solid media required in traditional analysis (1-4 days, depending on the specific pathogen and verification procedure). An external testing of this method was conducted in order to compare classical and mPCR methods. This evaluation was carried out on five types of food matrices (meat, dairy products, prepared foods, canned fish, and pastry products), which were artificially contaminated with each one of the microorganisms, demonstrating the equivalence between both methods (coincidence percentages between both methods ranged from 78 to 92%).
Villamizar-Rodríguez, Germán; Fernández, Javier; Marín, Laura; Muñiz, Juan; González, Isabel; Lombó, Felipe
2015-01-01
Routine microbiological quality analyses in food samples require, in some cases, an initial incubation in pre-enrichment medium. This is necessary in order to ensure that small amounts of pathogenic strains are going to be detected. In this work, a universal pre-enrichment medium has been developed for the simultaneous growth of Bacillus cereus, Campylobacter jejuni, Clostridium perfringens, Cronobacter sakazakii, Escherichia coli, Enterobacteriaceae family (38 species, 27 genera), Listeria monocytogenes, Staphylococcus aureus, Salmonella spp. (two species, 13 strains). Growth confirmation for all these species was achieved in all cases, with excellent enrichments. This was confirmed by plating on the corresponding selective agar media for each bacterium. This GVUM universal pre-enrichment medium could be useful in food microbiological analyses, where different pathogenic bacteria must be detected after a pre-enrichment step. Following, a mPCR reaction for detection of all these pathogens was developed, after designing a set of nine oligonucleotide pairs from specific genetic targets on gDNA from each of these bacteria, covering all available strains already sequenced in GenBank for each pathogen type. The detection limits have been 1 Genome Equivalent (GE), with the exception of the Fam. Enterobacteriaceae (5 GEs). We obtained amplification for all targets (from 70 to 251 bp, depending on the bacteria type), showing the capability of this method to detect the most important industrial and sanitary food-borne pathogens from a universal pre-enrichment medium. This method includes an initial pre-enrichment step (18 h), followed by a mPCR (2 h) and a capillary electrophoresis (30 min); avoiding the tedious and long lasting growing on solid media required in traditional analysis (1–4 days, depending on the specific pathogen and verification procedure). An external testing of this method was conducted in order to compare classical and mPCR methods. This evaluation was carried out on five types of food matrices (meat, dairy products, prepared foods, canned fish, and pastry products), which were artificially contaminated with each one of the microorganisms, demonstrating the equivalence between both methods (coincidence percentages between both methods ranged from 78 to 92%). PMID:26579100
NASA Astrophysics Data System (ADS)
Masychev, Victor I.
2000-11-01
In this research we present the results of approbation of two methods of optical caries diagnostics: PNC-spectral diagnostics and caries detection by laser integral fluorescence. The research was conducted in a dental clinic. PNC-method analyses parameters of probing laser radiation and PNC-spectrums of stimulated secondary radiations: backscattering and endogenous fluorescence of caries-involved bacterias. He-Ne-laser ((lambda) =632,8 nm, 1-2mW) was used as a source of probing (stimulated) radiation. For registration of signals, received from intact and pathological teeth PDA-detector was applied. PNC-spectrums were processed by special algorithms, and were displayed on PC monitor. The method of laser integral fluorescence was used for comparison. In this case integral power of fluorescence of human teeth was measured. As a source of probing (stimulated) radiation diode lasers ((lambda) =655 nm, 0.1 mW and 630nm, 1mW) and He-Ne laser were applied. For registration of signals Si-photodetector was used. Integral power was shown in a digital indicator. Advantages and disadvantages of these methods are described in this research. It is disclosed that the method of laser integral power of fluorescence has the following characteristics: simplicity of construction and schema-technical decisions. However the method of PNC-spectral diagnostics are characterized by considerably more sensitivity in diagnostics of initial caries and capability to differentiate pathologies of various stages (for example, calculus/initial caries). Estimation of spectral characteristics of PNC-signals allows eliminating a number of drawbacks, which are character for detection by method of laser integral fluorescence (for instance, detection of fluorescent fillings, plagues, calculus, discolorations generally, amalgam, gold fillings as if it were caries.
NASA Astrophysics Data System (ADS)
Muramatsu, Chisako; Ishida, Kyoko; Sawada, Akira; Hatanaka, Yuji; Yamamoto, Tetsuya; Fujita, Hiroshi
2016-03-01
Early detection of glaucoma is important to slow down or cease progression of the disease and for preventing total blindness. We have previously proposed an automated scheme for detection of retinal nerve fiber layer defect (NFLD), which is one of the early signs of glaucoma observed on retinal fundus images. In this study, a new multi-step detection scheme was included to improve detection of subtle and narrow NFLDs. In addition, new features were added to distinguish between NFLDs and blood vessels, which are frequent sites of false positives (FPs). The result was evaluated with a new test dataset consisted of 261 cases, including 130 cases with NFLDs. Using the proposed method, the initial detection rate was improved from 82% to 98%. At the sensitivity of 80%, the number of FPs per image was reduced from 4.25 to 1.36. The result indicates the potential usefulness of the proposed method for early detection of glaucoma.
Ying, Na; Ju, Chuanjing; Sun, Xiuwei; Li, Letian; Chang, Hongbiao; Song, Guangping; Li, Zhongyi; Wan, Jiayu; Dai, Enyong
2017-01-01
MicroRNAs (miRNAs) constitute novel biomarkers for various diseases. Accurate and quantitative analysis of miRNA expression is critical for biomedical research and clinical theranostics. In this study, a method was developed for sensitive and specific detection of miRNAs via dual signal amplification based on duplex specific nuclease (DSN) and hybridization chain reaction (HCR). A reporter probe (RP), comprising recognition sequence (3' end modified with biotin) for a target miRNA of miR-21 and capture sequence (5' end modified with Fam) for HCR product, was designed and synthesized. HCR was initiated by partial sequence of initiator probe (IP), the other part of which can hybridize with capture sequence of RP, and was assembled by hairpin probes modified with biotin (H1-bio and H2-bio). A miR-21 triggered cyclical DSN cleavage of RP, which was immobilized to a streptavidin (SA) coated magnetic bead (MB). The released Fam labeled capture sequence then hybridized with the HCR product to generate a detectable dsDNA. This polymer was then dropped on lateral flow strip and positive result was observed. The proposed method allowed quantitative sequence-specific detection of miR-21 (with a detection limit of 2.1 fM, S/N = 3) in a dynamic range from 100 fM to 100 pM, with an excellent ability to discriminate differences in miRNAs. The method showed acceptable testing recoveries for the determination of miRNAs in serum.
A visual model for object detection based on active contours and level-set method.
Satoh, Shunji
2006-09-01
A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.
Jasiewicz, Jan M; Allum, John H J; Middleton, James W; Barriskill, Andrew; Condie, Peter; Purcell, Brendan; Li, Raymond Che Tin
2006-12-01
We report on three different methods of gait event detection (toe-off and heel strike) using miniature linear accelerometers and angular velocity transducers in comparison to using standard pressure-sensitive foot switches. Detection was performed with normal and spinal-cord injured subjects. The detection of end contact (EC), normally toe-off, and initial contact (IC) normally, heel strike was based on either foot linear accelerations or foot sagittal angular velocity or shank sagittal angular velocity. The results showed that all three methods were as accurate as foot switches in estimating times of IC and EC for normal gait patterns. In spinal-cord injured subjects, shank angular velocity was significantly less accurate (p<0.02). We conclude that detection based on foot linear accelerations or foot angular velocity can correctly identify the timing of IC and EC events in both normal and spinal-cord injured subjects.
Studies of phase transitions in the aripiprazole solid dosage form.
Łaszcz, Marta; Witkowska, Anna
2016-01-05
Studies of the phase transitions in an active substance contained in a solid dosage form are very complicated but essential, especially if an active substance is classified as a BCS Class IV drug. The purpose of this work was the development of sensitive methods for the detection of the phase transitions in the aripiprazole tablets containing initially its form III. Aripiprazole exhibits polymorphism and pseudopolymorphism. Powder diffraction, Raman spectroscopy and differential scanning calorimetry methods were developed for the detection of the polymorphic transition between forms III and I as well as the phase transition of form III into aripiprazole monohydrate in tablets. The study involved the initial 10 mg and 30 mg tablets, as well as those stored in Al/Al blisters, a triplex blister pack and HDPE bottles (with and without desiccant) under accelerated and long term conditions. The polymorphic transition was not observed in the initial and stored tablets but it was visible on the DSC curve of the Abilify(®) 10 mg reference tablets. The formation of the monohydrate was observed in the diffractograms and Raman spectra in the tablets stored under accelerated conditions. The monohydrate phase was not detected in the tablets stored in the Al/Al blisters under long term conditions. The results showed that the Al/Al blisters can be recommended as the packaging of the aripiprazole tablets containing form III. Copyright © 2015 Elsevier B.V. All rights reserved.
Mitchell, J M; Griffiths, M W; McEwen, S A; McNab, W B; Yee, A J
1998-06-01
This paper presents a historical review of antimicrobial use in food animals, the causes of residues in meat and milk, the types of residues found, their regulation in Canada, tests used for their detection, and test performance parameters, with an emphasis on immunoassay techniques. The development of residue detection methods began shortly after the introduction of antimicrobials to food animal production in the late 1940s. From initial technical concerns expressed by the dairy industry to the present public health and international trade implications, there has been an ongoing need for reliable, sensitive, and economical methods for the detection of antimicrobial residues in food animal products such as milk and meat. Initially there were microbial growth inhibition tests, followed by more sensitive and specific methods based on receptor binding, immunochemical, and chromatographic principle. An understanding of basic test performance parameters and their implications is essential when choosing an analytical strategy for residue testing. While each test format has its own attributes, none test will meet all the required analytical needs. Therefore the use of a tiered or integrated system employing assays designated for screening and confirmation is necessary to ensure that foods containing violative residues are not introduced into the food chain.
Floor Identification with Commercial Smartphones in Wifi-Based Indoor Localization System
NASA Astrophysics Data System (ADS)
Ai, H. J.; Liu, M. Y.; Shi, Y. M.; Zhao, J. Q.
2016-06-01
In this paper, we utilize novel sensors built-in commercial smart devices to propose a schema which can identify floors with high accuracy and efficiency. This schema can be divided into two modules: floor identifying and floor change detection. Floor identifying module starts at initial phase of positioning, and responsible for determining which floor the positioning start. We have estimated two methods to identify initial floor based on K-Nearest Neighbors (KNN) and BP Neural Network, respectively. In order to improve performance of KNN algorithm, we proposed a novel method based on weighting signal strength, which can identify floors robust and quickly. Floor change detection module turns on after entering into continues positioning procedure. In this module, sensors (such as accelerometer and barometer) of smart devices are used to determine whether the user is going up and down stairs or taking an elevator. This method has fused different kinds of sensor data and can adapt various motion pattern of users. We conduct our experiment with mobile client on Android Phone (Nexus 5) at a four-floors building with an open area between the second and third floor. The results demonstrate that our scheme can achieve an accuracy of 99% to identify floor and 97% to detecting floor changes as a whole.
Possible standoff detection of ionizing radiation using high-power THz electromagnetic waves
NASA Astrophysics Data System (ADS)
Nusinovich, Gregory S.; Sprangle, Phillip; Romero-Talamas, Carlos A.; Rodgers, John; Pu, Ruifeng; Kashyn, Dmytro G.; Antonsen, Thomas M., Jr.; Granatstein, Victor L.
2012-06-01
Recently, a new method of remote detection of concealed radioactive materials was proposed. This method is based on focusing high-power short wavelength electromagnetic radiation in a small volume where the wave electric field exceeds the breakdown threshold. In the presence of free electrons caused by ionizing radiation, in this volume an avalanche discharge can then be initiated. When the wavelength is short enough, the probability of having even one free electron in this small volume in the absence of additional sources of ionization is low. Hence, a high breakdown rate will indicate that in the vicinity of this volume there are some materials causing ionization of air. To prove this concept a 0.67 THz gyrotron delivering 200-300 kW power in 10 microsecond pulses is under development. This method of standoff detection of concealed sources of ionizing radiation requires a wide range of studies, viz., evaluation of possible range, THz power and pulse duration, production of free electrons in air by gamma rays penetrating through container walls, statistical delay time in initiation of the breakdown in the case of low electron density, temporal evolution of plasma structure in the breakdown and scattering of THz radiation from small plasma objects. Most of these issues are discussed in the paper.
Zhang, Kai; Wang, Ke; Zhu, Xue; Xu, Fei; Xie, Minhao
2017-01-15
MicroRNA (miRNA) has become an important biomarker candidate for cancer diagnosis, prognosis, and therapy. In this study, we have developed a novel fluorescence method for sensitive and specific miRNA detection via duplex specific nuclease (DSN) signal amplification and demonstrated its practical application in biological samples. Malachite green (MG) was employed as a "label-free" signal transducer since fluorescence of MG could be enhanced by 100-fold when MG were binding to a G-quadruplex structure formed within the d(G 2 T) 13 G sequence. The proposed signal amplification strategy is an integrated "biological circuit" designed to initiate a cascade of enzymatic reactions in order to detect, amplify, and measure a specific miRNA sequence by using the isothermal cleavage property of a DSN. The circuit is composed of two molecular switches operating in series: the amplification reaction activated by a specific miRNA and the strand-displacement polymerization reaction designed to initiate molecular beacon-assisted amplification and signal transduction by using MG/G-quadruplex complex. The hsa-miR-141 (miR141) was chosen as a target miRNA because its level specifically abnormal in a wide range of common human cancers including breast, lung, colon, and prostate cancer. The proposed method allowed quantitative sequence-specific detection of miR141 (with a detection limit of 1.03pM) in a dynamic range from 1pM to 10μM, with an excellent ability to discriminate differences in miRNAs. Moreover, the detection assay was applied to quantify miR141 in cancerous cell lysates. On the basis of these findings, we believe that this proposed sensitive and specific assay has great potential as a miRNA quantification method for use in biomedical research and clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.
Forward collision warning based on kernelized correlation filters
NASA Astrophysics Data System (ADS)
Pu, Jinchuan; Liu, Jun; Zhao, Yong
2017-07-01
A vehicle detection and tracking system is one of the indispensable methods to reduce the occurrence of traffic accidents. The nearest vehicle is the most likely to cause harm to us. So, this paper will do more research on about the nearest vehicle in the region of interest (ROI). For this system, high accuracy, real-time and intelligence are the basic requirement. In this paper, we set up a system that combines the advanced KCF tracking algorithm with the HaarAdaBoost detection algorithm. The KCF algorithm reduces computation time and increase the speed through the cyclic shift and diagonalization. This algorithm satisfies the real-time requirement. At the same time, Haar features also have the same advantage of simple operation and high speed for detection. The combination of this two algorithm contribute to an obvious improvement of the system running rate comparing with previous works. The detection result of the HaarAdaBoost classifier provides the initial value for the KCF algorithm. This fact optimizes KCF algorithm flaws that manual car marking in the initial phase, which is more scientific and more intelligent. Haar detection and KCF tracking with Histogram of Oriented Gradient (HOG) ensures the accuracy of the system. We evaluate the performance of framework on dataset that were self-collected. The experimental results demonstrate that the proposed method is robust and real-time. The algorithm can effectively adapt to illumination variation, even in the night it can meet the detection and tracking requirements, which is an improvement compared with the previous work.
NASA Astrophysics Data System (ADS)
Kovalovs, A.; Rucevskis, S.; Akishin, P.; Kolupajevs, J.
2017-10-01
The paper presents numerical results of loss of prestress in the reinforced prestressed precast hollow core slabs by modal analysis. Loss of prestress is investigated by the 3D finite element method, using ANSYS software. In the numerical examples, variables initial stresses were introduced into seven-wire stress-relieved strands of the concrete slabs. The effects of span and material properties of concrete on the modal frequencies of the concrete structure under initial stress were studied. Modal parameters computed from the finite element models were compared. Applicability and effectiveness of the proposed method was investigated.
NASA Astrophysics Data System (ADS)
Masychev, Victor I.
2001-05-01
In this research we represent the results of approbation of two methods of optical caries diagnostics: PNC-spectral diagnostics and caries detection by laser integral fluorescence. The research was conducted in a dental clinic. PNC-method analyzes parameters of probing laser radiation and PNC-spectrums of stimulated secondary radiations: backscattering and endogenous fluorescence of caries- involved bacteria. Ia-Ne laser ((lambda) equals632.8 nm, 1-2 mW) was used as a source of probing (stimulated) radiation. For registration of signals, received from intact and pathological teeth PDA-detector was applied. PNC-spectrums were processed by special algorithms, and were displayed on PC monitor. The method of laser integral fluorescence was used for comparison. In this case integral power of fluorescence of human teeth was measured. As a source of probing (stimulated) radiation diode lasers ((lambda) equals655 nm, 0.1 mW and 630 nm, 1 mW) and Ia-Na laser were applied. For registration of signals Si-photodetector was used. Integral power was shown in a digital indicator. Advantages and disadvantages of these methods are described in this research. It is disclosed that the method of laser integral power of fluorescence has the following characteristics: simplicity of construction and schema-technical decisions. However the method of PNC-spectral diagnostics are characterized by considerably more sensitivity in diagnostics of initial caries and capability to differentiate pathologies of various stages (for example, calculus/initial caries). Estimation of spectral characteristics of PNC-signals allows eliminating a number of drawbacks, which are character for detection by method of laser integral fluorescence (for instance, detection of fluorescent fillings, plagues, calculus, discolorations generally, amalgam, gold fillings as if it were caries).
Sommer, D; Enderlein, D; Antakli, A; Schönenbrücher, H; Slaghuis, J; Redmann, T; Lierz, M
2012-01-01
The efficiency of two commercial PCR methods based on real-time technology, the foodproof® Salmonella detection system and the BAX® PCR Assay Salmonella system was compared to standardized culture methods (EN ISO 6579:2002 - Annex D) for the detection of Salmonella spp. in poultry samples. Four sample matrices (feed, dust, boot swabs, feces) obtained directly from poultry flocks, as well as artificially spiked samples of the same matrices, were used. All samples were tested for Salmonella spp. using culture methods first as the gold standard. In addition samples spiked with Salmonella Enteridis were tested to evaluate the sensitivity of both PCR methods. Furthermore all methods were evaluated in an annual ring-trial of the National Salmonella Reference Laboratory of Germany. Salmonella detection in the matrices feed, dust and boot swabs were comparable in both PCR systems whereas the results from feces differed markedly. The quality, especially the freshness, of the fecal samples had an influence on the sensitivity of the real-time PCR and the results of the culture methods. In fresh fecal samples an initial spiking level of 100cfu/25g Salmonella Enteritidis was detected. Two-days-dried fecal samples allowed the detection of 14cfu/25g. Both real- time PCR protocols appear to be suitable for the detection of Salmonella spp. in all four matrices. The foodproof® system detected eight samples more to be positive compared to the BAX® system, but had a potential false positive result in one case. In 7-days-dried samples none of the methods was able to detect Salmonella likely through letal cell damage. In general the advantage of PCR analyses over the culture method is the reduction of working time from 4-5 days to only 2 days. However, especially for the analysis of fecal samples official validation should be conducted according to the requirement of EN ISO6579:2002 - Annex D.
Automated detection of hospital outbreaks: A systematic review of methods.
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.
Xu, Yunying; Zhou, Wenjiao; Zhou, Ming; Xiang, Yun; Yuan, Ruo; Chai, Yaqin
2015-02-15
Based on a new signal amplification strategy by the toehold strand displacement-driven cyclic assembly of G-quadruplex DNA, the development of an enzyme-free and non-label aptamer sensing approach for sensitive fluorescent detection of thrombin is described. The target thrombin associates with the corresponding aptamer of the partial dsDNA probes and liberates single stranded initiation sequences, which trigger the toehold strand displacement assembly of two G-quadruplex containing hairpin DNAs. This toehold strand displacement reaction leads to the cyclic reuse of the initiation sequences and the production of DNA assemblies with numerous G-quadruplex structures. The fluorescent dye, N-Methyl mesoporphyrin IX, binds to these G-quadruplex structures and generates significantly amplified fluorescent signals to achieve highly sensitive detection of thrombin down to 5 pM. Besides, this method shows high selectivity towards the target thrombin against other control proteins. The developed thrombin sensing method herein avoids the modification of the probes and the involvement of any enzyme or nanomaterial labels for signal amplification. With the successful demonstration for thrombin detection, our approach can be easily adopted to monitor other target molecules in a simple, low-cost, sensitive and selective way by choosing appropriate aptamer/ligand pairs. Copyright © 2014 Elsevier B.V. All rights reserved.
Lin, Chi-Yueh; Wang, Hsiao-Chuan
2011-07-01
The voice onset time (VOT) of a stop consonant is the interval between its burst onset and voicing onset. Among a variety of research topics on VOT, one that has been studied for years is how VOTs are efficiently measured. Manual annotation is a feasible way, but it becomes a time-consuming task when the corpus size is large. This paper proposes an automatic VOT estimation method based on an onset detection algorithm. At first, a forced alignment is applied to identify the locations of stop consonants. Then a random forest based onset detector searches each stop segment for its burst and voicing onsets to estimate a VOT. The proposed onset detection can detect the onsets in an efficient and accurate manner with only a small amount of training data. The evaluation data extracted from the TIMIT corpus were 2344 words with a word-initial stop. The experimental results showed that 83.4% of the estimations deviate less than 10 ms from their manually labeled values, and 96.5% of the estimations deviate by less than 20 ms. Some factors that influence the proposed estimation method, such as place of articulation, voicing of a stop consonant, and quality of succeeding vowel, were also investigated. © 2011 Acoustical Society of America
Automated detection of hospital outbreaks: A systematic review of methods
Buckeridge, David L.; Lepelletier, Didier
2017-01-01
Objectives 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. Methods 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. Results 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%. Conclusion 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. PMID:28441422
A brief overview on radon measurements in drinking water.
Jobbágy, Viktor; Altzitzoglou, Timotheos; Malo, Petya; Tanner, Vesa; Hult, Mikael
2017-07-01
The aim of this paper is to present information about currently used standard and routine methods for radon analysis in drinking waters. An overview is given about the current situation and the performance of different measurement methods based on literature data. The following parameters are compared and discussed: initial sample volume and sample preparation, detection systems, minimum detectable activity, counting efficiency, interferences, measurement uncertainty, sample capacity and overall turnaround time. Moreover, the parametric levels for radon in drinking water from the different legislations and directives/guidelines on radon are presented. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Amplification of biological targets via on-chip culture for biosensing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harper, Jason C.; Edwards, Thayne L.; Carson, Bryan
The present invention, in part, relates to methods and apparatuses for on-chip amplification and/or detection of various targets, including biological targets and any amplifiable targets. In some examples, the microculture apparatus includes a single-use, normally-closed fluidic valve that is initially maintained in the closed position by a valve element bonded to an adhesive coating. The valve is opened using a magnetic force. The valve element includes a magnetic material or metal. Such apparatuses and methods are useful for in-field or real-time detection of targets, especially in limited resource settings.
NASA Astrophysics Data System (ADS)
Saito, Kazuo; Hara, Masahiro; Kunii, Masaru; Seko, Hiromu; Yamaguchi, Munehiko
2011-05-01
Different initial perturbation methods for the mesoscale ensemble prediction were compared by the Meteorological Research Institute (MRI) as a part of the intercomparison of mesoscale ensemble prediction systems (EPSs) of the World Weather Research Programme (WWRP) Beijing 2008 Olympics Research and Development Project (B08RDP). Five initial perturbation methods for mesoscale ensemble prediction were developed for B08RDP and compared at MRI: (1) a downscaling method of the Japan Meteorological Agency (JMA)'s operational one-week EPS (WEP), (2) a targeted global model singular vector (GSV) method, (3) a mesoscale model singular vector (MSV) method based on the adjoint model of the JMA non-hydrostatic model (NHM), (4) a mesoscale breeding growing mode (MBD) method based on the NHM forecast and (5) a local ensemble transform (LET) method based on the local ensemble transform Kalman filter (LETKF) using NHM. These perturbation methods were applied to the preliminary experiments of the B08RDP Tier-1 mesoscale ensemble prediction with a horizontal resolution of 15 km. To make the comparison easier, the same horizontal resolution (40 km) was employed for the three mesoscale model-based initial perturbation methods (MSV, MBD and LET). The GSV method completely outperformed the WEP method, confirming the advantage of targeting in mesoscale EPS. The GSV method generally performed well with regard to root mean square errors of the ensemble mean, large growth rates of ensemble spreads throughout the 36-h forecast period, and high detection rates and high Brier skill scores (BSSs) for weak rains. On the other hand, the mesoscale model-based initial perturbation methods showed good detection rates and BSSs for intense rains. The MSV method showed a rapid growth in the ensemble spread of precipitation up to a forecast time of 6 h, which suggests suitability of the mesoscale SV for short-range EPSs, but the initial large growth of the perturbation did not last long. The performance of the MBD method was good for ensemble prediction of intense rain with a relatively small computing cost. The LET method showed similar characteristics to the MBD method, but the spread and growth rate were slightly smaller and the relative operating characteristic area skill score and BSS did not surpass those of MBD. These characteristic features of the five methods were confirmed by checking the evolution of the total energy norms and their growth rates. Characteristics of the initial perturbations obtained by four methods (GSV, MSV, MBD and LET) were examined for the case of a synoptic low-pressure system passing over eastern China. With GSV and MSV, the regions of large spread were near the low-pressure system, but with MSV, the distribution was more concentrated on the mesoscale disturbance. On the other hand, large-spread areas were observed southwest of the disturbance in MBD and LET. The horizontal pattern of LET perturbation was similar to that of MBD, but the amplitude of the LET perturbation reflected the observation density.
FPFH-based graph matching for 3D point cloud registration
NASA Astrophysics Data System (ADS)
Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua
2018-04-01
Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.
Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi
2018-03-09
High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.
Detecting Edges in Images by Use of Fuzzy Reasoning
NASA Technical Reports Server (NTRS)
Dominguez, Jesus A.; Klinko, Steve
2003-01-01
A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image. During initial processing of image data at a low level of abstraction, the nature of the data is indeterminate. Fuzzy reasoning is used in the present method because it affords an ability to construct useful abstractions from approximate, incomplete, and otherwise imperfect sets of data. Humans are able to make some sense of even unfamiliar objects that have imperfect high-level representations. It appears that to perceive unfamiliar objects or to perceive familiar objects in imperfect images, humans apply heuristic algorithms to understand the images
GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harshaw, Chris R; Bridges, Robert A; Iannacone, Michael D
This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called \\textit{GraphPrints}. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets\\textemdash small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84\\% at the time-interval level, and 0.05\\% at the IP-level with 100\\% truemore » positive rates at both.« less
Santiago, E C; Bello, F B B
2003-06-01
The Association of Official Analytical Chemists (AOAC) Standard Method 972.23 (dry ashing and flame atomic absorption spectrophotometry (FAAS)), applied to the analysis of lead in tuna, was validated in three selected local laboratories to determine the acceptability of the method to both the Codex Alimentarius Commission (Codex) and the European Union (EU) Commission for monitoring lead in canned tuna. Initial validation showed that the standard AOAC method as performed in the three participating laboratories cannot satisfy the Codex/EU proposed criteria for the method detection limit for monitoring lead in fish at the present regulation level of 0.5 mg x kg(-1). Modification of the standard method by chelation/concentration of the digest solution before FAAS analysis showed that the modified method has the potential to meet Codex/EU criteria on sensitivity, accuracy and precision at the specified regulation level.
Wei, Xiaotong; Duan, Xiaolei; Zhou, Xiaoyan; Wu, Jiangling; Xu, Hongbing; Min, Xun; Ding, Shijia
2018-06-07
Herein, a dual channel surface plasmon resonance imaging (SPRi) biosensor has been developed for the simultaneous and highly sensitive detection of multiplex miRNAs based on strand displacement amplification (SDA) and DNA-functionalized AuNP signal enhancement. In the presence of target miRNAs (miR-21 or miR-192), the miRNAs could specifically hybridize with the corresponding hairpin probes (H) and initiate the SDA, resulting in massive triggers. Subsequently, the two parts of the released triggers could hybridize with capture probes (CP) and DNA-functionalized AuNPs, assembling DNA sandwiches with great mass on the chip surface. A significantly amplified SPR signal readout was achieved. This established biosensing method was capable of simultaneously detecting multiplex miRNAs with a limit of detection down to 0.15 pM for miR-21 and 0.22 pM for miR-192. This method exhibited good specificity and acceptable reproducibility. Moreover, the developed method was applied to the determination of target miRNAs in a complex matrix. Thus, this developed SPRi biosensing method may present a potential alternative tool for miRNA detection in biomedical research and clinical diagnosis.
Development of a Coded Aperture X-Ray Backscatter Imager for Explosive Device Detection
NASA Astrophysics Data System (ADS)
Faust, Anthony A.; Rothschild, Richard E.; Leblanc, Philippe; McFee, John Elton
2009-02-01
Defence R&D Canada has an active research and development program on detection of explosive devices using nuclear methods. One system under development is a coded aperture-based X-ray backscatter imaging detector designed to provide sufficient speed, contrast and spatial resolution to detect antipersonnel landmines and improvised explosive devices. The successful development of a hand-held imaging detector requires, among other things, a light-weight, ruggedized detector with low power requirements, supplying high spatial resolution. The University of California, San Diego-designed HEXIS detector provides a modern, large area, high-temperature CZT imaging surface, robustly packaged in a light-weight housing with sound mechanical properties. Based on the potential for the HEXIS detector to be incorporated as the detection element of a hand-held imaging detector, the authors initiated a collaborative effort to demonstrate the capability of a coded aperture-based X-ray backscatter imaging detector. This paper will discuss the landmine and IED detection problem and review the coded aperture technique. Results from initial proof-of-principle experiments will then be reported.
NASA Astrophysics Data System (ADS)
Xiao, Di; Vignarajan, Janardhan; An, Dong; Tay-Kearney, Mei-Ling; Kanagasingam, Yogi
2016-03-01
Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.
Pretreatment to avoid positive RT-PCR results with inactivated viruses.
Nuanualsuwan, Suphachai; Cliver, Dean O
2002-07-01
Enteric viruses that are important causes of human disease must often be detected by reverse transcription-polymerase chain reaction (RT-PCR), a method that commonly yields positive results with samples that contain only inactivated virus. This study was intended to develop a pretreatment for samples, so that inactivated viruses would not be detected by the RT-PCR procedure. Model viruses were human hepatitis A virus, vaccine poliovirus 1 and feline calicivirus as a surrogate for the Norwalk-like viruses. Each virus was inactivated (from an initial titer of approximately 10(3) PFU/ml) by ultraviolet light, hypochlorite or heating at 72 degrees C. Inactivated viruses, that were treated with proteinase K and ribonuclease for 30 min at 37 degrees C before RT-PCR, gave a negative result, which is to say that no amplicon was detected after the reaction was completed. This antecedent to the RT-PCR method may be applicable to other types of viruses, to viruses inactivated in other ways and to other molecular methods of virus detection.
Mass sensing based on deterministic and stochastic responses of elastically coupled nanocantilevers.
Gil-Santos, Eduardo; Ramos, Daniel; Jana, Anirban; Calleja, Montserrat; Raman, Arvind; Tamayo, Javier
2009-12-01
Coupled nanomechanical systems and their entangled eigenstates offer unique opportunities for the detection of ultrasmall masses. In this paper we show theoretically and experimentally that the stochastic and deterministic responses of a pair of coupled nanocantilevers provide different and complementary information about the added mass of an analyte and its location. This method allows the sensitive detection of minute quantities of mass even in the presence of large initial differences in the active masses of the two cantilevers. Finally, we show the fundamental limits in mass detection of this sensing paradigm.
Rapid, convenient method for screening imidazole-containing compounds for heme oxygenase inhibition.
Vlahakis, Jason Z; Rahman, Mona N; Roman, Gheorghe; Jia, Zongchao; Nakatsu, Kanji; Szarek, Walter A
2011-01-01
Sensitive assays for measuring heme oxygenase activity have been based on the gas-chromatographic detection of carbon monoxide using elaborate, expensive equipment. The present study describes a rapid and convenient method for screening imidazole-containing candidates for inhibitory activity against heme oxygenase using a plate reader, based on the spectroscopic evaluation of heme degradation. A PowerWave XS plate reader was used to monitor the absorbance (as a function of time) of heme bound to purified truncated human heme oxygenase-1 (hHO-1) in the individual wells of a standard 96-well plate (with or without the addition of a test compound). The degradation of heme by heme oxygenase-1 was initiated using l-ascorbic acid, and the collected relevant absorbance data were analyzed by three different methods to calculate the percent control activity occurring in wells containing test compounds relative to that occurring in control wells with no test compound present. In the cases of wells containing inhibitory compounds, significant shifts in λ(max) from 404 to near 412 nm were observed as well as a decrease in the rate of heme degradation relative to that of the control. Each of the three methods of data processing (overall percent drop in absorbance over 1.5h, initial rate of reaction determined over the first 5 min, and estimated pseudo first-order reaction rate constant determined over 1.5h) gave similar and reproducible results for percent control activity. The fastest and easiest method of data analysis was determined to be that using initial rates, involving data acquisition for only 5 min once reactions have been initiated using l-ascorbic acid. The results of the study demonstrate that this simple assay based on the spectroscopic detection of heme represents a rapid, convenient method to determine the relative inhibitory activity of candidate compounds, and is useful in quickly screening a series or library of compounds for heme oxygenase inhibition. Copyright © 2010 Elsevier Inc. All rights reserved.
Region-based automatic building and forest change detection on Cartosat-1 stereo imagery
NASA Astrophysics Data System (ADS)
Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.
2013-05-01
In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.
Mondal, Bhairab; N, Bhavanashri; Ramlal, Shylaja; Kingston, Joseph
2018-02-14
In the present study, a colorimetric DNAzymes biosensor strategy was devised in combination with immunomagnetic separation for rapid and easy detection of enterotoxin B harboring Staphylococcus aureus from food and clinical samples. The method employs immunocapture of S. aureus and amplification of seb gene by DNAzyme complementary sequence integrated forward primer and with specific reverse primer. The DNAzyme sequence integrated dsDNA PCR products when treated with hemin and TMB (3,3',5,5'-tetramethylbenzidine) in the presence of H 2 O 2 produce colorimetric signal. A linear relationship of optical signal with the initial template of seb was obtained which could be monitored by visually or spectrophotrometrically for qualitative and quantitative detection. The limit of detection for the assay was approximately 10 2 CFU/mL of seb gene harboring target. This method is convenient compared to gel based and ELISA systems. Further, spiking studies and analysis on natural samples emphasized the robustness and applicability of developed method. Altogether, the established assay could be a reliable alternative, low-cost, viable detection tool for the routine investigation of seb from food and clinical sources.
Combining spatial and spectral information to improve crop/weed discrimination algorithms
NASA Astrophysics Data System (ADS)
Yan, L.; Jones, G.; Villette, S.; Paoli, J. N.; Gée, C.
2012-01-01
Reduction of herbicide spraying is an important key to environmentally and economically improve weed management. To achieve this, remote sensors such as imaging systems are commonly used to detect weed plants. We developed spatial algorithms that detect the crop rows to discriminate crop from weeds. These algorithms have been thoroughly tested and provide robust and accurate results without learning process but their detection is limited to inter-row areas. Crop/Weed discrimination using spectral information is able to detect intra-row weeds but generally needs a prior learning process. We propose a method based on spatial and spectral information to enhance the discrimination and overcome the limitations of both algorithms. The classification from the spatial algorithm is used to build the training set for the spectral discrimination method. With this approach we are able to improve the range of weed detection in the entire field (inter and intra-row). To test the efficiency of these algorithms, a relevant database of virtual images issued from SimAField model has been used and combined to LOPEX93 spectral database. The developed method based is evaluated and compared with the initial method in this paper and shows an important enhancement from 86% of weed detection to more than 95%.
NASA Astrophysics Data System (ADS)
Huang, Alex S.; Belghith, Akram; Dastiridou, Anna; Chopra, Vikas; Zangwill, Linda M.; Weinreb, Robert N.
2017-06-01
The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm's canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC's was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.
Illumination Invariant Change Detection (iicd): from Earth to Mars
NASA Astrophysics Data System (ADS)
Wan, X.; Liu, J.; Qin, M.; Li, S. Y.
2018-04-01
Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.
Hu, Qinqin; Xu, Xiahong; Li, Zhanming; Zhang, Ying; Wang, Jianping; Fu, Yingchun; Li, Yanbin
2014-04-15
Acrylamide is a neurotoxin and potential carcinogen, but is found in various thermally processed foods such as potato chips, biscuits, and coffee. Simple and sensitive methods for on-line detection of acrylamide are needed to ensure food safety. In this paper, a novel fluorescent sensing method based on acrylamide polymerization-induced distance increase between quantum dots (QDs) was proposed for detecting acrylamide in potato chips. The functional QDs were prepared by their binding with N-acryloxysuccinimide (NAS), which was characterized by Fourier transform infrared (FR-IR) spectra. The carbon-carbon double bonds of NAS modified QDs polymerized with assistance of photo initiator under UV irradiation, leading to QDs getting closer along with fluorescence intensity decreasing. Acrylamide in the sample participated in the polymerization and induced an increase of fluorescence intensity. This method possessed a linear range from 3.5×10(-5) to 3.5 g L(-1) (r(2)=0.94) and a limit of detection of 3.5×10(-5) g L(-1). Although the sensitivity and specificity cannot be compared with standard LC-MS/MS analysis, this new method requires much less time and cost, which is promising for on-line rapid detection of acrylamide in food processing. © 2013 Published by Elsevier B.V.
Khan, Sylvie; Alibay, Taher Arif; Merad, Mansouria; DiPalma, Mario; Raynard, Bruno; Antoun, Sami
2016-09-01
Malnutrition is frequently observed in oncology. The consequences on patient survival, chemotherapy toxicities and quality of life need to be identified and treated appropriately. A set of tools are available that enable clinicians to diagnose and detect malnutrition. Each tool must consider three items: the patient's current nutritional status, reduced food intake and the characteristics of the underlying disease. The parameters and thresholds used to detect malnutrition differ according to the objective pursued. It can be economic, increasing the reimbursement of hospital stays, it can help define prognostic risk groups or its purpose can be to initiate nutritional treatment. Recent data support the assessment of parameters such as inflammatory markers, decreased muscle mass (i.e. sarcopenia) whose diagnosis is associated with a worse outcome and the quantification of food intake with simplified methods. The benefit for the patient of detecting malnutrition will be the initiation of a nutritional treatment when its efficacy has been demonstrated. A case in point is the nutritional support provided to malnourished patients before surgery with benefits in terms of mortality and morbidity and in certain head and neck cancer situations where nutritional support is systematically implemented. It is probably relevant to detect and initiate treatment early in order to promote muscle anabolism. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.
Initial alignment method for free space optics laser beam
NASA Astrophysics Data System (ADS)
Shimada, Yuta; Tashiro, Yuki; Izumi, Kiyotaka; Yoshida, Koichi; Tsujimura, Takeshi
2016-08-01
The authors have newly proposed and constructed an active free space optics transmission system. It is equipped with a motor driven laser emitting mechanism and positioning photodiodes, and it transmits a collimated thin laser beam and accurately steers the laser beam direction. It is necessary to introduce the laser beam within sensible range of the receiver in advance of laser beam tracking control. This paper studies an estimation method of laser reaching point for initial laser beam alignment. Distributed photodiodes detect laser luminescence at respective position, and the optical axis of laser beam is analytically presumed based on the Gaussian beam optics. Computer simulation evaluates the accuracy of the proposed estimation methods, and results disclose that the methods help us to guide the laser beam to a distant receiver.
Fatigue crack identification method based on strain amplitude changing
NASA Astrophysics Data System (ADS)
Guo, Tiancai; Gao, Jun; Wang, Yonghong; Xu, Youliang
2017-09-01
Aiming at the difficulties in identifying the location and time of crack initiation in the castings of helicopter transmission system during fatigue tests, by introducing the classification diagnostic criteria of similar failure mode to find out the similarity of fatigue crack initiation among castings, an engineering method and quantitative criterion for detecting fatigue cracks based on strain amplitude changing is proposed. This method is applied on the fatigue test of a gearbox housing, whose results indicates: during the fatigue test, the system alarms when SC strain meter reaches the quantitative criterion. The afterwards check shows that a fatigue crack less than 5mm is found at the corresponding location of SC strain meter. The test result proves that the method can provide accurate test data for strength life analysis.
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2014-10-28
Methods and systems for engine control optimization are provided. A first and a second operating condition of a vehicle engine are detected. An initial value is identified for a first and a second engine control parameter corresponding to a combination of the detected operating conditions according to a first and a second engine map look-up table. The initial values for the engine control parameters are adjusted based on a detected engine performance variable to cause the engine performance variable to approach a target value. A first and a second sensitivity of the engine performance variable are determined in response to changes in the engine control parameters. The first engine map look-up table is adjusted when the first sensitivity is greater than a threshold, and the second engine map look-up table is adjusted when the second sensitivity is greater than a threshold.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chang, X; Liu, S; Kalet, A
Purpose: The purpose of this work was to investigate the ability of a machine-learning based probabilistic approach to detect radiotherapy treatment plan anomalies given initial disease classes information. Methods In total we obtained 1112 unique treatment plans with five plan parameters and disease information from a Mosaiq treatment management system database for use in the study. The plan parameters include prescription dose, fractions, fields, modality and techniques. The disease information includes disease site, and T, M and N disease stages. A Bayesian network method was employed to model the probabilistic relationships between tumor disease information, plan parameters and an anomalymore » flag. A Bayesian learning method with Dirichlet prior was useed to learn the joint probabilities between dependent variables in error-free plan data and data with artificially induced anomalies. In the study, we randomly sampled data with anomaly in a specified anomaly space.We tested the approach with three groups of plan anomalies – improper concurrence of values of all five plan parameters and values of any two out of five parameters, and all single plan parameter value anomalies. Totally, 16 types of plan anomalies were covered by the study. For each type, we trained an individual Bayesian network. Results: We found that the true positive rate (recall) and positive predictive value (precision) to detect concurrence anomalies of five plan parameters in new patient cases were 94.45±0.26% and 93.76±0.39% respectively. To detect other 15 types of plan anomalies, the average recall and precision were 93.61±2.57% and 93.78±3.54% respectively. The computation time to detect the plan anomaly of each type in a new plan is ∼0.08 seconds. Conclusion: The proposed method for treatment plan anomaly detection was found effective in the initial tests. The results suggest that this type of models could be applied to develop plan anomaly detection tools to assist manual and automated plan checks. The senior author received research grants from ViewRay Inc. and Varian Medical System.« less
SAR image change detection using watershed and spectral clustering
NASA Astrophysics Data System (ADS)
Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie
2011-12-01
A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu
Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less
An incremental anomaly detection model for virtual machines.
Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu
2017-01-01
Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform.
An incremental anomaly detection model for virtual machines
Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu
2017-01-01
Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform. PMID:29117245
An object detection and tracking system for unmanned surface vehicles
NASA Astrophysics Data System (ADS)
Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao
2017-10-01
Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.
Hard exudates segmentation based on learned initial seeds and iterative graph cut.
Kusakunniran, Worapan; Wu, Qiang; Ritthipravat, Panrasee; Zhang, Jian
2018-05-01
(Background and Objective): The occurrence of hard exudates is one of the early signs of diabetic retinopathy which is one of the leading causes of the blindness. Many patients with diabetic retinopathy lose their vision because of the late detection of the disease. Thus, this paper is to propose a novel method of hard exudates segmentation in retinal images in an automatic way. (Methods): The existing methods are based on either supervised or unsupervised learning techniques. In addition, the learned segmentation models may often cause miss-detection and/or fault-detection of hard exudates, due to the lack of rich characteristics, the intra-variations, and the similarity with other components in the retinal image. Thus, in this paper, the supervised learning based on the multilayer perceptron (MLP) is only used to identify initial seeds with high confidences to be hard exudates. Then, the segmentation is finalized by unsupervised learning based on the iterative graph cut (GC) using clusters of initial seeds. Also, in order to reduce color intra-variations of hard exudates in different retinal images, the color transfer (CT) is applied to normalize their color information, in the pre-processing step. (Results): The experiments and comparisons with the other existing methods are based on the two well-known datasets, e_ophtha EX and DIARETDB1. It can be seen that the proposed method outperforms the other existing methods in the literature, with the sensitivity in the pixel-level of 0.891 for the DIARETDB1 dataset and 0.564 for the e_ophtha EX dataset. The cross datasets validation where the training process is performed on one dataset and the testing process is performed on another dataset is also evaluated in this paper, in order to illustrate the robustness of the proposed method. (Conclusions): This newly proposed method integrates the supervised learning and unsupervised learning based techniques. It achieves the improved performance, when compared with the existing methods in the literature. The robustness of the proposed method for the scenario of cross datasets could enhance its practical usage. That is, the trained model could be more practical for unseen data in the real-world situation, especially when the capturing environments of training and testing images are not the same. Copyright © 2018 Elsevier B.V. All rights reserved.
Aggressive periodontitis: case definition and diagnostic criteria.
Albandar, Jasim M
2014-06-01
Aggressive periodontitis is a destructive disease characterized by the following: the involvement of multiple teeth with a distinctive pattern of periodontal tissue loss; a high rate of disease progression; an early age of onset; and the absence of systemic diseases. In some patients periodontal tissue loss may commence before puberty, whereas in most patients the age of onset is during or somewhat after the circumpubertal period. Besides infection with specific microorganisms, a host predisposition seems to play a key role in the pathogenesis of aggressive periodontitis, as evidenced by the familial aggregation of the disease. In this article we review the historical background of the diagnostic criteria of aggressive periodontitis, present a contemporary case definition and describe the clinical parameters of the disease. At present, the diagnosis of aggressive periodontitis is achieved using case history, clinical examination and radiographic evaluation. The data gathered using these methods are prone to relatively high measurement errors. Besides, this diagnostic approach measures past disease history and may not reliably measure existing disease activity or accurately predict future tissue loss. A diagnosis is often made years after the onset of the disease, partly because current assessment methods detect established disease more readily and reliably than they detect incipient or initial lesions where the tissue loss is minimal and usually below the detection threshold of present examination methods. Future advancements in understanding the pathogenesis of this disease may contribute to an earlier diagnosis. Insofar, future case definitions may involve the identification of key etiologic and risk factors, combined with high-precision methodologies that enable the early detection of initial lesions. This may significantly enhance the predictive value of these tests and detect cases of aggressive periodontitis before significant tissue loss develops. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Soejima, Mikiko; Tsuchiya, Yuji; Egashira, Kouichi; Kawano, Hiroyuki; Sagawa, Kimitaka; Koda, Yoshiro
2010-06-01
Anhaptoglobinemic patients run the risk of severe anaphylactic transfusion reaction because they produce serum haptoglobin (Hp) antibodies. Being homozygous for the Hp gene deletion (HP(del)) is the only known cause of congenital anhaptoglobinemia, and clinical diagnosis of HP(del) before transfusion is important to prevent anaphylactic shock. We recently developed a 5'-nuclease (TaqMan) real-time polymerase chain reaction (PCR) method. A SYBR Green I-based duplex real-time PCR assay using two forward primers and a common reverse primer followed by melting curve analysis was developed to determine HP(del) zygosity in a single tube. In addition, to obviate initial DNA extraction, we examined serially diluted blood samples as PCR templates. Allelic discrimination of HP(del) yielded optimal results at blood sample dilutions of 1:64 to 1:1024. The results from 2231 blood samples were fully concordant with those obtained by the TaqMan-based real-time PCR method. The detection rate of the HP(del) allele by the SYBR Green I-based method is comparable with that using the TaqMan-based method. This method is readily applicable due to its low initial cost and analyzability using economical real-time PCR machines and is suitable for high-throughput analysis as an alternative method for allelic discrimination of HP(del).
Wang, Minghui; Zhou, Yunlei; Yin, Huanshun; Jiang, Wenjing; Wang, Haiyan; Ai, Shiyun
2018-06-01
MicroRNAs play crucial role in regulating gene expression in organism, thus it is very necessary to exploit an efficient method for the sensitive and specific detection of microRNA. Herein, a signal-on electrochemiluminescence biosensor was fabricated for microRNA-319a detection based on two-stage isothermal strand-displacement polymerase reaction (ISDPR). In the presence of target microRNA, amounts of trigger DNA could be generated by the first ISDPR. Then, the trigger DNA and the primer hybridized simultaneously with the hairpin probe to open the stem of the probe, and then the ECL signal will be emitted. In the presence of phi29 DNA polymerase and dNTPs, the trigger DNA could be displaced to initiate a new cycle which was the second ISDPR. Due to the two-stage amplification, this method presented excellent detection sensitivity with a low detection limit of 0.14 fM. Moreover, the applicability of the developed method was demonstrated by detecting the change of microRNA-319a content in the leaves of rice seedlings after the rice seeds were incubated with chemical mutagen of ethyl methanesulfonate. Copyright © 2018 Elsevier B.V. All rights reserved.
Szymanik, Barbara; Frankowski, Paweł Karol; Chady, Tomasz; John Chelliah, Cyril Robinson Azariah
2016-01-01
The purpose of this paper is to present a multi-sensor approach to the detection and inspection of steel bars in reinforced concrete structures. In connection with our past experience related to non-destructive testing of different materials, we propose using two potentially effective methods: active infrared thermography with microwave excitation and the eddy current technique. In this article active infrared thermography with microwave excitation is analyzed both by numerical modeling and experiments. This method, based on thermal imaging, due to its characteriatics should be considered as a preliminary method for the assessment of relatively shallowly located steel bar reinforcements. The eddy current technique, on the other hand, allows for more detailed evaluation and detection of deeply located rebars. In this paper a series of measurement results, together with the initial identification of certain features of steel reinforcement bars will be presented. PMID:26891305
Szymanik, Barbara; Frankowski, Paweł Karol; Chady, Tomasz; John Chelliah, Cyril Robinson Azariah
2016-02-16
The purpose of this paper is to present a multi-sensor approach to the detection and inspection of steel bars in reinforced concrete structures. In connection with our past experience related to non-destructive testing of different materials, we propose using two potentially effective methods: active infrared thermography with microwave excitation and the eddy current technique. In this article active infrared thermography with microwave excitation is analyzed both by numerical modeling and experiments. This method, based on thermal imaging, due to its characteriatics should be considered as a preliminary method for the assessment of relatively shallowly located steel bar reinforcements. The eddy current technique, on the other hand, allows for more detailed evaluation and detection of deeply located rebars. In this paper a series of measurement results, together with the initial identification of certain features of steel reinforcement bars will be presented.
Liu, Yang; Wang, Xiao-Yue; Wei, Xue-Min; Gao, Zi-Tong; Han, Jian-Ping
2018-05-22
Species adulteration in herbal products (HPs) exposes consumers to health risks. Chemical and morphological methods have their own deficiencies when dealing with the detection of species containing the same active compounds in HPs. In this study, we developed a rapid identification method using the recombinase polymerase amplification (RPA) assay to detect two species, Ginkgo biloba and Sophora japonica (as adulteration), in Ginkgo biloba HPs. Among 36 Ginkgo biloba HP samples, 34 were found to have Ginkgo biloba sequences, and 9 were found to have Sophora japonica sequences. During the authentication process, the RPA-LFS assay showed a higher specificity, sensitivity and efficiency than PCR-based methods. We initially applied the RPA-LSF technique to detect plant species in HPs, demonstrating that this assay can be developed into an efficient tool for the rapid on-site authentication of plant species in Ginkgo biloba HPs.
Nonparametric evaluation of birth cohort trends in disease rates.
Tarone, R E; Chu, K C
2000-01-01
Although interpretation of age-period-cohort analyses is complicated by the non-identifiability of maximum likelihood estimates, changes in the slope of the birth-cohort effect curve are identifiable and have potential aetiologic significance. A nonparametric test for a change in the slope of the birth-cohort trend has been developed. The test is a generalisation of the sign test and is based on permutational distributions. A method for identifying interactions between age and calendar-period effects is also presented. The nonparametric method is shown to be powerful in detecting changes in the slope of the birth-cohort trend, although its power can be reduced considerably by calendar-period patterns of risk. The method identifies a previously unidentified decrease in the birth-cohort risk of lung-cancer mortality from 1912 to 1919, which appears to reflect a reduction in the initiation of smoking by young men at the beginning of the Great Depression (1930s). The method also detects an interaction between age and calendar period in leukemia mortality rates, reflecting the better response of children to chemotherapy. The proposed nonparametric method provides a data analytic approach, which is a useful adjunct to log-linear Poisson analysis of age-period-cohort models, either in the initial model building stage, or in the final interpretation stage.
Orion MPCV Touchdown Detection Threshold Development and Testing
NASA Technical Reports Server (NTRS)
Daum, Jared; Gay, Robert
2013-01-01
A robust method of detecting Orion Multi ]Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post ]landing segment of the Flight Software (FSW). The vehicle crew is the prime input for touchdown detection, followed by an autonomous FSW algorithm, and finally a strictly time based backup timer. RCS thrusters must be inhibited before submersion in water to protect against possible damage due to firing these jets under water. In addition, neglecting to declare touchdown will not allow the vehicle to transition to post ]landing activities such as activating the Crew Module Up ]righting System (CMUS), resulting in possible loss of communication and difficult recovery. A previous AIAA paper gAssessment of an Automated Touchdown Detection Algorithm for the Orion Crew Module h concluded that a strictly Inertial Measurement Unit (IMU) based detection method using an acceleration spike algorithm had the highest safety margins and shortest detection times of other methods considered. That study utilized finite element simulations of vehicle splashdown, generated by LS ]DYNA, which were expanded to a larger set of results using a Kriging surface fit. The study also used the Decelerator Systems Simulation (DSS) to generate flight dynamics during vehicle descent under parachutes. Proto ]type IMU and FSW MATLAB models provided the basis for initial algorithm development and testing. This paper documents an in ]depth trade study, using the same dynamics data and MATLAB simulations as the earlier work, to further develop the acceleration detection method. By studying the combined effects of data rate, filtering on the rotational acceleration correction, data persistence limits and values of acceleration thresholds, an optimal configuration was determined. The lever arm calculation, which removes the centripetal acceleration caused by vehicle rotation, requires that the vehicle angular acceleration be derived from vehicle body rates, necessitating the addition of a 2nd order filter to smooth the data. It was determined that using 200 Hz data directly from the vehicle IMU outperforms the 40 Hz FSW data rate. Data persistence counter values and acceleration thresholds were balanced in order to meet desired safety and performance. The algorithm proved to exhibit ample safety margin against early detection while under parachutes, and adequate performance upon vehicle splashdown. Fall times from algorithm initiation were also studied, and a backup timer length was chosen to provide a large safety margin, yet still trigger detection before CMUS inflation. This timer serves as a backup to the primary acceleration detection method. Additionally, these parameters were tested for safety on actual flight test data, demonstrating expected safety margins.
Thermal wake/vessel detection technique
Roskovensky, John K [Albuquerque, NM; Nandy, Prabal [Albuquerque, NM; Post, Brian N [Albuquerque, NM
2012-01-10
A computer-automated method for detecting a vessel in water based on an image of a portion of Earth includes generating a thermal anomaly mask. The thermal anomaly mask flags each pixel of the image initially deemed to be a wake pixel based on a comparison of a thermal value of each pixel against other thermal values of other pixels localized about each pixel. Contiguous pixels flagged by the thermal anomaly mask are grouped into pixel clusters. A shape of each of the pixel clusters is analyzed to determine whether each of the pixel clusters represents a possible vessel detection event. The possible vessel detection events are represented visually within the image.
Defining a region of optimization based on engine usage data
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2015-08-04
Methods and systems for engine control optimization are provided. One or more operating conditions of a vehicle engine are detected. A value for each of a plurality of engine control parameters is determined based on the detected one or more operating conditions of the vehicle engine. A range of the most commonly detected operating conditions of the vehicle engine is identified and a region of optimization is defined based on the range of the most commonly detected operating conditions of the vehicle engine. The engine control optimization routine is initiated when the one or more operating conditions of the vehicle engine are within the defined region of optimization.
Gimenez, Thais; Braga, Mariana Minatel; Raggio, Daniela Procida; Deery, Chris; Ricketts, David N; Mendes, Fausto Medeiros
2013-01-01
Fluorescence-based methods have been proposed to aid caries lesion detection. Summarizing and analysing findings of studies about fluorescence-based methods could clarify their real benefits. We aimed to perform a comprehensive systematic review and meta-analysis to evaluate the accuracy of fluorescence-based methods in detecting caries lesions. Two independent reviewers searched PubMed, Embase and Scopus through June 2012 to identify papers/articles published. Other sources were checked to identify non-published literature. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND DIAGNOSTIC METHODS: The eligibility criteria were studies that: (1) have assessed the accuracy of fluorescence-based methods of detecting caries lesions on occlusal, approximal or smooth surfaces, in both primary or permanent human teeth, in the laboratory or clinical setting; (2) have used a reference standard; and (3) have reported sufficient data relating to the sample size and the accuracy of methods. A diagnostic 2×2 table was extracted from included studies to calculate the pooled sensitivity, specificity and overall accuracy parameters (Diagnostic Odds Ratio and Summary Receiver-Operating curve). The analyses were performed separately for each method and different characteristics of the studies. The quality of the studies and heterogeneity were also evaluated. Seventy five studies met the inclusion criteria from the 434 articles initially identified. The search of the grey or non-published literature did not identify any further studies. In general, the analysis demonstrated that the fluorescence-based method tend to have similar accuracy for all types of teeth, dental surfaces or settings. There was a trend of better performance of fluorescence methods in detecting more advanced caries lesions. We also observed moderate to high heterogeneity and evidenced publication bias. Fluorescence-based devices have similar overall performance; however, better accuracy in detecting more advanced caries lesions has been observed.
Liquid-based cytology for primary cervical cancer screening: a multi-centre study
Monsonego, J; Autillo-Touati, A; Bergeron, C; Dachez, R; Liaras, J; Saurel, J; Zerat, L; Chatelain, P; Mottot, C
2001-01-01
The aim of this six-centre, split-sample study was to compare ThinPrep fluid-based cytology to the conventional Papanicolaou smear. Six cytopathology laboratories and 35 gynaecologists participated. 5428 patients met the inclusion criteria (age > 18 years old, intact cervix, informed consent). Each cervical sample was used first to prepare a conventional Pap smear, then the sampling device was rinsed into a PreservCyt vial, and a ThinPrep slide was made. Screening of slide pairs was blinded (n = 5428). All non-negative concordant cases (n = 101), all non-concordant cases (n = 206), and a 5% random sample of concordant negative cases (n = 272) underwent review by one independent pathologist then by the panel of 6 investigators. Initial (blinded) screening results for ThinPrep and conventional smears were correlated. Initial diagnoses were correlated with consensus cytological diagnoses. Differences in disease detection were evaluated using McNemar's test. On initial screening, 29% more ASCUS cases and 39% more low-grade squamous intraepithelial lesions (LSIL) and more severe lesions (LSIL+) were detected on the ThinPrep slides than on the conventional smears (P = 0.001), including 50% more LSIL and 18% more high-grade SIL (HSIL). The ASCUS:SIL ratio was lower for the ThinPrep method (115:132 = 0.87:1) than for the conventional smear method (89:94 = 0.95:1). The same trend was observed for the ASCUS/AGUS:LSIL ratio. Independent and consensus review confirmed 145 LSIL+ diagnoses; of these, 18% more had been detected initially on the ThinPrep slides than on the conventional smears (P = 0.041). The ThinPrep Pap Test is more accurate than the conventional Pap test and has the potential to optimize the effectiveness of primary cervical cancer screening. © 2001 Cancer Research Campaign http://www.bjcancer.com PMID:11161401
Jean, Julie; D'Souza, Doris H; Jaykus, Lee-Ann
2004-11-01
Human enteric viruses are currently recognized as one of the most important causes of food-borne disease. Implication of enteric viruses in food-borne outbreaks can be difficult to confirm due to the inadequacy of the detection methods available. In this study, a nucleic acid sequence-based amplification (NASBA) method was developed in a multiplex format for the specific, simultaneous, and rapid detection of epidemiologically relevant human enteric viruses. Three previously reported primer sets were used in a single reaction for the amplification of RNA target fragments of 474, 371, and 165 nucleotides for the detection of hepatitis A virus and genogroup I and genogroup II noroviruses, respectively. Amplicons were detected by agarose gel electrophoresis and confirmed by electrochemiluminescence and Northern hybridization. Endpoint detection sensitivity for the multiplex NASBA assay was approximately 10(-1) reverse transcription-PCR-detectable units (or PFU, as appropriate) per reaction. When representative ready-to-eat foods (deli sliced turkey and lettuce) were inoculated with various concentrations of each virus and processed for virus detection with the multiplex NASBA method, all three human enteric viruses were simultaneously detected at initial inoculum levels of 10(0) to 10(2) reverse transcription-PCR-detectable units (or PFU)/9 cm2 in both food commodities. The multiplex NASBA system provides rapid and simultaneous detection of clinically relevant food-borne viruses in a single reaction tube and may be a promising alternative to reverse transcription-PCR for the detection of viral contamination of foods.
NASA Astrophysics Data System (ADS)
Kenefic, L.; Morton, E.; Bilek, S.
2017-12-01
It is well known that subduction zones create the largest earthquakes in the world, like the magnitude 9.5 Chile earthquake in 1960, or the more recent 9.1 magnitude Japan earthquake in 2011, both of which are in the top five largest earthquakes ever recorded. However, off the coast of the Pacific Northwest region of the U.S., the Cascadia subduction zone (CSZ) remains relatively quiet and modern seismic instruments have not recorded earthquakes of this size in the CSZ. The last great earthquake, a magnitude 8.7-9.2, occurred in 1700 and is constrained by written reports of the resultant tsunami in Japan and dating a drowned forest in the U.S. Previous studies have suggested the margin is most likely segmented along-strike. However, variations in frictional conditions in the CSZ fault zone are not well known. Geodetic modeling indicates that the locked seismogenic zone is likely completely offshore, which may be too far from land seismometers to adequately detect related seismicity. Ocean bottom seismometers, as part of the Cascadia Initiative Amphibious Network, were installed directly above the inferred seismogenic zone, which we use to better detect small interplate seismicity. Using the subspace detection method, this study looks to find new seismogenic zone earthquakes. This subspace detection method uses multiple previously known event templates concurrently to scan through continuous seismic data. Template events that make up the subspace are chosen from events in existing catalogs that likely occurred along the plate interface. Corresponding waveforms are windowed on the nearby Cascadia Initiative ocean bottom seismometers and coastal land seismometers for scanning. Detections that are found by the scan are similar to the template waveforms based upon a predefined threshold. Detections are then visually examined to determine if an event is present. The presence of repeating event clusters can indicate persistent seismic patches, likely corresponding to areas of stronger coupling. This work will ultimately improve the understanding of CSZ fault zone heterogeneity. Preliminary results gathered indicate 96 possible new events between August 2, 2013 and July 1, 2014 for four target clusters off the coast of northern Oregon.
Christodoulides, Nicolaos; De La Garza, Richard; Simmons, Glennon W.; McRae, Michael P.; Wong, Jorge; Newton, Thomas F.; Smith, Regina; Mahoney, James J.; Hohenstein, Justin; Gomez, Sobeyda; Floriano, Pierre N.; Talavera, Humberto; Sloan, Daniel J.; Moody, David E.; Andrenyak, David M.; Kosten, Thomas R.; Haque, Ahmed; McDevitt, John T.
2015-01-01
Objective There is currently a gap in on-site drug of abuse monitoring. Current detection methods involve invasive sampling of blood and urine specimens, or collection of oral fluid, followed by qualitative screening tests using immunochromatographic cartridges. While remote laboratories then may provide confirmation and quantitative assessment of a presumptive positive, this instrumentation is expensive and decoupled from the initial sampling making the current drug-screening program inefficient and costly. The authors applied a noninvasive oral fluid sampling approach integrated with the in-development chip-based Programmable Bio-Nano-Chip (p-BNC) platform for the detection of drugs of abuse. Method The p-BNC assay methodology was applied for the detection of tetrahydrocannabinol, morphine, amphetamine, methamphetamine, cocaine, methadone and benzodiazepines, initially using spiked buffered samples and, ultimately, using oral fluid specimen collected from consented volunteers. Results Rapid (~10 minutes), sensitive detection (~ng/ml) and quantitation of 12 drugs of abuse was demonstrated on the p-BNC platform. Furthermore, the system provided visibility to time-course of select drug and metabolite profiles in oral fluids; for the drug cocaine, three regions of slope were observed that, when combined with concentration measurements from this and prior impairment studies, information about cocaine-induced impairment may be revealed. Conclusions This chip-based p-BNC detection modality has significant potential to be used in the future by law enforcement officers for roadside drug testing and to serve a variety of other settings, including outpatient and inpatient drug rehabilitation centers, emergency rooms, prisons, schools, and in the workplace. PMID:26048639
Huan, L N; Tejani, A M; Egan, G
2014-10-01
An increasing amount of recently published literature has implicated outcome reporting bias (ORB) as a major contributor to skewing data in both randomized controlled trials and systematic reviews; however, little is known about the current methods in place to detect ORB. This study aims to gain insight into the detection and management of ORB by biomedical journals. This was a cross-sectional analysis involving standardized questions via email or telephone with the top 30 biomedical journals (2012) ranked by impact factor. The Cochrane Database of Systematic Reviews was excluded leaving 29 journals in the sample. Of 29 journals, 24 (83%) responded to our initial inquiry of which 14 (58%) answered our questions and 10 (42%) declined participation. Five (36%) of the responding journals indicated they had a specific method to detect ORB, whereas 9 (64%) did not have a specific method in place. The prevalence of ORB in the review process seemed to differ with 4 (29%) journals indicating ORB was found commonly, whereas 7 (50%) indicated ORB was uncommon or never detected by their journal previously. The majority (n = 10/14, 72%) of journals were unwilling to report or make discrepancies found in manuscripts available to the public. Although the minority, there were some journals (n = 4/14, 29%) which described thorough methods to detect ORB. Many journals seemed to lack a method with which to detect ORB and its estimated prevalence was much lower than that reported in literature suggesting inadequate detection. There exists a potential for overestimation of treatment effects of interventions and unclear risks. Fortunately, there are journals within this sample which appear to utilize comprehensive methods for detection of ORB, but overall, the data suggest improvements at the biomedical journal level for detecting and minimizing the effect of this bias are needed. © 2014 John Wiley & Sons Ltd.
Senkomago, V; Des Marais, A C; Rahangdale, L; Vibat, C R T; Erlander, M G; Smith, J S
2016-01-01
Urine testing for high-risk human papillomavirus (HR-HPV) detection could provide a non-invasive, simple method for cervical cancer screening. We examined whether HR-HPV detection is affected by urine collection time, portion of urine stream, or urine fraction tested, and assessed the performance of HR-HPV testing in urine for detection of cervical intraepithelial neoplasia grade II or worse (CIN2+). A total of 37 female colposcopy clinic attendees, ≥ 30 years, provided three urine samples: "first void" urine collected at home, and "initial stream" and "mid-stream" urine samples collected at the clinic later in the day. Self- and physician-collected brush specimens were obtained at the same clinic visit. Colposcopy was performed and directed biopsies obtained if clinically indicated. For each urine sample, HR-HPV DNA testing was conducted for unfractionated, pellet, and supernatant fractions using the Trovagene test. HR-HPV mRNA testing was performed on brush specimens using the Aptima HPV assay. HR-HPV prevalence was similar in unfractionated and pellet fractions of all urine samples. For supernatant urine fractions, HR-HPV prevalence appeared lower in mid-stream urine (56.8%[40.8-72.7%]) than in initial stream urine (75.7%[61.9-89.5%]). Sensitivity of CIN2+ detection was identical for initial stream urine and physician-collected cervical specimen (89.9%[95%CI=62.7-99.6%]), and similar to self-collected vaginal specimen (79.1%[48.1-96.6%]). This is among the first studies to compare methodologies for collection and processing of urine for HR-HPV detection. HR-HPV prevalence was similar in first void and initial stream urine, and was highly sensitive for CIN2+ detection. Additional research in a larger and general screening population is needed. Copyright © 2015 Elsevier B.V. All rights reserved.
Optimization of OT-MACH Filter Generation for Target Recognition
NASA Technical Reports Server (NTRS)
Johnson, Oliver C.; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin
2009-01-01
An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.
Damage identification via asymmetric active magnetic bearing acceleration feedback control
NASA Astrophysics Data System (ADS)
Zhao, Jie; DeSmidt, Hans; Yao, Wei
2015-04-01
A Floquet-based damage detection methodology for cracked rotor systems is developed and demonstrated on a shaft-disk system. This approach utilizes measured changes in the system natural frequencies to estimate the severity and location of shaft structural cracks during operation. The damage detection algorithms are developed with the initial guess solved by least square method and iterative damage parameter vector by updating the eigenvector updating. Active Magnetic Bearing is introduced to break the symmetric structure of rotor system and the tuning range of proper stiffness/virtual mass gains is studied. The system model is built based on energy method and the equations of motion are derived by applying assumed modes method and Lagrange Principle. In addition, the crack model is based on the Strain Energy Release Rate (SERR) concept in fracture mechanics. Finally, the method is synthesized via harmonic balance and numerical examples for a shaft/disk system demonstrate the effectiveness in detecting both location and severity of the structural damage.
Misdaq, M A; Aitnouh, F; Khajmi, H; Ezzahery, H; Berrazzouk, S
2001-08-01
A Monte Carlo computer code for determining detection efficiencies of the CR-39 and LR-115 II solid-state nuclear track detectors (SSNTD) for alpha-particles emitted by the uranium and thorium series inside different natural material samples was developed. The influence of the alpha-particle initial energy on the SSNTD detection efficiencies was investigated. Radon (222Rn) and thoron (220Rn) alpha-activities per unit volume were evaluated inside and outside the natural material samples by exploiting data obtained for the detection efficiencies of the SSNTD utilized for the emitted alpha-particles, and measuring the resulting track densities. Results obtained were compared to those obtained by other methods. Radon emanation coefficients have been determined for some of the considered material samples.
DOT National Transportation Integrated Search
1993-12-01
The Alternating Current Potential Drop (ACPD) method is investigated as a means of making measurements in laboratory experiments on the initiation and growth of multiple site damage (MSD) cracks in a common aluminum alloy used for aircraft constructi...
ERIC Educational Resources Information Center
Zhang, Yanling; Dorans, Neil J.; Matthews-López, Joy L.
2005-01-01
Statistical procedures for detecting differential item functioning (DIF) are often used as an initial step to screen items for construct irrelevant variance. This research applies a DIF dissection method and a two-way classification scheme to SAT Reasoning Test™ verbal section data and explores the effects of deleting sizable DIF items on reported…
NASA Astrophysics Data System (ADS)
Sahiner, Berkman; Petrick, Nicholas; Chan, Heang-Ping; Paquerault, Sophie; Helvie, Mark A.; Hadjiiski, Lubomir M.
2001-07-01
We used the correspondence of detected structures on two views of the same breast for false-positive (FP) reduction in computerized detection of mammographic masses. For each initially detected object on one view, we considered all possible pairings with objects on the other view that fell within a radial band defined by the nipple-to-object distances. We designed a 'correspondence classifier' to classify these pairs as either the same mass (a TP-TP pair) or a mismatch (a TP-FP, FP-TP or FP-FP pair). For each pair, similarity measures of morphological and texture features were derived and used as input features in the correspondence classifier. Two-view mammograms from 94 cases were used as a preliminary data set. Initial detection provided 6.3 FPs/image at 96% sensitivity. Further FP reduction in single view resulted in 1.9 FPs/image at 80% sensitivity and 1.1 FPs/image at 70% sensitivity. By combining single-view detection with the correspondence classifier, detection accuracy improved to 1.5 FPs/image at 80% sensitivity and 0.7 FPs/image at 70% sensitivity. Our preliminary results indicate that the correspondence of geometric, morphological, and textural features of a mass on two different views provides valuable additional information for reducing FPs.
Madsen, James F.; Sandstrom, Mark W.; Zaugg, Steven D.
2002-01-01
A method for the isolation and detemrination of fipronil and four of its degradates has been developed. This method adapts an analytical method created by the U.S. Geological Survey National Water Quality Laboratory in 1995 for the determination of a broad range of high-use pesticides typically found in filtered natural-water samples. In 2000, fipronil and four of its degradates were extracted, analyzed, and validated using this method. The recoveries for these five compounds in reagent-water samples fortified at 1 microgram per liter (ug/L) avereraged 98 percent. Initial method detection limits averaged 0.0029 ug/L. The performance of these five new compounds is consistent with the performance of the compounds in the initial method, making it possible to include them in addition to the other 41 pesticides and pesticide degradates in the original method.
NASA Astrophysics Data System (ADS)
Ashour, Safwan; Bayram, Roula
2015-04-01
New, accurate, sensitive and reliable kinetic spectrophotometric method for the assay of moxifloxacin hydrochloride (MOXF) in pure form and pharmaceutical formulations has been developed. The method involves the oxidative coupling reaction of MOXF with 3-methyl-2-benzothiazolinone hydrazone hydrochloride monohydrate (MBTH) in the presence of Ce(IV) in an acidic medium to form colored product with lambda max at 623 and 660 nm. The reaction is followed spectrophotometrically by measuring the increase in absorbance at 623 nm as a function of time. The initial rate and fixed time methods were adopted for constructing the calibration curves. The linearity range was found to be 1.89-40.0 μg mL-1 for initial rate and fixed time methods. The limit of detection for initial rate and fixed time methods is 0.644 and 0.043 μg mL-1, respectively. Molar absorptivity for the method was found to be 0.89 × 104 L mol-1 cm-1. Statistical treatment of the experimental results indicates that the methods are precise and accurate. The proposed method has been applied successfully for the estimation of moxifloxacin hydrochloride in tablet dosage form with no interference from the excipients. The results are compared with the official method.
From thermometric to spectrophotometric kinetic-catalytic methods of analysis. A review.
Cerdà, Víctor; González, Alba; Danchana, Kaewta
2017-05-15
Kinetic-catalytic analytical methods have proved to be very easy and highly sensitive strategies for chemical analysis, that rely on simple instrumentation [1,2]. Molecular absorption spectrophotometry is commonly used as the detection technique. However, other detection systems, like electrochemical or thermometric ones, offer some interesting possibilities since they are not affected by the color or turbidity of the samples. In this review some initial experience with thermometric kinetic-catalytic methods is described, up to our current experience exploiting spectrophotometric flow techniques to automate this kind of reactions, including the use of integrated chips. Procedures for determination of inorganic and organic species in organic and inorganic matrices are presented. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Bruynooghe, Michel M.
1998-04-01
In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.
New pediatric vision screener, part II: electronics, software, signal processing and validation.
Gramatikov, Boris I; Irsch, Kristina; Wu, Yi-Kai; Guyton, David L
2016-02-04
We have developed an improved pediatric vision screener (PVS) that can reliably detect central fixation, eye alignment and focus. The instrument identifies risk factors for amblyopia, namely eye misalignment and defocus. The device uses the birefringence of the human fovea (the most sensitive part of the retina). The optics have been reported in more detail previously. The present article focuses on the electronics and the analysis algorithms used. The objective of this study was to optimize the analog design, data acquisition, noise suppression techniques, the classification algorithms and the decision making thresholds, as well as to validate the performance of the research instrument on an initial group of young test subjects-18 patients with known vision abnormalities (eight male and 10 female), ages 4-25 (only one above 18) and 19 controls with proven lack of vision issues. Four statistical methods were used to derive decision making thresholds that would best separate patients with abnormalities from controls. Sensitivity and specificity were calculated for each method, and the most suitable one was selected. Both the central fixation and the focus detection criteria worked robustly and allowed reliable separation between normal test subjects and symptomatic subjects. The sensitivity of the instrument was 100 % for both central fixation and focus detection. The specificity was 100 % for central fixation and 89.5 % for focus detection. The overall sensitivity was 100 % and the overall specificity was 94.7 %. Despite the relatively small initial sample size, we believe that the PVS instrument design, the analysis methods employed, and the device as a whole, will prove valuable for mass screening of children.
Automated location detection of injection site for preclinical stereotactic neurosurgery procedure
NASA Astrophysics Data System (ADS)
Abbaszadeh, Shiva; Wu, Hemmings C. H.
2017-03-01
Currently, during stereotactic neurosurgery procedures, the manual task of locating the proper area for needle insertion or implantation of electrode/cannula/optic fiber can be time consuming. The requirement of the task is to quickly and accurately find the location for insertion. In this study we investigate an automated method to locate the entry point of region of interest. This method leverages a digital image capture system, pattern recognition, and motorized stages. Template matching of known anatomical identifiable regions is used to find regions of interest (e.g. Bregma) in rodents. For our initial study, we tackle the problem of automatically detecting the entry point.
Image-based tracking of the suturing needle during laparoscopic interventions
NASA Astrophysics Data System (ADS)
Speidel, S.; Kroehnert, A.; Bodenstedt, S.; Kenngott, H.; Müller-Stich, B.; Dillmann, R.
2015-03-01
One of the most complex and difficult tasks for surgeons during minimally invasive interventions is suturing. A prerequisite to assist the suturing process is the tracking of the needle. The endoscopic images provide a rich source of information which can be used for needle tracking. In this paper, we present an image-based method for markerless needle tracking. The method uses a color-based and geometry-based segmentation to detect the needle. Once an initial needle detection is obtained, a region of interest enclosing the extracted needle contour is passed on to a reduced segmentation. It is evaluated with in vivo images from da Vinci interventions.
System and method for quench and over-current protection of superconductor
Huang, Xianrui; Laskaris, Evangelos Trifon; Sivasubramaniam, Kiruba Haran; Bray, James William; Ryan, David Thomas; Fogarty, James Michael; Steinbach, Albert Eugene
2005-05-31
A system and method for protecting a superconductor. The system may comprise a current sensor operable to detect a current flowing through the superconductor. The system may comprise a coolant temperature sensor operable to detect the temperature of a cryogenic coolant used to cool the superconductor to a superconductive state. The control circuit is operable to estimate the superconductor temperature based on the current flow and the coolant temperature. The system may also be operable to compare the estimated superconductor temperature to at least one threshold temperature and to initiate a corrective action when the superconductor temperature exceeds the at least one threshold temperature.
Jayawardene, Wasantha Parakrama; YoussefAgha, Ahmed Hassan
2014-01-01
This study aimed to identify the sequential patterns of drug use initiation, which included prescription drugs misuse (PDM), among 12th-grade students in Indiana. The study also tested the suitability of the data mining method Market Basket Analysis (MBA) to detect common drug use initiation sequences in large-scale surveys. Data from 2007 to 2009 Annual Surveys of Alcohol, Tobacco, and Other Drug Use by Indiana Children and Adolescents were used for this study. A close-ended, self-administered questionnaire was used to ask adolescents about the use of 21 substance categories and the age of first use. "Support%" and "confidence%" statistics of Market Basket Analysis detected multiple and substitute addictions, respectively. The lifetime prevalence of using any addictive substance was 73.3%, and it has been decreasing during past few years. Although the lifetime prevalence of PDM was 19.2%, it has been increasing. Males and whites were more likely to use drugs and engage in multiple addictions. Market Basket Analysis identified common drug use initiation sequences that involved 11 drugs. High levels of support existed for associations among alcohol, cigarettes, and marijuana, whereas associations that included prescription drugs had medium levels of support. Market Basket Analysis is useful for the detection of common substance use initiation sequences in large-scale surveys. Before initiation of prescription drugs, physicians should consider the adolescents' risk of addiction. Prevention programs should address multiple addictions, substitute addictions, common sequences in drug use initiation, sex and racial differences in PDM, and normative beliefs of parents and adolescents in relation to PDM.
Tao, Chenyu; Zhang, Qingde; Zhai, Shanli; Liu, Bang
2013-11-01
In this study, sensitive and rapid detection systems were designed using a loop-mediated isothermal amplification (LAMP) method to detect the genetically modified goats. A set of 4 primers were designed for each exogenous nucleic acids HBsAg and hATIII. The DNA samples were first amplified with the outer and inner primers and released a single-stranded DNA,of which both ends were stem-loop structure. Then one inner primer hybridized with the loop, and initiated displacement synthesis in less than 1 h. The result could be visualized by both agarose gel electrophoresis and unaided eyes directly after adding SYBR GREEN 1. The detection limit of LAMP was ten copies of target molecules, indicating that LAMP was tenfold more sensitive than the classical PCR. Furthermore, all the samples of genetically modified goats were tested positively by LAMP, and the results demonstrated that the LAMP was a rapid and sensitive method for detecting the genetically modified organism.
Hofman, Paul
2017-01-01
Patients with advanced-stage non-small cell lung carcinoma (NSCLC) harboring an ALK rearrangement, detected from a tissue sample, can benefit from targeted ALK inhibitor treatment. Several increasingly effective ALK inhibitors are now available for treatment of patients. However, despite an initial favorable response to treatment, in most cases relapse or progression occurs due to resistance mechanisms mainly caused by mutations in the tyrosine kinase domain of ALK. The detection of an ALK rearrangement is pivotal and can be done using different methods, which have variable sensitivity and specificity depending, in particular, on the quality and quantity of the patient’s sample. This review will first highlight briefly some information regarding the pathobiology of an ALK rearrangement and the epidemiology of patients harboring this genomic alteration. The different methods used to detect an ALK rearrangement as well as their advantages and disadvantages will then be examined and algorithms proposed for detection in daily routine practice. PMID:28805682
Hofman, Paul
2017-08-12
Patients with advanced-stage non-small cell lung carcinoma (NSCLC) harboring an ALK rearrangement, detected from a tissue sample, can benefit from targeted ALK inhibitor treatment. Several increasingly effective ALK inhibitors are now available for treatment of patients. However, despite an initial favorable response to treatment, in most cases relapse or progression occurs due to resistance mechanisms mainly caused by mutations in the tyrosine kinase domain of ALK. The detection of an ALK rearrangement is pivotal and can be done using different methods, which have variable sensitivity and specificity depending, in particular, on the quality and quantity of the patient's sample. This review will first highlight briefly some information regarding the pathobiology of an ALK rearrangement and the epidemiology of patients harboring this genomic alteration. The different methods used to detect an ALK rearrangement as well as their advantages and disadvantages will then be examined and algorithms proposed for detection in daily routine practice.
A possibility for standoff bomb detection
NASA Astrophysics Data System (ADS)
Akar Tarim, U.; Ozmutlu, E. N.; Gurler, O.; Yalcin, S.
2015-01-01
The response functions of backscattered photons, which are initially collimated with an energy of 662 keV, were obtained by a Monte Carlo method in an NaI(Tl) scintillation detector using a suitcase or briefcase full of paper, clothing, ammonium nitrate or other generic explosives, as these can be used for terrorism. The results show that characteristic response functions for ammonium nitrate and generic explosives may be found, and using this information, standoff detection of these materials may be possible.
Environmental surveillance for polioviruses in the Global Polio Eradication Initiative.
Asghar, Humayun; Diop, Ousmane M; Weldegebriel, Goitom; Malik, Farzana; Shetty, Sushmitha; El Bassioni, Laila; Akande, Adefunke O; Al Maamoun, Eman; Zaidi, Sohail; Adeniji, Adekunle J; Burns, Cara C; Deshpande, Jagadish; Oberste, M Steve; Lowther, Sara A
2014-11-01
This article summarizes the status of environmental surveillance (ES) used by the Global Polio Eradication Initiative, provides the rationale for ES, gives examples of ES methods and findings, and summarizes how these data are used to achieve poliovirus eradication. ES complements clinical acute flaccid paralysis (AFP) surveillance for possible polio cases. ES detects poliovirus circulation in environmental sewage and is used to monitor transmission in communities. If detected, the genetic sequences of polioviruses isolated from ES are compared with those of isolates from clinical cases to evaluate the relationships among viruses. To evaluate poliovirus transmission, ES programs must be developed in a manner that is sensitive, with sufficiently frequent sampling, appropriate isolation methods, and specifically targeted sampling sites in locations at highest risk for poliovirus transmission. After poliovirus ceased to be detected in human cases, ES documented the absence of endemic WPV transmission and detected imported WPV. ES provides valuable information, particularly in high-density populations where AFP surveillance is of poor quality, persistent virus circulation is suspected, or frequent virus reintroduction is perceived. Given the benefits of ES, GPEI plans to continue and expand ES as part of its strategic plan and as a supplement to AFP surveillance. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
NASA Astrophysics Data System (ADS)
Hošek, Tomáš; Gil-Caballero, Sergi; Pierattelli, Roberta; Brutscher, Bernhard; Felli, Isabella C.
2015-05-01
Intrinsically disordered proteins (IDPs) are functional proteins containing large fragments characterized by high local mobility. Bioinformatic studies have suggested that a significant fraction (more than 30%) of eukaryotic proteins has disordered regions of more than 50 amino acids in length. Hence, NMR methods for the characterization of local compactness and solvent accessibility in such highly disordered proteins are of high importance. Among the available approaches, the HET-SOFAST/BEST experiments (Schanda et al., 2006, Rennella et al., 2014) provide semi-quantitative information by monitoring longitudinal 1H relaxation of amide protons under different initial conditions. However, when approaching physiological sample conditions, the potential of these amide 1H detected experiments is reduced due to rapid amide proton solvent exchange. 13C direct detection methods therefore provide a valuable alternative thanks to a higher chemical shift dispersion and their intrinsic insensitivity toward solvent exchange. Here we present two sets of 13C-detected experiments, which indirectly measure 1HN and 1Hα inversion recovery profiles. The experiments consist of an initial spin inversion-recovery block optimized for selective manipulation of different types of proton spins followed by a CON read-out scheme. The proposed experiments were tested on human α-synuclein and ubiquitin, two representative examples of unfolded and folded proteins.
Polarization Resistance Measurement in Tap Water: The Influence of Rust Electrochemical Activity
NASA Astrophysics Data System (ADS)
Vasyliev, Georgii
2017-08-01
Corrosion rate of mild steel in tap water during 4300 h was estimated by LPR and weight-loss methods coupled with OCP measurements. The LPR results were found to be overestimated compared to the weight-loss data within initial 2000 h of exposure. The electrochemical activity of the rust separated from the metal surface was studied by cycling voltammetry using a home-built powder graphite electrode. High redox currents corresponding to the initial 2000 h of exposure were detected. Rust composition was characterized with IR and XRD, and the highest amounts of electrochemically active β- and γ-FeOOH were again detected for the initial 2000 h. Current consumption in rust transformation processes during LPR measurement in the galvanostatic mode accounts for overestimation of the corrosion rate. The time dependence of rust electrochemical activity correlates with OCP variation with time. During initial 2000 h, OCP values are shifted by 50 mV to cathodic side. For the period of a higher rust electrochemical activity, the use of a reduced B is suggested to increase accuracy of LPR technique in tap water.
Robust feature matching via support-line voting and affine-invariant ratios
NASA Astrophysics Data System (ADS)
Li, Jiayuan; Hu, Qingwu; Ai, Mingyao; Zhong, Ruofei
2017-10-01
Robust image matching is crucial for many applications of remote sensing and photogrammetry, such as image fusion, image registration, and change detection. In this paper, we propose a robust feature matching method based on support-line voting and affine-invariant ratios. We first use popular feature matching algorithms, such as SIFT, to obtain a set of initial matches. A support-line descriptor based on multiple adaptive binning gradient histograms is subsequently applied in the support-line voting stage to filter outliers. In addition, we use affine-invariant ratios computed by a two-line structure to refine the matching results and estimate the local affine transformation. The local affine model is more robust to distortions caused by elevation differences than the global affine transformation, especially for high-resolution remote sensing images and UAV images. Thus, the proposed method is suitable for both rigid and non-rigid image matching problems. Finally, we extract as many high-precision correspondences as possible based on the local affine extension and build a grid-wise affine model for remote sensing image registration. We compare the proposed method with six state-of-the-art algorithms on several data sets and show that our method significantly outperforms the other methods. The proposed method achieves 94.46% average precision on 15 challenging remote sensing image pairs, while the second-best method, RANSAC, only achieves 70.3%. In addition, the number of detected correct matches of the proposed method is approximately four times the number of initial SIFT matches.
Road detection in SAR images using a tensor voting algorithm
NASA Astrophysics Data System (ADS)
Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian
2007-11-01
In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.
A toxicity identification evaluation (TIE) was conducted on effluent from a major industrial discharger. Initial monitoring showed slight chronic toxicity to Ceriodaphnia dubia; later sample showed substantial toxicity to C. dubia. Chemical analysis detected hexavalent chromium ...
Xu, Kefeng; Chen, Zhonghui; Zhou, Ling; Zheng, Ou; Wu, Xiaoping; Guo, Longhua; Qiu, Bin; Lin, Zhenyu; Chen, Guonan
2015-01-06
A fluorometric method for pyrophosphatase (PPase) activity detection was developed based on click chemistry. Cu(II) can coordinate with pyrophosphate (PPi), the addition of pyrophosphatase (PPase) into the above system can destroy the coordinate compound because PPase catalyzes the hydrolysis of PPi into inorganic phosphate and produces free Cu(II), and free Cu(II) can be reduced by sodium ascorbate (SA) to form Cu(I), which in turn initiates the ligating reaction between nonfluorescent 3-azidocoumarins and terminal alkynes to produce a highly fluorescent triazole complex, based on which, a simple and sensitive turn on fluorometric method for PPase can be developed. The fluorescence intensity of the system has a linear relationship with the logarithm of the PPase concentration in the range of 0.5 and 10 mU with a detection limit down to 0.2 mU (S/N = 3). This method is cost-effective and convenient without any labels or complicated operations. The proposed system was applied to screen the potential PPase inhibitor with high efficiency. The proposed method can be applied to diagnosis of PPase-related diseases.
Detection of Drug-Resistant Mycobacterium tuberculosis.
Engström, Anna; Juréen, Pontus
2015-01-01
Tuberculosis (TB) remains a global health problem. The increasing prevalence of drug-resistant Mycobacterium tuberculosis, the causative agent of TB, demands new measures to combat the situation. Rapid and accurate diagnosis of the pathogen and its drug susceptibility pattern is essential for timely initiation of optimal treatment, and, ultimately, control of the disease. We have developed a molecular method for detection of first- and second-line drug resistance in M. tuberculosis by Pyrosequencing(®). The method consists of seven Pyrosequencing assays for the detection of mutations in the genes or promoter regions, which are most commonly responsible for resistance to the drugs rifampicin, isoniazid, ethambutol, amikacin, kanamycin, capreomycin, and fluoroquinolones. The method was validated on clinical isolates and it was shown that the sensitivity and specificity of the method were comparable to those of Sanger sequencing. In the protocol in this chapter we describe the steps necessary for setting up and performing Pyrosequencing for M. tuberculosis. The first part of the protocol describes the assay development and the second part of the protocol describes utilization of the method.
Yingram, Manop; Premrudeepreechacharn, Suttichai
2015-01-01
The mainly used local islanding detection methods may be classified as active and passive methods. Passive methods do not perturb the system but they have larger nondetection zones, whereas active methods have smaller nondetection zones but they perturb the system. In this paper, a new hybrid method is proposed to solve this problem. An over/undervoltage (passive method) has been used to initiate an undervoltage shift (active method), which changes the undervoltage shift of inverter, when the passive method cannot have a clear discrimination between islanding and other events in the system. Simulation results on MATLAB/SIMULINK show that over/undervoltage and undervoltage shifts of hybrid islanding detection method are very effective because they can determine anti-islanding condition very fast. ΔP/P > 38.41% could determine anti-islanding condition within 0.04 s; ΔP/P < -24.39% could determine anti-islanding condition within 0.04 s; -24.39% ≤ ΔP/P ≤ 38.41% could determine anti-islanding condition within 0.08 s. This method perturbed the system, only in the case of -24.39% ≤ ΔP/P ≤ 38.41% at which the control system of inverter injected a signal of undervoltage shift as necessary to check if the occurrence condition was an islanding condition or not.
Perspectives on the Future Search for Life on Mars and Beyond
NASA Technical Reports Server (NTRS)
Nealson, K. H.
1998-01-01
One can view the search for life on Mars in two ways: first, as the initial step in the search for life elsewhere, and second, as the one place where in situ methods for life detection can be tested and proved via sample return. After Mars, most of the life detection will he done via in situ studies with data return. Mars offers us the opportunity to fine tune our methods - perhaps for a long time to come. Our group is involved in the development of methods for life detection that are independent of specific signals used for detection of life on Earth. These approaches include general indicators of metabolic activity and organismal structure and composition. Using such approaches, we hope to detect the signals of life (biosignatures) that are independent of preconceived notions and yet are convincing and unambiguous. The approaches we are focusing on include stable isotopic analyses of metals, mineral formation and disolution, and elemental analysis. These methods allow us to examine samples at a variety of scales, looking for nonequilibrium distribution of elements that serve as biosignatures. For futures studies of Mars and beyond, they, or some variation of them, should allow inference or proof of life in non-Earth locations.
Real-time fluorescence loop mediated isothermal amplification for the diagnosis of malaria.
Lucchi, Naomi W; Demas, Allison; Narayanan, Jothikumar; Sumari, Deborah; Kabanywanyi, Abdunoor; Kachur, S Patrick; Barnwell, John W; Udhayakumar, Venkatachalam
2010-10-29
Molecular diagnostic methods can complement existing tools to improve the diagnosis of malaria. However, they require good laboratory infrastructure thereby restricting their use to reference laboratories and research studies. Therefore, adopting molecular tools for routine use in malaria endemic countries will require simpler molecular platforms. The recently developed loop-mediated isothermal amplification (LAMP) method is relatively simple and can be improved for better use in endemic countries. In this study, we attempted to improve this method for malaria diagnosis by using a simple and portable device capable of performing both the amplification and detection (by fluorescence) of LAMP in one platform. We refer to this as the RealAmp method. Published genus-specific primers were used to test the utility of this method. DNA derived from different species of malaria parasites was used for the initial characterization. Clinical samples of P. falciparum were used to determine the sensitivity and specificity of this system compared to microscopy and a nested PCR method. Additionally, directly boiled parasite preparations were compared with a conventional DNA isolation method. The RealAmp method was found to be simple and allowed real-time detection of DNA amplification. The time to amplification varied but was generally less than 60 minutes. All human-infecting Plasmodium species were detected. The sensitivity and specificity of RealAmp in detecting P. falciparum was 96.7% and 91.7% respectively, compared to microscopy and 98.9% and 100% respectively, compared to a standard nested PCR method. In addition, this method consistently detected P. falciparum from directly boiled blood samples. This RealAmp method has great potential as a field usable molecular tool for diagnosis of malaria. This tool can provide an alternative to conventional PCR based diagnostic methods for field use in clinical and operational programs.
NASA Astrophysics Data System (ADS)
Tseng, Kuo-Kun; Lo, Jiao; Liu, Yiming; Chang, Shih-Hao; Merabti, Madjid; Ng, Felix, C. K.; Wu, C. H.
2017-10-01
The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.
Procedure for rapid concentration and detection of enteric viruses from berries and vegetables.
Butot, S; Putallaz, T; Sánchez, G
2007-01-01
Several hepatitis A virus (HAV) and norovirus (NV) outbreaks due to consumption of berries and vegetables have been reported during recent years. To facilitate the detection of enteric viruses that may be present on different fresh and frozen products, we developed a rapid and sensitive detection method for HAV, NV, and rotavirus (RV). Initial experiments focused on optimizing the composition of the elution buffer, improving the viral concentration method, and evaluating the performance of various extraction kits. Viruses were extracted from the food surface by a direct elution method in a glycine-Tris (pH 9.5) buffer containing 1% beef extract and concentrated by ultrafiltration. Occasionally, PCR inhibitors were present in the processed berry samples, which gave relatively poor detection limits. However, this problem was overcome by adding a pectinase treatment in the protocol, which markedly improved the sensitivity of the method. After optimization, this concentration method was applied in combination with real-time reverse transcription-PCR (RT-PCR) using specific primers in various types of berries and vegetables. The average detection limits were 1 50% tissue culture infective dose (TCID(50)), 54 RT-PCR units, and 0.02 TCID(50) per 15 g of food for HAV, NV, and RV, respectively. Based on our results, it is concluded that this procedure is suitable to detect and quantify enteric viruses within 6 h and can be applied for surveillance of enteric viruses in fresh and frozen products.
Accurate detection of blood vessels improves the detection of exudates in color fundus images.
Youssef, Doaa; Solouma, Nahed H
2012-12-01
Exudates are one of the earliest and most prevalent symptoms of diseases leading to blindness such as diabetic retinopathy and macular degeneration. Certain areas of the retina with such conditions are to be photocoagulated by laser to stop the disease progress and prevent blindness. Outlining these areas is dependent on outlining the lesions and the anatomic structures of the retina. In this paper, we provide a new method for the detection of blood vessels that improves the detection of exudates in fundus photographs. The method starts with an edge detection algorithm which results in a over segmented image. Then the new feature-based algorithm can be used to accurately detect the blood vessels. This algorithm considers the characteristics of a retinal blood vessel such as its width range, intensities and orientations for the purpose of selective segmentation. Because of its bulb shape and its color similarity with exudates, the optic disc can be detected using the common Hough transform technique. The extracted blood vessel tree and optic disc could be subtracted from the over segmented image to get an initial estimate of exudates. The final estimation of exudates can then be obtained by morphological reconstruction based on the appearance of exudates. This method is shown to be promising since it increases the sensitivity and specificity of exudates detection to 80% and 100% respectively. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Huang, Alex S; Belghith, Akram; Dastiridou, Anna; Chopra, Vikas; Zangwill, Linda M; Weinreb, Robert N
2017-06-01
The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm’s canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC’s was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moeglein, W. A.; Griswold, R.; Mehdi, B. L.
In-situ (scanning) transmission electron microscopy (S/TEM) is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreasesmore » (there is more information that is available in the first few milliseconds of the process). Here we show that video shot boundary detection (SBD) can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react.« less
Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection.
Plazzotta, Giacomo; Cohen, Ted; Colijn, Caroline
2015-03-07
High resolution tests for genetic variation reveal that individuals may simultaneously host more than one distinct strain of Mycobacterium tuberculosis. Previous studies find that this phenomenon, which we will refer to as "mixed infection", may affect the outcomes of treatment for infected individuals and may influence the impact of population-level interventions against tuberculosis. In areas where the incidence of TB is high, mixed infections have been found in nearly 20% of patients; these studies may underestimate the actual prevalence of mixed infection given that tests may not be sufficiently sensitive for detecting minority strains. Specific reasons for failing to detect mixed infections would include low initial numbers of minority strain cells in sputum, stochastic growth in culture and the physical division of initial samples into parts (typically only one of which is genotyped). In this paper, we develop a mathematical framework that models the study designs aimed to detect mixed infections. Using both a deterministic and a stochastic approach, we obtain posterior estimates of the prevalence of mixed infection. We find that the posterior estimate of the prevalence of mixed infection may be substantially higher than the fraction of cases in which it is detected. We characterize this bias in terms of the sensitivity of the genotyping method and the relative growth rates and initial population sizes of the different strains collected in sputum. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Chen, Neng; Tranebjærg, Lisbeth; Rendtorff, Nanna Dahl; Schrijver, Iris
2011-01-01
Pendred syndrome and DFNB4 (autosomal recessive nonsyndromic congenital deafness, locus 4) are associated with autosomal recessive congenital sensorineural hearing loss and mutations in the SLC26A4 gene. Extensive allelic heterogeneity, however, necessitates analysis of all exons and splice sites to identify mutations for individual patients. Although Sanger sequencing is the gold standard for mutation detection, screening methods supplemented with targeted sequencing can provide a cost-effective alternative. One such method, denaturing high-performance liquid chromatography, was developed for clinical mutation detection in SLC26A4. However, this method inherently cannot distinguish homozygous changes from wild-type sequences. High-resolution melting (HRM), on the other hand, can detect heterozygous and homozygous changes cost-effectively, without any post-PCR modifications. We developed a closed-tube HRM mutation detection method specific for SLC26A4 that can be used in the clinical diagnostic setting. Twenty-eight primer pairs were designed to cover all 21 SLC26A4 exons and splice junction sequences. Using the resulting amplicons, initial HRM analysis detected all 45 variants previously identified by sequencing. Subsequently, a 384-well plate format was designed for up to three patient samples per run. Blinded HRM testing on these plates of patient samples collected over 1 year in a clinical diagnostic laboratory accurately detected all variants identified by sequencing. In conclusion, HRM with targeted sequencing is a reliable, simple, and cost-effective method for SLC26A4 mutation screening and detection. PMID:21704276
Woo, Victoria Gah Hay; Cohen, Craig R; Bukusi, Elizabeth A; Huchko, Megan J
2013-02-01
In resource-limited settings, detection of sexually transmitted infections (STIs) often relies on self-reported symptoms to initiate management. We found self-report demonstrated poor sensitivity for STI detection. Adding clinician-initiated questions about symptoms improved detection rates. Vaginal examination further increased sensitivity. Including clinician-initiated screening in resource-limited settings would improve management of treatable STIs.
NASA Astrophysics Data System (ADS)
Chen, Jingbo; Yue, Anzhi; Wang, Chengyi; Huang, Qingqing; Chen, Jiansheng; Meng, Yu; He, Dongxu
2018-01-01
The wind turbine is a device that converts the wind's kinetic energy into electrical power. Accurate and automatic extraction of wind turbine is instructive for government departments to plan wind power plant projects. A hybrid and practical framework based on saliency detection for wind turbine extraction, using Google Earth image at spatial resolution of 1 m, is proposed. It can be viewed as a two-phase procedure: coarsely detection and fine extraction. In the first stage, we introduced a frequency-tuned saliency detection approach for initially detecting the area of interest of the wind turbines. This method exploited features of color and luminance, was simple to implement, and was computationally efficient. Taking into account the complexity of remote sensing images, in the second stage, we proposed a fast method for fine-tuning results in frequency domain and then extracted wind turbines from these salient objects by removing the irrelevant salient areas according to the special properties of the wind turbines. Experiments demonstrated that our approach consistently obtains higher precision and better recall rates. Our method was also compared with other techniques from the literature and proves that it is more applicable and robust.
Tan, Feng; Saucedo, Nuvia Maria; Ramnani, Pankaj; Mulchandani, Ashok
2015-08-04
Microcystin-LR (MCLR) is one of the most commonly detected and toxic cyclic heptapeptide cyanotoxins released by cyanobacterial blooms in surface waters, for which sensitive and specific detection methods are necessary to carry out its recognition and quantification. Here, we present a single-walled carbon nanotube (SWCNTs)-based label-free chemiresistive immunosensor for highly sensitive and specific detection of MCLR in different source waters. MCLR was initially immobilized on SWCNTs modified interdigitated electrode, followed by incubation with monoclonal anti-MCLR antibody. The competitive binding of MCLR in sample solutions induced departure of the antibody from the antibody-antigen complexes formed on SWCNTs, resulting in change in the conductivity between source and drain of the sensor. The displacement assay greatly improved the sensitivity of the sensor compared with direct immunoassay on the same device. The immunosensor exhibited a wide linear response to log value of MCLR concentration ranging from 1 to 1000 ng/L, with a detection limit of 0.6 ng/L. This method showed good reproducibility, stability and recovery. The proposed method provides a powerful tool for rapid and sensitive monitoring of MCLR in environmental samples.
Road extraction from aerial images using a region competition algorithm.
Amo, Miriam; Martínez, Fernando; Torre, Margarita
2006-05-01
In this paper, we present a user-guided method based on the region competition algorithm to extract roads, and therefore we also provide some clues concerning the placement of the points required by the algorithm. The initial points are analyzed in order to find out whether it is necessary to add more initial points, and this process will be based on image information. Not only is the algorithm able to obtain the road centerline, but it also recovers the road sides. An initial simple model is deformed by using region growing techniques to obtain a rough road approximation. This model will be refined by region competition. The result of this approach is that it delivers the simplest output vector information, fully recovering the road details as they are on the image, without performing any kind of symbolization. Therefore, we tried to refine a general road model by using a reliable method to detect transitions between regions. This method is proposed in order to obtain information for feeding large-scale Geographic Information System.
Multislice CT perfusion imaging of the lung in detection of pulmonary embolism
NASA Astrophysics Data System (ADS)
Hong, Helen; Lee, Jeongjin
2006-03-01
We propose a new subtraction technique for accurately imaging lung perfusion and efficiently detecting pulmonary embolism in chest MDCT angiography. Our method is composed of five stages. First, optimal segmentation technique is performed for extracting same volume of the lungs, major airway and vascular structures from pre- and post-contrast images with different lung density. Second, initial registration based on apex, hilar point and center of inertia (COI) of each unilateral lung is proposed to correct the gross translational mismatch. Third, initial alignment is refined by iterative surface registration. For fast and robust convergence of the distance measure to the optimal value, a 3D distance map is generated by the narrow-band distance propagation. Fourth, 3D nonlinear filter is applied to the lung parenchyma to compensate for residual spiral artifacts and artifacts caused by heart motion. Fifth, enhanced vessels are visualized by subtracting registered pre-contrast images from post-contrast images. To facilitate visualization of parenchyma enhancement, color-coded mapping and image fusion is used. Our method has been successfully applied to ten patients of pre- and post-contrast images in chest MDCT angiography. Experimental results show that the performance of our method is very promising compared with conventional methods with the aspects of its visual inspection, accuracy and processing time.
Lee, Ji-Yun; Kim, Chang Jong
2010-01-01
Egg allergy is one of the most common food allergies in both adults and children, and foods including eggs and their byproducts should be declared under food allergen labeling policies in industrial countries. Therefore, to develop and validate a sensitive and specific method to detect hidden egg allergens in foods, we compared immunochemical, DNA-based, and proteomic methods for detecting egg allergens in foods using egg allergen standards such as egg whole protein, egg white protein, egg yolk protein, ovomucoid, ovalbumin, ovotransferrin, lysozyme, and alpha-livetin. Protein-based immunochemical methods, including ELISA as an initial screening quantitative analysis and immunoblotting as a final confirmatory qualitative analysis, were very sensitive and specific in detecting potentially allergenic egg residues in processed foods in trace amounts. In contrast, the proteomics-based, matrix-assisted laser desorption/ionization time-of-flight MS and LC-tandem quadrupole time-of-flight MS methods were not able to detect some egg allergens, such as ovomucoid, because of its nondenaturing property under urea and trypsin. The DNA-based PCR method could not distinguish between egg and chicken meat because it is tissue-nonspecific. In further studies for the feasibility of these immunochemical methods on 100 real raw dietary samples, four food samples without listed egg ingredients produced a positive response by ELISA, but exhibited negative results by immunoblotting.
Murphy, Christine M; Devlin, John J; Beuhler, Michael C; Cheifetz, Paul; Maynard, Susan; Schwartz, Michael D; Kacinko, Sherri
2018-04-01
Nitromethane, found in fuels used for short distance racing, model cars, and model airplanes, produces a falsely elevated serum creatinine with standard creatinine analysis via the Jaffé method. Erroneous creatinine elevation often triggers extensive testing, leads to inaccurate diagnoses, and delayed or inappropriate medical interventions. Multiple reports in the literature identify "enzymatic assays" as an alternative method to detect the true value of creatinine, but this ambiguity does not help providers translate what type of enzymatic assay testing can be done in real time to determine if there is indeed false elevation. We report seven cases of ingested nitromethane where creatinine was determined via Beckman Coulter ® analyser using the Jaffé method, Vitros ® analyser, or i-Stat ® point-of-care testing. Nitromethane was detected and semi-quantified using a common clinical toxic alcohol analysis method, and quantified by headspace-gas chromatography-mass spectrometry. When creatinine was determined using i-Stat ® point-of-care testing or a Vitros ® analyser, levels were within the normal range. Comparatively, all initial creatinine levels obtained via the Jaffé method were elevated. Nitromethane concentrations ranged from 42 to 310 μg/mL. These cases demonstrate reliable assessment of creatinine through other enzymatic methods using a Vitros ® analyser or i-STAT ® . Additionally, nitromethane is detectable and quantifiable using routine alcohols gas chromatography analysis and by headspace-gas chromatography-mass spectrometry.
NASA Astrophysics Data System (ADS)
Marston, Philip L.
2004-05-01
In 1976, research in collaboration with Bob Apfel demonstrated that low-frequency shape oscillations of hydrocarbon drops levitated in water could be driven using modulated radiation pressure. While that response to modulated ultrasound was subsequently extended to a range of systems, the emphasis here is to recall the initial stages of development in Bob Apfel's laboratory leading to some publications [P. L. Marston and R. E. Apfel, J. Colloid Interface Sci. 68, 280-286 (1979); J. Acoust. Soc. Am. 67, 27-37 (1980)]. The levitation technology used at that time was such that it was helpful to develop a sensitive method for detecting weak oscillations using the interference pattern in laser light scattered by levitated drops. The initial experiments to verify this scattering method used shape oscillations induced by modulated electric fields within the acoustic levitator. Light scattering was subsequently used to detect shape oscillations induced by amplitude modulating a carrier having a high frequency (around 680 kHz) at a resonance of the transducer. Methods were also developed for quantitative measurements of the drop's response and with improved acoustic coupling drop fission was observed. The connection with research currently supported by NASA will also be noted.
Jean, Julie; D'Souza, Doris H.; Jaykus, Lee-Ann
2004-01-01
Human enteric viruses are currently recognized as one of the most important causes of food-borne disease. Implication of enteric viruses in food-borne outbreaks can be difficult to confirm due to the inadequacy of the detection methods available. In this study, a nucleic acid sequence-based amplification (NASBA) method was developed in a multiplex format for the specific, simultaneous, and rapid detection of epidemiologically relevant human enteric viruses. Three previously reported primer sets were used in a single reaction for the amplification of RNA target fragments of 474, 371, and 165 nucleotides for the detection of hepatitis A virus and genogroup I and genogroup II noroviruses, respectively. Amplicons were detected by agarose gel electrophoresis and confirmed by electrochemiluminescence and Northern hybridization. Endpoint detection sensitivity for the multiplex NASBA assay was approximately 10−1 reverse transcription-PCR-detectable units (or PFU, as appropriate) per reaction. When representative ready-to-eat foods (deli sliced turkey and lettuce) were inoculated with various concentrations of each virus and processed for virus detection with the multiplex NASBA method, all three human enteric viruses were simultaneously detected at initial inoculum levels of 100 to 102 reverse transcription-PCR-detectable units (or PFU)/9 cm2 in both food commodities. The multiplex NASBA system provides rapid and simultaneous detection of clinically relevant food-borne viruses in a single reaction tube and may be a promising alternative to reverse transcription-PCR for the detection of viral contamination of foods. PMID:15528524
A unique circovirus-like genome detected in pig feces
USDA-ARS?s Scientific Manuscript database
Using a metagenomic approach and molecular cloning methods, we identified, cloned, and sequenced the complete genome of a novel circular DNA virus, porcine stool-associated virus (PoSCV4), from pig feces. Phylogenetic analysis of the deduced replication initiator protein showed that PoSCV4 is most r...
USDA-ARS?s Scientific Manuscript database
Background: Until now, antioxidant based initiatives for preventing dementia have lacked a means to detect deficiency or measure pharmacologic effect in the human brain in situ. Objective: Our objective was to apply a novel method to measure key human brain antioxidant concentrations throughout the ...
40 CFR 65.120 - Reporting provisions.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) CONSOLIDATED FEDERAL AIR RULE Equipment Leaks § 65.120 Reporting provisions. (a) Initial Compliance Status... equipment in vacuum service; and (iii) Method of compliance with the standard (for example, “monthly leak... in a summary format by equipment type the number of components for which leaks were detected, and for...
Sensitive, Selective Test For Hydrazines
NASA Technical Reports Server (NTRS)
Roundbehler, David; Macdonald, Stephen
1993-01-01
Derivatives of hydrazines formed, then subjected to gas chromatography and detected via chemiluminescence. In method of detecting and quantifying hydrazine vapors, vapors reacted with dinitro compound to enhance sensitivity and selectivity. Hydrazine (HZ), monomethyl hydrazine, (MMH), and unsymmetrical dimethylhydrazine (UDMH) analyzed quantitatively and qualitatively, either alone or in mixtures. Vapors collected and reacted with 2,4-dinitrobenzaldehyde, (DNB), making it possible to concentrate hydrazine in derivative form, thereby increasing sensitivity to low initial concentrations. Increases selectivity because only those constituents of sample reacting with DNB concentrated for analysis.
Three-dimensional images contribute to the diagnosis of mucous retention cyst in maxillary sinus.
Donizeth-Rodrigues, Cleomar; Fonseca-Da Silveira, Márcia; Gonçalves-De Alencar, Ana-Helena; Garcia-Santos-Silva, Maria-Alves; Francisco-De-Mendonça, Elismauro; Estrela, Carlos
2013-01-01
To evaluate the detection of mucous retention cyst of maxillary sinus (MRCMS) using panoramic radiography and cone beam computed tomography (CBCT). A digital database with 6,000 panoramic radiographs was reviewed for MRCMS. Suggestive images of MRCMS were detected on 185 radiographs, and patients were located and invited to return for follow-up. Thirty patients returned, and control panoramic radiographs were obtained 6 to 46 months after the initial radiograph. When MRCMS was found on control radiographs, CBCT scans were obtained. Cysts were measured and compared on radiographs and scans. The Wilcoxon, Spearman and Kolmorogov-Smirnov tests were used for statistical analysis. The level of significance was set at 5%. There were statistically significant differences between the two methods (p<0.05): 23 MRCMS detected on panoramic radiographs were confirmed by CBCT, but 5 MRCMS detected on CBCT images had not been identified by panoramic radiography. Eight MRCMS detected on control radiographs were not confirmed by CBCT. MRCMS size differences from initial to control panoramic radiographs and CBCT scans were not statistically significant (p= 0.617 and p= 0.626). The correlation between time and MRCMS size differences was not significant (r = -0.16, p = 0.381). CBCT scanning detect MRCMS more accurately than panoramic radiography.
Detection of Dry Intrusion on Water Vapor Images Over Central Europe - June 2010 TO September 2011
NASA Astrophysics Data System (ADS)
Novotny, J.; Dejmal, K.; Hudec, F.; Kolar, P.
2016-06-01
The knowledge of evaluation of the intensity of cyclogenesis which could be connected with the weather having a significant impact on Earth's surface is quite useful. If, as one of the basic assumptions, the existence of connection between dry intrusions, dry bands, tropopause height and warm dark areas distribution on water vapor images (WV images) is considered, it is possible to set up a method of detecting dry intrusions on searching and tracking areas with higher brightness temperature compared with the surrounding environment. This paper covers the period between June 2010 and September 2011 over Central Europe. The ISIS method (Instrument de Suivi dans I'Imagerie satellitaire), originally developed for detection of cold cloud tops, was used as an initial ideological point. Subsequently, this method was modified by Michel and Bouttier for usage on WV images. Some of the applied criteria and parameters were chosen with reference to the results published by Michel and Bouttier as well as by Novotny. The procedure can be divided into two steps: detection of warm areas and their tracking. Cases of detection of areas not evidently connected with dry intrusions can be solved by filtering off based on the connection between detected warm areas to the cyclonic side of jet streams and significant lowering of the tropopause.
Detection of protein complex from protein-protein interaction network using Markov clustering
NASA Astrophysics Data System (ADS)
Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.
2017-05-01
Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.
Automatic quantification framework to detect cracks in teeth
Shah, Hina; Hernandez, Pablo; Budin, Francois; Chittajallu, Deepak; Vimort, Jean-Baptiste; Walters, Rick; Mol, André; Khan, Asma; Paniagua, Beatriz
2018-01-01
Studies show that cracked teeth are the third most common cause for tooth loss in industrialized countries. If detected early and accurately, patients can retain their teeth for a longer time. Most cracks are not detected early because of the discontinuous symptoms and lack of good diagnostic tools. Currently used imaging modalities like Cone Beam Computed Tomography (CBCT) and intraoral radiography often have low sensitivity and do not show cracks clearly. This paper introduces a novel method that can detect, quantify, and localize cracks automatically in high resolution CBCT (hr-CBCT) scans of teeth using steerable wavelets and learning methods. These initial results were created using hr-CBCT scans of a set of healthy teeth and of teeth with simulated longitudinal cracks. The cracks were simulated using multiple orientations. The crack detection was trained on the most significant wavelet coefficients at each scale using a bagged classifier of Support Vector Machines. Our results show high discriminative specificity and sensitivity of this method. The framework aims to be automatic, reproducible, and open-source. Future work will focus on the clinical validation of the proposed techniques on different types of cracks ex-vivo. We believe that this work will ultimately lead to improved tracking and detection of cracks allowing for longer lasting healthy teeth. PMID:29769755
Theron, Grant; Peter, Jonny; Meldau, Richard; Khalfey, Hoosain; Gina, Phindile; Matinyena, Brian; Lenders, Laura; Calligaro, Gregory; Allwood, Brian; Symons, Gregory; Govender, Ureshnie; Setshedi, Mashiko; Dheda, Keertan
2017-01-01
Rationale The accuracy and impact of new tuberculosis (TB) tests, such as Xpert MTB/RIF, when performed on bronchoalveolar lavage fluid (BALF) obtained from patients with sputum-scarce or smear-negative TB is unclear. Methods South African patients with suspected pulmonary TB (n=160) who were sputum-scarce or smear-negative underwent bronchoscopy. MTB/RIF was performed on uncentrifuged BALF (1 ml) and/or a resuspended pellet of centrifuged BALF (~10 ml). Time to TB detection and anti-TB treatment initiation were compared between phase one, when MTB/RIF was performed as a research tool, and phase two, when it was used for patient management. Results 27 of 154 patients with complete data had culture-confirmed TB. Of these, a significantly lower proportion were detected by smear microscopy compared with MTB/RIF (58%, 95% CI 39% to 75% versus 93%, 77% to 98%; p<0.001). Of the 127 patients who were culture negative, 96% (91% to 98%) were MTB/RIF negative. When phase two was compared with phase one, MTB/RIF reduced the median days to TB detection (29 (18–41) to 0 (0–0); p<0.001). However, more patients initiated empirical therapy (absence of a positive test in those commencing treatment) in phase one versus phase two (79% (11/14) versus 28% (10/25); p=0.026). Consequently, there was no detectable difference in the overall proportion of patients initiating treatment (26% (17/67; 17% to 37%) versus 36% (26/73; 26% to 47%); p=0.196) or the days to treatment initiation (10 (1–49) versus 7 (0–21); p=0.330). BALF centrifugation, HIV coinfection and a second MTB/RIF did not result in detectable changes in accuracy. Conclusions MTB/RIF detected TB cases more accurately and more rapidly than smear microscopy and significantly reduced the rate of empirical treatment. PMID:23811536
Sergueev, Kirill V; He, Yunxiu; Borschel, Richard H; Nikolich, Mikeljon P; Filippov, Andrey A
2010-06-28
Yersinia pestis, the agent of plague, has caused many millions of human deaths and still poses a serious threat to global public health. Timely and reliable detection of such a dangerous pathogen is of critical importance. Lysis by specific bacteriophages remains an essential method of Y. pestis detection and plague diagnostics. The objective of this work was to develop an alternative to conventional phage lysis tests--a rapid and highly sensitive method of indirect detection of live Y. pestis cells based on quantitative real-time PCR (qPCR) monitoring of amplification of reporter Y. pestis-specific bacteriophages. Plague diagnostic phages phiA1122 and L-413C were shown to be highly effective diagnostic tools for the detection and identification of Y. pestis by using qPCR with primers specific for phage DNA. The template DNA extraction step that usually precedes qPCR was omitted. phiA1122-specific qPCR enabled the detection of an initial bacterial concentration of 10(3) CFU/ml (equivalent to as few as one Y. pestis cell per 1-microl sample) in four hours. L-413C-mediated detection of Y. pestis was less sensitive (up to 100 bacteria per sample) but more specific, and thus we propose parallel qPCR for the two phages as a rapid and reliable method of Y. pestis identification. Importantly, phiA1122 propagated in simulated clinical blood specimens containing EDTA and its titer rise was detected by both a standard plating test and qPCR. Thus, we developed a novel assay for detection and identification of Y. pestis using amplification of specific phages monitored by qPCR. The method is simple, rapid, highly sensitive, and specific and allows the detection of only live bacteria.
a Weighted Closed-Form Solution for Rgb-D Data Registration
NASA Astrophysics Data System (ADS)
Vestena, K. M.; Dos Santos, D. R.; Oilveira, E. M., Jr.; Pavan, N. L.; Khoshelham, K.
2016-06-01
Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.
Kargupta, Roli; Puttaswamy, Sachidevi; Lee, Aiden J; Butler, Timothy E; Li, Zhongyu; Chakraborty, Sounak; Sengupta, Shramik
2017-06-10
Multiple techniques exist for detecting Mycobacteria, each having its own advantages and drawbacks. Among them, automated culture-based systems like the BACTEC-MGIT™ are popular because they are inexpensive, reliable and highly accurate. However, they have a relatively long "time-to-detection" (TTD). Hence, a method that retains the reliability and low-cost of the MGIT system, while reducing TTD would be highly desirable. Living bacterial cells possess a membrane potential, on account of which they store charge when subjected to an AC-field. This charge storage (bulk capacitance) can be estimated using impedance measurements at multiple frequencies. An increase in the number of living cells during culture is reflected in an increase in bulk capacitance, and this forms the basis of our detection. M. bovis BCG and M. smegmatis suspensions with differing initial loads are cultured in MGIT media supplemented with OADC and Middlebrook 7H9 media respectively, electrical "scans" taken at regular intervals and the bulk capacitance estimated from the scans. Bulk capacitance estimates at later time-points are statistically compared to the suspension's baseline value. A statistically significant increase is assumed to indicate the presence of proliferating mycobacteria. Our TTDs were 60 and 36 h for M. bovis BCG and 20 and 9 h for M. smegmatis with initial loads of 1000 CFU/ml and 100,000 CFU/ml respectively. The corresponding TTDs for the commercial BACTEC MGIT 960 system were 131 and 84.6 h for M. bovis BCG and 41.7 and 12 h for M smegmatis, respectively. Our culture-based detection method using multi-frequency impedance measurements is capable of detecting mycobacteria faster than current commercial systems.
NASA Astrophysics Data System (ADS)
Merk, D.; Zinner, T.
2013-08-01
In this paper a new detection scheme for convective initiation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting CI with geostationary satellite data. It uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared (IR) criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one high-resolution visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims to identify the typical development of quickly developing convective cells in an early stage. The different criteria include time trends of the 10.8 IR channel, and IR channel differences, as well as their time trends. To provide the trend fields an optical-flow-based method is used: the pyramidal matching algorithm, which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM, and is verified for seven days which comprise different weather situations in central Europe. Contrasted with the original early-stage detection scheme of Cb-TRAM, skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for the synoptic class "cold air" masses.
Fife, Kenneth H.; Wu, Julia W.; Squires, Kathleen E.; Watts, D. Heather; Andersen, Janet W.; Brown, Darron R.
2009-01-01
Objective To determine the prevalence of HPV DNA in cervical specimens from treatment-naïve women initiating highly active antiretroviral therapy (HAART) and explore the longitudinal association of HPV DNA with CD4 count and HIV viral load (VL). Methods Women enrolled prior to HAART were evaluated at baseline, weeks 24, 48, and 96 with CD4 count, VL, and cervical swab for HPV DNA. Results The 146 subjects had a median CD4 count of 238 cells/μL and VL of 13,894 copies/mL. Ninety-seven (66%) subjects had HPV DNA detected in the baseline specimen including 90 subjects (62%) positive for one or more high risk HPV types. HPV DNA detection declined to 49% at week 96, and that of a high risk HPV type to 39%. The duration of follow-up was associated with decreased detection of HPV DNA of any type (p=0.045) and of high risk HPV types (p=0.003). There was at most a marginal association between HAART response and loss of detection of cervical HPV DNA. Conclusions Women initiating HAART had a high prevalence of cervical HPV DNA that declined over 96 weeks of HAART. The relationship of CD4 count and VL response to the decline of cervical HPV DNA was not strong. PMID:19387354
Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang
2017-06-09
Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.
Luo, Jun; Li, Junhua; Yang, Hang; Yu, Junping; Wei, Hongping
2017-10-01
Accurate and rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is needed to screen MRSA carriers and improve treatment. The current widely used duplex PCR methods are not able to differentiate MRSA from coexisting methicillin-susceptible S. aureus (MSSA) or other methicillin-resistant staphylococci. In this study, we aimed to develop a direct method for accurate and rapid detection of MRSA in clinical samples from open environments, such as nasal swabs. The new molecular assay is based on detecting the cooccurrence of nuc and mecA markers in a single bacterial cell by utilizing droplet digital PCR (ddPCR) with the chimeric lysin ClyH for cell lysis. The method consists of (i) dispersion of an intact single bacterium into nanoliter droplets, (ii) temperature-controlled release of genomic DNA (gDNA) by ClyH at 37°C, and (iii) amplification and detection of the markers ( nuc and mecA ) using standard TaqMan chemistries with ddPCR. Results were analyzed based on MRSA index ratios used for indicating the presence of the duplex-positive markers in droplets. The method was able to achieve an absolute limit of detection (LOD) of 2,900 CFU/ml for MRSA in nasal swabs spiked with excess amounts of Escherichia coli , MSSA, and other mecA -positive bacteria within 4 h. Initial testing of 104 nasal swabs showed that the method had 100% agreement with the standard culture method, while the normal duplex qPCR method had only about 87.5% agreement. The single-bacterium duplex ddPCR assay is rapid and powerful for more accurate detection of MRSA directly from clinical specimens. Copyright © 2017 American Society for Microbiology.
Luo, Jun; Li, Junhua; Yang, Hang; Yu, Junping
2017-01-01
ABSTRACT Accurate and rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is needed to screen MRSA carriers and improve treatment. The current widely used duplex PCR methods are not able to differentiate MRSA from coexisting methicillin-susceptible S. aureus (MSSA) or other methicillin-resistant staphylococci. In this study, we aimed to develop a direct method for accurate and rapid detection of MRSA in clinical samples from open environments, such as nasal swabs. The new molecular assay is based on detecting the cooccurrence of nuc and mecA markers in a single bacterial cell by utilizing droplet digital PCR (ddPCR) with the chimeric lysin ClyH for cell lysis. The method consists of (i) dispersion of an intact single bacterium into nanoliter droplets, (ii) temperature-controlled release of genomic DNA (gDNA) by ClyH at 37°C, and (iii) amplification and detection of the markers (nuc and mecA) using standard TaqMan chemistries with ddPCR. Results were analyzed based on MRSA index ratios used for indicating the presence of the duplex-positive markers in droplets. The method was able to achieve an absolute limit of detection (LOD) of 2,900 CFU/ml for MRSA in nasal swabs spiked with excess amounts of Escherichia coli, MSSA, and other mecA-positive bacteria within 4 h. Initial testing of 104 nasal swabs showed that the method had 100% agreement with the standard culture method, while the normal duplex qPCR method had only about 87.5% agreement. The single-bacterium duplex ddPCR assay is rapid and powerful for more accurate detection of MRSA directly from clinical specimens. PMID:28724560
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.
The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency formore » all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.« less
Zhang, Y; Huang, S L; Wang, S; Zhao, W
2016-05-01
The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert-Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.
An investigation of gear mesh failure prediction techniques. M.S. Thesis - Cleveland State Univ.
NASA Technical Reports Server (NTRS)
Zakrajsek, James J.
1989-01-01
A study was performed in which several gear failure prediction methods were investigated and applied to experimental data from a gear fatigue test apparatus. The primary objective was to provide a baseline understanding of the prediction methods and to evaluate their diagnostic capabilities. The methods investigated use the signal average in both the time and frequency domain to detect gear failure. Data from eleven gear fatigue tests were recorded at periodic time intervals as the gears were run from initiation to failure. Four major failure modes, consisting of heavy wear, tooth breakage, single pits, and distributed pitting were observed among the failed gears. Results show that the prediction methods were able to detect only those gear failures which involved heavy wear or distributed pitting. None of the methods could predict fatigue cracks, which resulted in tooth breakage, or single pits. It is suspected that the fatigue cracks were not detected because of limitations in data acquisition rather than in methodology. Additionally, the frequency response between the gear shaft and the transducer was found to significantly affect the vibration signal. The specific frequencies affected were filtered out of the signal average prior to application of the methods.
Multiple pedestrian detection using IR LED stereo camera
NASA Astrophysics Data System (ADS)
Ling, Bo; Zeifman, Michael I.; Gibson, David R. P.
2007-09-01
As part of the U.S. Department of Transportations Intelligent Vehicle Initiative (IVI) program, the Federal Highway Administration (FHWA) is conducting R&D in vehicle safety and driver information systems. There is an increasing number of applications where pedestrian monitoring is of high importance. Visionbased pedestrian detection in outdoor scenes is still an open challenge. People dress in very different colors that sometimes blend with the background, wear hats or carry bags, and stand, walk and change directions unpredictably. The background is various, containing buildings, moving or parked cars, bicycles, street signs, signals, etc. Furthermore, existing pedestrian detection systems perform only during daytime, making it impossible to detect pedestrians at night. Under FHWA funding, we are developing a multi-pedestrian detection system using IR LED stereo camera. This system, without using any templates, detects the pedestrians through statistical pattern recognition utilizing 3D features extracted from the disparity map. A new IR LED stereo camera is being developed, which can help detect pedestrians during daytime and night time. Using the image differencing and denoising, we have also developed new methods to estimate the disparity map of pedestrians in near real time. Our system will have a hardware interface with the traffic controller through wireless communication. Once pedestrians are detected, traffic signals at the street intersections will change phases to alert the drivers of approaching vehicles. The initial test results using images collected at a street intersection show that our system can detect pedestrians in near real time.
Ultracentrifugation in the Concentration and Detection of Enteroviruses
Cliver, Dean O.; Yeatman, John
1965-01-01
Ultracentrifugation has been evaluated as a method of concentrating enteroviruses from suspensions whose initial titers ranged from 1.7 × 108 to 1.6 × 10-2 plaque-forming units (PFU) per ml. A technique employing a “trap” of 0.1 ml of 2% gelatin solution at the point at which the pellet forms in tubes for the number 30 and number 50 rotors of the Spinco model L preparative ultracentrifuge has been tested and found to have a number of advantages. Qualitative studies have been performed to determine the sensitivity of the ultracentrifuge technique in detecting the presence of enteroviruses in very dilute suspensions. There was found to be at least a 50% probability of detecting virus present initially at levels as low as 0.12 PFU per ml by means of the number 50 rotor. The input level for similar results with the number 30 rotor was found to be 0.025 PFU per ml. PMID:14325278
Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng
2017-01-01
Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.
Dual sensitivity mode system for monitoring processes and sensors
Wilks, Alan D.; Wegerich, Stephan W.; Gross, Kenneth C.
2000-01-01
A method and system for analyzing a source of data. The system and method involves initially training a system using a selected data signal, calculating at least two levels of sensitivity using a pattern recognition methodology, activating a first mode of alarm sensitivity to monitor the data source, activating a second mode of alarm sensitivity to monitor the data source and generating a first alarm signal upon the first mode of sensitivity detecting an alarm condition and a second alarm signal upon the second mode of sensitivity detecting an associated alarm condition. The first alarm condition and second alarm condition can be acted upon by an operator and/or analyzed by a specialist or computer program.
Increased efficacy for in-house validation of real-time PCR GMO detection methods.
Scholtens, I M J; Kok, E J; Hougs, L; Molenaar, B; Thissen, J T N M; van der Voet, H
2010-03-01
To improve the efficacy of the in-house validation of GMO detection methods (DNA isolation and real-time PCR, polymerase chain reaction), a study was performed to gain insight in the contribution of the different steps of the GMO detection method to the repeatability and in-house reproducibility. In the present study, 19 methods for (GM) soy, maize canola and potato were validated in-house of which 14 on the basis of an 8-day validation scheme using eight different samples and five on the basis of a more concise validation protocol. In this way, data was obtained with respect to the detection limit, accuracy and precision. Also, decision limits were calculated for declaring non-conformance (>0.9%) with 95% reliability. In order to estimate the contribution of the different steps in the GMO analysis to the total variation variance components were estimated using REML (residual maximum likelihood method). From these components, relative standard deviations for repeatability and reproducibility (RSD(r) and RSD(R)) were calculated. The results showed that not only the PCR reaction but also the factors 'DNA isolation' and 'PCR day' are important factors for the total variance and should therefore be included in the in-house validation. It is proposed to use a statistical model to estimate these factors from a large dataset of initial validations so that for similar GMO methods in the future, only the PCR step needs to be validated. The resulting data are discussed in the light of agreed European criteria for qualified GMO detection methods.
ECALS: loading studies interim report July 2013
Klymus, Katy E.; Richter, Catherine A.; Chapman, Duane C.; Paukert, Craig P.
2013-01-01
Since the initial detection of Asian carp moving up the Mississippi Basin, the potential for invasion of the Great Lakes by Silver Carp and Bighead Carp has been a major concern to stakeholders. To combat this problem, sampling for environmental DNA (eDNA) is used to monitor the waterways near Lake Michigan. This monitoring area includes the Chicago Area Waterways System (CAWS) and the Des Plaines River. By sampling waters that may be inhabited by Asian carp, the extraction and amplification of carp DNA from the collected cellular debris is possible. This technique has been successfully used in several other contexts (Ficetola et al., 2008; Foote et al., 2008) and is believed to be a highly sensitive method for species detection (Dejean et al., 2012). Compared to traditional methods for surveying aquatic invasive species (fishing, rotenone application, and electrofishing), the increased sensitivity of this method could be a valuable asset. Early detection could lead to a more rapid response to the threat of a Great Lakes invasion by Asian carp.
Cheyne, Bo M; Van Dyke, Michele I; Anderson, William B; Huck, Peter M
2010-09-01
Yersinia enterocolitica has been detected in surface water, and drinking untreated water is a risk factor for infection. PCR-based methods have been used to detect Y. enterocolitica in various sample types, but quantitative studies have not been conducted in water. In this study, quantitative PCR (qPCR)-based methods targeting the Yersinia virulence genes ail and yadA were used to survey the Grand River watershed in southern Ontario, Canada. Initial testing of reference strains showed that ail and yadA PCR assays were specific for pathogenic biotypes of Y. enterocolitica; however the genes were also detected in one clinical Yersinia intermedia isolate. A survey of surface water from the Grand River watershed showed that both genes were detected at five sampling locations, with the ail and yadA genes detected in 38 and 21% of samples, respectively. Both genes were detected more frequently at colder water temperatures. A screening of Yersinia strains isolated from the watershed showed that the ail gene was detected in three Y. enterocolitica 1A/O:5 isolates. Results of this study show that Yersinia virulence genes were commonly detected in a watershed used as a source of drinking water, and that the occurrence of these genes was seasonal.
Bykova, L G; Bazylev, V N
1994-01-01
By means of dichotic test the comparative research of the brain activity in dynamics in 84 adult students was conducted during their traditional (36 persons) and intensive (48 persons) learning of foreign languages. By different methods of learning the reliable distinction of the hemisphere's asymmetry was not detected. By both methods in the reliable majority of students the activation of the hemisphere opposite to the one dominating initially was observed. The correlation between the maximum quantitative shift of the right ear coefficient and the level of success in colloquial practice by the same initial level of language start and initial comparable size of memory was revealed. The authors discuss the possibility of the individual map composition for every student using the results of dichotic tests in dynamics for the help in the profession of a teacher.
Improved Real-Time Scan Matching Using Corner Features
NASA Astrophysics Data System (ADS)
Mohamed, H. A.; Moussa, A. M.; Elhabiby, M. M.; El-Sheimy, N.; Sesay, Abu B.
2016-06-01
The automation of unmanned vehicle operation has gained a lot of research attention, in the last few years, because of its numerous applications. The vehicle localization is more challenging in indoor environments where absolute positioning measurements (e.g. GPS) are typically unavailable. Laser range finders are among the most widely used sensors that help the unmanned vehicles to localize themselves in indoor environments. Typically, automatic real-time matching of the successive scans is performed either explicitly or implicitly by any localization approach that utilizes laser range finders. Many accustomed approaches such as Iterative Closest Point (ICP), Iterative Matching Range Point (IMRP), Iterative Dual Correspondence (IDC), and Polar Scan Matching (PSM) handles the scan matching problem in an iterative fashion which significantly affects the time consumption. Furthermore, the solution convergence is not guaranteed especially in cases of sharp maneuvers or fast movement. This paper proposes an automated real-time scan matching algorithm where the matching process is initialized using the detected corners. This initialization step aims to increase the convergence probability and to limit the number of iterations needed to reach convergence. The corner detection is preceded by line extraction from the laser scans. To evaluate the probability of line availability in indoor environments, various data sets, offered by different research groups, have been tested and the mean numbers of extracted lines per scan for these data sets are ranging from 4.10 to 8.86 lines of more than 7 points. The set of all intersections between extracted lines are detected as corners regardless of the physical intersection of these line segments in the scan. To account for the uncertainties of the detected corners, the covariance of the corners is estimated using the extracted lines variances. The detected corners are used to estimate the transformation parameters between the successive scan using least squares. These estimated transformation parameters are used to calculate an adjusted initialization for scan matching process. The presented method can be employed solely to match the successive scans and also can be used to aid other accustomed iterative methods to achieve more effective and faster converge. The performance and time consumption of the proposed approach is compared with ICP algorithm alone without initialization in different scenarios such as static period, fast straight movement, and sharp manoeuvers.
Fatemeh, Dehghan; Reza, Zolfaghari Mohammad; Mohammad, Arjomandzadegan; Salomeh, Kalantari; Reza, Ahmari Gholam; Hossein, Sarmadian; Maryam, Sadrnia; Azam, Ahmadi; Mana, Shojapoor; Negin, Najarian; Reza, Kasravi Alii; Saeed, Falahat
2014-01-01
Objective To analyse molecular detection of coliforms and shorten the time of PCR. Methods Rapid detection of coliforms by amplification of lacZ and uidA genes in a multiplex PCR reaction was designed and performed in comparison with most probably number (MPN) method for 16 artificial and 101 field samples. The molecular method was also conducted on isolated coliforms from positive MPN samples; standard sample for verification of microbial method certificated reference material; isolated strains from certificated reference material and standard bacteria. The PCR and electrophoresis parameters were changed for reducing the operation time. Results Results of PCR for lacZ and uidA genes were similar in all of standard, operational and artificial samples and showed the 876 bp and 147 bp bands of lacZ and uidA genes by multiplex PCR. PCR results were confirmed by MPN culture method by sensitivity 86% (95% CI: 0.71-0.93). Also the total execution time, with a successful change of factors, was reduced to less than two and a half hour. Conclusions Multiplex PCR method with shortened operation time was used for the simultaneous detection of total coliforms and Escherichia coli in distribution system of Arak city. It's recommended to be used at least as an initial screening test, and then the positive samples could be randomly tested by MPN. PMID:25182727
Phased Array Ultrasound: Initial Development of PAUT Inspection of Self-Reacting Friction Stir Welds
NASA Technical Reports Server (NTRS)
Rairigh, Ryan
2008-01-01
This slide presentation reviews the development of Phased Array Ultrasound (PAUT) as a non-destructive examination method for Self Reacting Friction Stir Welds (SR-FSW). PAUT is the only NDE method which has been shown to detect detrimental levels of Residual Oxide Defect (ROD), which can result in significant decrease in weld strength. The presentation reviews the PAUT process, and shows the results in comparison with x-ray radiography.
Aircraft Flight Envelope Determination using Upset Detection and Physical Modeling Methods
NASA Technical Reports Server (NTRS)
Keller, Jeffrey D.; McKillip, Robert M. Jr.; Kim, Singwan
2009-01-01
The development of flight control systems to enhance aircraft safety during periods of vehicle impairment or degraded operations has been the focus of extensive work in recent years. Conditions adversely affecting aircraft flight operations and safety may result from a number of causes, including environmental disturbances, degraded flight operations, and aerodynamic upsets. To enhance the effectiveness of adaptive and envelope limiting controls systems, it is desirable to examine methods for identifying the occurrence of anomalous conditions and for assessing the impact of these conditions on the aircraft operational limits. This paper describes initial work performed toward this end, examining the use of fault detection methods applied to the aircraft for aerodynamic performance degradation identification and model-based methods for envelope prediction. Results are presented in which a model-based fault detection filter is applied to the identification of aircraft control surface and stall departure failures/upsets. This application is supported by a distributed loading aerodynamics formulation for the flight dynamics system reference model. Extensions for estimating the flight envelope due to generalized aerodynamic performance degradation are also described.
[Detection of lung nodules. New opportunities in chest radiography].
Pötter-Lang, S; Schalekamp, S; Schaefer-Prokop, C; Uffmann, M
2014-05-01
Chest radiography still represents the most commonly performed X-ray examination because it is readily available, requires low radiation doses and is relatively inexpensive. However, as previously published, many initially undetected lung nodules are retrospectively visible in chest radiographs. The great improvements in detector technology with the increasing dose efficiency and improved contrast resolution provide a better image quality and reduced dose needs. The dual energy acquisition technique and advanced image processing methods (e.g. digital bone subtraction and temporal subtraction) reduce the anatomical background noise by reduction of overlapping structures in chest radiography. Computer-aided detection (CAD) schemes increase the awareness of radiologists for suspicious areas. The advanced image processing methods show clear improvements for the detection of pulmonary lung nodules in chest radiography and strengthen the role of this method in comparison to 3D acquisition techniques, such as computed tomography (CT). Many of these methods will probably be integrated into standard clinical treatment in the near future. Digital software solutions offer advantages as they can be easily incorporated into radiology departments and are often more affordable as compared to hardware solutions.
Development and evaluation of modified envelope correlation method for deep tectonic tremor
NASA Astrophysics Data System (ADS)
Mizuno, N.; Ide, S.
2017-12-01
We develop a new location method for deep tectonic tremors, as an improvement of widely used envelope correlation method, and applied it to construct a tremor catalog in western Japan. Using the cross-correlation functions as objective functions and weighting components of data by the inverse of error variances, the envelope cross-correlation method is redefined as a maximum likelihood method. This method is also capable of multiple source detection, because when several events occur almost simultaneously, they appear as local maxima of likelihood.The average of weighted cross-correlation functions, defined as ACC, is a nonlinear function whose variable is a position of deep tectonic tremor. The optimization method has two steps. First, we fix the source depth to 30 km and use a grid search with 0.2 degree intervals to find the maxima of ACC, which are candidate event locations. Then, using each of the candidate locations as initial values, we apply a gradient method to determine horizontal and vertical components of a hypocenter. Sometimes, several source locations are determined in a time window of 5 minutes. We estimate the resolution, which is defined as a distance of sources to be detected separately by the location method, is about 100 km. The validity of this estimation is confirmed by a numerical test using synthetic waveforms. Applying to continuous seismograms in western Japan for over 10 years, the new method detected 27% more tremors than a previous method, owing to the multiple detection and improvement of accuracy by appropriate weighting scheme.
Dera, Dimah; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M
2016-07-01
We address the problem of fully automated region discovery and robust image segmentation by devising a new deformable model based on the level set method (LSM) and the probabilistic nonnegative matrix factorization (NMF). We describe the use of NMF to calculate the number of distinct regions in the image and to derive the local distribution of the regions, which is incorporated into the energy functional of the LSM. The results demonstrate that our NMF-LSM method is superior to other approaches when applied to synthetic binary and gray-scale images and to clinical magnetic resonance images (MRI) of the human brain with and without a malignant brain tumor, glioblastoma multiforme. In particular, the NMF-LSM method is fully automated, highly accurate, less sensitive to the initial selection of the contour(s) or initial conditions, more robust to noise and model parameters, and able to detect as small distinct regions as desired. These advantages stem from the fact that the proposed method relies on histogram information instead of intensity values and does not introduce nuisance model parameters. These properties provide a general approach for automated robust region discovery and segmentation in heterogeneous images. Compared with the retrospective radiological diagnoses of two patients with non-enhancing grade 2 and 3 oligodendroglioma, the NMF-LSM detects earlier progression times and appears suitable for monitoring tumor response. The NMF-LSM method fills an important need of automated segmentation of clinical MRI.
NASA Technical Reports Server (NTRS)
Pelletier, R. E.; Griffin, R. H.
1985-01-01
The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.
Application of DBNs for concerned internet information detecting
NASA Astrophysics Data System (ADS)
Wang, Yanfang; Gao, Song
2017-03-01
In recent years, deep learning has achieved great success in many fields, ranging from voice recognition and image classification to computer vision. In this study we apply DBNs to concerned internet information in Chinese detecting problem, since there are inherent differences between English and Chinese. Contrastive divergence (CD) is employed in the DBNs to learn a multi-layer generative model from numerous unlabeled data. The features obtained by this model are used to initialize the feed-forward neural network, which can be fine-tuned with backpropagation. Experiment results indicate that, the model and training method we proposed can be used to detect the concerned internet information effectively and accurately.
Aircraft target detection algorithm based on high resolution spaceborne SAR imagery
NASA Astrophysics Data System (ADS)
Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing
2018-03-01
In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.
Huang, Shu-Huan; Lin, Yi-Fang; Tsai, Ming-Han; Yang, Shuan; Liao, Mei-Ling; Chao, Shao-Wen; Hwang, Cheng-Cheng
2018-06-01
Conventional methods for identifying gastroenteritis pathogens are time consuming, more likely to result in a false-negative, rely on personnel with diagnostic expertise, and are dependent on the specimen status. Alternatively, molecular diagnostic methods permit the rapid, simultaneous detection of multiple pathogens with high sensitivity and specificity. The present study compared conventional methods with the Luminex xTAG Gastrointestinal Pathogen Panel (xTAG GPP) for the diagnosis of infectious gastroenteritis in northern Taiwan. From July 2015 to April 2016, 217 clinical fecal samples were collected from patients with suspected infectious gastroenteritis. All specimens were tested using conventional diagnostic techniques following physicians' orders as well as with the xTAG GPP. The multiplex polymerase chain reaction (PCR) approach detected significantly more positive samples with bacterial, viral, and/or parasitic infections as compared to conventional analysis (55.8% vs 40.1%, respectively; P < .001). Moreover, multiplex PCR could detect Escherichia coli O157, enterotoxigenic E coli, Shiga-like toxin-producing E coli, Cryptosporidium, and Giardia, which were undetectable by conventional methods. Furthermore, 48 pathogens in 23 patients (10.6%) with coinfections were identified only using the multiplex PCR approach. Of which, 82.6% were from pediatric patients. Because the detection rates using multiplex PCR are higher than conventional methods, and some pediatric pathogens could only be detected by multiplex PCR, this approach may be useful in rapidly diagnosing diarrheal disease in children and facilitating treatment initiation. Further studies are necessary to determine if multiplex PCR improves patient outcomes and reduces costs.
Huang, Shu-Huan; Lin, Yi-Fang; Tsai, Ming-Han; Yang, Shuan; Liao, Mei-Ling; Chao, Shao-Wen; Hwang, Cheng-Cheng
2018-01-01
Abstract Conventional methods for identifying gastroenteritis pathogens are time consuming, more likely to result in a false-negative, rely on personnel with diagnostic expertise, and are dependent on the specimen status. Alternatively, molecular diagnostic methods permit the rapid, simultaneous detection of multiple pathogens with high sensitivity and specificity. The present study compared conventional methods with the Luminex xTAG Gastrointestinal Pathogen Panel (xTAG GPP) for the diagnosis of infectious gastroenteritis in northern Taiwan. From July 2015 to April 2016, 217 clinical fecal samples were collected from patients with suspected infectious gastroenteritis. All specimens were tested using conventional diagnostic techniques following physicians’ orders as well as with the xTAG GPP. The multiplex polymerase chain reaction (PCR) approach detected significantly more positive samples with bacterial, viral, and/or parasitic infections as compared to conventional analysis (55.8% vs 40.1%, respectively; P < .001). Moreover, multiplex PCR could detect Escherichia coli O157, enterotoxigenic E coli, Shiga-like toxin-producing E coli, Cryptosporidium, and Giardia, which were undetectable by conventional methods. Furthermore, 48 pathogens in 23 patients (10.6%) with coinfections were identified only using the multiplex PCR approach. Of which, 82.6% were from pediatric patients. Because the detection rates using multiplex PCR are higher than conventional methods, and some pediatric pathogens could only be detected by multiplex PCR, this approach may be useful in rapidly diagnosing diarrheal disease in children and facilitating treatment initiation. Further studies are necessary to determine if multiplex PCR improves patient outcomes and reduces costs. PMID:29879060
NASA Astrophysics Data System (ADS)
Sun, Weiwei; Liu, Xiaoming; Yang, Zhou
2017-07-01
Age-related Macular Degeneration (AMD) is a kind of macular disease which mostly occurs in old people,and it may cause decreased vision or even lead to permanent blindness. Drusen is an important clinical indicator for AMD which can help doctor diagnose disease and decide the strategy of treatment. Optical Coherence Tomography (OCT) is widely used in the diagnosis of ophthalmic diseases, include AMD. In this paper, we propose a classification method based on Multiple Instance Learning (MIL) to detect AMD. Drusen can exist in a few slices of OCT images, and MIL is utilized in our method. We divided the method into two phases: training phase and testing phase. We train the initial features and clustered to create a codebook, and employ the trained classifier in the test set. Experiment results show that our method achieved high accuracy and effectiveness.
Premrudeepreechacharn, Suttichai
2015-01-01
The mainly used local islanding detection methods may be classified as active and passive methods. Passive methods do not perturb the system but they have larger nondetection zones, whereas active methods have smaller nondetection zones but they perturb the system. In this paper, a new hybrid method is proposed to solve this problem. An over/undervoltage (passive method) has been used to initiate an undervoltage shift (active method), which changes the undervoltage shift of inverter, when the passive method cannot have a clear discrimination between islanding and other events in the system. Simulation results on MATLAB/SIMULINK show that over/undervoltage and undervoltage shifts of hybrid islanding detection method are very effective because they can determine anti-islanding condition very fast. ΔP/P > 38.41% could determine anti-islanding condition within 0.04 s; ΔP/P < −24.39% could determine anti-islanding condition within 0.04 s; −24.39% ≤ ΔP/P ≤ 38.41% could determine anti-islanding condition within 0.08 s. This method perturbed the system, only in the case of −24.39% ≤ ΔP/P ≤ 38.41% at which the control system of inverter injected a signal of undervoltage shift as necessary to check if the occurrence condition was an islanding condition or not. PMID:25879064
Detection of Delamination in Concrete Bridge Decks Using Mfcc of Acoustic Impact Signals
NASA Astrophysics Data System (ADS)
Zhang, G.; Harichandran, R. S.; Ramuhalli, P.
2010-02-01
Delamination of the concrete cover is a commonly observed damage in concrete bridge decks. The delamination is typically initiated by corrosion of the upper reinforcing bars and promoted by freeze-thaw cycling and traffic loading. The detection of delamination is important for bridge maintenance and acoustic non-destructive evaluation (NDE) is widely used due to its low cost, speed, and easy implementation. In traditional acoustic approaches, the inspector sounds the surface of the deck by impacting it with a hammer or bar, or by dragging a chain, and assesses delamination by the "hollowness" of the sound. The detection of the delamination is subjective and requires extensive training. To improve performance, this paper proposes an objective method for delamination detection. In this method, mel-frequency cepstral coefficients (MFCC) of the signal are extracted. Some MFCC are then selected as features for detection purposes using a mutual information criterion. Finally, the selected features are used to train a classifier which is subsequently used for detection. In this work, a simple quadratic Bayesian classifier is used. Different numbers of features are used to compare the performance of the detection method. The results show that the performance first increases with the number of features, but then decreases after an optimal value. The optimal number of features based on the recorded signals is four, and the mean error rate is only 3.3% when four features are used. Therefore, the proposed algorithm has sufficient accuracy to be used in field detection.
Object-based change detection method using refined Markov random field
NASA Astrophysics Data System (ADS)
Peng, Daifeng; Zhang, Yongjun
2017-01-01
In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.
Back-Face Strain for Monitoring Stable Crack Extension in Precracked Flexure Specimens
NASA Technical Reports Server (NTRS)
Salem, Jonathan A.; Ghosn, Louis J.
2010-01-01
Calibrations relating back-face strain to crack length in precracked flexure specimens were developed for different strain gage sizes. The functions were verified via experimental compliance measurements of notched and precracked ceramic beams. Good agreement between the functions and experiments occurred, and fracture toughness was calculated via several operational methods: maximum test load and optically measured precrack length; load at 2 percent crack extension and optical precrack length; maximum load and back-face strain crack length. All the methods gave vary comparable results. The initiation toughness, K(sub Ii) , was also estimated from the initial compliance and load.The results demonstrate that stability of precracked ceramics specimens tested in four-point flexure is a common occurrence, and that methods such as remotely-monitored load-point displacement are only adequate for detecting stable extension of relatively deep cracks.
Protein Analysis Meets Visual Word Recognition: A Case for String Kernels in the Brain
ERIC Educational Resources Information Center
Hannagan, Thomas; Grainger, Jonathan
2012-01-01
It has been recently argued that some machine learning techniques known as Kernel methods could be relevant for capturing cognitive and neural mechanisms (Jakel, Scholkopf, & Wichmann, 2009). We point out that "String kernels," initially designed for protein function prediction and spam detection, are virtually identical to one contending proposal…
An Investigation of Automatic Change Detection for Topographic Map Updating
NASA Astrophysics Data System (ADS)
Duncan, P.; Smit, J.
2012-08-01
Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.
Ren, Fulong; Cao, Peng; Li, Wei; Zhao, Dazhe; Zaiane, Osmar
2017-01-01
Diabetic retinopathy (DR) is a progressive disease, and its detection at an early stage is crucial for saving a patient's vision. An automated screening system for DR can help in reduce the chances of complete blindness due to DR along with lowering the work load on ophthalmologists. Among the earliest signs of DR are microaneurysms (MAs). However, current schemes for MA detection appear to report many false positives because detection algorithms have high sensitivity. Inevitably some non-MAs structures are labeled as MAs in the initial MAs identification step. This is a typical "class imbalance problem". Class imbalanced data has detrimental effects on the performance of conventional classifiers. In this work, we propose an ensemble based adaptive over-sampling algorithm for overcoming the class imbalance problem in the false positive reduction, and we use Boosting, Bagging, Random subspace as the ensemble framework to improve microaneurysm detection. The ensemble based over-sampling methods we proposed combine the strength of adaptive over-sampling and ensemble. The objective of the amalgamation of ensemble and adaptive over-sampling is to reduce the induction biases introduced from imbalanced data and to enhance the generalization classification performance of extreme learning machines (ELM). Experimental results show that our ASOBoost method has higher area under the ROC curve (AUC) and G-mean values than many existing class imbalance learning methods. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Khumaeni, A.; Sugito, H.; Setia Budi, W.; Yoyo Wardaya, A.
2018-01-01
A rapid detection of heavy metals in soil was presented by the metal-assisted gas plasma method using specific characteristics of a pulsed, transversely excited atmospheric (TEA) CO2 laser. The soil particles were placed in a hole made of acrylic plate. The sample was covered by a to prevent the soil particles from being blown off. The mesh also functioned to initiate a luminous plasma. When a TEA CO2 laser (1500 mJ, 200 ns) was focused on the soil sample, passing through the metal mesh, some of the laser energy was used to generate the gas plasma on the mesh surface, and the remaining laser energy was employed to ablate the soil particles. The fine, ablated soil particles moved into the gas plasma region to be dissociated and excited. Using this technique, analysis can be made with reduced sample pretreatment, and therefore a rapid analysis can be performed efficiently. The results proved that the signal to noise ratio (S/N) of the emission spectral lines is much better for the case of the present method (mesh method) compared to the case of standard laser-induced breakdown spectroscopy using the pellet method. Rapid detection of heavy metal elements in soil has been successfully carried out. The detection limits of Cu and Hg in soil were estimated to be 3 and 10 mg/kg, respectively. The present method has good potential for rapid and sensitive detection of heavy metals in soil samples.
Panda, Rakhi; Zoerb, Hans F; Cho, Chung Y; Jackson, Lauren S; Garber, Eric A E
2015-06-01
In 2013 the U.S. Food and Drug Administration (FDA) defined the term ''gluten-free'' and identified a gap in the analytical methodology for detection and quantification of gluten in foods subjected to fermentation and hydrolysis. To ascertain the ability of current enzyme-linked immunosorbent assays (ELISAs) to detect and quantify gluten in fermented and hydrolyzed products, sorghum beer was spiked in the initial phases of production with 0, 20, and 200 μg/ml wheat gluten, and samples were collected throughout the beer production process. The samples were analyzed using five sandwich ELISAs and two competitive ELISAs and by sodium dodecyl sulfate-polyacrylamide gel electrophoresis with Western analysis employing four antibodies (MIoBS, R5, G12, and Skerritt). The sensitivity of the MIoBS ELISA (0.25 ppm) enabled the reliable detection of gluten throughout the manufacturing process, including fermentation, when the initial concentration of 20 μg/ml dropped to 2 μg/ml. The R5 antibody-based and G12 antibody-based sandwich ELISAs were unable to reliably detect gluten, initially at 20 μg/ml, after the onset of production. The Skerritt antibody-based sandwich ELISA overestimated the gluten concentration in all samples. The R5 antibody-based and G12 antibody-based competitive ELISAs were less sensitive than the sandwich ELISAs and did not provide accurate results for quantifying gluten concentration. The Western analyses were able to detect gluten at less than 5 μg/ml in the samples and confirmed the results of the ELISAs. Although further research is necessary before all problems associated with detection and quantification of hydrolyzed and fermented gluten are resolved, the analytical methods recommended by the FDA for regulatory samples can detect ≥ 20 μg/ml gluten that has undergone brewing and fermentation processes associated with the manufacture of beer.
Kaufmann, A; Maden, K; Leisser, W; Matera, M; Gude, T
2005-11-01
Inorganic polyphosphates (di-, tri- and higher polyphosphates) can be used to treat fish, fish fillets and shrimps in order to improve their water-binding capacity. The practical relevance of this treatment is a significant gain of weight caused by the retention/uptake of water and natural juice into the fish tissues. This practice is legal; however, the use of phosphates has to be declared. The routine control testing of fish for the presence of polyphosphates, produced some results that were difficult to explain. One of the two analytical methods used determined low diphosphate concentrations in a number of untreated samples, while the other ion chromatography (IC) method did not detect them. This initiated a number of investigations: results showed that polyphosphates in fish and shrimps tissue undergo a rapid enzymatic degradation, producing the ubiquitous orthophosphate. This led to the conclusion that sensitive analytical methods are required in order to detect previous polyphosphate treatment of a sample. The polyphosphate concentrations detected by one of the analytical methods could not be explained by the degradation of endogenous high-energy nucleotides like ATP into diphosphate, but by a coeluting compound. Further investigations by LC-MS-MS proved that the substance responsible for the observed peak was inosine monophsosphate (IMP) and not as thought the inorganic diphosphate. The method producing the false-positive result was modified and both methods were ultimately able to detect polyphosphates well separated from natural nucleotides. Polyphosphates could no longer be detected (<0.5 mg kg-1) after modification of the analytical methodology. The relevance of these findings lies in the fact that similar analytical methods are employed in various control laboratories, which might lead to false interpretation of measurements.
Cross-validated detection of crack initiation in aerospace materials
NASA Astrophysics Data System (ADS)
Vanniamparambil, Prashanth A.; Cuadra, Jefferson; Guclu, Utku; Bartoli, Ivan; Kontsos, Antonios
2014-03-01
A cross-validated nondestructive evaluation approach was employed to in situ detect the onset of damage in an Aluminum alloy compact tension specimen. The approach consisted of the coordinated use primarily the acoustic emission, combined with the infrared thermography and digital image correlation methods. Both tensile loads were applied and the specimen was continuously monitored using the nondestructive approach. Crack initiation was witnessed visually and was confirmed by the characteristic load drop accompanying the ductile fracture process. The full field deformation map provided by the nondestructive approach validated the formation of a pronounced plasticity zone near the crack tip. At the time of crack initiation, a burst in the temperature field ahead of the crack tip as well as a sudden increase of the acoustic recordings were observed. Although such experiments have been attempted and reported before in the literature, the presented approach provides for the first time a cross-validated nondestructive dataset that can be used for quantitative analyses of the crack initiation information content. It further allows future development of automated procedures for real-time identification of damage precursors including the rarely explored crack incubation stage in fatigue conditions.
A new technique to expose the hypopharyngeal space: The modified Killian's method.
Sakai, Akihiro; Okami, Kenji; Sugimoto, Ryousuke; Ebisumoto, Koji; Yamamoto, Hikaru; Maki, Daisuke; Saito, Kosuke; Iida, Masahiro
2014-04-01
Recent remarkable progress in endoscopic technology has enabled the detection of superficial cancers that were undetectable in the past. However, even though advanced endoscopic technology can detect early lesions, it is useless unless it can provide wide exposure of an area. By modifying the Killian position, it is possible to observe a wider range of the hypopharyngeal space than is possible with conventional head positions. We report a revolutionary method that uses a new head position to widely open the hypopharynx. The technique is named "the Modified Killian's method." The patient is initially placed in the Killian position and then bent further forward from the original position (i.e., the modified Killian position). While in this position, the patient's head is turned and the Valsalva maneuver is applied. These additional maneuvers constitute the Modified Killian's method and widely expands the hypopharyngeal space. The conventional head position cannot open the hypopharyngeal space sufficiently; however, the Modified Killian's method opens the hypopharyngeal space very widely. The Modified Killian's method enables observation of the entire circumference of the hypopharyngeal space and the cervical esophageal entry. The Modified Killian's method may become an indispensable technique for observing the hypopharynx and detecting hypopharyngeal cancers. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Russ, Alissa L; Jahn, Michelle A; Patel, Himalaya; Porter, Brian W; Nguyen, Khoa A; Zillich, Alan J; Linsky, Amy; Simon, Steven R
2018-06-01
An electronic medication reconciliation tool was previously developed by another research team to aid provider-patient communication for medication reconciliation. To evaluate the usability of this tool, we integrated artificial safety probes into standard usability methods. The objective of this article is to describe this method of using safety probes, which enabled us to evaluate how well the tool supports users' detection of medication discrepancies. We completed a mixed-method usability evaluation in a simulated setting with 30 participants: 20 healthcare professionals (HCPs) and 10 patients. We used factual scenarios but embedded three artificial safety probes: (1) a missing medication (i.e., omission); (2) an extraneous medication (i.e., commission); and (3) an inaccurate dose (i.e., dose discrepancy). We measured users' detection of each probe to estimate the probability that a HCP or patient would detect these discrepancies. Additionally, we recorded participants' detection of naturally occurring discrepancies. Each safety probe was detected by ≤50% of HCPs. Patients' detection rates were generally higher. Estimates indicate that a HCP and patient, together, would detect 44.8% of these medication discrepancies. Additionally, HCPs and patients detected 25 and 45 naturally-occurring discrepancies, respectively. Overall, detection of medication discrepancies was low. Findings indicate that more advanced interface designs are warranted. Future research is needed on how technologies can be designed to better aid HCPs' and patients' detection of medication discrepancies. This is one of the first studies to evaluate the usability of a collaborative medication reconciliation tool and assess HCPs' and patients' detection of medication discrepancies. Results demonstrate that embedded safety probes can enhance standard usability methods by measuring additional, clinically-focused usability outcomes. The novel safety probes we used may serve as an initial, standard set for future medication reconciliation research. More prevalent use of safety probes could strengthen usability research for a variety of health information technologies. Published by Elsevier Inc.
Huang, Si-Qiang; Hu, Juan; Zhu, Guichi; Zhang, Chun-Yang
2015-03-15
Accurate identification of point mutation is particularly imperative in the field of biomedical research and clinical diagnosis. Here, we develop a sensitive and specific method for point mutation assay using exponential strand displacement amplification (SDA)-based surface enhanced Raman spectroscopy (SERS). In this method, a discriminating probe and a hairpin probe are designed to specifically recognize the sequence of human K-ras gene. In the presence of K-ras mutant target (C→T), the 3'-terminal of discriminating probe and the 5'-terminal of hairpin probe can be ligated to form a SDA template. Subsequently, the 3'-terminal of hairpin probe can function as a primer to initiate the SDA reaction, producing a large amount of triggers. The resultant triggers can further hybridize with the discriminating probes to initiate new rounds of SDA reaction, leading to an exponential amplification reaction. With the addition of capture probe-modified gold nanoparticles (AuNPs) and the Rox-labeled reporter probes, the amplified triggers can be assembled on the surface of AuNPs through the formation of sandwich hybrids of capture probe-trigger-reporter probe, generating a strong Raman signal. While in the presence of K-ras wild-type target (C), neither ligation nor SDA reaction can be initiated and no Raman signal is observed. The proposed method exhibits high sensitivity with a detection limit of 1.4pM and can accurately discriminate as low as 1% variant frequency from the mixture of mutant target and wild-type target. Importantly, this method can be further applied to analyze the mutant target in the spiked HEK293T cell lysate, holding great potential for genetic analysis and disease prognosis. Copyright © 2014 Elsevier B.V. All rights reserved.
Detection of Early Ischemic Changes in Noncontrast CT Head Improved with "Stroke Windows".
Mainali, Shraddha; Wahba, Mervat; Elijovich, Lucas
2014-01-01
Introduction. Noncontrast head CT (NCCT) is the standard radiologic test for patients presenting with acute stroke. Early ischemic changes (EIC) are often overlooked on initial NCCT. We determine the sensitivity and specificity of improved EIC detection by a standardized method of image evaluation (Stroke Windows). Methods. We performed a retrospective chart review to identify patients with acute ischemic stroke who had NCCT at presentation. EIC was defined by the presence of hyperdense MCA/basilar artery sign; sulcal effacement; basal ganglia/subcortical hypodensity; and loss of cortical gray-white differentiation. NCCT was reviewed with standard window settings and with specialized Stroke Windows. Results. Fifty patients (42% females, 58% males) with a mean NIHSS of 13.4 were identified. EIC was detected in 9 patients with standard windows, while EIC was detected using Stroke Windows in 35 patients (18% versus 70%; P < 0.0001). Hyperdense MCA sign was the most commonly reported EIC; it was better detected with Stroke Windows (14% and 36%; P < 0.0198). Detection of the remaining EIC also improved with Stroke Windows (6% and 46%; P < 0.0001). Conclusions. Detection of EIC has important implications in diagnosis and treatment of acute ischemic stroke. Utilization of Stroke Windows significantly improved detection of EIC.
Paglieroni, David W [Pleasanton, CA; Manay, Siddharth [Livermore, CA
2011-12-20
A stochastic method and system for detecting polygon structures in images, by detecting a set of best matching corners of predetermined acuteness .alpha. of a polygon model from a set of similarity scores based on GDM features of corners, and tracking polygon boundaries as particle tracks using a sequential Monte Carlo approach. The tracking involves initializing polygon boundary tracking by selecting pairs of corners from the set of best matching corners to define a first side of a corresponding polygon boundary; tracking all intermediate sides of the polygon boundaries using a particle filter, and terminating polygon boundary tracking by determining the last side of the tracked polygon boundaries to close the polygon boundaries. The particle tracks are then blended to determine polygon matches, which may be made available, such as to a user, for ranking and inspection.
Hoskinson, Reed L [Rigby, ID; Svoboda, John M [Idaho Falls, ID; Bauer, William F [Idaho Falls, ID; Elias, Gracy [Idaho Falls, ID
2008-05-06
A method and apparatus is provided for monitoring a flow path having plurality of different solid components flowing therethrough. For example, in the harvesting of a plant material, many factors surrounding the threshing, separating or cleaning of the plant material and may lead to the inadvertent inclusion of the component being selectively harvested with residual plant materials being discharged or otherwise processed. In accordance with the present invention the detection of the selectively harvested component within residual materials may include the monitoring of a flow path of such residual materials by, for example, directing an excitation signal toward of flow path of material and then detecting a signal initiated by the presence of the selectively harvested component responsive to the excitation signal. The detected signal may be used to determine the presence or absence of a selected plant component within the flow path of residual materials.
An iterative method for airway segmentation using multiscale leakage detection
NASA Astrophysics Data System (ADS)
Nadeem, Syed Ahmed; Jin, Dakai; Hoffman, Eric A.; Saha, Punam K.
2017-02-01
There are growing applications of quantitative computed tomography for assessment of pulmonary diseases by characterizing lung parenchyma as well as the bronchial tree. Many large multi-center studies incorporating lung imaging as a study component are interested in phenotypes relating airway branching patterns, wall-thickness, and other morphological measures. To our knowledge, there are no fully automated airway tree segmentation methods, free of the need for user review. Even when there are failures in a small fraction of segmentation results, the airway tree masks must be manually reviewed for all results which is laborious considering that several thousands of image data sets are evaluated in large studies. In this paper, we present a CT-based novel airway tree segmentation algorithm using iterative multi-scale leakage detection, freezing, and active seed detection. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses simple intensity based connectivity and a new leakage detection algorithm to iteratively grow an airway tree starting from an initial seed inside the trachea. It begins with a conservative threshold and then, iteratively shifts toward generous values. The method was applied on chest CT scans of ten non-smoking subjects at total lung capacity and ten at functional residual capacity. Airway segmentation results were compared to an expert's manually edited segmentations. Branch level accuracy of the new segmentation method was examined along five standardized segmental airway paths (RB1, RB4, RB10, LB1, LB10) and two generations beyond these branches. The method successfully detected all branches up to two generations beyond these segmental bronchi with no visual leakages.
Multi-Objective Community Detection Based on Memetic Algorithm
2015-01-01
Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646
Multi-objective community detection based on memetic algorithm.
Wu, Peng; Pan, Li
2015-01-01
Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.
Elbert, Yevgeniy; Burkom, Howard S
2009-11-20
This paper discusses further advances in making robust predictions with the Holt-Winters forecasts for a variety of syndromic time series behaviors and introduces a control-chart detection approach based on these forecasts. Using three collections of time series data, we compare biosurveillance alerting methods with quantified measures of forecast agreement, signal sensitivity, and time-to-detect. The study presents practical rules for initialization and parameterization of biosurveillance time series. Several outbreak scenarios are used for detection comparison. We derive an alerting algorithm from forecasts using Holt-Winters-generalized smoothing for prospective application to daily syndromic time series. The derived algorithm is compared with simple control-chart adaptations and to more computationally intensive regression modeling methods. The comparisons are conducted on background data from both authentic and simulated data streams. Both types of background data include time series that vary widely by both mean value and cyclic or seasonal behavior. Plausible, simulated signals are added to the background data for detection performance testing at signal strengths calculated to be neither too easy nor too hard to separate the compared methods. Results show that both the sensitivity and the timeliness of the Holt-Winters-based algorithm proved to be comparable or superior to that of the more traditional prediction methods used for syndromic surveillance.
A surface plasmon resonance based biochip for the detection of patulin toxin
NASA Astrophysics Data System (ADS)
Pennacchio, Anna; Ruggiero, Giuseppe; Staiano, Maria; Piccialli, Gennaro; Oliviero, Giorgia; Lewkowicz, Aneta; Synak, Anna; Bojarski, Piotr; D'Auria, Sabato
2014-08-01
Patulin is a toxic secondary metabolite of a number of fungal species belonging to the genera Penicillium and Aspergillus. One important aspect of the patulin toxicity in vivo is an injury of the gastrointestinal tract including ulceration and inflammation of the stomach and intestine. Recently, patulin has been shown to be genotoxic by causing oxidative damage to the DNA, and oxidative DNA base modifications have been considered to play a role in mutagenesis and cancer initiation. Conventional analytical methods for patulin detection involve chromatographic analyses, such as HPLC, GC, and, more recently, techniques such as LC/MS and GC/MS. All of these methods require the use of extensive protocols and the use of expensive analytical instrumentation. In this work, the conjugation of a new derivative of patulin to the bovine serum albumin for the production of polyclonal antibodies is described, and an innovative competitive immune-assay for detection of patulin is presented. Experimentally, an important part of the detection method is based on the optical technique called surface plasmon resonance (SPR). Laser beam induced interactions between probe and target molecules in the vicinity of gold surface of the biochip lead to the shift in resonance conditions and consequently to slight but easily detectable change of reflectivity.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thanjavur, Karun; Willis, Jon; Crampton, David, E-mail: karun@uvic.c
2009-11-20
We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg{sup 2} images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulationsmore » show that the false detection rate for these data, at our selected threshold, is only approx1%, and that the cluster catalogs are approx80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z approx 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg{sup 2} are detected, with 1-2 Fornax-like or richer clusters every 2 deg{sup 2}. Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses-one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.« less
NASA Astrophysics Data System (ADS)
An, L.; Zhang, J.; Gong, L.
2018-04-01
Playing an important role in gathering information of social infrastructure damage, Synthetic Aperture Radar (SAR) remote sensing is a useful tool for monitoring earthquake disasters. With the wide application of this technique, a standard method, comparing post-seismic to pre-seismic data, become common. However, multi-temporal SAR processes, are not always achievable. To develop a post-seismic data only method for building damage detection, is of great importance. In this paper, the authors are now initiating experimental investigation to establish an object-based feature analysing classification method for building damage recognition.
Three-dimensional images contribute to the diagnosis of mucous retention cyst in maxillary sinus
Donizeth-Rodrigues, Cleomar; Fonseca-Da Silveira, Márcia; Gonçalves-De Alencar, Ana H.; Garcia-Santos-Silva, Maria A.; Francisco-De-Mendonça, Elismauro
2013-01-01
Objective: To evaluate the detection of mucous retention cyst of maxillary sinus (MRCMS) using panoramic radiography and cone beam computed tomography (CBCT). Study Design: A digital database with 6,000 panoramic radiographs was reviewed for MRCMS. Suggestive images of MRCMS were detected on 185 radiographs, and patients were located and invited to return for follow-up. Thirty patients returned, and control panoramic radiographs were obtained 6 to 46 months after the initial radiograph. When MRCMS was found on control radiographs, CBCT scans were obtained. Cysts were measured and compared on radiographs and scans. The Wilcoxon, Spearman and Kolmorogov-Smirnov tests were used for statistical analysis. The level of significance was set at 5%. Results: There were statistically significant differences between the two methods (p<0.05): 23 MRCMS detected on panoramic radiographs were confirmed by CBCT, but 5 MRCMS detected on CBCT images had not been identified by panoramic radiography. Eight MRCMS detected on control radiographs were not confirmed by CBCT. MRCMS size differences from initial to control panoramic radiographs and CBCT scans were not statistically significant (p= 0.617 and p= 0.626). The correlation between time and MRCMS size differences was not significant (r = -0.16, p = 0.381). Conclusion: CBCT scanning detect MRCMS more accurately than panoramic radiography. Key words:Mucous cyst, maxillary sinus, panoramic radiograph, cone beam computed tomography. PMID:23229251
Mambetsariev, Isa; Vora, Lalit; Yu, Kim Wai; Salgia, Ravi
2018-03-21
We report the successful treatment of the patient with osimertinib 80 mg/day following disease progression and a discordance in the detection of a mechanism of resistance epithelial growth factor receptor (EGFR) T790 M between liquid biopsy and tissue biopsy methods. A 57-year-old Hispanic male patient initially diagnosed with an EGFR 19 deletion positive lung adenocarcinoma and clinically responded to initial erlotinib treatment. The patient subsequently progressed on erlotinib 150 mg/day and repeat biopsies both tissue and liquid were sent for next-generation sequencing (NGS). A T790 M EGFR mutation was detected in the blood sample using a liquid biopsy technique, but the tissue biopsy failed to show a T790 M mutation in a newly biopsied tissue sample. He was then successfully treated with osimertinib 80 mg/day, has clinically and radiologically responded, and remains on osimertinib treatment after 10 months. Second-line osimertinib treatment, when administered at 80 mg/day, is both well tolerated and efficacious in a patient with previously erlotinib treated lung adenocarcinoma and a T790 M mutation detected by liquid biopsy.
NASA Astrophysics Data System (ADS)
Nohtomi, Akihiro; Wakabayashi, Genichiro
2015-11-01
We evaluated the accuracy of a self-activation method with iodine-containing scintillators in quantifying 128I generation in an activation detector; the self-activation method was recently proposed for photo-neutron on-line measurements around X-ray radiotherapy machines. Here, we consider the accuracy of determining the initial count rate R0, observed just after termination of neutron irradiation of the activation detector. The value R0 is directly related to the amount of activity generated by incident neutrons; the detection efficiency of radiation emitted from the activity should be taken into account for such an evaluation. Decay curves of 128I activity were numerically simulated by a computer program for various conditions including different initial count rates (R0) and background rates (RB), as well as counting statistical fluctuations. The data points sampled at minute intervals and integrated over the same period were fit by a non-linear least-squares fitting routine to obtain the value R0 as a fitting parameter with an associated uncertainty. The corresponding background rate RB was simultaneously calculated in the same fitting routine. Identical data sets were also evaluated by a well-known integration algorithm used for conventional activation methods and the results were compared with those of the proposed fitting method. When we fixed RB = 500 cpm, the relative uncertainty σR0 /R0 ≤ 0.02 was achieved for R0/RB ≥ 20 with 20 data points from 1 min to 20 min following the termination of neutron irradiation used in the fitting; σR0 /R0 ≤ 0.01 was achieved for R0/RB ≥ 50 with the same data points. Reasonable relative uncertainties to evaluate initial count rates were reached by the decay-fitting method using practically realistic sampling numbers. These results clarified the theoretical limits of the fitting method. The integration method was found to be potentially vulnerable to short-term variations in background levels, especially instantaneous contaminations by spike-like noise. The fitting method easily detects and removes such spike-like noise.
Early detection of materials degradation
NASA Astrophysics Data System (ADS)
Meyendorf, Norbert
2017-02-01
Lightweight components for transportation and aerospace applications are designed for an estimated lifecycle, taking expected mechanical and environmental loads into account. The main reason for catastrophic failure of components within the expected lifecycle are material inhomogeneities, like pores and inclusions as origin for fatigue cracks, that have not been detected by NDE. However, material degradation by designed or unexpected loading conditions or environmental impacts can accelerate the crack initiation or growth. Conventional NDE methods are usually able to detect cracks that are formed at the end of the degradation process, but methods for early detection of fatigue, creep, and corrosion are still a matter of research. For conventional materials ultrasonic, electromagnetic, or thermographic methods have been demonstrated as promising. Other approaches are focused to surface damage by using optical methods or characterization of the residual surface stresses that can significantly affect the creation of fatigue cracks. For conventional metallic materials, material models for nucleation and propagation of damage have been successfully applied for several years. Material microstructure/property relations are well established and the effect of loading conditions on the component life can be simulated. For advanced materials, for example carbon matrix composites or ceramic matrix composites, the processes of nucleation and propagation of damage is still not fully understood. For these materials NDE methods can not only be used for the periodic inspections, but can significantly contribute to the material scientific knowledge to understand and model the behavior of composite materials.
Development of a novel constellation based landmark detection algorithm
NASA Astrophysics Data System (ADS)
Ghayoor, Ali; Vaidya, Jatin G.; Johnson, Hans J.
2013-03-01
Anatomical landmarks such as the anterior commissure (AC) and posterior commissure (PC) are commonly used by researchers for co-registration of images. In this paper, we present a novel, automated approach for landmark detection that combines morphometric constraining and statistical shape models to provide accurate estimation of landmark points. This method is made robust to large rotations in initial head orientation by extracting extra information of the eye centers using a radial Hough transform and exploiting the centroid of head mass (CM) using a novel estimation approach. To evaluate the effectiveness of this method, the algorithm is trained on a set of 20 images with manually selected landmarks, and a test dataset is used to compare the automatically detected against the manually detected landmark locations of the AC, PC, midbrain-pons junction (MPJ), and fourth ventricle notch (VN4). The results show that the proposed method is accurate as the average error between the automatically and manually labeled landmark points is less than 1 mm. Also, the algorithm is highly robust as it was successfully run on a large dataset that included different kinds of images with various orientation, spacing, and origin.
Lv, Yun; Yang, Lili; Mao, Xiaoxia; Lu, Mengjia; Zhao, Jing; Yin, Yongmei
2016-11-15
Glutathione (GSH) plays an important role in numerous cellular functions, and the abnormal GSH expression is closely related with many dangerous human diseases. In this work, we have proposed a simple but sensitive electrochemical method for quantitative detection of GSH based on an Hg(2+)-mediated strand displacement reaction. Owing to the specific binding of Hg(2+) with T-T mismatches, helper DNA can bind to 3' terminal of probe DNA 1 and initiate the displacement of probe DNA 2 immobilized on an electrode surface. However, Hg(2+)-mediated strand displacement reaction can be inhibited by the chelation of GSH with Hg(2+), thereby leading to an obvious electrochemical response obtained from methylene blue that is modified onto the probe DNA. Our method can sensitively detect GSH in a wide linear range from 0.5nM to 5μM with a low detection limit of 0.14nM, which can also easily distinguish target molecules in complex serum samples and even cell extractions. Therefore, this method may have great potential to monitor GSH in the physiological and pathological condition in the future. Copyright © 2016 Elsevier B.V. All rights reserved.
Won, Helen; Yang, Samuel; Gaydos, Charlotte; Hardick, Justin; Ramachandran, Padmini; Hsieh, Yu-Hsiang; Kecojevic, Alexander; Njanpop-Lafourcade, Berthe-Marie; Mueller, Judith E; Tameklo, Tsidi Agbeko; Badziklou, Kossi; Gessner, Bradford D; Rothman, Richard E
2012-09-01
This study aimed to conduct a pilot evaluation of broad-based multiprobe polymerase chain reaction (PCR) in clinical cerebrospinal fluid (CSF) samples compared to local conventional PCR/culture methods used for bacterial meningitis surveillance. A previously described PCR consisting of initial broad-based detection of Eubacteriales by a universal probe, followed by Gram typing, and pathogen-specific probes was designed targeting variable regions of the 16S rRNA gene. The diagnostic performance of the 16S rRNA assay in "127 CSF samples was evaluated in samples from patients from Togo, Africa, by comparison to conventional PCR/culture methods. Our probes detected Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae. Uniprobe sensitivity and specificity versus conventional PCR were 100% and 54.6%, respectively. Sensitivity and specificity of uniprobe versus culture methods were 96.5% and 52.5%, respectively. Gram-typing probes correctly typed 98.8% (82/83) and pathogen-specific probes identified 96.4% (80/83) of the positives. This broad-based PCR algorithm successfully detected and provided species level information for multiple bacterial meningitis agents in clinical samples. Copyright © 2012 Elsevier Inc. All rights reserved.
Won, Helen; Yang, Samuel; Gaydos, Charlotte; Hardick, Justin; Ramachandran, Padmini; Hsieh, Yu-Hsiang; Kecojevic, Alexander; Njanpop-Lafourcade, Berthe-Marie; Mueller, Judith E.; Tameklo, Tsidi Agbeko; Badziklou, Kossi; Gessner, Bradford D.; Rothman, Richard E.
2012-01-01
This study aimed to conduct a pilot evaluation of broad-based multiprobe polymerase chain reaction (PCR) in clinical cerebrospinal fluid (CSF) samples compared to local conventional PCR/culture methods used for bacterial meningitis surveillance. A previously described PCR consisting of initial broad-based detection of Eubacteriales by a universal probe, followed by Gram typing, and pathogen-specific probes was designed targeting variable regions of the 16S rRNA gene. The diagnostic performance of the 16S rRNA assay in “”127 CSF samples was evaluated in samples from patients from Togo, Africa, by comparison to conventional PCR/culture methods. Our probes detected Neisseria meningitidis, Streptococcus pneumoniae, and Haemophilus influenzae. Uniprobe sensitivity and specificity versus conventional PCR were 100% and 54.6%, respectively. Sensitivity and specificity of uniprobe versus culture methods were 96.5% and 52.5%, respectively. Gram-typing probes correctly typed 98.8% (82/83) and pathogen-specific probes identified 96.4% (80/83) of the positives. This broad-based PCR algorithm successfully detected and provided species level information for multiple bacterial meningitis agents in clinical samples. PMID:22809694
Herrera, Melina E; Mobilia, Liliana N; Posse, Graciela R
2011-01-01
The objective of this study is to perform a comparative evaluation of the prediffusion and minimum inhibitory concentration (MIC) methods for the detection of sensitivity to colistin, and to detect Acinetobacter baumanii-calcoaceticus complex (ABC) heteroresistant isolates to colistin. We studied 75 isolates of ABC recovered from clinically significant samples obtained from various centers. Sensitivity to colistin was determined by prediffusion as well as by MIC. All the isolates were sensitive to colistin, with MIC = 2µg/ml. The results were analyzed by dispersion graph and linear regression analysis, revealing that the prediffusion method did not correlate with the MIC values for isolates sensitive to colistin (r² = 0.2017). Detection of heteroresistance to colistin was determined by plaque efficiency of all the isolates with the same initial MICs of 2, 1, and 0.5 µg/ml, which resulted in 14 of them with a greater than 8-fold increase in the MIC in some cases. When the sensitivity of these resistant colonies was determined by prediffusion, the resulting dispersion graph and linear regression analysis yielded an r² = 0.604, which revealed a correlation between the methodologies used.
Petrini, Stefano; Pierini, Ilaria; Giammarioli, Monica; Feliziani, Francesco; De Mia, Gian Mario
2017-03-01
We evaluated the use of oral fluid as an alternative to serum samples for Classical swine fever virus (CSFV) detection. Individual oral fluid and serum samples were collected at different times post-infection from pigs that were experimentally inoculated with CSFV Alfort 187 strain. We found no evidence of CSFV neutralizing antibodies in swine oral fluid samples under our experimental conditions. In contrast, real-time reverse transcription-polymerase chain reaction could detect CSFV nucleic acid from the oral fluid as early as 8 d postinfection, which also coincided with the time of initial detection in blood samples. The probability of CSFV detection in oral fluid was identical or even higher than in the corresponding blood sample. Our results support the feasibility of using this sampling method for CSFV genome detection, which may represent an additional cost-effective tool for CSF control.
Measurement of aerosol optical properties by cw cavity enhanced spectroscopy
NASA Astrophysics Data System (ADS)
Jie, Guo; Ye, Shan-Shan; Yang, Xiao; Han, Ye-Xing; Tang, Huai-Wu; Yu, Zhi-Wei
2016-10-01
The CAPS (Cavity Attenuated Phase shift Spectroscopy) system, which detects the extinction coefficients within a 10 nm bandpass centered at 532 nm, comprises a green LED with center wavelength in 532nm, a resonant optical cavity (36 cm length), a Photo Multiplier Tube detector, and a lock in amplifier. The square wave modulated light from the LED passes through the optical cavity and is detected as a distorted waveform which is characterized by a phase shift with respect to the initial modulation. Extinction coefficients are determined from changes in the phase shift of the distorted waveform of the square wave modulated LED light that is transmitted through the optical cavity. The performance of the CAPS system was evaluated by using measurements of the stability and response of the system. The minima ( 0.1 Mm-1) in the Allan plots show the optimum average time ( 100s) for optimum detection performance of the CAPS system. In the paper, it illustrates that extinction coefficient was correlated with PM2.5 mass (0.91). These figures indicate that this method has the potential to become one of the most sensitive on-line analytical techniques for extinction coefficient detection. This work aims to provide an initial validation of the CAPS extinction monitor in laboratory and field environments. Our initial results presented in this paper show that the CAPS extinction monitor is capable of providing state-of-the-art performance while dramatically reducing the complexity of optical instrumentation for directly measuring the extinction coefficients.
Hepatitis B virus replication is upregulated in proliferated peripheral blood lymphocytes.
Yan, Qin; Lan, Ying-Hua; Huang, Yan-Xin; Fan, Rong-Shan; Liu, Lan; Song, Shu-Peng; Li, Yong-Guo
2016-04-01
Increasing evidence indicates that the hepatitis B virus (HBV) replicates in peripheral blood mononuclear cells (PBMCs), but at a low level. The present study aimed to establish a reliable and sensitive method that effectively detects HBV viral products for monitoring antiviral therapy, organ transplantation screening, and diagnosing occult HBV infection. In the present study, PBMCs (obtained from six healthy volunteers) were inoculated with HBV, and cultured with phytohemagglutinin (PHA) and interleukin‑2 (IL‑2) to stimulate cell proliferation. PBMCs were harvested, and quantitative detection of HBV DNA in cell suspension and intracellular hepatitis B surface antigen (HBsAg) was conducted on days 0, 1, 6 and 12, respectively. In situ hybridization, immunohistochemistry and reverse transcription‑polymerase chain reaction (RT‑PCR) were performed to analyze the HBV infection. The results demonstrated that HBV DNA increased concurrently with proliferation of PBMCs isolated from three of six healthy volunteers, and the mean number of PBMCs on day 12 was 13.61 times higher than the initially seeded cell number (P<0.01). The mean copies of HBV DNA at day 12 were 2.98 times higher compared with initial levels (P<0.05). Furthermore, intracellular HBsAg levels increased concurrently with proliferation of PBMCs in one group of cultured PBMCs, which was accompanied by increased HBV DNA levels. In addition, HBV nucleic acids were detected in PBMCs using in situ hybridization. Intracellular HBsAg was observed in PBMCs and HBV RNA was also detected by RT‑PCR. The present study demonstrated that HBV replicates in proliferating PBMCs, which were induced by PHA and IL‑2. This method offers a novel investigative tool to detect HBV infection in PBMCs and to monitor the course of HBV infection.
Individual Tree Crown Delineation Using Multi-Wavelength Titan LIDAR Data
NASA Astrophysics Data System (ADS)
Naveed, F.; Hu, B.
2017-10-01
The inability to detect the Emerald Ash Borer (EAB) at an early stage has led to the enumerable loss of different species of ash trees. Due to the increasing risk being posed by the EAB, a robust and accurate method is needed for identifying Individual Tree Crowns (ITCs) that are at a risk of being infected or are already diseased. This paper attempts to outline an ITC delineation method that employs airborne multi-spectral Light Detection and Ranging (LiDAR) to accurately delineate tree crowns. The raw LiDAR data were initially pre-processed to generate the Digital Surface Models (DSM) and Digital Elevation Models (DEM) using an iterative progressive TIN (Triangulated Irregular Network) densification method. The DSM and DEM were consequently used for Canopy Height Model (CHM) generation, from which the structural information pertaining to the size and shape of the tree crowns was obtained. The structural information along with the spectral information was used to segment ITCs using a region growing algorithm. The availability of the multi-spectral LiDAR data allows for delineation of crowns that have otherwise homogenous structural characteristics and hence cannot be isolated from the CHM alone. This study exploits the spectral data to derive initial approximations of individual tree tops and consequently grow those regions based on the spectral constraints of the individual trees.
Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency.
Zhang, Ying-Ying; Yang, Cai; Zhang, Ping
2017-05-01
In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.
System and method for quench protection of a superconductor
Huang, Xianrui; Sivasubramaniam, Kiruba Haran; Bray, James William; Ryan, David Thomas
2008-03-11
A system and method for protecting a superconductor from a quench condition. A quench protection system is provided to protect the superconductor from damage due to a quench condition. The quench protection system comprises a voltage detector operable to detect voltage across the superconductor. The system also comprises a frequency filter coupled to the voltage detector. The frequency filter is operable to couple voltage signals to a control circuit that are representative of a rise in superconductor voltage caused by a quench condition and to block voltage signals that are not. The system is operable to detect whether a quench condition exists in the superconductor based on the voltage signal received via the frequency filter and to initiate a protective action in response.
Improved flaw detection and characterization with difference thermography
NASA Astrophysics Data System (ADS)
Winfree, William P.; Zalameda, Joseph N.; Howell, Patricia A.
2011-05-01
Flaw detection and characterization with thermographic techniques in graphite polymer composites is often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, variations in fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These variations result in a noise floor that increases the difficulty of detecting and characterizing deeper flaws. The paper investigates comparing thermographic responses taken before and after a change in state in a composite to improve the detection of subsurface flaws. A method is presented for registration of the responses before finding the difference. A significant improvement in the detectability is achieved by comparing the differences in response. Examples of changes in state due to application of a load and impact are presented.
Improved Flaw Detection and Characterization with Difference Thermography
NASA Technical Reports Server (NTRS)
Winfree, William P.; Zalameda, Joseph N.; Howell, Patricia A.
2011-01-01
Flaw detection and characterization with thermographic techniques in graphite polymer composites is often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, variations in fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These variations result in a noise floor that increases the difficulty of detecting and characterizing deeper flaws. The paper investigates comparing thermographic responses taken before and after a change in state in a composite to improve the detection of subsurface flaws. A method is presented for registration of the responses before finding the difference. A significant improvement in the detectability is achieved by comparing the differences in response. Examples of changes in state due to application of a load and impact are presented.
Wang, Wei; Zhou, Fang; Zhao, Liang; Zhang, Jian-Rong; Zhu, Jun-Jie
2008-02-01
A simple method of hydrostatic pressure sample injection towards a disposable microchip CE device was developed. The liquid level in the sample reservoir was higher than that in the sample waste reservoir (SWR) by tilting microchip and hydrostatic pressure was generated, the sample was driven to pass through injection channel into SWR. After sample loading, the microchip was levelled for separation under applied high separation voltage. Effects of tilted angle, initial liquid height and injection duration on electrophoresis were investigated. With enough injection duration, the injection result was little affected by tilted angle and initial liquid heights in the reservoirs. Injection duration for obtaining a stable sample plug was mainly dependent on the tilted angle rather than the initial height of liquid. Experimental results were consistent with theoretical prediction. Fluorescence observation and electrochemical detection of dopamine and catechol were employed to verify the feasibility of tilted microchip hydrostatic pressure injection. Good reproducibility of this injection method was obtained. Because the instrumentation was simplified and no additional hardware was needed in this technology, the proposed method would be potentially useful in disposable devices.
Khan, Arifa S; Vacante, Dominick A; Cassart, Jean-Pol; Ng, Siemon H S; Lambert, Christophe; Charlebois, Robert L; King, Kathryn E
Several nucleic-acid based technologies have recently emerged with capabilities for broad virus detection. One of these, high throughput sequencing, has the potential for novel virus detection because this method does not depend upon prior viral sequence knowledge. However, the use of high throughput sequencing for testing biologicals poses greater challenges as compared to other newly introduced tests due to its technical complexities and big data bioinformatics. Thus, the Advanced Virus Detection Technologies Users Group was formed as a joint effort by regulatory and industry scientists to facilitate discussions and provide a forum for sharing data and experiences using advanced new virus detection technologies, with a focus on high throughput sequencing technologies. The group was initiated as a task force that was coordinated by the Parenteral Drug Association and subsequently became the Advanced Virus Detection Technologies Interest Group to continue efforts for using new technologies for detection of adventitious viruses with broader participation, including international government agencies, academia, and technology service providers. © PDA, Inc. 2016.
Interdisciplinary Program for Quantitative Flaw Definition.
1978-01-01
Ceramics .................... 284 UNIT C, TASK 4 - Microfocus X-Ray and Image Enhance- ment of Radiographic Data ....................... 292 UNIT C, TASK 5...Conventional Ultrasonic Inspection Methods Applied to Ceramics ..................... 294 iii 7! SC595.32SA OVERVIEW PROJECT I - QUANTITATIVE...parameters. Unit C was initiated in October of 1977 following encouraging nondestructive defect detectability studies in structural ceramics , using
USDA-ARS?s Scientific Manuscript database
Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. We previously detected genetic variation for BCWD resistance in our rainbow trout population, and a family-based selection program to improve resistance was initiated at the National Center for Cool and Col...
USDA-ARS?s Scientific Manuscript database
Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. We previously detected genetic variation for BCWD resistance in our rainbow trout population, and a family-based selection program to improve resistance was initiated at the NCCCWA in 2005. The main objec...
Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng
2017-01-01
Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902
Faigen, Zachary; Deyneka, Lana; Ising, Amy; Neill, Daniel; Conway, Mike; Fairchild, Geoffrey; Gunn, Julia; Swenson, David; Painter, Ian; Johnson, Lauren; Kiley, Chris; Streichert, Laura
2015-01-01
Introduction: We document a funded effort to bridge the gap between constrained scientific challenges of public health surveillance and methodologies from academia and industry. Component tasks are the collection of epidemiologists’ use case problems, multidisciplinary consultancies to refine them, and dissemination of problem requirements and shareable datasets. We describe an initial use case and consultancy as a concrete example and challenge to developers. Materials and Methods: Supported by the Defense Threat Reduction Agency Biosurveillance Ecosystem project, the International Society for Disease Surveillance formed an advisory group to select tractable use case problems and convene inter-disciplinary consultancies to translate analytic needs into well-defined problems and to promote development of applicable solution methods. The initial consultancy’s focus was a problem originated by the North Carolina Department of Health and its NC DETECT surveillance system: Derive a method for detection of patient record clusters worthy of follow-up based on free-text chief complaints and without syndromic classification. Results: Direct communication between public health problem owners and analytic developers was informative to both groups and constructive for the solution development process. The consultancy achieved refinement of the asyndromic detection challenge and of solution requirements. Participants summarized and evaluated solution approaches and discussed dissemination and collaboration strategies. Practice Implications: A solution meeting the specification of the use case described above could improve human monitoring efficiency with expedited warning of events requiring follow-up, including otherwise overlooked events with no syndromic indicators. This approach can remove obstacles to collaboration with efficient, minimal data-sharing and without costly overhead. PMID:26834939
Wijesinghe, Ruchire Eranga; Lee, Seung-Yeol; Kim, Pilun; Jung, Hee-Young; Jeon, Mansik; Kim, Jeehyun
2016-08-12
The feasibility of using the bio-photonic imaging technique to assess symptoms of circular leaf spot (CLS) disease in Diospyros kaki (persimmon) leaf samples was investigated. Leaf samples were selected from persimmon plantations and were categorized into three groups: healthy leaf samples, infected leaf samples, and healthy-looking leaf samples from infected trees. Visually non-identifiable reduction of the palisade parenchyma cell layer thickness is the main initial symptom, which occurs at the initial stage of the disease. Therefore, we established a non-destructive bio-photonic inspection method using a 1310 nm swept source optical coherence tomography (SS-OCT) system. These results confirm that this method is able to identify morphological differences between healthy leaves from infected trees and leaves from healthy and infected trees. In addition, this method has the potential to generate significant cost savings and good control of CLS disease in persimmon fields.
Wijesinghe, Ruchire Eranga; Lee, Seung-Yeol; Kim, Pilun; Jung, Hee-Young; Jeon, Mansik; Kim, Jeehyun
2016-01-01
The feasibility of using the bio-photonic imaging technique to assess symptoms of circular leaf spot (CLS) disease in Diospyros kaki (persimmon) leaf samples was investigated. Leaf samples were selected from persimmon plantations and were categorized into three groups: healthy leaf samples, infected leaf samples, and healthy-looking leaf samples from infected trees. Visually non-identifiable reduction of the palisade parenchyma cell layer thickness is the main initial symptom, which occurs at the initial stage of the disease. Therefore, we established a non-destructive bio-photonic inspection method using a 1310 nm swept source optical coherence tomography (SS-OCT) system. These results confirm that this method is able to identify morphological differences between healthy leaves from infected trees and leaves from healthy and infected trees. In addition, this method has the potential to generate significant cost savings and good control of CLS disease in persimmon fields. PMID:27529250
NASA Astrophysics Data System (ADS)
Xu, Jiayuan; Yu, Chengtao; Bo, Bin; Xue, Yu; Xu, Changfu; Chaminda, P. R. Dushantha; Hu, Chengbo; Peng, Kai
2018-03-01
The automatic recognition of the high voltage isolation switch by remote video monitoring is an effective means to ensure the safety of the personnel and the equipment. The existing methods mainly include two ways: improving monitoring accuracy and adopting target detection technology through equipment transformation. Such a method is often applied to specific scenarios, with limited application scope and high cost. To solve this problem, a high voltage isolation switch state recognition method based on background difference and iterative search is proposed in this paper. The initial position of the switch is detected in real time through the background difference method. When the switch starts to open and close, the target tracking algorithm is used to track the motion trajectory of the switch. The opening and closing state of the switch is determined according to the angle variation of the switch tracking point and the center line. The effectiveness of the method is verified by experiments on different switched video frames of switching states. Compared with the traditional methods, this method is more robust and effective.
NASA Astrophysics Data System (ADS)
Matheus, B. R. N.; Centurion, B. S.; Rubira-Bullen, I. R. F.; Schiabel, H.
2017-03-01
Cone Beam Computed Tomography (CBCT), a kind of face and neck exams can be opportunity to identify, as an incidental finding, calcifications of the carotid artery (CACA). Given the similarity of the CACA with calcification found in several x-ray exams, this work suggests that a similar technique designed to detect breast calcifications in mammography images could be applied to detect such calcifications in CBCT. The method used a 3D version of the calcification detection technique [1], based on a signal enhancement using a convolution with a 3D Laplacian of Gaussian (LoG) function followed by removing the high contrast bone structure from the image. Initial promising results show a 71% sensitivity with 0.48 false positive per exam.
Online monitoring of oil film using electrical capacitance tomography and level set method.
Xue, Q; Sun, B Y; Cui, Z Q; Ma, M; Wang, H X
2015-08-01
In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.
Online monitoring of oil film using electrical capacitance tomography and level set method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xue, Q., E-mail: xueqian@tju.edu.cn; Ma, M.; Sun, B. Y.
2015-08-15
In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for onlinemore » monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.« less
NASA Astrophysics Data System (ADS)
Karlita, Tita; Yuniarno, Eko Mulyanto; Purnama, I. Ketut Eddy; Purnomo, Mauridhi Hery
2017-06-01
Analyzing ultrasound (US) images to get the shapes and structures of particular anatomical regions is an interesting field of study since US imaging is a non-invasive method to capture internal structures of a human body. However, bone segmentation of US images is still challenging because it is strongly influenced by speckle noises and it has poor image quality. This paper proposes a combination of local phase symmetry and quadratic polynomial fitting methods to extract bone outer contour (BOC) from two dimensional (2D) B-modes US image as initial steps of three-dimensional (3D) bone surface reconstruction. By using local phase symmetry, the bone is initially extracted from US images. BOC is then extracted by scanning one pixel on the bone boundary in each column of the US images using first phase features searching method. Quadratic polynomial fitting is utilized to refine and estimate the pixel location that fails to be detected during the extraction process. Hole filling method is then applied by utilize the polynomial coefficients to fill the gaps with new pixel. The proposed method is able to estimate the new pixel position and ensures smoothness and continuity of the contour path. Evaluations are done using cow and goat bones by comparing the resulted BOCs with the contours produced by manual segmentation and contours produced by canny edge detection. The evaluation shows that our proposed methods produces an excellent result with average MSE before and after hole filling at the value of 0.65.
Gaudin, Valérie; Hedou, Celine; Soumet, Christophe; Verdon, Eric
2016-01-01
The Evidence Investigator™ system (Randox, UK) is a biochip and semi-automated system. The microarray kit II (AM II) is capable of detecting several compounds belonging to different families of antibiotics: quinolones, ceftiofur, thiamphenicol, streptomycin, tylosin and tetracyclines. The performance of this innovative system was evaluated for the detection of antibiotic residues in new matrices, in muscle of different animal species and in aquaculture products. The method was validated according to the European Decision No. EC/2002/657 and the European guideline for the validation of screening methods, which represents a complete initial validation. The false-positive rate was equal to 0% in muscle and in aquaculture products. The detection capabilities CCβ for 12 validated antibiotics (enrofloxacin, difloxacin, ceftiofur, desfuroyl ceftiofur cysteine disulfide, thiamphenicol, florfenicol, tylosin, tilmicosin, streptomycin, dihydrostreptomycin, tetracycline, doxycycline) were all lower than the respective maximum residue limits (MRLs) in muscle from different animal origins (bovine, ovine, porcine, poultry). No cross-reactions were observed with other antibiotics, neither with the six detected families nor with other families of antibiotics. The AM II kit could be applied to aquaculture products but with higher detection capabilities from those in muscle. The detection capabilities CCβ in aquaculture products were respectively at 0.25, 0.10 and 0.5 of the respective MRL in aquaculture products for enrofloxacin, tylosin and oxytetracycline. The performance of the AM II kit has been compared with other screening methods and with the performance characteristics previously determined in honey.
1991-04-23
in this section. In our investigation of higher order processing methods for remote acoustic sensing we sought to understand the principles of laser...magnitude less than those presently detected in laboratory measurements. An initial study of several potential higher order processing techniques was...incoherent. The use of higher order processing methods to provide some level of discrimination against noise thus appears tractable. Finally, the effects
Chen, Dong; Giampapa, Mark; Heidelberger, Philip; Ohmacht, Martin; Satterfield, David L; Steinmacher-Burow, Burkhard; Sugavanam, Krishnan
2013-05-21
A system and method for enhancing performance of a computer which includes a computer system including a data storage device. The computer system includes a program stored in the data storage device and steps of the program are executed by a processer. The processor processes instructions from the program. A wait state in the processor waits for receiving specified data. A thread in the processor has a pause state wherein the processor waits for specified data. A pin in the processor initiates a return to an active state from the pause state for the thread. A logic circuit is external to the processor, and the logic circuit is configured to detect a specified condition. The pin initiates a return to the active state of the thread when the specified condition is detected using the logic circuit.
Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs
NASA Technical Reports Server (NTRS)
Hammond, Marcus; Clark, Ashley; Mahajan, Aditya; Sharma, Sumant; Rock, Stephen
2015-01-01
An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.
PCR Testing of IVC Filter Tops as a Method for Detecting Murine Pinworms and Fur Mites.
Gerwin, Philip M; Ricart Arbona, Rodolfo J; Riedel, Elyn R; Henderson, Kenneth S; Lipman, Neil S
2017-11-01
We evaluated PCR testing of filter tops from cages maintained on an IVC system through which exhaust air is filtered at the cage level as a method for detecting parasite-infected and -infested cages. Cages containing 4 naïve Swiss Webster mice received 360 mL of uncontaminated aspen chip or α-cellulose bedding (n = 18 cages each) and 60 mL of the same type of bedding weekly from each of the following 4 groups of cages housing mice infected or infested with Syphacia obvelata (SO), Aspiculuris tetraptera (AT), Myocoptes musculinus (MC), or Myobia musculi (MB) and Radfordia affinis (RA; 240 mL bedding total). Detection rates were compared at 30, 60, and 90 d after initiating bedding exposure, by using PCR analysis of filter tops (media extract and swabs) and testing of mouse samples (fur swab [direct] PCR testing, fecal flotation, anal tape test, direct examination of intestinal contents, and skin scrape). PCR testing of filter media extract detected 100% of all parasites at 30 d (both bedding types) except for AT (α-cellulose bedding, 67% detection rate); identified more cages with fur mites (MB and MC) than direct PCR when cellulose bedding was used; and was better at detecting parasites than all nonmolecular methods evaluated. PCR analysis of filter media extract was superior to swab and direct PCR for all parasites cumulatively for each bedding type. Direct PCR more effectively detected MC and all parasites combined for aspen chip compared with cellulose bedding. PCR analysis of filter media extract for IVC systems in which exhaust air is filtered at the cage level was shown to be a highly effective environmental testing method.
Vertebra identification using template matching modelmp and K-means clustering.
Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd
2014-03-01
Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.
PCR Testing of IVC Filter Tops as a Method for Detecting Murine Pinworms and Fur Mites
Gerwin, Philip M; Arbona, Rodolfo J Ricart; Riedel, Elyn R; Henderson, Kenneth S; Lipman, Neil S
2017-01-01
We evaluated PCR testing of filter tops from cages maintained on an IVC system through which exhaust air is filtered at the cage level as a method for detecting parasite- infected and -infested cages. Cages containing 4 naïve Swiss Webster mice received 360 mL of uncontaminated aspen chip or α-cellulose bedding (n = 18 cages each) and 60 mL of the same type of bedding weekly from each of the following 4 groups of cages housing mice infected or infested with Syphacia obvelata (SO), Aspiculuris tetraptera (AT), Myocoptes musculinus (MC), or Myobia musculi (MB) and Radfordia affinis (RA; 240 mL bedding total). Detection rates were compared at 30, 60, and 90 d after initiating bedding exposure, by using PCR analysis of filter tops (media extract and swabs) and testing of mouse samples (fur swab [direct] PCR testing, fecal flotation, anal tape test, direct examination of intestinal contents, and skin scrape). PCR testing of filter media extract detected 100% of all parasites at 30 d (both bedding types) except for AT (α-cellulose bedding, 67% detection rate); identified more cages with fur mites (MB and MC) than direct PCR when cellulose bedding was used; and was better at detecting parasites than all nonmolecular methods evaluated. PCR analysis of filter media extract was superior to swab and direct PCR for all parasites cumulatively for each bedding type. Direct PCR more effectively detected MC and all parasites combined for aspen chip compared with cellulose bedding. PCR analysis of filter media extract for IVC systems in which exhaust air is filtered at the cage level was shown to be a highly effective environmental testing method. PMID:29256370
Gottschlich, Carsten; Schuhmacher, Dominic
2014-01-01
Finding solutions to the classical transportation problem is of great importance, since this optimization problem arises in many engineering and computer science applications. Especially the Earth Mover's Distance is used in a plethora of applications ranging from content-based image retrieval, shape matching, fingerprint recognition, object tracking and phishing web page detection to computing color differences in linguistics and biology. Our starting point is the well-known revised simplex algorithm, which iteratively improves a feasible solution to optimality. The Shortlist Method that we propose substantially reduces the number of candidates inspected for improving the solution, while at the same time balancing the number of pivots required. Tests on simulated benchmarks demonstrate a considerable reduction in computation time for the new method as compared to the usual revised simplex algorithm implemented with state-of-the-art initialization and pivot strategies. As a consequence, the Shortlist Method facilitates the computation of large scale transportation problems in viable time. In addition we describe a novel method for finding an initial feasible solution which we coin Modified Russell's Method.
Gottschlich, Carsten; Schuhmacher, Dominic
2014-01-01
Finding solutions to the classical transportation problem is of great importance, since this optimization problem arises in many engineering and computer science applications. Especially the Earth Mover's Distance is used in a plethora of applications ranging from content-based image retrieval, shape matching, fingerprint recognition, object tracking and phishing web page detection to computing color differences in linguistics and biology. Our starting point is the well-known revised simplex algorithm, which iteratively improves a feasible solution to optimality. The Shortlist Method that we propose substantially reduces the number of candidates inspected for improving the solution, while at the same time balancing the number of pivots required. Tests on simulated benchmarks demonstrate a considerable reduction in computation time for the new method as compared to the usual revised simplex algorithm implemented with state-of-the-art initialization and pivot strategies. As a consequence, the Shortlist Method facilitates the computation of large scale transportation problems in viable time. In addition we describe a novel method for finding an initial feasible solution which we coin Modified Russell's Method. PMID:25310106
Summers, Thomas; Johnson, Viviana V; Stephan, John P; Johnson, Gloria J; Leonard, George
2009-08-01
Massive transfusion of D- trauma patients in the combat setting involves the use of D+ red blood cells (RBCs) or whole blood along with suboptimal pretransfusion test result documentation. This presents challenges to the transfusion service of tertiary care military hospitals who ultimately receive these casualties because initial D typing results may only reflect the transfused RBCs. After patients are stabilized, mixed-field reaction results on D typing indicate the patient's true inherited D phenotype. This case series illustrates the utility of automated gel column agglutination in detecting mixed-field reactions in these patients. The transfusion service test results, including the automated gel column agglutination D typing results, of four massively transfused D- patients transfused D+ RBCs is presented. To test the sensitivity of the automated gel column agglutination method in detecting mixed-field agglutination reactions, a comparative analysis of three automated technologies using predetermined mixtures of D+ and D- RBCs is also presented. The automated gel column agglutination method detected mixed-field agglutination in D typing in all four patients and in the three prepared control specimens. The automated microwell tube method identified one of the three prepared control specimens as indeterminate, which was subsequently manually confirmed as a mixed-field reaction. The automated solid-phase method was unable to detect any mixed fields. The automated gel column agglutination method provides a sensitive means for detecting mixed-field agglutination reactions in the determination of the true inherited D phenotype of combat casualties transfused massive amounts of D+ RBCs.
Linardy, Evelyn M; Erskine, Simon M; Lima, Nicole E; Lonergan, Tina; Mokany, Elisa; Todd, Alison V
2016-01-15
Advancements in molecular biology have improved the ability to characterize disease-related nucleic acids and proteins. Recently, there has been an increasing desire for tests that can be performed outside of centralised laboratories. This study describes a novel isothermal signal amplification cascade called EzyAmp (enzymatic signal amplification) that is being developed for detection of targets at the point of care. EzyAmp exploits the ability of some restriction endonucleases to cleave substrates containing nicks within their recognition sites. EzyAmp uses two oligonucleotide duplexes (partial complexes 1 and 2) which are initially cleavage-resistant as they lack a complete recognition site. The recognition site of partial complex 1 can be completed by hybridization of a triggering oligonucleotide (Driver Fragment 1) that is generated by a target-specific initiation event. Binding of Driver Fragment 1 generates a completed complex 1, which upon cleavage, releases Driver Fragment 2. In turn, binding of Driver Fragment 2 to partial complex 2 creates completed complex 2 which when cleaved releases additional Driver Fragment 1. Each cleavage event separates fluorophore quencher pairs resulting in an increase in fluorescence. At this stage a cascade of signal production becomes independent of further target-specific initiation events. This study demonstrated that the EzyAmp cascade can facilitate detection and quantification of nucleic acid targets with sensitivity down to aM concentration. Further, the same cascade detected VEGF protein with a sensitivity of 20nM showing that this universal method for amplifying signal may be linked to the detection of different types of analytes in an isothermal format. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
Röhrich, J; Schimmel, I; Zörntlein, S; Becker, J; Drobnik, S; Kaufmann, T; Kuntz, V; Urban, R
2010-05-01
Cannabinoid concentrations in blood and urine after passive exposure to cannabis smoke under real-life conditions were investigated in this study. Eight healthy volunteers were exposed to cannabis smoke for 3 h in a well-attended coffee shop in Maastricht, Netherlands. An initial blood and urine sample was taken from each volunteer before exposure. Blood samples were taken 1.5, 3.5, 6, and 14 h after start of initial exposure, and urine samples were taken after 3.5, 6, 14, 36, 60, and 84 h. The samples were subjected to immunoassay screening for cannabinoids and analyzed using gas chromatography-mass spectrometry (GC-MS) for Delta(9)-tetrahydrocannabinol (THC), 11-nor-hydroxy-Delta(9)-tetrahydrocannabinol (THC-OH), and 11-nor-9-carboxy-Delta(9)-tetrahydrocannabinol (THC-COOH). It could be demonstrated that all volunteers absorbed THC. However, the detected concentrations were rather small. None of the urine samples produced immunoassay results above the cutoff concentration of 25 ng/mL. THC-COOH concentrations up to 5.0 and 7.8 ng/mL before and after hydrolysis, respectively, were found in the quantitative GC-MS analysis of urine. THC could be detected in trace amounts close to the detection limit of the used method in the first two blood samples after initial exposure (1.5 and 3.5 h). In the 6 h blood samples, THC was not detectable anymore. THC-COOH could be detected after 1.5 h and was still found in 3 out of 8 blood samples after 14 h in concentrations between 0.5 and 1.0 ng/mL.
Garrido-Martín, Diego; Pazos, Florencio
2018-02-27
The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.
Abeyrathne, Chathurika D; Huynh, Duc H; Mcintire, Thomas W; Nguyen, Thanh C; Nasr, Babak; Zantomio, Daniela; Chana, Gursharan; Abbott, Iain; Choong, Peter; Catton, Mike; Skafidas, Efstratios
2016-03-21
The Gram-positive bacterium, Staphylococcus aureus (S. aureus), is a major pathogen responsible for a variety of infectious diseases ranging from cellulitis to more serious conditions such as septic arthritis and septicaemia. Timely treatment with appropriate antibiotic therapy is essential to ensure clinical defervescence and to prevent further complications such as infective endocarditis or organ impairment due to septic shock. To date, initial antibiotic choice is empirical, using a "best guess" of likely organism and sensitivity- an approach adopted due to the lack of rapid identification methods for bacteria. Current culture based methods take up to 5 days to identify the causative bacterial pathogen and its antibiotic sensitivity. This paper provides proof of concept for a biosensor, based on interdigitated electrodes, to detect the presence of S. aureus and ascertain its sensitivity to flucloxacillin rapidly (within 2 hours) in a cost effective manner. The proposed method is label-free and uses non-faradic measurements. This is the first study to successfully employ interdigitated electrodes for the rapid detection of antibiotic resistance. The method described has important potential outcomes of faster definitive antibiotic treatment and more rapid clinical response to treatment.
Segmentation of human face using gradient-based approach
NASA Astrophysics Data System (ADS)
Baskan, Selin; Bulut, M. Mete; Atalay, Volkan
2001-04-01
This paper describes a method for automatic segmentation of facial features such as eyebrows, eyes, nose, mouth and ears in color images. This work is an initial step for wide range of applications based on feature-based approaches, such as face recognition, lip-reading, gender estimation, facial expression analysis, etc. Human face can be characterized by its skin color and nearly elliptical shape. For this purpose, face detection is performed using color and shape information. Uniform illumination is assumed. No restrictions on glasses, make-up, beard, etc. are imposed. Facial features are extracted using the vertically and horizontally oriented gradient projections. The gradient of a minimum with respect to its neighbor maxima gives the boundaries of a facial feature. Each facial feature has a different horizontal characteristic. These characteristics are derived by extensive experimentation with many face images. Using fuzzy set theory, the similarity between the candidate and the feature characteristic under consideration is calculated. Gradient-based method is accompanied by the anthropometrical information, for robustness. Ear detection is performed using contour-based shape descriptors. This method detects the facial features and circumscribes each facial feature with the smallest rectangle possible. AR database is used for testing. The developed method is also suitable for real-time systems.
Kołacińska, Kamila; Chajduk, Ewelina; Dudek, Jakub; Samczyński, Zbigniew; Łokas, Edyta; Bojanowska-Czajka, Anna; Trojanowicz, Marek
2017-07-01
90 Sr is a widely determined radionuclide for environmental purposes, nuclear waste control, and can be also monitored in coolants in nuclear reactor plants. In the developed method, the ICP-MS detection was employed together with sample processing in sequential injection analysis (SIA) setup, equipped with a lab-on-valve with mechanized renewal of sorbent bed for solid-phase extraction. The optimized conditions of determination included preconcentration of 90 Sr on cation-exchange column and removal of different type of interferences using extraction Sr-resin. The limit of detection of the developed procedure depends essentially on the configuration of the employed ICP-MS spectrometer and on the available volume of the sample to be analyzed. For 1L initial sample volume, the method detection limit (MDL) value was evaluated as 2.9ppq (14.5BqL -1 ). The developed method was applied to analyze spiked river water samples, water reference materials, and also simulated and real samples of the nuclear reactor coolant. Copyright © 2016 Elsevier B.V. All rights reserved.
Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry.
Yao, Jingwen; Utsunomiya, Shin-Ichi; Kajihara, Shigeki; Tabata, Tsuyoshi; Aoshima, Ken; Oda, Yoshiya; Tanaka, Koichi
2014-01-01
A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/).
Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry
Yao, Jingwen; Utsunomiya, Shin-ichi; Kajihara, Shigeki; Tabata, Tsuyoshi; Aoshima, Ken; Oda, Yoshiya; Tanaka, Koichi
2014-01-01
A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/). PMID:26819872
Dağdeviren, Semahat; Altunay, Nail; Sayman, Yasin; Gürkan, Ramazan
2018-07-30
The study developed a new method for proline detection in honey, wine and fruit juice using ultrasound assisted-cloud point extraction (UA-CPE) and spectrophotometry. Initially, a quaternary complex was built, containing proline, histamine, Cu(II), and fluorescein at pH 5.5. Samples were treated with ethanol-water mixture before extraction and preconcentration, using an ultrasonic bath for 10 min at 40 °C (40 kHz, 300 W). After the optimization of variables affecting extraction efficiency, good linearity was obtained between 15 and 600 µg L -1 with sensitivity enhancement factor of 105. The limits of detection and quantification were 5.7 and 19.0 µg L -1 , respectively. The recovery percentage and relative standard deviations (RSD %) were between 95.3 and 103.3%, and 2.5 and 4.2%, respectively. The accuracy of the method was verified by the analysis of a standard reference material (SRM 2389a). Copyright © 2018 Elsevier Ltd. All rights reserved.
Pereira, Danilo Cesar; Ramos, Rodrigo Pereira; do Nascimento, Marcelo Zanchetta
2014-04-01
In Brazil, the National Cancer Institute (INCA) reports more than 50,000 new cases of the disease, with risk of 51 cases per 100,000 women. Radiographic images obtained from mammography equipments are one of the most frequently used techniques for helping in early diagnosis. Due to factors related to cost and professional experience, in the last two decades computer systems to support detection (Computer-Aided Detection - CADe) and diagnosis (Computer-Aided Diagnosis - CADx) have been developed in order to assist experts in detection of abnormalities in their initial stages. Despite the large number of researches on CADe and CADx systems, there is still a need for improved computerized methods. Nowadays, there is a growing concern with the sensitivity and reliability of abnormalities diagnosis in both views of breast mammographic images, namely cranio-caudal (CC) and medio-lateral oblique (MLO). This paper presents a set of computational tools to aid segmentation and detection of mammograms that contained mass or masses in CC and MLO views. An artifact removal algorithm is first implemented followed by an image denoising and gray-level enhancement method based on wavelet transform and Wiener filter. Finally, a method for detection and segmentation of masses using multiple thresholding, wavelet transform and genetic algorithm is employed in mammograms which were randomly selected from the Digital Database for Screening Mammography (DDSM). The developed computer method was quantitatively evaluated using the area overlap metric (AOM). The mean ± standard deviation value of AOM for the proposed method was 79.2 ± 8%. The experiments demonstrate that the proposed method has a strong potential to be used as the basis for mammogram mass segmentation in CC and MLO views. Another important aspect is that the method overcomes the limitation of analyzing only CC and MLO views. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo
2016-10-01
Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.
Zhang, Baixia; Li, Yanwen; Zhang, Yanling; Li, Zhiyong; Bi, Tian; He, Yusu; Song, Kuokui; Wang, Yun
2016-01-01
Identification of bioactive components is an important area of research in traditional Chinese medicine (TCM) formula. The reported identification methods only consider the interaction between the components and the target proteins, which is not sufficient to explain the influence of TCM on the gene expression. Here, we propose the Initial Transcription Process-based Identification (ITPI) method for the discovery of bioactive components that influence transcription factors (TFs). In this method, genome-wide chip detection technology was used to identify differentially expressed genes (DEGs). The TFs of DEGs were derived from GeneCards. The components influencing the TFs were derived from STITCH. The bioactive components in the formula were identified by evaluating the molecular similarity between the components in formula and the components that influence the TF of DEGs. Using the formula of Tian-Zhu-San (TZS) as an example, the reliability and limitation of ITPI were examined and 16 bioactive components that influence TFs were identified. PMID:27034696
Perturbing engine performance measurements to determine optimal engine control settings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan
Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initialmore » value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.« less
Analysis of modal behavior at frequency cross-over
NASA Astrophysics Data System (ADS)
Costa, Robert N., Jr.
1994-11-01
The existence of the mode crossing condition is detected and analyzed in the Active Control of Space Structures Model 4 (ACOSS4). The condition is studied for its contribution to the inability of previous algorithms to successfully optimize the structure and converge to a feasible solution. A new algorithm is developed to detect and correct for mode crossings. The existence of the mode crossing condition is verified in ACOSS4 and found not to have appreciably affected the solution. The structure is then successfully optimized using new analytic methods based on modal expansion. An unrelated error in the optimization algorithm previously used is verified and corrected, thereby equipping the optimization algorithm with a second analytic method for eigenvector differentiation based on Nelson's Method. The second structure is the Control of Flexible Structures (COFS). The COFS structure is successfully reproduced and an initial eigenanalysis completed.
Konecki, Dariusz; Grabowska-Derlatka, Laretta; Pacho, Ryszard; Rowiński, Olgierd
2017-01-01
Endoscopic methods (gastroscopy and colonoscopy) are considered fundamental for the diagnosis of gastrointestinal bleeding. In recent years, multidetector computed tomography (MDCT) has also gained importance in diagnosing gastrointestinal bleeding, particularly in hemodynamically unstable patients and in cases with suspected lower gastrointestinal tract bleeding. CT can detect both the source and the cause of active gastrointestinal bleeding, thereby expediting treatment initiation. The study group consisted of 16 patients with clinical symptoms of gastrointestinal bleeding in whom features of active bleeding were observed on CT. In all patients, bleeding was verified by means of other methods such as endoscopic examinations, endovascular procedures, or surgery. The bleeding source was identified on CT in all 16 patients. In 14 cases (87.5%), bleeding was confirmed by other methods. CT is an efficient, fast, and readily available tool for detecting the location of acute gastrointestinal bleeding.
NASA Astrophysics Data System (ADS)
Tang, Xiaojing
Fast and accurate monitoring of tropical forest disturbance is essential for understanding current patterns of deforestation as well as helping eliminate illegal logging. This dissertation explores the use of data from different satellites for near real-time monitoring of forest disturbance in tropical forests, including: development of new monitoring methods; development of new assessment methods; and assessment of the performance and operational readiness of existing methods. Current methods for accuracy assessment of remote sensing products do not address the priority of near real-time monitoring of detecting disturbance events as early as possible. I introduce a new assessment framework for near real-time products that focuses on the timing and the minimum detectable size of disturbance events. The new framework reveals the relationship between change detection accuracy and the time needed to identify events. In regions that are frequently cloudy, near real-time monitoring using data from a single sensor is difficult. This study extends the work by Xin et al. (2013) and develops a new time series method (Fusion2) based on fusion of Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) data. Results of three test sites in the Amazon Basin show that Fusion2 can detect 44.4% of the forest disturbance within 13 clear observations (82 days) after the initial disturbance. The smallest event detected by Fusion2 is 6.5 ha. Also, Fusion2 detects disturbance faster and has less commission error than more conventional methods. In a comparison of coarse resolution sensors, MODIS Terra and Aqua combined provides faster and more accurate detection of disturbance events than VIIRS (Visible Infrared Imaging Radiometer Suite) and MODIS single sensor data. The performance of near real-time monitoring using VIIRS is slightly worse than MODIS Terra but significantly better than MODIS Aqua. New monitoring methods developed in this dissertation provide forest protection organizations the capacity to monitor illegal logging events promptly. In the future, combining two Landsat and two Sentinel-2 satellites will provide global coverage at 30 m resolution every 4 days, and routine monitoring may be possible at high resolution. The methods and assessment framework developed in this dissertation are adaptable to newly available datasets.
Reliability-based optimization of maintenance scheduling of mechanical components under fatigue
Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.
2012-01-01
This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979
NASA Astrophysics Data System (ADS)
Huang, Weilin; Wang, Runqiu; Chen, Yangkang
2018-05-01
Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.
NASA Astrophysics Data System (ADS)
Auborn, K. J.; Little, R. D.; Platt, T. H. K.; Vaccariello, M. A.; Schildkraut, C. L.
1994-07-01
We have examined the structures of replication intermediates from the human papillomavirus type 11 genome in DNA extracted from papilloma lesions (laryngeal papillomas). The sites of replication initiation and termination utilized in vivo were mapped by using neutral/neutral and neutral/alkaline two-dimensional agarose gel electrophoresis methods. Initiation of replication was detected in or very close to the upstream regulatory region (URR; the noncoding, regulatory sequences upstream of the open reading frames in the papillomavirus genome). We also show that replication forks proceed bidirectionally from the origin and converge 180circ opposite the URR. These results demonstrate the feasibility of analysis of replication of viral genomes directly from infected tissue.
Automated Microorganism Detector
NASA Astrophysics Data System (ADS)
Keahey, Pelham; Hardy, Will; Cradit, Mason; Solis, Steven; Holland, Andrea; Wade, Gerry
2010-10-01
The detection and identification of bacteria in blood samples is crucial for treating patients suspected of having a blood infection. Current hospital methods for pathogen detection are time-consuming processes with multiple steps. This project's goal was to develop an efficient biomedical device to detect bacterial growth in blood samples, based on Gerald J. Wade's 1979 invention (US patents 4250266 and 4267276). Detection was accomplished using a system of electronics to examine the change in the electrochemical properties of a sample in response to bacterial growth, by measuring the sample's electrical charging and charge dispersion characteristics. After initial trials, it was found that a sample yielded consistent voltage measurements of approximately 200 millivolts prior to any detectable microbial growth. The first species tested, Escherichia coli (E. coli), was detected 11.7 hours after its inoculation in a culture bottle at a concentration of approximately 5-10 organisms per milliliter. In future tests, it is expected that detection times will vary in proportion to the growth rate of each species.
Using the Detectability Index to Predict P300 Speller Performance
Mainsah, B.O.; Collins, L.M.; Throckmorton, C.S.
2017-01-01
Objective The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping algorithms and other stimulus paradigms is desirable. Approach We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian dynamic stopping (DS) algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance The proposed method could serve as a useful tool to initially asses BCI performance without extensive online testing, in order to estimate the amount of data required to achieve a desired accuracy level. PMID:27705956
Using the detectability index to predict P300 speller performance
NASA Astrophysics Data System (ADS)
Mainsah, B. O.; Collins, L. M.; Throckmorton, C. S.
2016-12-01
Objective. The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping (DS) algorithms and other stimulus paradigms is desirable. Approach. We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian DS algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results. Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance. The proposed method could serve as a useful tool to initially assess BCI performance without extensive online testing, in order to estimate the amount of data required to achieve a desired accuracy level.
A decade of aquatic invasive species (AIS) early detection ...
As an invasion prone location, the St. Louis River Estuary (SLRE) has been a case study for ongoing research to develop the framework for a practical Great Lakes monitoring network for early detection of aquatic invasive species (AIS). Early detection, however, necessitates finding new invaders before they are common. Here we outline our research (2005 present) approach and findings, including strategies to increase detection efficiency by optimizing specimen collection and identification methods. Initial surveys were designed to over-sample to amass data as the basis for numerical experiments to investigate to the effort required for a given detection probability. Later surveys tested the outcome of implementing these strategies, examined the potential benefits of sampling larval fish instead of adults and explored the prospect of using advanced DNA based methods as an alternative to traditional taxonomy. To date we have identified several previously undetected invertebrate invaders, developed survey design and gear recommendations and have refined the search strategy for systems beyond the SLRE. In addition, because we’ve accumulated such a large body of data we now have the basis to show spatial-temporal trends for native and non-native species in the SLRE. not applicable
Automated retinal nerve fiber layer defect detection using fundus imaging in glaucoma.
Panda, Rashmi; Puhan, N B; Rao, Aparna; Padhy, Debananda; Panda, Ganapati
2018-06-01
Retinal nerve fiber layer defect (RNFLD) provides an early objective evidence of structural changes in glaucoma. RNFLD detection is currently carried out using imaging modalities like OCT and GDx which are expensive for routine practice. In this regard, we propose a novel automatic method for RNFLD detection and angular width quantification using cost effective redfree fundus images to be practically useful for computer-assisted glaucoma risk assessment. After blood vessel inpainting and CLAHE based contrast enhancement, the initial boundary pixels are identified by local minima analysis of the 1-D intensity profiles on concentric circles. The true boundary pixels are classified using random forest trained by newly proposed cumulative zero count local binary pattern (CZC-LBP) and directional differential energy (DDE) along with Shannon, Tsallis entropy and intensity features. Finally, the RNFLD angular width is obtained by random sample consensus (RANSAC) line fitting on the detected set of boundary pixels. The proposed method is found to achieve high RNFLD detection performance on a newly created dataset with sensitivity (SN) of 0.7821 at 0.2727 false positives per image (FPI) and the area under curve (AUC) value is obtained as 0.8733. Copyright © 2018 Elsevier Ltd. All rights reserved.
Synthesis of zinc oxide thin films prepared by sol-gel for specific bioactivity
NASA Astrophysics Data System (ADS)
Adam, Tijjani; Basri, B.; Dhahi, Th. S.; Mohammed, Mohammed; Hashim, U.; Noriman, N. Z.; Dahham, Omar S.
2017-09-01
Zinc oxide (ZnO) thin films this device to used for many application like chemical sensor, biosensor, solar energy, etc but my project to use for bioactivity(biosensor). Zinc oxide (ZnO) thin films have been grown using sol-gel technique. Characterization was done using Scanning Electron Microscope (SEM), Energy Dispersive X-ray(EDX) and Electrical Measurement(I-V). ZnO thin film was successfully synthesized using low cost sol-gel spin coating method. The coupling of DNA probe to ZnO thin film supports modified with carboxylic acid (COOH) is certainly the best practical method to make DNA immobilization and it does not require any coupling agent which could be a source of variability during the spotting with an automatic device. So, selected this coupling procedure for further experiments. The sensor was tested with initial trial with low concentrated DNA and able to detect detection of the disease effectively. Silicon-on-insulator (SOI) wafer device with ZnO can detect at different concentration in order to valid the device capabilities for detecting development. The lowest concentration 1 µM HPV DNA probe can detect is 0.1 nM HPV target DNA.
Colitis detection on abdominal CT scans by rich feature hierarchies
NASA Astrophysics Data System (ADS)
Liu, Jiamin; Lay, Nathan; Wei, Zhuoshi; Lu, Le; Kim, Lauren; Turkbey, Evrim; Summers, Ronald M.
2016-03-01
Colitis is inflammation of the colon due to neutropenia, inflammatory bowel disease (such as Crohn disease), infection and immune compromise. Colitis is often associated with thickening of the colon wall. The wall of a colon afflicted with colitis is much thicker than normal. For example, the mean wall thickness in Crohn disease is 11-13 mm compared to the wall of the normal colon that should measure less than 3 mm. Colitis can be debilitating or life threatening, and early detection is essential to initiate proper treatment. In this work, we apply high-capacity convolutional neural networks (CNNs) to bottom-up region proposals to detect potential colitis on CT scans. Our method first generates around 3000 category-independent region proposals for each slice of the input CT scan using selective search. Then, a fixed-length feature vector is extracted from each region proposal using a CNN. Finally, each region proposal is classified and assigned a confidence score with linear SVMs. We applied the detection method to 260 images from 26 CT scans of patients with colitis for evaluation. The detection system can achieve 0.85 sensitivity at 1 false positive per image.
NASA Astrophysics Data System (ADS)
Barrie, A.; Gliese, U.; Gershman, D. J.; Avanov, L. A.; Rager, A. C.; Pollock, C. J.; Dorelli, J.
2015-12-01
The Fast Plasma Investigation (FPI) on the Magnetospheric Multiscale mission (MMS) combines data from eight spectrometers, each with four deflection states, into a single map of the sky. Any systematic discontinuity, artifact, noise source, etc. present in this map may be incorrectly interpreted as legitimate data and incorrect conclusions reached. For this reason it is desirable to have all spectrometers return the same output for a given input, and for this output to be low in noise sources or other errors. While many missions use statistical analyses of data to calibrate instruments in flight, this process is difficult with FPI for two reasons: 1. Only a small fraction of high resolution data is downloaded to the ground due to bandwidth limitations and 2: The data that is downloaded is, by definition, scientifically interesting and therefore not ideal for calibration. FPI uses a suite of new tools to calibrate in flight. A new method for detection system ground calibration has been developed involving sweeping the detection threshold to fully define the pulse height distribution. This method has now been extended for use in flight as a means to calibrate MCP voltage and threshold (together forming the operating point) of the Dual Electron Spectrometers (DES) and Dual Ion Spectrometers (DIS). A method of comparing higher energy data (which has low fractional voltage error) to lower energy data (which has a higher fractional voltage error) will be used to calibrate the high voltage outputs. Finally, a comparison of pitch angle distributions will be used to find remaining discrepancies among sensors. Initial flight results from the four MMS observatories will be discussed here. Specifically, data from initial commissioning, inter-instrument cross calibration and interference testing, and initial Phase1A routine calibration results. Success and performance of the in flight calibration as well as deviation from the ground calibration will be discussed.
Versteeg, Roelof J; Few, Douglas A; Kinoshita, Robert A; Johnson, Doug; Linda, Ondrej
2015-02-24
Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.
Versteeg, Roelof J.; Few, Douglas A.; Kinoshita, Robert A.; Johnson, Douglas; Linda, Ondrej
2015-12-15
Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.
Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.
Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H
2017-01-01
A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.
Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification
Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried
2017-01-01
A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows. PMID:28125723
Toward Failure Modeling In Complex Dynamic Systems: Impact of Design and Manufacturing Variations
NASA Technical Reports Server (NTRS)
Tumer, Irem Y.; McAdams, Daniel A.; Clancy, Daniel (Technical Monitor)
2001-01-01
When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes during a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the. modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle vibration monitoring systems.
Thin and Slow Smoke Detection by Using Frequency Image
NASA Astrophysics Data System (ADS)
Zheng, Guang; Oe, Shunitiro
In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.
Zhu, Yingdi; Gasilova, Natalia; Jović, Milica; Qiao, Liang; Liu, Baohong; Lovey, Lysiane Tissières; Pick, Horst
2018-01-01
Titanium dioxide-modified target plates were developed to enhance intact bacteria analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The plates were designed to photocatalytically destroy the bacterial envelope structure and improve the ionization efficiency of intracellular components, thereby promoting the measurable mass range and the achievable detection sensitivity. Accordingly, a method for rapid detection of antimicrobial resistance-associated proteins, conferring bacterial resistance against antimicrobial drugs, was established by mass spectrometric fingerprinting of intact bacteria without the need for any sample pre-treatment. With this method, the variations in resistance proteins’ expression levels within bacteria were quickly measured from the relative peak intensities. This approach of resistance protein detection directly from intact bacteria by mass spectrometry is useful for fast discrimination of antimicrobial-resistant bacteria from their non-resistant counterparts whilst performing species identification. Also, it could be used as a rapid and convenient way for initial determination of the underlying resistance mechanisms. PMID:29719694
Mobile phones improve case detection and management of malaria in rural Bangladesh
2013-01-01
Background The recent introduction of mobile phones into the rural Bandarban district of Bangladesh provided a resource to improve case detection and treatment of patients with malaria. Methods During studies to define the epidemiology of malaria in villages in south-eastern Bangladesh, an area with hypoendemic malaria, the project recorded 986 mobile phone calls from families because of illness suspected to be malaria between June 2010 and June 2012. Results Based on phone calls, field workers visited the homes with ill persons, and collected blood samples for malaria on 1,046 people. 265 (25%) of the patients tested were positive for malaria. Of the 509 symptomatic malaria cases diagnosed during this study period, 265 (52%) were detected because of an initial mobile phone call. Conclusion Mobile phone technology was found to be an efficient and effective method for rapidly detecting and treating patients with malaria in this remote area. This technology, when combined with local knowledge and field support, may be applicable to other hard-to-reach areas to improve malaria control. PMID:23374585
Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah
2009-01-01
Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657
NASA Astrophysics Data System (ADS)
Lartizien, Carole; Kinahan, Paul E.; Comtat, Claude; Lin, Michael; Swensson, Richard G.; Trebossen, Regine; Bendriem, Bernard
2000-04-01
This work presents initial results from observer detection performance studies using the same volume visualization software tools that are used in clinical PET oncology imaging. Research into the FORE+OSEM and FORE+AWOSEM statistical image reconstruction methods tailored to whole- body 3D PET oncology imaging have indicated potential improvements in image SNR compared to currently used analytic reconstruction methods (FBP). To assess the resulting impact of these reconstruction methods on the performance of human observers in detecting and localizing tumors, we use a non- Monte Carlo technique to generate multiple statistically accurate realizations of 3D whole-body PET data, based on an extended MCAT phantom and with clinically realistic levels of statistical noise. For each realization, we add a fixed number of randomly located 1 cm diam. lesions whose contrast is varied among pre-calibrated values so that the range of true positive fractions is well sampled. The observer is told the number of tumors and, similar to the AFROC method, asked to localize all of them. The true positive fraction for the three algorithms (FBP, FORE+OSEM, FORE+AWOSEM) as a function of lesion contrast is calculated, although other protocols could be compared. A confidence level for each tumor is also recorded for incorporation into later AFROC analysis.
Radiation Detection Material Discovery Initiative at PNNL
NASA Astrophysics Data System (ADS)
Milbrath, Brian
2006-05-01
Today's security threats are being met with 30-year old radiation technology. Discovery of new radiation detection materials is currently a slow and Edisonian process. With heightened concerns over nuclear proliferation, terrorism and unconventional warfare, an alternative strategy for identification and development of potential radiation detection materials must be adopted. Through the Radiation Detection Materials Discovery Initiative, PNNL focuses on the science-based discovery of next generation materials for radiation detection by addressing three ``grand challenges'': fundamental understanding of radiation detection, identification of new materials, and accelerating the discovery process. The new initiative has eight projects addressing these challenges, which will be described, including early work, paths forward and the opportunities for collaboration.
Eads, David A.; Biggins, Dean E.; Doherty, Paul F.; Gage, Kenneth L.; Huyvaert, Kathryn P.; Long, Dustin H.; Antolin, Michael F.
2013-01-01
Ectoparasites are often difficult to detect in the field. We developed a method that can be used with occupancy models to estimate the prevalence of ectoparasites on hosts, and to investigate factors that influence rates of ectoparasite occupancy while accounting for imperfect detection. We describe the approach using a study of fleas (Siphonaptera) on black-tailed prairie dogs (Cynomys ludovicianus). During each primary occasion (monthly trapping events), we combed a prairie dog three consecutive times to detect fleas (15 s/combing). We used robust design occupancy modeling to evaluate hypotheses for factors that might correlate with the occurrence of fleas on prairie dogs, and factors that might influence the rate at which prairie dogs are colonized by fleas. Our combing method was highly effective; dislodged fleas fell into a tub of water and could not escape, and there was an estimated 99.3% probability of detecting a flea on an occupied host when using three combings. While overall detection was high, the probability of detection was always <1.00 during each primary combing occasion, highlighting the importance of considering imperfect detection. The combing method (removal of fleas) caused a decline in detection during primary occasions, and we accounted for that decline to avoid inflated estimates of occupancy. Regarding prairie dogs, flea occupancy was heightened in old/natural colonies of prairie dogs, and on hosts that were in poor condition. Occupancy was initially low in plots with high densities of prairie dogs, but, as the study progressed, the rate of flea colonization increased in plots with high densities of prairie dogs in particular. Our methodology can be used to improve studies of ectoparasites, especially when the probability of detection is low. Moreover, the method can be modified to investigate the co-occurrence of ectoparasite species, and community level factors such as species richness and interspecific interactions.
ERIC Educational Resources Information Center
Grané, Aurea; Romera, Rosario
2018-01-01
Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variables). Multidimensional scaling (MDS) is one of the most extended methodologies to visualize the profile structure of the data. Since the past 60s, MDS methods have been introduced in the literature, initially in publications in the psychometrics area.…
An application of artificial neural networks to experimental data approximation
NASA Technical Reports Server (NTRS)
Meade, Andrew J., Jr.
1993-01-01
As an initial step in the evaluation of networks, a feedforward architecture is trained to approximate experimental data by the backpropagation algorithm. Several drawbacks were detected and an alternative learning algorithm was then developed to partially address the drawbacks. This noniterative algorithm has a number of advantages over the backpropagation method and is easily implemented on existing hardware.
Quantifying noise in optical tweezers by allan variance.
Czerwinski, Fabian; Richardson, Andrew C; Oddershede, Lene B
2009-07-20
Much effort is put into minimizing noise in optical tweezers experiments because noise and drift can mask fundamental behaviours of, e.g., single molecule assays. Various initiatives have been taken to reduce or eliminate noise but it has been difficult to quantify their effect. We propose to use Allan variance as a simple and efficient method to quantify noise in optical tweezers setups.We apply the method to determine the optimal measurement time, frequency, and detection scheme, and quantify the effect of acoustic noise in the lab. The method can also be used on-the-fly for determining optimal parameters of running experiments.
Mazumder, Avik; Gupta, Hemendra K; Garg, Prabhat; Jain, Rajeev; Dubey, Devendra K
2009-07-03
This paper details an on-flow liquid chromatography-ultraviolet-nuclear magnetic resonance (LC-UV-NMR) method for the retrospective detection and identification of alkyl alkylphosphonic acids (AAPAs) and alkylphosphonic acids (APAs), the markers of the toxic nerve agents for verification of the Chemical Weapons Convention (CWC). Initially, the LC-UV-NMR parameters were optimized for benzyl derivatives of the APAs and AAPAs. The optimized parameters include stationary phase C(18), mobile phase methanol:water 78:22 (v/v), UV detection at 268nm and (1)H NMR acquisition conditions. The protocol described herein allowed the detection of analytes through acquisition of high quality NMR spectra from the aqueous solution of the APAs and AAPAs with high concentrations of interfering background chemicals which have been removed by preceding sample preparation. The reported standard deviation for the quantification is related to the UV detector which showed relative standard deviations (RSDs) for quantification within +/-1.1%, while lower limit of detection upto 16mug (in mug absolute) for the NMR detector. Finally the developed LC-UV-NMR method was applied to identify the APAs and AAPAs in real water samples, consequent to solid phase extraction and derivatization. The method is fast (total experiment time approximately 2h), sensitive, rugged and efficient.
Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries.
Balasingham, Katherine D; Walter, Ryan P; Mandrak, Nicholas E; Heath, Daniel D
2018-01-01
The extraction and characterization of DNA from aquatic environmental samples offers an alternative, noninvasive approach for the detection of rare species. Environmental DNA, coupled with PCR and next-generation sequencing ("metabarcoding"), has proven to be very sensitive for the detection of rare aquatic species. Our study used a custom-designed group-specific primer set and next-generation sequencing for the detection of three species at risk (Eastern Sand Darter, Ammocrypta pellucida; Northern Madtom, Noturus stigmosus; and Silver Shiner, Notropis photogenis), one invasive species (Round Goby, Neogobius melanostomus) and an additional 78 native species from two large Great Lakes tributary rivers in southern Ontario, Canada: the Grand River and the Sydenham River. Of 82 fish species detected in both rivers using capture-based and eDNA methods, our eDNA method detected 86.2% and 72.0% of the fish species in the Grand River and the Sydenham River, respectively, which included our four target species. Our analyses also identified significant positive and negative species co-occurrence patterns between our target species and other identified species. Our results demonstrate that eDNA metabarcoding that targets the fish community as well as individual species of interest provides a better understanding of factors affecting the target species spatial distribution in an ecosystem than possible with only target species data. Additionally, eDNA is easily implemented as an initial survey tool, or alongside capture-based methods, for improved mapping of species distribution patterns. © 2017 John Wiley & Sons Ltd.
Rodriguez-Lazaro, David; Gonzalez-García, Patricia; Delibato, Elisabetta; De Medici, Dario; García-Gimeno, Rosa Maria; Valero, Antonio; Hernandez, Marta
2014-08-01
The microbiological standard for detection of Salmonella relies on several cultural steps and requires more than 5 days for final confirmation, and as consequence there is a need for an alternative rapid methodology for its detection. The aim of this study was to compare different detection strategies based on real-time PCR for a rapid and sensitive detection in an ample range of food products: raw pork and poultry meat, ready to eat lettuce salad and raw sheep milk cured cheese. Three main parameters were evaluated to reduce the time and cost for final results: the initial sample size (25 and 50 g), the incubation times (6, 10 and 18 h) and the bacterial DNA extraction (simple boiling of the culture after washing the bacterial pellet, the use of the Chelex resin, and a commercial silica column). The results obtained demonstrate that a combination of an incubation in buffered peptone water for 18 h of a 25 g-sample coupled to a DNA extraction by boiling and a real-time PCR assay detected down to 2-4 Salmonella spp.CFU per sample in less than 21 h in different types of food products. This RTi-PCR-based method is fully compatible with the ISO standard, providing results more rapidly and cost-effectively. The results were confirmed in a large number of naturally contaminated food samples with at least the same analytical performance as the reference method. Copyright © 2014 Elsevier B.V. All rights reserved.
Kotiadis, D; Hermens, H J; Veltink, P H
2010-05-01
An Inertial Gait Phase Detection system was developed to replace heel switches and footswitches currently being used for the triggering of drop foot stimulators. A series of four algorithms utilising accelerometers and gyroscopes individually and in combination were tested and initial results are shown. Sensors were positioned on the outside of the upper shank. Tests were performed on data gathered from a subject, sufferer of stroke, implanted with a drop foot stimulator and triggered with the current trigger, the heel switch. Data tested includes a variety of activities representing everyday life. Flat surface walking, rough terrain and carpet walking show 100% detection and the ability of the algorithms to ignore non-gait events such as weight shifts. Timing analysis is performed against the current triggering method, the heel switch. After evaluating the heel switch timing against a reference system, namely the Vicon 370 marker and force plates system. Initial results show a close correlation between the current trigger detection and the inertial sensor based triggering algorithms. Algorithms were tested for stairs up and stairs down. Best results are observed for algorithms using gyroscope data. Algorithms were designed using threshold techniques for lowest possible computational load and with least possible sensor components to minimize power requirements and to allow for potential future implantation of sensor system.
Konecki, Dariusz; Pacho, Ryszard; Rowiński, Olgierd
2017-01-01
Summary Background Endoscopic methods (gastroscopy and colonoscopy) are considered fundamental for the diagnosis of gastrointestinal bleeding. In recent years, multidetector computed tomography (MDCT) has also gained importance in diagnosing gastrointestinal bleeding, particularly in hemodynamically unstable patients and in cases with suspected lower gastrointestinal tract bleeding. CT can detect both the source and the cause of active gastrointestinal bleeding, thereby expediting treatment initiation. Material/Methods The study group consisted of 16 patients with clinical symptoms of gastrointestinal bleeding in whom features of active bleeding were observed on CT. In all patients, bleeding was verified by means of other methods such as endoscopic examinations, endovascular procedures, or surgery. Results The bleeding source was identified on CT in all 16 patients. In 14 cases (87.5%), bleeding was confirmed by other methods. Conclusions CT is an efficient, fast, and readily available tool for detecting the location of acute gastrointestinal bleeding. PMID:29662594
Distributed fiber optic system for oil pipeline leakage detection
NASA Astrophysics Data System (ADS)
Paranjape, R.; Liu, N.; Rumple, C.; Hara, Elmer H.
2003-02-01
We present a novel approach for the detection of leakage in oil pipelines using methods of fiber optic distributed sensors, a presence-of-oil based actuator, and Optical Time Domain Reflectometry (OTDR). While the basic concepts of our approach are well understood, the integration of the components into a complete system is a real world engineering design problem. Our focus has been on the development of the actuator design and testing using installed dark fiber. Initial results are promising, however environmental studies into the long term effects of exposure to the environment are still pending.
Eddy Current System for Material Inspection and Flaw Visualization
NASA Technical Reports Server (NTRS)
Bachnak, R.; King, S.; Maeger, W.; Nguyen, T.
2007-01-01
Eddy current methods have been successfully used in a variety of non-destructive evaluation applications including detection of cracks, measurements of material thickness, determining metal thinning due to corrosion, measurements of coating thickness, determining electrical conductivity, identification of materials, and detection of corrosion in heat exchanger tubes. This paper describes the development of an eddy current prototype that combines positional and eddy-current data to produce a C-scan of tested material. The preliminary system consists of an eddy current probe, a position tracking mechanism, and basic data visualization capability. Initial test results of the prototype are presented in this paper.
Diagnosis of toxic alcohols: limitations of present methods.
Kraut, Jeffrey A
2015-01-01
Methanol, ethylene glycol, diethylene glycol, and propylene glycol intoxications are associated with cellular dysfunction and an increased risk of death. Adverse effects can develop quickly; thus, there is a need for methods for rapidly detecting their presence. To examine the value and limitations of present methods to diagnose patients with possible toxic alcohol exposure. I searched MEDLINE for articles published between 1969 and 2014 using the terms: toxic alcohols, serum osmolality, serum osmol gap, serum anion gap, metabolic acidosis, methanol, ethylene glycol, diethylene glycol, propylene glycol, and fomepizole. Each article was reviewed for additional references. The diagnosis of toxic alcohol exposure is often made on the basis of this history and physical findings along with an increase in the serum osmol and anion gaps. However, an increase in the osmol and/or anion gaps is not always present. Definitive detection in blood requires gas or liquid chromatography, laborious and expensive procedures which are not always available. Newer methods including a qualitative colorimetric test for detection of all alcohols or enzymatic tests for a specific alcohol might allow for more rapid diagnosis. Exposure to toxic alcohols is associated with cellular dysfunction and increased risk of death. Treatment, if initiated early, can markedly improve outcome, but present methods of diagnosis including changes in serum osmol and anion gap, and use of gas or liquid chromatography have important limitations. Development of more rapid and effective tests for detection of these intoxications is essential for optimal care of patients.
Józwa, Wojciech; Czaczyk, Katarzyna
2012-04-02
Flow cytometry constitutes an alternative for traditional methods of microorganisms identification and analysis, including methods requiring cultivation step. It enables the detection of pathogens and other microorganisms contaminants without the need to culture microbial cells meaning that the sample (water, waste or food e.g. milk, wine, beer) may be analysed directly. This leads to a significant reduction of time required for analysis allowing monitoring of production processes and immediate reaction in case of contamination or any disruption occurs. Apart from the analysis of raw materials or products on different stages of manufacturing process, the flow cytometry seems to constitute an ideal tool for the assessment of microbial contamination on the surface of technological lines. In the present work samples comprising smears from 3 different surfaces of technological lines from fruit and vegetable processing company from Greater Poland were analysed directly with flow cytometer. The measured parameters were forward and side scatter of laser light signals allowing the estimation of microbial cell contents in each sample. Flow cytometric analysis of the surface of food industry production lines enable the preliminary evaluation of microbial contamination within few minutes from the moment of sample arrival without the need of sample pretreatment. The presented method of fl ow cytometric initial evaluation of microbial state of food industry technological lines demonstrated its potential for developing a robust, routine method for the rapid and labor-saving detection of microbial contamination in food industry.
Ben Mansour, Khaireddine; Rezzoug, Nasser; Gorce, Philippe
2015-10-01
The purpose of this paper was to determine which types of inertial sensors and which advocated locations should be used for reliable and accurate gait event detection and temporal parameter assessment in normal adults. In addition, we aimed to remove the ambiguity found in the literature of the definition of the initial contact (IC) from the lumbar accelerometer. Acceleration and angular velocity data was gathered from the lumbar region and the distal edge of each shank. This data was evaluated in comparison to an instrumented treadmill and an optoelectronic system during five treadmill speed sessions. The lumbar accelerometer showed that the peak of the anteroposterior component was the most accurate for IC detection. Similarly, the valley that followed the peak of the vertical component was the most precise for terminal contact (TC) detection. Results based on ANOVA and Tukey tests showed that the set of inertial methods was suitable for temporal gait assessment and gait event detection in able-bodied subjects. For gait event detection, an exception was found with the shank accelerometer. The tool was suitable for temporal parameters assessment, despite the high root mean square error on the detection of IC (RMSEIC) and TC (RMSETC). The shank gyroscope was found to be as accurate as the kinematic method since the statistical tests revealed no significant difference between the two techniques for the RMSE off all gait events and temporal parameters. The lumbar and shank accelerometers were the most accurate alternative to the shank gyroscope for gait event detection and temporal parameters assessment, respectively. Copyright © 2015. Published by Elsevier B.V.
Enhanced Detection of Surface-Associated Bacteria in Indoor Environments by Quantitative PCR
Buttner, Mark P.; Cruz-Perez, Patricia; Stetzenbach, Linda D.
2001-01-01
Methods for detecting microorganisms on surfaces are needed to locate biocontamination sources and to relate surface and airborne concentrations. Research was conducted in an experimental room to evaluate surface sampling methods and quantitative PCR (QPCR) for enhanced detection of a target biocontaminant present on flooring materials. QPCR and culture analyses were used to quantitate Bacillus subtilis (Bacillus globigii) endospores on vinyl tile, commercial carpet, and new and soiled residential carpet with samples obtained by four surface sampling methods: a swab kit, a sponge swipe, a cotton swab, and a bulk method. The initial data showed that greater overall sensitivity was obtained with the QPCR than with culture analysis; however, the QPCR results for bulk samples from residential carpet were negative. The swab kit and the sponge swipe methods were then tested with two levels of background biological contamination consisting of Penicillium chrysogenum spores. The B. subtilis values obtained by the QPCR method were greater than those obtained by culture analysis. The differences between the QPCR and culture data were significant for the samples obtained with the swab kit for all flooring materials except soiled residential carpet and with the sponge swipe for commercial carpet. The QPCR data showed that there were no significant differences between the swab kit and sponge swipe sampling methods for any of the flooring materials. Inhibition of QPCR due solely to biological contamination of flooring materials was not evident. However, some degree of inhibition was observed with the soiled residential carpet, which may have been caused by the presence of abiotic contaminants, alone or in combination with biological contaminants. The results of this research demonstrate the ability of QPCR to enhance detection and enumeration of biocontaminants on surface materials and provide information concerning the comparability of currently available surface sampling methods. PMID:11375164
Segmentation of optic disc and optic cup in retinal fundus images using shape regression.
Sedai, Suman; Roy, Pallab K; Mahapatra, Dwarikanath; Garnavi, Rahil
2016-08-01
Glaucoma is one of the leading cause of blindness. The manual examination of optic cup and disc is a standard procedure used for detecting glaucoma. This paper presents a fully automatic regression based method which accurately segments optic cup and disc in retinal colour fundus image. First, we roughly segment optic disc using circular hough transform. The approximated optic disc is then used to compute the initial optic disc and cup shapes. We propose a robust and efficient cascaded shape regression method which iteratively learns the final shape of the optic cup and disc from a given initial shape. Gradient boosted regression trees are employed to learn each regressor in the cascade. A novel data augmentation approach is proposed to improve the regressors performance by generating synthetic training data. The proposed optic cup and disc segmentation method is applied on an image set of 50 patients and demonstrate high segmentation accuracy for optic cup and disc with dice metric of 0.95 and 0.85 respectively. Comparative study shows that our proposed method outperforms state of the art optic cup and disc segmentation methods.
Extended Kalman filtering for the detection of damage in linear mechanical structures
NASA Astrophysics Data System (ADS)
Liu, X.; Escamilla-Ambrosio, P. J.; Lieven, N. A. J.
2009-09-01
This paper addresses the problem of assessing the location and extent of damage in a vibrating structure by means of vibration measurements. Frequency domain identification methods (e.g. finite element model updating) have been widely used in this area while time domain methods such as the extended Kalman filter (EKF) method, are more sparsely represented. The difficulty of applying EKF in mechanical system damage identification and localisation lies in: the high computational cost, the dependence of estimation results on the initial estimation error covariance matrix P(0), the initial value of parameters to be estimated, and on the statistics of measurement noise R and process noise Q. To resolve these problems in the EKF, a multiple model adaptive estimator consisting of a bank of EKF in modal domain was designed, each filter in the bank is based on different P(0). The algorithm was iterated by using the weighted global iteration method. A fuzzy logic model was incorporated in each filter to estimate the variance of the measurement noise R. The application of the method is illustrated by simulated and real examples.
Texture-based segmentation and analysis of emphysema depicted on CT images
NASA Astrophysics Data System (ADS)
Tan, Jun; Zheng, Bin; Wang, Xingwei; Lederman, Dror; Pu, Jiantao; Sciurba, Frank C.; Gur, David; Leader, J. Ken
2011-03-01
In this study we present a texture-based method of emphysema segmentation depicted on CT examination consisting of two steps. Step 1, a fractal dimension based texture feature extraction is used to initially detect base regions of emphysema. A threshold is applied to the texture result image to obtain initial base regions. Step 2, the base regions are evaluated pixel-by-pixel using a method that considers the variance change incurred by adding a pixel to the base in an effort to refine the boundary of the base regions. Visual inspection revealed a reasonable segmentation of the emphysema regions. There was a strong correlation between lung function (FEV1%, FEV1/FVC, and DLCO%) and fraction of emphysema computed using the texture based method, which were -0.433, -.629, and -0.527, respectively. The texture-based method produced more homogeneous emphysematous regions compared to simple thresholding, especially for large bulla, which can appear as speckled regions in the threshold approach. In the texture-based method, single isolated pixels may be considered as emphysema only if neighboring pixels meet certain criteria, which support the idea that single isolated pixels may not be sufficient evidence that emphysema is present. One of the strength of our complex texture-based approach to emphysema segmentation is that it goes beyond existing approaches that typically extract a single or groups texture features and individually analyze the features. We focus on first identifying potential regions of emphysema and then refining the boundary of the detected regions based on texture patterns.
Analysis of k-means clustering approach on the breast cancer Wisconsin dataset.
Dubey, Ashutosh Kumar; Gupta, Umesh; Jain, Sonal
2016-11-01
Breast cancer is one of the most common cancers found worldwide and most frequently found in women. An early detection of breast cancer provides the possibility of its cure; therefore, a large number of studies are currently going on to identify methods that can detect breast cancer in its early stages. This study was aimed to find the effects of k-means clustering algorithm with different computation measures like centroid, distance, split method, epoch, attribute, and iteration and to carefully consider and identify the combination of measures that has potential of highly accurate clustering accuracy. K-means algorithm was used to evaluate the impact of clustering using centroid initialization, distance measures, and split methods. The experiments were performed using breast cancer Wisconsin (BCW) diagnostic dataset. Foggy and random centroids were used for the centroid initialization. In foggy centroid, based on random values, the first centroid was calculated. For random centroid, the initial centroid was considered as (0, 0). The results were obtained by employing k-means algorithm and are discussed with different cases considering variable parameters. The calculations were based on the centroid (foggy/random), distance (Euclidean/Manhattan/Pearson), split (simple/variance), threshold (constant epoch/same centroid), attribute (2-9), and iteration (4-10). Approximately, 92 % average positive prediction accuracy was obtained with this approach. Better results were found for the same centroid and the highest variance. The results achieved using Euclidean and Manhattan were better than the Pearson correlation. The findings of this work provided extensive understanding of the computational parameters that can be used with k-means. The results indicated that k-means has a potential to classify BCW dataset.
Invasive candidiasis: future directions in non-culture based diagnosis.
Posch, Wilfried; Heimdörfer, David; Wilflingseder, Doris; Lass-Flörl, Cornelia
2017-09-01
Delayed initial antifungal therapy is associated with high mortality rates caused by invasive candida infections, since accurate detection of the opportunistic pathogenic yeast and its identification display a diagnostic challenge. diagnosis of candida infections relies on time-consuming methods such as blood cultures, serologic and histopathologic examination. to allow for fast detection and characterization of invasive candidiasis, there is a need to improve diagnostic tools. trends in diagnostics switch to non-culture-based methods, which allow specified diagnosis within significantly shorter periods of time in order to provide early and appropriate antifungal treatment. Areas covered: within this review comprise novel pathogen- and host-related testing methods, e.g. multiplex-PCR analyses, T2 magnetic resonance, fungus-specific DNA microarrays, microRNA characterization or analyses of IL-17 as biomarker for early detection of invasive candidiasis. Expert commentary: Early recognition and diagnosis of fungal infections is a key issue for improved patient management. As shown in this review, a broad range of novel molecular based tests for the detection and identification of Candida species is available. However, several assays are in-house assays and lack standardization, clinical validation as well as data on sensitivity and specificity. This underscores the need for the development of faster and more accurate diagnostic tests.
Multimodal Sensing Strategy Using pH Dependent Fluorescence Switchable System
NASA Astrophysics Data System (ADS)
Muthurasu, A.; Ganesh, V.
2016-12-01
Biomolecules assisted preparation of fluorescent gold nanoparticles (FL-Au NPs) has been reported in this work using glucose oxidase enzyme as both reducing and stabilizing agent and demonstrated their application through multimodal sensing strategy for selective detection of cysteine (Cys). Three different methods namely fluorescence turn OFF-ON strategy, naked eye detection and electrochemical methods are used for Cys detection by employing FL-Au NPs as a common probe. In case of fluorescence turn-OFF method a strong interaction between Au NPs and thiol results in quenching of fluorescence due to replacement of glucose oxidase by Cys at neutral pH. Second mode is based on fluorescence switch-ON strategy where initial fluorescence is significantly quenched by either excess acid or base and further addition of Cys results in appearance of rosy-red and green fluorescence respectively. Visual colour change and fluorescence emission arises due to etching of Au atoms on the surface by thiol leading to formation of Au nanoclusters. Finally, electrochemical sensing of Cys is also carried out using cyclic voltammetry in 0.1 M PBS solution. These findings provide a suitable platform for Cys detection over a wide range of pH and concentration levels and hence the sensitivity can also be tuned accordingly.
Detection of 22 common leukemic fusion genes using a single-step multiplex qRT-PCR-based assay.
Lyu, Xiaodong; Wang, Xianwei; Zhang, Lina; Chen, Zhenzhu; Zhao, Yu; Hu, Jieying; Fan, Ruihua; Song, Yongping
2017-07-25
Fusion genes generated from chromosomal translocation play an important role in hematological malignancies. Detection of fusion genes currently employ use of either conventional RT-PCR methods or fluorescent in situ hybridization (FISH), where both methods involve tedious methodologies and require prior characterization of chromosomal translocation events as determined by cytogenetic analysis. In this study, we describe a real-time quantitative reverse transcription PCR (qRT-PCR)-based multi-fusion gene screening method with the capacity to detect 22 fusion genes commonly found in leukemia. This method does not require pre-characterization of gene translocation events, thereby facilitating immediate diagnosis and therapeutic management. We performed fluorescent qRT-PCR (F-qRT-PCR) using a commercially-available multi-fusion gene detection kit on a patient cohort of 345 individuals comprising 108 cases diagnosed with acute myeloid leukemia (AML) for initial evaluation; remaining patients within the cohort were assayed for confirmatory diagnosis. Results obtained by F-qRT-PCR were compared alongside patient analysis by cytogenetic characterization. Gene translocations detected by F-qRT-PCR in AML cases were diagnosed in 69.4% of the patient cohort, which was comparatively similar to 68.5% as diagnosed by cytogenetic analysis, thereby demonstrating 99.1% concordance. Overall gene fusion was detected in 53.7% of the overall patient population by F-qRT-PCR, 52.9% by cytogenetic prediction in leukemia, and 9.1% in non-leukemia patients by both methods. The overall concordance rate was calculated to be 99.0%. Fusion genes were detected by F-qRT-PCR in 97.3% of patients with CML, followed by 69.4% with AML, 33.3% with acute lymphoblastic leukemia (ALL), 9.1% with myelodysplastic syndromes (MDS), and 0% with chronic lymphocytic leukemia (CLL). We describe the use of a F-qRT-PCR-based multi-fusion gene screening method as an efficient one-step diagnostic procedure as an effective alternative to lengthy conventional diagnostic procedures requiring both cytogenetic analysis followed by targeted quantitative reverse transcription (qRT-PCR) methods, thus allowing timely patient management.
Zhu, Zhijie; Yu, Xi; Liu, Hailiang; Wang, Huizhu; Fan, Hongwei; Wang, Dawei; Jiang, Guorong; Hong, Min
2014-01-01
Yu-ping-feng-san (YPFS) is a Chinese medical formula that is used clinically for allergic diseases and characterized by reducing allergy relapse. Our previous studies demonstrated that YPFS efficiently inhibited T helper 2 cytokines in allergic inflammation. The underlying mechanisms of action of YPFS and its effective components remain unclear. In this study, it was shown that YPFS significantly inhibited production of thymic stromal lymphopoietin (TSLP), an epithelial cell-derived initiative factor in allergic inflammation, in vitro and in vivo. A method of human bronchial epithelial cell (16HBE) binding combined with HPLC-MS (named 16HBE-HPLC-MS) was established to explore potential active components of YPFS. The following five components bound to 16HBE cells: calycosin-7-glucoside, ononin, claycosin, sec-o-glucosylhamaudol and formononetin. Serum from YPFS-treated mice was analyzed and three major components were detected claycosin, formononetin and cimifugin. Among these, claycosin and formononetin were detected by 16HBE-HPLC-MS and in the serum of YPFS-treated mice. Claycosin and formononetin decreased the level of TSLP markedly at the initial stage of allergic inflammation in vivo. Nuclear factor (NF)-κB, a key transcription factor in TSLP production, was also inhibited by claycosin and formononetin, either in terms of transcriptional activation or its nuclear translocation in vitro. Allergic inflammation was reduced by claycosin and formononetin when they are administered only at the initial stage in a murine model of atopic contact dermatitis. Thus, epithelial cell binding combined with HPLC-MS is a valid method for screening active components from complex mixtures of Chinese medicine. It was demonstrated that the compounds screened from YPFS significantly attenuated allergic inflammation probably by reducing TSLP production via regulating NF-κB activation. PMID:25198676
Multispectral processing based on groups of resolution elements
NASA Technical Reports Server (NTRS)
Richardson, W.; Gleason, J. M.
1975-01-01
Several nine-point rules are defined and compared with previously studied rules. One of the rules performed well in boundary areas, but with reduced efficiency in field interiors; another combined best performance on field interiors with good sensitivity to boundary detail. The basic threshold gradient and some modifications were investigated as a means of boundary point detection. The hypothesis testing methods of closed-boundary formation were also tested and evaluated. An analysis of the boundary detection problem was initiated, employing statistical signal detection and parameter estimation techniques to analyze various formulations of the problem. These formulations permit the atmospheric and sensor system effects on the data to be thoroughly analyzed. Various boundary features and necessary assumptions can also be investigated in this manner.
Overview of field gamma spectrometries based on Si-photomultiplier
NASA Astrophysics Data System (ADS)
Denisov, Viktor; Korotaev, Valery; Titov, Aleksandr; Blokhina, Anastasia; Kleshchenok, Maksim
2017-05-01
Design of optical-electronic devices and systems involves the selection of such technical patterns that under given initial requirements and conditions are optimal according to certain criteria. The original characteristic of the OES for any purpose, defining its most important feature ability is a threshold detection. Based on this property, will be achieved the required functional quality of the device or system. Therefore, the original criteria and optimization methods have to subordinate to the idea of a better detectability. Generally reduces to the problem of optimal selection of the expected (predetermined) signals in the predetermined observation conditions. Thus the main purpose of optimization of the system when calculating its detectability is the choice of circuits and components that provide the most effective selection of a target.
The detection of objects in a turbid underwater medium using orbital angular momentum (OAM)
NASA Astrophysics Data System (ADS)
Cochenour, Brandon; Rodgers, Lila; Laux, Alan; Mullen, Linda; Morgan, Kaitlyn; Miller, Jerome K.; Johnson, Eric G.
2017-05-01
We present an investigation of the optical property of orbital angular momentum (OAM) for use in the detection of objects obscured by a turbid underwater channel. In our experiment, a target is illuminated by a Gaussian beam. An optical vortex is formed by passing the object-reflected and backscattered light through a diffractive spiral phase plate at the receiver, which allows for the spatial separation of coherent and non-coherent light. This provides a method for discriminating target from environment. Initial laboratory results show that the ballistic target return can be detected 2-3 orders of magnitude below the backscatter clutter level. Furthermore, the detection of this coherent component is accomplished with the use of a complicated optical heterodyning scheme. The results suggest new optical sensing techniques for underwater imaging or LIDAR.
Dubois, Eric; Agier, Cécilia; Traoré, Ousmane; Hennechart, Catherine; Merle, Ghislaine; Crucière, Catherine; Laveran, Henri
2002-12-01
Fruits and vegetables may act as a vehicle of human enteric virus if they are irrigated with sewage-contaminated water or prepared by infected food handlers. An elution-concentration method was modified to efficiently detect, by reverse transcriptase-polymerase chain reaction (RT-PCR) or by cell culture, contamination by poliovirus, hepatitis A virus (HAV), and Norwalk-like virus (NLV) of various fresh and frozen berries and fresh vegetables. The protocol included washing the fruit or vegetable surface with 100 mM Tris-HCl, 50 mM glycine, and 3% beef extract, pH 9.5 buffer, which favors viral elution from acid-releasing berries, supplemented with 50 mM MgCl2 to reduce the decrease in viral infectivity during the process. The viral concentration method was based on polyethylene glycol precipitation. Copurified RT-PCR inhibitors and cytotoxic compounds were removed from viral concentrates by chloroform-butanol extraction. Viruses from 100 g of vegetal products could be recovered in volumes of 3 to 5 ml. Viral RNAs were isolated by a spin column method before molecular detection or concentrates were filtered (0.22-microm porosity) and inoculated on cell culture for infectious virus detection. About 15% of infectious poliovirus and 20% of infectious HAV were recovered from frozen raspberry surfaces. The percentage of viral RNA recovery was estimated by RT-PCR to be about 13% for NLV, 17% for HAV, and 45 to 100% for poliovirus. By this method, poliovirus and HAV RNA were detected on products inoculated with a titer of about 5 x 10(1) 50% tissue culture infectious dose per 100 g. NLV RNA was detected at an initial inoculum of 1.2 x 10(3) RT-PCR amplifiable units. This method would be useful for the viral analysis of fruits or vegetables during an epidemiological investigation of foodborne diseases.
2014-01-01
Background Although sophisticated methodologies are available, the use of endpoint polymerase chain reaction (PCR) to detect 16S rDNA genes remains a good approach for estimating the incidence and prevalence of specific infections and for monitoring infections. Considering the importance of the early diagnosis of sexually transmitted infections (STIs), the development of a sensitive and affordable method for identifying pathogens in clinical samples is needed. Highly specific and efficient primers for a multiplex polymerase chain reaction (m-PCR) system were designed in silico to detect the 16S rDNA genes of four bacteria that cause genital infections, and the PCR method was developed. Methods The Genosensor Probe Designer (GPD) (version 1.0a) software was initially used to design highly specific and efficient primers for in-house m-PCR. Single-locus PCR reactions were performed and standardised, and then primers for each locus in turn were added individually in subsequent amplifications until m-PCR was achieved. Amplicons of the expected size were obtained from each of the four bacterial gene fragments. Finally, the analytical specificity and limits of detection were tested. Results Because they did not amplify any product from non-STI tested species, the primers were specific. The detection limits for the Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum primer sets were 5.12 × 105, 3.9 × 103, 61.19 × 106 and 6.37 × 105 copies of a DNA template, respectively. Conclusions The methodology designed and standardised here could be applied satisfactorily for the simultaneous or individual detection of Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum. This method is at least as efficient as other previously described methods; however, this method is more affordable for low-income countries. PMID:24997675
SYBR Green Real-Time PCR Method To Detect Clostridium botulinum Type A▿
Fenicia, Lucia; Anniballi, Fabrizio; De Medici, Dario; Delibato, Elisabetta; Aureli, Paolo
2007-01-01
Botulinum toxins (BoNTs) are classically produced by Clostridium botulinum but rarely also from neurotoxigenic strains of Clostridium baratii and Clostridium butyricum. BoNT type A (BoNT/A), BoNT/B, BoNT/E, and very rarely BoNT/F are mainly responsible for human botulism. Standard microbiological methods take into consideration only the detection of C. botulinum. The presumptive identification of the toxigenic strains together with the typing of BoNT has to be performed by mouse bioassay. The development of PCR-based methods for the detection and typing of BoNT-producing clostridia would be an ideal alternative to the mouse bioassay. The objective of this study was to develop a rapid and robust real-time PCR method for detecting C. botulinum type A. Four different techniques for the extraction and purification of DNA from cultured samples were initially compared. Of the techniques used, Chelex 100, DNeasy tissue kit, InstaGene matrix DNA, and boiling, the boiling technique was significantly less efficient than the other three. These did not give statistically different results, and Chelex 100 was chosen because it was less expensive than the others. In order to eliminate any false-negative results, an internal amplification control was synthesized and included in the amplification mixture according to ISO 22174. The specificity of the method was tested against 75 strains of C. botulinum type A, 4 strains of C. botulinum type Ab, and 101 nontarget strains. The detection limit of the reaction was less than 6 × 101 copies of C. botulinum type A DNA. The robustness of the method was confirmed using naturally contaminated stool specimens to evaluate the tolerance of inhibitor substances. SYBR green real-time PCR showed very high specificity for the detection of C. botulinum types A and Ab (inclusivity and exclusivity, 100%). PMID:17369349
Whole vertebral bone segmentation method with a statistical intensity-shape model based approach
NASA Astrophysics Data System (ADS)
Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer
2011-03-01
An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.
Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)
NASA Astrophysics Data System (ADS)
Saleh Ahmar, Ansari; Guritno, Suryo; Abdurakhman; Rahman, Abdul; Awi; Alimuddin; Minggi, Ilham; Arif Tiro, M.; Kasim Aidid, M.; Annas, Suwardi; Utami Sutiksno, Dian; Ahmar, Dewi S.; Ahmar, Kurniawan H.; Abqary Ahmar, A.; Zaki, Ahmad; Abdullah, Dahlan; Rahim, Robbi; Nurdiyanto, Heri; Hidayat, Rahmat; Napitupulu, Darmawan; Simarmata, Janner; Kurniasih, Nuning; Andretti Abdillah, Leon; Pranolo, Andri; Haviluddin; Albra, Wahyudin; Arifin, A. Nurani M.
2018-01-01
The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt = 0,106+0,204Z t-1+0,401Z t-2-329X 1(t)+115X 2(t)+35,9X 3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.
Clement, Matthew; O'Keefe, Joy M; Walters, Brianne
2015-01-01
While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.
Smith, Emery; Janovick, Jo Ann; Bannister, Thomas D; Shumate, Justin; Scampavia, Louis; Conn, P Michael; Spicer, Timothy P
2016-09-01
Pharmacoperones correct the folding of otherwise misfolded protein mutants, restoring function (i.e., providing "rescue") by correcting their trafficking. Currently, most pharmacoperones possess intrinsic antagonist activity because they were identified using methods initially aimed at discovering such functions. Here, we describe an ultra-high-throughput homogeneous cell-based assay with a cAMP detection system, a method specifically designed to identify pharmacoperones of the vasopressin type 2 receptor (V2R), a GPCR that, when mutated, is associated with nephrogenic diabetes insipidus. Previously developed methods to identify compounds capable of altering cellular trafficking of V2R were modified and used to screen a 645,000 compound collection by measuring the ability of library compounds to rescue a mutant hV2R [L83Q], using a cell-based luminescent detection system. The campaign initially identified 3734 positive modulators of cAMP. The confirmation and counterscreen identified only 147 of the active compounds with an EC50 of ≤5 µM. Of these, 83 were reconfirmed as active through independently obtained pure samples and were also inactive in a relevant counterscreen. Active and tractable compounds within this set can be categorized into three predominant structural clusters, described here, in the first report detailing the results of a large-scale pharmacoperone high-throughput screening campaign. © 2016 Society for Laboratory Automation and Screening.
Zhang, Ying-Ying; Yang, Cai; Zhang, Ping
2017-08-01
In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.
Arabski, Michał; Wasik, Sławomir; Piskulak, Patrycja; Góźdź, Natalia; Slezak, Andrzej; Kaca, Wiesław
2011-01-01
The aim of this study was to analysis of antibiotics (ampicilin, streptomycin, ciprofloxacin or colistin) release from agarose gel by spectrophotmetry and laser interferometry methods. The interferometric system consisted of a Mach-Zehnder interferometer with a He-Ne laser, TV-CCD camera, computerised data acquisition system and a gel system. The gel system under study consists of two cuvettes. We filled the lower cuvette with an aqueous 1% agarose solution with the antibiotics at initial concentration of antibiotics in the range of 0.12-2 mg/ml for spectrophotmetry analysis or 0.05-0.5 mg/ml for laser interferometry methods, while in the upper cuvette there was pure water. The diffusion was analysed from 120 to 2400 s with a time interval of deltat = 120 s by both methods. We observed that 0.25-1 mg/ml and 0,05 mg/ml are minimal initial concentrations detected by spectrophotometric and laser interferometry methods, respectively. Additionally, we observed differences in kinetic of antibiotic diffusion from gel measured by both methods. In conclusion, the laser interferometric method is a useful tool for studies of antibiotic release from agarose gel, especially for substances are not fully soluble in water, for example: colistin.
Abdelaziz, Marwa; Krejci, Ivo; Perneger, Thomas; Feilzer, Albert; Vazquez, Lydia
2018-03-01
To compare near infrared transillumination device, DIAGNOcam (DC) and bitewing radiography (BW) for the detection of proximal caries. This retrospective analysis of DC and BW images of 18 students in dental medicine who had consented to the anonymous use of their dental record. The data included BW and DC images performed for a check-up in 2013, and corresponding follow-up images performed in 2015. Two observers rated 376 proximal surfaces on a 4-level dentin lesion scale and reached a unanimous rating for each surface. Calculated measures of agreement for each assessment method over time provided the reproducibility of the information obtained by each method. Agreement between 2013 and 2015 within each method was excellent (intraclass correlation coefficient, BW: 0.86, DC: 0.90). Agreement between DC and BW was similar for dentin lesion detection, but was low for enamel caries detection; DC detected more enamel caries than BW. Agreement between DC and BW was modest (0.33 in 2013 and 0.36 in 2015), chiefly because DC identified more enamel caries. This study shows that DC is as reliable as BW to detect proximal dentin lesions. DC detects proximal enamel lesions at an earlier stage than BW. DC enables clinicians to differentiate lesions limited to the enamel from lesions that have reached the enamel dentin junction. Regular monitoring with DC should help provide individualized preventive measures and early non-invasive caries management. The early detection of enamel lesions with near infrared transillumination can help clinicians undertake early non invasive treatments to prevent or slow down the progression of initial proximal lesions. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mijailovic, Aleksandar S; Qing, Bo; Fortunato, Daniel; Van Vliet, Krystyn J
2018-04-15
Precise and accurate measurement of viscoelastic mechanical properties becomes increasingly challenging as sample stiffness decreases to elastic moduli <1 kPa, largely due to difficulties detecting initial contact with the compliant sample surface. This limitation is particularly relevant to characterization of biological soft tissues and compliant gels. Here, we employ impact indentation which, in contrast to shear rheology and conventional indentation, does not require contact detection a priori, and present a novel method to extract viscoelastic moduli and relaxation time constants directly from the impact response. We first validate our approach by using both impact indentation and shear rheology to characterize polydimethylsiloxane (PDMS) elastomers of stiffness ranging from 100 s of Pa to nearly 10 kPa. Assuming a linear viscoelastic constitutive model for the material, we find that the moduli and relaxation times obtained from fitting the impact response agree well with those obtained from fitting the rheological response. Next, we demonstrate our validated method on hydrated, biological soft tissues obtained from porcine brain, murine liver, and murine heart, and report the equilibrium shear moduli, instantaneous shear moduli, and relaxation time constants for each tissue. Together, our findings provide a new and straightforward approach capable of probing local mechanical properties of highly compliant viscoelastic materials with millimeter scale spatial resolution, mitigating complications involving contact detection or sample geometric constraints. Characterization and optimization of mechanical properties can be essential for the proper function of biomaterials in diverse applications. However, precise and accurate measurement of viscoelastic mechanical properties becomes increasingly difficult with increased compliance (particularly for elastic moduli <1 kPa), largely due to challenges detecting initial contact with the compliant sample surface and measuring response at short timescale or high frequency. By contrast, impact indentation has highly accurate contact detection and can be used to measure short timescale (glassy) response. Here, we demonstrate an experimental and analytical method that confers significant advantages over existing approaches to extract spatially resolved viscoelastic moduli and characteristic time constants of biological tissues (e.g., brain and heart) and engineered biomaterials. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Cano, I; Ferro, P; Alonso, M C; Bergmann, S M; Römer-Oberdörfer, A; Garcia-Rosado, E; Castro, D; Borrego, J J
2007-01-01
The development and evaluation of a protocol based on polymerase chain reaction (PCR) and nucleic acid hybridization techniques for the specific detection of lymphocystis disease virus (LCDV) in several marine fish species. The pair of primers for PCR, OBL3 and OBL4, was designed based on published nucleotide sequence (LCDV-1) and amplifies a fragment within the major capsid protein. The sensitivity was evaluated using DNA from purified viral particles, as well as from cells inoculated with several viral concentrations. The PCR combined with slot blot was the most sensitive methodology, detecting 2.5 ng of viral DNA. Using this methodology LCDV was detected at 5 days postinoculation from SAF-1 cells initially inoculated with 10(-5) TCID(50) ml(-1). The combination of PCR with membrane hybridization has also been proved to be adequate to detect LCDV from apparently healthy carriers by means of caudal fin sample analysis. This asymptomatic infection was also demonstrated by classical virological methods (cell culture and immunoblot). The protocol described in this study allows the specific detection of LCDV, both in cell cultures and in fin homogenates from asymptomatic fish. The detection of asymptomatic carriers by a rapid molecular method using caudal fin sampling, which does not imply animal killing, could be an important tool to control epizootics caused by LCDV, as fish could be analysed before their introduction and/or mobilization in farm facilities.
Geng, Yunyun; Wang, Jianchang; Liu, Libing; Lu, Yan; Tan, Ke; Chang, Yan-Zhong
2017-11-06
Canine parvovirus 2, a linear single-stranded DNA virus belonging to the genus Parvovirus within the family Parvoviridae, is a highly contagious pathogen of domestic dogs and several wild canidae species. Early detection of canine parvovirus (CPV-2) is crucial to initiating appropriate outbreak control strategies. Recombinase polymerase amplification (RPA), a novel isothermal gene amplification technique, has been developed for the molecular detection of diverse pathogens. In this study, a real-time RPA assay was developed for the detection of CPV-2 using primers and an exo probe targeting the CPV-2 nucleocapsid protein gene. The real-time RPA assay was performed successfully at 38 °C, and the results were obtained within 4-12 min for 10 5 -10 1 molecules of template DNA. The assay only detected CPV-2, and did not show cross-detection of other viral pathogens, demonstrating a high level of specificity. The analytical sensitivity of the real-time RPA was 10 1 copies/reaction of a standard DNA template, which was 10 times more sensitive than the common RPA method. The clinical sensitivity of the real-time RPA assay matched 100% (n = 91) to the real-time PCR results. The real-time RPA assay is a simple, rapid, reliable and affordable method that can potentially be applied for the detection of CPV-2 in the research laboratory and point-of-care diagnosis.
Nika, Varvara; Babyn, Paul; Zhu, Hongmei
2014-07-01
Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.
Equilibrium sampling by reweighting nonequilibrium simulation trajectories
NASA Astrophysics Data System (ADS)
Yang, Cheng; Wan, Biao; Xu, Shun; Wang, Yanting; Zhou, Xin
2016-03-01
Based on equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space of complex systems, which are separated into some metastable regions by high free energy barriers. Nonequilibrium simulations could enhance transitions among these metastable regions and then be applied to sample equilibrium distributions in complex systems, since the associated nonequilibrium effects can be removed by employing the Jarzynski equality (JE). Here we present such a systematical method, named reweighted nonequilibrium ensemble dynamics (RNED), to efficiently sample equilibrium conformations. The RNED is a combination of the JE and our previous reweighted ensemble dynamics (RED) method. The original JE reproduces equilibrium from lots of nonequilibrium trajectories but requires that the initial distribution of these trajectories is equilibrium. The RED reweights many equilibrium trajectories from an arbitrary initial distribution to get the equilibrium distribution, whereas the RNED has both advantages of the two methods, reproducing equilibrium from lots of nonequilibrium simulation trajectories with an arbitrary initial conformational distribution. We illustrated the application of the RNED in a toy model and in a Lennard-Jones fluid to detect its liquid-solid phase coexistence. The results indicate that the RNED sufficiently extends the application of both the original JE and the RED in equilibrium sampling of complex systems.
Equilibrium sampling by reweighting nonequilibrium simulation trajectories.
Yang, Cheng; Wan, Biao; Xu, Shun; Wang, Yanting; Zhou, Xin
2016-03-01
Based on equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space of complex systems, which are separated into some metastable regions by high free energy barriers. Nonequilibrium simulations could enhance transitions among these metastable regions and then be applied to sample equilibrium distributions in complex systems, since the associated nonequilibrium effects can be removed by employing the Jarzynski equality (JE). Here we present such a systematical method, named reweighted nonequilibrium ensemble dynamics (RNED), to efficiently sample equilibrium conformations. The RNED is a combination of the JE and our previous reweighted ensemble dynamics (RED) method. The original JE reproduces equilibrium from lots of nonequilibrium trajectories but requires that the initial distribution of these trajectories is equilibrium. The RED reweights many equilibrium trajectories from an arbitrary initial distribution to get the equilibrium distribution, whereas the RNED has both advantages of the two methods, reproducing equilibrium from lots of nonequilibrium simulation trajectories with an arbitrary initial conformational distribution. We illustrated the application of the RNED in a toy model and in a Lennard-Jones fluid to detect its liquid-solid phase coexistence. The results indicate that the RNED sufficiently extends the application of both the original JE and the RED in equilibrium sampling of complex systems.
NASA Astrophysics Data System (ADS)
Poudel, Joemini; Matthews, Thomas P.; Mitsuhashi, Kenji; Garcia-Uribe, Alejandro; Wang, Lihong V.; Anastasio, Mark A.
2017-03-01
Photoacoustic computed tomography (PACT) is an emerging computed imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the photoacoustically induced initial pressure distribution within tissue. The PACT reconstruction problem corresponds to a time-domain inverse source problem, where the initial pressure distribution is recovered from the measurements recorded on an aperture outside the support of the source. A major challenge in transcranial PACT brain imaging is to compensate for aberrations in the measured data due to the propagation of the photoacoustic wavefields through the skull. To properly account for these effects, a wave equation-based inversion method should be employed that can model the heterogeneous elastic properties of the medium. In this study, an iterative image reconstruction method for 3D transcranial PACT is developed based on the elastic wave equation. To accomplish this, a forward model based on a finite-difference time-domain discretization of the elastic wave equation is established. Subsequently, gradient-based methods are employed for computing penalized least squares estimates of the initial source distribution that produced the measured photoacoustic data. The developed reconstruction algorithm is validated and investigated through computer-simulation studies.
NASA Technical Reports Server (NTRS)
Cleary, T.; Grosshandler, W.
1999-01-01
As part of the National Aeronautics and Space Administration (NASA) initiated program on global civil aviation, NIST is assisting Federal Aviation Administration in its research to improve fire detection in aircraft cargo compartments. Aircraft cargo compartment detection certification methods have been reviewed. The Fire Emulator-Detector Evaluator (FE/DE) has been designed to evaluate fire detection technologies such as new sensors, multi-element detectors, and detectors that employ complex algorithms. The FE/DE is a flow tunnel that can reproduce velocity, temperature, smoke, and Combustion gas levels to which a detector might be exposed during a fire. A scientific literature survey and patent search have been conducted relating to existing and emerging fire detection technologies, and the potential use of new fire detection strategies in cargo compartment areas has been assessed. In the near term, improved detector signal processing and multi-sensor detectors based on combinations of smoke measurements, combustion gases and temperature are envisioned as significantly impacting detector system performance.
NASA Astrophysics Data System (ADS)
Mohammad, Fatimah; Ansari, Rashid; Shahidi, Mahnaz
2013-03-01
The visibility and continuity of the inner segment outer segment (ISOS) junction layer of the photoreceptors on spectral domain optical coherence tomography images is known to be related to visual acuity in patients with age-related macular degeneration (AMD). Automatic detection and segmentation of lesions and pathologies in retinal images is crucial for the screening, diagnosis, and follow-up of patients with retinal diseases. One of the challenges of using the classical level-set algorithms for segmentation involves the placement of the initial contour. Manually defining the contour or randomly placing it in the image may lead to segmentation of erroneous structures. It is important to be able to automatically define the contour by using information provided by image features. We explored a level-set method which is based on the classical Chan-Vese model and which utilizes image feature information for automatic contour placement for the segmentation of pathologies in fluorescein angiograms and en face retinal images of the ISOS layer. This was accomplished by exploiting a priori knowledge of the shape and intensity distribution allowing the use of projection profiles to detect the presence of pathologies that are characterized by intensity differences with surrounding areas in retinal images. We first tested our method by applying it to fluorescein angiograms. We then applied our method to en face retinal images of patients with AMD. The experimental results included demonstrate that the proposed method provided a quick and improved outcome as compared to the classical Chan-Vese method in which the initial contour is randomly placed, thus indicating the potential to provide a more accurate and detailed view of changes in pathologies due to disease progression and treatment.
NASA Astrophysics Data System (ADS)
Bhatia, Parmeet S.; Reda, Fitsum; Harder, Martin; Zhan, Yiqiang; Zhou, Xiang Sean
2017-02-01
Automatically detecting anatomy orientation is an important task in medical image analysis. Specifically, the ability to automatically detect coarse orientation of structures is useful to minimize the effort of fine/accurate orientation detection algorithms, to initialize non-rigid deformable registration algorithms or to align models to target structures in model-based segmentation algorithms. In this work, we present a deep convolution neural network (DCNN)-based method for fast and robust detection of the coarse structure orientation, i.e., the hemi-sphere where the principal axis of a structure lies. That is, our algorithm predicts whether the principal orientation of a structure is in the northern hemisphere or southern hemisphere, which we will refer to as UP and DOWN, respectively, in the remainder of this manuscript. The only assumption of our method is that the entire structure is located within the scan's field-of-view (FOV). To efficiently solve the problem in 3D space, we formulated it as a multi-planar 2D deep learning problem. In the training stage, a large number coronal-sagittal slice pairs are constructed as 2-channel images to train a DCNN to classify whether a scan is UP or DOWN. During testing, we randomly sample a small number of coronal-sagittal 2-channel images and pass them through our trained network. Finally, coarse structure orientation is determined using majority voting. We tested our method on 114 Elbow MR Scans. Experimental results suggest that only five 2-channel images are sufficient to achieve a high success rate of 97.39%. Our method is also extremely fast and takes approximately 50 milliseconds per 3D MR scan. Our method is insensitive to the location of the structure in the FOV.
An automatic segmentation method of a parameter-adaptive PCNN for medical images.
Lian, Jing; Shi, Bin; Li, Mingcong; Nan, Ziwei; Ma, Yide
2017-09-01
Since pre-processing and initial segmentation steps in medical images directly affect the final segmentation results of the regions of interesting, an automatic segmentation method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two segmentation steps into one. This method has a low computational complexity for different kinds of medical images and has a high segmentation precision. The method comprises four steps. Firstly, an optimal histogram threshold is used to determine the parameter [Formula: see text] for different kinds of images. Secondly, we acquire the parameter [Formula: see text] according to a simplified pulse-coupled neural network (SPCNN). Thirdly, we redefine the parameter V of the SPCNN model by sub-intensity distribution range of firing pixels. Fourthly, we add an offset [Formula: see text] to improve initial segmentation precision. Compared with the state-of-the-art algorithms, the new method achieves a comparable performance by the experimental results from ultrasound images of the gallbladder and gallstones, magnetic resonance images of the left ventricle, and mammogram images of the left and the right breast, presenting the overall metric UM of 0.9845, CM of 0.8142, TM of 0.0726. The algorithm has a great potential to achieve the pre-processing and initial segmentation steps in various medical images. This is a premise for assisting physicians to detect and diagnose clinical cases.
Rawstron, A C; Fazi, C; Agathangelidis, A; Villamor, N; Letestu, R; Nomdedeu, J; Palacio, C; Stehlikova, O; Kreuzer, K-A; Liptrot, S; O'Brien, D; de Tute, R M; Marinov, I; Hauwel, M; Spacek, M; Dobber, J; Kater, A P; Gambell, P; Soosapilla, A; Lozanski, G; Brachtl, G; Lin, K; Boysen, J; Hanson, C; Jorgensen, J L; Stetler-Stevenson, M; Yuan, C; Broome, H E; Rassenti, L; Craig, F; Delgado, J; Moreno, C; Bosch, F; Egle, A; Doubek, M; Pospisilova, S; Mulligan, S; Westerman, D; Sanders, C M; Emerson, R; Robins, H S; Kirsch, I; Shanafelt, T; Pettitt, A; Kipps, T J; Wierda, W G; Cymbalista, F; Hallek, M; Hillmen, P; Montserrat, E; Ghia, P
2016-04-01
In chronic lymphocytic leukemia (CLL) the level of minimal residual disease (MRD) after therapy is an independent predictor of outcome. Given the increasing number of new agents being explored for CLL therapy, using MRD as a surrogate could greatly reduce the time necessary to assess their efficacy. In this European Research Initiative on CLL (ERIC) project we have identified and validated a flow-cytometric approach to reliably quantitate CLL cells to the level of 0.0010% (10(-5)). The assay comprises a core panel of six markers (i.e. CD19, CD20, CD5, CD43, CD79b and CD81) with a component specification independent of instrument and reagents, which can be locally re-validated using normal peripheral blood. This method is directly comparable to previous ERIC-designed assays and also provides a backbone for investigation of new markers. A parallel analysis of high-throughput sequencing using the ClonoSEQ assay showed good concordance with flow cytometry results at the 0.010% (10(-4)) level, the MRD threshold defined in the 2008 International Workshop on CLL guidelines, but it also provides good linearity to a detection limit of 1 in a million (10(-6)). The combination of both technologies would permit a highly sensitive approach to MRD detection while providing a reproducible and broadly accessible method to quantify residual disease and optimize treatment in CLL.
Chen, Xiancheng; Gan, Weidong; Ye, Qing; Yang, Jun; Guo, Hongqian; Li, Dongmei
2014-12-16
To explore the value of self-designed fluorescent in situ hybridization (FISH) polyclonal break-apart probes specific for TFE3 gene in the diagnosis of Xp11.2 translocation renal cell carcinoma. All tissue samples were collected from 2006 to 2013, including Xp11.2 translocation renal cell carcinoma (n = 10), renal clear cell carcinoma (n = 10) and renal papillary cell carcinoma (n = 10). FISH was conducted for paraffin-embedded tumor tissue sections with probes. The types of fluorescence were observed by fluorescent microscopy to determine the existence or non-existence of translocated TFE3 gene. All sections were successfully probed. The split red and green signals within a single nucleus were detected simultaneously in 9 cases of Xp11.2 translocation renal cell carcinoma as diagnosed by traditional pathological and immunohistochemical methods. And it was consistent with the initial diagnosis. Detection of fusion signal in 1/10 and negative FISH result did not conform to the initial diagnosis. The fluorescent types of renal clear cell carcinoma and renal papillary cell carcinoma were all fusion signals. FISH tests were negative for renal clear and papillary cell carcinomas. Xp11.2 translocation renal cell carcinomas diagnosed by traditional pathological and immunohistochemical methods are sometimes misdiagnosed. Detecting the translocation of TFE3 gene with FISH polyclonal break-apart probes is both accurate and reliable for diagnosing Xp11.2 translocation renal cell carcinoma.
Della, Lindsay J.; DeJoy, David M.; Goetzel, Ron Z.; Ozminkowski, Ronald J.; Wilson, Mark G.
2009-01-01
Objective This paper describes the development of the Leading by Example (LBE) instrument. Methods Exploratory factor analysis was used to obtain an initial factor structure. Factor validity was evaluated using confirmatory factor analysis methods. Cronbach’s alpha and item-total correlations provided information on the reliability of the factor subscales. Results Four subscales were identified: business alignment with health promotion objectives; awareness of the health-productivity link; worksite support for health promotion; leadership support for health promotion. Factor by group comparisons revealed that the initial factor structure is effective in detecting differences in organizational support for health promotion across different employee groups Conclusions Management support for health promotion can be assessed using the LBE, a brief, self-report questionnaire. Researchers can use the LBE to diagnose, track, and evaluate worksite health promotion programs. PMID:18517097
Natural frequency identification of smart washer by using adaptive observer
NASA Astrophysics Data System (ADS)
Ito, Hitoshi; Okugawa, Masayuki
2014-04-01
Bolted joints are used in many machines/structures and some of them have been loosened during long time use, and unluckily these bolt loosening may cause a great accident of machines/structures system. These bolted joint, especially in important places, are main object of maintenance inspection. Maintenance inspection with human- involvement is desired to be improved owing to time-consuming, labor-intensive and high-cost. By remote and full automation monitoring of the bolt loosening, constantly monitoring of bolted joint is achieved. In order to detect loosening of bolted joints without human-involvement, applying a structural health monitoring technique and smart structures/materials concept is the key objective. In this study, a new method of bolt loosening detection by adopting a smart washer has been proposed, and the basic detection principle was discussed with numerical analysis about frequency equation of the system, was confirmed experimentally. The smart washer used in this study is in cantilever type with piezoelectric material, which adds the washer the self-sensing and actuation function. The principle used to detect the loosening of the bolts is a method of a bolt loosening detection noted that the natural frequency of a smart washer system is decreasing by the change of the bolt tightening axial tension. The feature of this proposed method is achieving to identify the natural frequency at current condition on demand by adopting the self-sensing and actuation function and system identification algorithm for varying the natural frequency depending the bolt tightening axial tension. A novel bolt loosening detection method by adopting adaptive observer is proposed in this paper. The numerical simulations are performed to verify the possibility of the adaptive observer-based loosening detection. Improvement of the detection accuracy for a bolt loosening is confirmed by adopting initial parameter and variable adaptive gain by numerical simulation.
Wang, Jiamian; Wang, Xiuyun; Wu, Shuo; Che, Ruping; Luo, Pinchen; Meng, Changgong
2017-01-15
A facile label-free sensing method is developed for the one-step and highly sensitive fluorescent detection of DNA, which couples the specific C-C mismatch bonding and fluorescent quenching property of a trimethyl-substituted naphthyridine dye (ATMND) with the exonuclease III (Exo III) assisted cascade target recycling amplification strategy. In the absence of target DNA, the DNA hairpin probe with a C-C mismatch in the stem and more than 4 bases overhung at the 3' terminus could entrap and quench the fluorescence of ATMND and resist the digestion of Exo III, thus showing a low fluorescence background. In the presence of the target, however, the hybridization event between the two protruding segments and the target triggers the digestion reaction of Exo III, recycles the initial target, and simultaneously releases both the secondary target analogue and the ATMND caged in the stem. The released initial and secondary targets take part in another cycle of digestion, thus leading to the release of a huge amount of free ATMND for signal transducing. Based on the fluorescence recovery, the as-proposed label-free fluorescent sensing strategy shows very good analytical performances towards DNA detection, such as a wide linear range from 10pM to 1μM, a low limit of detection of 6pM, good selectivity, and a facile one-step operation at room temperature. Practical sample analysis in serum samples indicates the method has good precision and accuracy, which may thus have application potentials for point-of-care screening of DNA in complex clinical and environmental samples. Copyright © 2016 Elsevier B.V. All rights reserved.
Riahi, Aouatef; Kharrat, Maher; Lariani, Imen; Chaabouni-Bouhamed, Habiba
2014-12-01
Germline deleterious mutations in the BRCA1/BRCA2 genes are associated with an increased risk for the development of breast and ovarian cancer. Given the large size of these genes the detection of such mutations represents a considerable technical challenge. Therefore, the development of cost-effective and rapid methods to identify these mutations became a necessity. High resolution melting analysis (HRM) is a rapid and efficient technique extensively employed as high-throughput mutation scanning method. The purpose of our study was to assess the specificity and sensitivity of HRM for BRCA1 and BRCA2 genes scanning. As a first step we estimate the ability of HRM for detection mutations in a set of 21 heterozygous samples harboring 8 different known BRCA1/BRCA2 variations, all samples had been preliminarily investigated by direct sequencing, and then we performed a blinded analysis by HRM in a set of 68 further sporadic samples of unknown genotype. All tested heterozygous BRCA1/BRCA2 variants were easily identified. However the HRM assay revealed further alteration that we initially had not searched (one unclassified variant). Furthermore, sequencing confirmed all the HRM detected mutations in the set of unknown samples, including homozygous changes, indicating that in this cohort, with the optimized assays, the mutations detections sensitivity and specificity were 100 %. HRM is a simple, rapid and efficient scanning method for known and unknown BRCA1/BRCA2 germline mutations. Consequently the method will allow for the economical screening of recurrent mutations in Tunisian population.
A Simple Method for Automated Equilibration Detection in Molecular Simulations.
Chodera, John D
2016-04-12
Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure and demonstrate its utility on typical molecular simulation data.
A simple method for automated equilibration detection in molecular simulations
Chodera, John D.
2016-01-01
Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest, in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure, and demonstrate its utility on typical molecular simulation data. PMID:26771390
Ito, Kentaro; Suzuki, Yuta; Saiki, Haruko; Sakaguchi, Tadashi; Hayashi, Kosuke; Nishii, Yoichi; Watanabe, Fumiaki; Hataji, Osamu
2018-03-01
The clinical benefit of liquid biopsy for unselected patients at initial diagnosis has thus far been unclear. We aimed to evaluate the utility of liquid biopsy at initial diagnosis, as well as the efficacy of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) based on liquid biopsy results in clinical practice, using the improved peptide nucleic acid-locked nucleic acid (PNA-LNA) PCR clamp method. We routinely performed liquid biopsy using the improved PNA-LNA PCR clamp method for all patients diagnosed with non-small-cell lung cancer (NSCLC) between June 2015 and October 2016. We retrospectively evaluated the reliability of liquid biopsy based either on clinical stage or between sensitizing EGFR mutation and T790M mutation, and the clinical benefit of EGFR-TKI based on the liquid biopsy results in practice. A total of 244 patients underwent liquid biopsies, with 168 patients tested at diagnosis and 22 tested for T790M after pretreatment of EGFR-TKI. For detecting a sensitizing EGFR mutation, the sensitivity, specificity, positive predictive value, and negative predictive value were 72.7%, 100%, 100%, and 93.7% in the group with advanced-stage NSCLC and 0, 100%, not evaluable, and 70.5% in the group with early-stage NSCLC. The positive predictive value and negative predictive value for T790M were 33.3% and 55.6%, respectively. Fourteen patients in the liquid-positive group and 16 patients in the tissue-positive group received EGFR-TKI. The objective response rates of first- and second-generation EGFR-TKI for the liquid-positive and tissue-positive groups were 90.0% and 90.9%, respectively. There was no significant difference in median progression-free survival between the liquid-positive and tissue-positive groups (P = .839). Patients with early-stage NSCLC should not be candidates for this liquid biopsy method. We recommend tissue biopsy as the preferred initial method of molecular analysis, with the exception of patients who are T790M positive or patients who are unable to tolerate invasive biopsy. Copyright © 2017 Elsevier Inc. All rights reserved.
Fourier Method for Calculating Fission Chain Neutron Multiplicity Distributions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chambers, David H.; Chandrasekaran, Hema; Walston, Sean E.
Here, a new way of utilizing the fast Fourier transform is developed to compute the probability distribution for a fission chain to create n neutrons. We then extend this technique to compute the probability distributions for detecting n neutrons. Lastly, our technique can be used for fission chains initiated by either a single neutron inducing a fission or by the spontaneous fission of another isotope.
Fourier Method for Calculating Fission Chain Neutron Multiplicity Distributions
Chambers, David H.; Chandrasekaran, Hema; Walston, Sean E.
2017-03-27
Here, a new way of utilizing the fast Fourier transform is developed to compute the probability distribution for a fission chain to create n neutrons. We then extend this technique to compute the probability distributions for detecting n neutrons. Lastly, our technique can be used for fission chains initiated by either a single neutron inducing a fission or by the spontaneous fission of another isotope.
Environmental DNA as a Tool for Inventory and Monitoring of Aquatic Vertebrates
2017-07-01
geomorphic calculations and description of each reach. Methods Channel Surveys We initially selected reaches based on access and visual indicators...WA 99164 I-2 Environmental DNA lab protocol: designing species-specific qPCR assays Species-specific surveys should use quantitative polymerase...to traditional field sampling with respect to sensitivity, detection probabilities, and cost efficiency. Compared to field surveys , eDNA sampling
3D registration of surfaces for change detection in medical images
NASA Astrophysics Data System (ADS)
Fisher, Elizabeth; van der Stelt, Paul F.; Dunn, Stanley M.
1997-04-01
Spatial registration of data sets is essential for quantifying changes that take place over time in cases where the position of a patient with respect to the sensor has been altered. Changes within the region of interest can be problematic for automatic methods of registration. This research addresses the problem of automatic 3D registration of surfaces derived from serial, single-modality images for the purpose of quantifying changes over time. The registration algorithm utilizes motion-invariant, curvature- based geometric properties to derive an approximation to an initial rigid transformation to align two image sets. Following the initial registration, changed portions of the surface are detected and excluded before refining the transformation parameters. The performance of the algorithm was tested using simulation experiments. To quantitatively assess the registration, random noise at various levels, known rigid motion transformations, and analytically-defined volume changes were applied to the initial surface data acquired from models of teeth. These simulation experiments demonstrated that the calculated transformation parameters were accurate to within 1.2 percent of the total applied rotation and 2.9 percent of the total applied translation, even at the highest applied noise levels and simulated wear values.
Nokhbatolfoghahaie, Hanieh; Alikhasi, Marzieh; Chiniforush, Nasim; Khoei, Farzaneh; Safavi, Nassimeh; Yaghoub Zadeh, Behnoush
2013-01-01
Introduction: Today the prevalence of teeth decays has considerably decreased. Related organizations and institutions mention several reasons for it such as improvement of decay diagnostic equipment and tools which are even capable of detecting caries in their initial stages. This resulted in reduction of costs for patients and remarkable increase in teeth life span. There are many methods for decay diagnostic, like: visual and radiographic methods, devices with fluorescence such as Quantitative light-induced fluorescence (QLF), Vista proof, Laser fluorescence (LF or DIAGNOdent), Fluorescence Camera (FC) and Digital radiography. Although DIAGNOdent is considered a valuable device for decay diagnostic ,there are concerns regarding its efficacy and accuracy. Considering the sensitivity of decaydiagnosis and the exorbitant annual expenses supported by government and people for caries treatment, finding the best method for early caries detection is of the most importance. Numerous studies were performed to compare different diagnostic methods with conflicting results. The objective of this study is a comparative review of the efficiency of DIAGNOdent in comparison to visual methods and radiographic methods in the diagnostic of teeth occlusal surfaces. Methods: Search of PubMed, Google Scholar electronic resources was performed in order to find clinical trials in English in the period between 1998 and 2013. Full texts of only 35 articles were available. Conclusion: Considering the sensitivity and specificity reported in the different studies, it seems that DIAGNOdent is an appropriate modality for caries detection as a complementary method beside other methods and its use alone to obtain treatment plan is not enough. PMID:25606325
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
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gorham, P.W.; /Hawaii U.; Allison, P.
We report initial results of the Antarctic Impulsive Transient Antenna (ANITA) 2006-2007 Long Duration Balloon flight, which searched for evidence of the flux of cosmogenic neutrinos. ANITA flew for 35 days looking for radio impulses that might be due to the Askaryan effect in neutrino-induced electromagnetic showers within the Antarctic ice sheets. In our initial high-threshold robust analysis, no neutrino candidates are seen, with no physics background. In a non-signal horizontal-polarization channel, we do detect 6 events consistent with radio impulses from extensive air showers, which helps to validate the effectiveness of our method. Upper limits derived from our analysismore » now begin to eliminate the highest cosmogenic neutrino models.« less
Requirements UML Tool (RUT) Expanded for Extreme Programming (CI02)
NASA Technical Reports Server (NTRS)
McCoy, James R.
2003-01-01
A procedure for capturing and managing system requirements that incorporates XP user stories. Because costs associated with identifying problems in requirements increase dramatically over the lifecycle of a project, a method for identifying sources of software risks in user stories is urgently needed. This initiative aims to determine a set of guide-lines for user stories that will result in high-quality requirement. To further this initiative, a tool is needed to analyze user stories that can assess the quality of individual user stories, detect sources cf software risk's, produce software metrics, and identify areas in user stories that can be improved.
Ye, Tao; Wang, Baocheng; Song, Ping; Li, Juan
2018-06-12
Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN) is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net). It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.
Detecting nonlinearity and chaos in epidemic data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ellner, S.; Gallant, A.R.; Theiler, J.
1993-08-01
Historical data on recurrent epidemics have been central to the debate about the prevalence of chaos in biological population dynamics. Schaffer and Kot who first recognized that the abundance and accuracy of disease incidence data opened the door to applying a range of methods for detecting chaos that had been devised in the early 1980`s. Using attractor reconstruction, estimates of dynamical invariants, and comparisons between data and simulation of SEIR models, the ``case for chaos in childhood epidemics`` was made through a series of influential papers beginning in the mid 1980`s. The proposition that the precise timing and magnitude ofmore » epidemic outbreaks are deterministic but chaotic is appealing, since it raises the hope of finding determinism and simplicity beneath the apparently stochastic and complicated surface of the data. The initial enthusiasm for methods of detecting chaos in data has been followed by critical re-evaluations of their limitations. Early hopes of a ``one size fits all`` algorithm to diagnose chaos vs. noise in any data set have given way to a recognition that a variety of methods must be used, and interpretation of results must take into account the limitations of each method and the imperfections of the data. Our goals here are to outline some newer methods for detecting nonlinearity and chaos that have a solid statistical basis and are suited to epidemic data, and to begin a re-evaluation of the claims for nonlinear dynamics and chaos in epidemics using these newer methods. We also identify features of epidemic data that create problems for the older, better known methods of detecting chaos. When we ask ``are epidemics nonlinear?``, we are not questioning the existence of global nonlinearities in epidemic dynamics, such as nonlinear transmission rates. Our question is whether the data`s deviations from an annual cyclic trend (which would reflect global nonlinearities) are described by a linear, noise-driven stochastic process.« less
Elsa, Jourdain; Duron, Olivier; Séverine, Barry; González-Acuña, Daniel; Sidi-Boumedine, Karim
2015-01-01
Background Q fever is a widespread zoonotic disease caused by Coxiella burnetii. Ticks may act as vectors, and many epidemiological studies aim to assess C. burnetii prevalence in ticks. Because ticks may also be infected with Coxiella-like bacteria, screening tools that differentiate between C. burnetii and Coxiella-like bacteria are essential. Methods In this study, we screened tick specimens from 10 species (Ornithodoros rostratus, O. peruvianus, O. capensis, Ixodes ricinus, Rhipicephalus annulatus, R. decoloratus, R. geigy, O. sonrai, O. occidentalis, and Amblyomma cajennense) known to harbor specific Coxiella-like bacteria, by using quantitative PCR primers usually considered to be specific for C. burnetii and targeting, respectively, the IS1111, icd, scvA, p1, and GroEL/htpB genes. Results We found that some Coxiella-like bacteria, belonging to clades A and C, yield positive PCR results when screened with primers initially believed to be C. burnetii-specific. Conclusions These results suggest that PCR-based surveys that aim to detect C. burnetii in ticks by using currently available methods must be interpreted with caution if the amplified products cannot be sequenced. Future molecular methods that aim at detecting C. burnetii need to take into account the possibility that cross-reactions may exist with Coxiella-like bacteria. PMID:26609691
DOE Office of Scientific and Technical Information (OSTI.GOV)
Donnelly, H.; Fullwood, R.; Glancy, J.
This is the second volume of a two volume report on the VISA method for evaluating safeguards at fixed-site facilities. This volume contains appendices that support the description of the VISA concept and the initial working version of the method, VISA-1, presented in Volume I. The information is separated into four appendices, each describing details of one of the four analysis modules that comprise the analysis sections of the method. The first appendix discusses Path Analysis methodology, applies it to a Model Fuel Facility, and describes the computer codes that are being used. Introductory material on Path Analysis given inmore » Chapter 3.2.1 and Chapter 4.2.1 of Volume I. The second appendix deals with Detection Analysis, specifically the schemes used in VISA-1 for classifying adversaries and the methods proposed for evaluating individual detection mechanisms in order to build the data base required for detection analysis. Examples of evaluations on identity-access systems, SNM portal monitors, and intrusion devices are provided. The third appendix describes the Containment Analysis overt-segment path ranking, the Monte Carlo engagement model, the network simulation code, the delay mechanism data base, and the results of a sensitivity analysis. The last appendix presents general equations used in Interruption Analysis for combining covert-overt segments and compares them with equations given in Volume I, Chapter 3.« less
Zhang, Mengliang; Zhao, Yang; Harrington, Peter de B; Chen, Pei
2016-03-01
Two simple fingerprinting methods, flow-injection coupled to ultraviolet spectroscopy and proton nuclear magnetic resonance, were used for discriminating between Aurantii fructus immaturus and Fructus poniciri trifoliatae immaturus . Both methods were combined with partial least-squares discriminant analysis. In the flow-injection method, four data representations were evaluated: total ultraviolet absorbance chromatograms, averaged ultraviolet spectra, absorbance at 193, 205, 225, and 283 nm, and absorbance at 225 and 283 nm. Prediction rates of 100% were achieved for all data representations by partial least-squares discriminant analysis using leave-one-sample-out cross-validation. The prediction rate for the proton nuclear magnetic resonance data by partial least-squares discriminant analysis with leave-one-sample-out cross-validation was also 100%. A new validation set of data was collected by flow-injection with ultraviolet spectroscopic detection two weeks later and predicted by partial least-squares discriminant analysis models constructed by the initial data representations with no parameter changes. The classification rates were 95% with the total ultraviolet absorbance chromatograms datasets and 100% with the other three datasets. Flow-injection with ultraviolet detection and proton nuclear magnetic resonance are simple, high throughput, and low-cost methods for discrimination studies.
Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods
NASA Astrophysics Data System (ADS)
Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.
2017-04-01
In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.
Mindukshev, Igor; Gambaryan, Stepan; Kehrer, Linda; Schuetz, Claudia; Kobsar, Anna; Rukoyatkina, Natalia; Nikolaev, Viacheslav O; Krivchenko, Alexander; Watson, Steve P; Walter, Ulrich; Geiger, Joerg
2012-07-01
Determinations of platelet receptor functions are indispensable diagnostic indicators of cardiovascular and hemostatic diseases including hereditary and acquired receptor defects and receptor responses to drugs. However, presently available techniques for assessing platelet function have some disadvantages, such as low sensitivity and the requirement of large sample sizes and unphysiologically high agonist concentrations. Our goal was to develop and initially characterize a new technique designed to quantitatively analyze platelet receptor activation and platelet function on the basis of measuring changes in low angle light scattering. We developed a novel technique based on low angle light scattering registering changes in light scattering at a range of different angles in platelet suspensions during activation. The method proved to be highly sensitive for simultaneous real time detection of changes in size and shape of platelets during activation. Unlike commonly-used methods, the light scattering method could detect platelet shape change and aggregation in response to nanomolar concentrations of extracellular nucleotides. Furthermore, our results demonstrate that the advantages of the light scattering method make it a choice method for platelet receptor monitoring and for investigation of both murine and human platelets in disease models. Our data demonstrate the suitability and superiority of this new low angle light scattering method for comprehensive analyses of platelet receptors and functions. This highly sensitive, quantitative, and online detection of essential physiological, pathophysiological and pharmacological-response properties of human and mouse platelets is a significant improvement over conventional techniques.
Management of low-grade cervical abnormalities detected at screening: which method do women prefer?
Whynes, D K; Woolley, C; Philips, Z
2008-12-01
To establish whether women with low-grade abnormalities detected during screening for cervical cancer prefer to be managed by cytological surveillance or by immediate colposcopy. TOMBOLA (Trial of Management of Borderline and Other Low-grade Abnormal smears) is a randomized controlled trial comparing alternative management strategies following the screen-detection of low-grade cytological abnormalities. At exit, a sample of TOMBOLA women completed a questionnaire eliciting opinions on their management, contingent valuations (CV) of the management methods and preferences. Within-trial quality of life (EQ-5D) data collected for a sample of TOMBOLA women throughout their follow-up enabled the comparison of self-reported health at various time points, by management method. Once management had been initiated, self-reported health in the colposcopy arm rose relative to that in the surveillance arm, although the effect was short-term only. For the majority of women, the satisfaction ratings and the CV indicated approval of the management method to which they had been randomized. Of the minority manifesting a preference for the method which they had not experienced, relatively more would have preferred colposcopy than would have preferred surveillance. The findings must be interpreted in the light of sample bias with respect to preferences, whereby enthusiasm for colposcopy was probably over-represented amongst trial participants. The study suggests that neither of the management methods is preferred unequivocally; rather, individual women have individual preferences, although many would be indifferent between methods.
Automated Detection of Knickpoints and Knickzones Across Transient Landscapes
NASA Astrophysics Data System (ADS)
Gailleton, B.; Mudd, S. M.; Clubb, F. J.
2017-12-01
Mountainous regions are ubiquitously dissected by river channels, which transmit climate and tectonic signals to the rest of the landscape by adjusting their long profiles. Fluvial response to allogenic forcing is often expressed through the upstream propagation of steepened reaches, referred to as knickpoints or knickzones. The identification and analysis of these steepened reaches has numerous applications in geomorphology, such as modelling long-term landscape evolution, understanding controls on fluvial incision, and constraining tectonic uplift histories. Traditionally, the identification of knickpoints or knickzones from fluvial profiles requires manual selection or calibration. This process is both time-consuming and subjective, as different workers may select different steepened reaches within the profile. We propose an objective, statistically-based method to systematically pick knickpoints/knickzones on a landscape scale using an outlier-detection algorithm. Our method integrates river profiles normalised by drainage area (Chi, using the approach of Perron and Royden, 2013), then separates the chi-elevation plots into a series of transient segments using the method of Mudd et al. (2014). This method allows the systematic detection of knickpoints across a DEM, regardless of size, using a high-performance algorithm implemented in the open-source Edinburgh Land Surface Dynamics Topographic Tools (LSDTopoTools) software package. After initial knickpoint identification, outliers are selected using several sorting and binning methods based on the Median Absolute Deviation, to avoid the influence sample size. We test our method on a series of DEMs and grid resolutions, and show that our method consistently identifies accurate knickpoint locations across each landscape tested.
Measuring and Specifying Combinatorial Coverage of Test Input Configurations
Kuhn, D. Richard; Kacker, Raghu N.; Lei, Yu
2015-01-01
A key issue in testing is how many tests are needed for a required level of coverage or fault detection. Estimates are often based on error rates in initial testing, or on code coverage. For example, tests may be run until a desired level of statement or branch coverage is achieved. Combinatorial methods present an opportunity for a different approach to estimating required test set size, using characteristics of the test set. This paper describes methods for estimating the coverage of, and ability to detect, t-way interaction faults of a test set based on a covering array. We also develop a connection between (static) combinatorial coverage and (dynamic) code coverage, such that if a specific condition is satisfied, 100% branch coverage is assured. Using these results, we propose practical recommendations for using combinatorial coverage in specifying test requirements. PMID:28133442
AESA diagnostics in operational environments
NASA Astrophysics Data System (ADS)
Hull, W. P.
The author discusses some possible solutions to ASEA (active electronically scanned array) diagnostics in the operational environment using built-in testing (BIT), which can play a key role in reducing life-cycle cost if accurately implemented. He notes that it is highly desirable to detect and correct in the operational environment all degradation that impairs mission performance. This degradation must be detected with low false alarm rate and the appropriate action initiated consistent with low life-cycle cost. Mutual coupling is considered as a BIT signal injection method and is shown to have potential. However, the limits of the diagnostic capability using this method clearly depend on its stability and on the level of multipath for a specific application. BIT using mutual coupling may need to be supplemented on the ground by an externally mounted passive antenna that interfaces with onboard avionics.
Effective Multifocus Image Fusion Based on HVS and BP Neural Network
Yang, Yong
2014-01-01
The aim of multifocus image fusion is to fuse the images taken from the same scene with different focuses to obtain a resultant image with all objects in focus. In this paper, a novel multifocus image fusion method based on human visual system (HVS) and back propagation (BP) neural network is presented. Three features which reflect the clarity of a pixel are firstly extracted and used to train a BP neural network to determine which pixel is clearer. The clearer pixels are then used to construct the initial fused image. Thirdly, the focused regions are detected by measuring the similarity between the source images and the initial fused image followed by morphological opening and closing operations. Finally, the final fused image is obtained by a fusion rule for those focused regions. Experimental results show that the proposed method can provide better performance and outperform several existing popular fusion methods in terms of both objective and subjective evaluations. PMID:24683327
2010-01-01
Background The existence of circulating tumor cells (CTCs) in peripheral blood as an indicator of tumor recurrence has not been clearly established, particularly for gastric cancer patients. We conducted a retrospective analysis of the relationship between CTCs in peripheral blood at initial diagnosis and clinicopathologic findings in patients with gastric carcinoma. Methods Blood samples were obtained from 123 gastric carcinoma patients at initial diagnosis. mRNA was extracted and amplified for carcinoembryonic antigen (CEA) mRNA detection using real-time RT-PCR. Periodic 3-month follow-up examinations included serum CEA measurements and imaging. Results The minimum threshold for corrected CEA mRNA score [(CEA mRNA/GAPDH mRNA) × 106] was set at 100. Forty-five of 123 patients (36.6%) were positive for CEA mRNA expression. CEA mRNA expression significantly correlated with T stage and postoperative recurrence status (P = 0.001). Recurrent disease was found in 44 of 123 cases (35.8%), and 25 of these (56.8%) were positive for CEA mRNA. Of these patients, CEA mRNA was more sensitive than serum CEA in indicating recurrence. Three-year disease-free survival of patients positive for CEA mRNA was significantly poorer than of patients negative for CEA mRNA (P < 0.001). Only histological grade and CEA mRNA positivity were independent factors for disease-free survival using multivariate analysis. Conclusions CEA mRNA copy number in peripheral blood at initial diagnosis was significantly associated with disease recurrence in gastric adenocarcinoma patients. Real-time RT-PCR detection of CEA mRNA levels at initial diagnosis appears to be a promising predictor for disease recurrence in gastric adenocarcinoma patients. PMID:21040522
Automatic evaluation of skin histopathological images for melanocytic features
NASA Astrophysics Data System (ADS)
Koosha, Mohaddeseh; Hoseini Alinodehi, S. Pourya; Nicolescu, Mircea; Safaei Naraghi, Zahra
2017-03-01
Successfully detecting melanocyte cells in the skin epidermis has great significance in skin histopathology. Because of the existence of cells with similar appearance to melanocytes in hematoxylin and eosin (HE) images of the epidermis, detecting melanocytes becomes a challenging task. This paper proposes a novel technique for the detection of melanocytes in HE images of the epidermis, based on the melanocyte color features, in the HSI color domain. Initially, an effective soft morphological filter is applied to the HE images in the HSI color domain to remove noise. Then a novel threshold-based technique is applied to distinguish the candidate melanocytes' nuclei. Similarly, the method is applied to find the candidate surrounding halos of the melanocytes. The candidate nuclei are associated with their surrounding halos using the suggested logical and statistical inferences. Finally, a fuzzy inference system is proposed, based on the HSI color information of a typical melanocyte in the epidermis, to calculate the similarity ratio of each candidate cell to a melanocyte. As our review on the literature shows, this is the first method evaluating epidermis cells for melanocyte similarity ratio. Experimental results on various images with different zooming factors show that the proposed method improves the results of previous works.
McFall, Sally M; Wagner, Robin L; Jangam, Sujit R; Yamada, Douglas H; Hardie, Diana; Kelso, David M
2015-03-01
Early diagnosis and access to treatment for infants with human immunodeficiency virus-1 (HIV-1) is critical to reduce infant mortality. The lack of simple point-of-care tests impedes the timely initiation of antiretroviral therapy. The development of FINA, filtration isolation of nucleic acids, a novel DNA extraction method that can be performed by clinic personnel in less than 2 min has been reported previously. In this report, significant improvements in the DNA extraction and amplification methods are detailed that allow sensitive quantitation of as little as 10 copies of HIV-1 proviral DNA and detection of 3 copies extracted from 100 μl of whole blood. An internal control to detect PCR inhibition was also incorporated. In a preliminary field evaluation of 61 South African infants, the FINA test demonstrated 100% sensitivity and specificity. The proviral copy number of the infant specimens was quantified, and it was established that 100 microliters of whole blood is required for sensitive diagnosis of infants. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kassab, A.J.; Pollard, J.E.
An algorithm is presented for the high-resolution detection of irregular-shaped subsurface cavities within irregular-shaped bodies by the IR-CAT method. The theoretical basis of the algorithm is rooted in the solution of an inverse geometric steady-state heat conduction problem. A Cauchy boundary condition is prescribed at the exposed surface, and the inverse geometric heat conduction problem is formulated by specifying the thermal condition at the inner cavities walls, whose unknown geometries are to be detected. The location of the inner cavities is initially estimated, and the domain boundaries are discretized. Linear boundary elements are used in conjunction with cubic splines formore » high resolution of the cavity walls. An anchored grid pattern (AGP) is established to constrain the cubic spline knots that control the inner cavity geometry to evolve along the AGP at each iterative step. A residual is defined measuring the difference between imposed and computed boundary conditions. A Newton-Raphson method with a Broyden update is used to automate the detection of inner cavity walls. During the iterative procedure, the movement of the inner cavity walls is restricted to physically realistic intermediate solutions. Numerical simulation demonstrates the superior resolution of the cubic spline AGP algorithm over the linear spline-based AGP in the detection of an irregular-shaped cavity. Numerical simulation is also used to test the sensitivity of the linear and cubic spline AGP algorithms by simulating bias and random error in measured surface temperature. The proposed AGP algorithm is shown to satisfactorily detect cavities with these simulated data.« less
Ammonia Analysis by Gas Chromatograph/Infrared Detector (GC/IRD)
NASA Technical Reports Server (NTRS)
Scott, Joseph P.; Whitfield, Steve W.
2003-01-01
Methods are being developed at Marshall Space Flight Center's Toxicity Lab on a CG/IRD System that will be used to detect ammonia in low part per million (ppm) levels. These methods will allow analysis of gas samples by syringe injections. The GC is equipped with a unique cryogenic-cooled inlet system that will enable our lab to make large injections of a gas sample. Although the initial focus of the work will be analysis of ammonia, this instrument could identify other compounds on a molecular level. If proper methods can be developed, the IRD could work as a powerful addition to our offgassing capabilities.
Parodi, S; Balbi, C; Abelmoschi, M L; Pala, M; Russo, P; Santi, L
1983-12-01
Alkaline elution is a well-known method for detecting DNA damage. Recently we have developed a viscosimetric method that is even more sensitive than alkaline elution. Here we report that the two methods, although apparently both revealing alkaline DNA fragmentation, can give dramatically different results for a significant series of compounds. We suspect that alkaline elution might reveal not only DNA fragmentation but also the extent of disentanglement of chromatin structure, whereas this DNA disentanglement rate, when evaluated viscosimetrically , is more strictly correlated with the initiation of DNA unwinding.
Text extraction method for historical Tibetan document images based on block projections
NASA Astrophysics Data System (ADS)
Duan, Li-juan; Zhang, Xi-qun; Ma, Long-long; Wu, Jian
2017-11-01
Text extraction is an important initial step in digitizing the historical documents. In this paper, we present a text extraction method for historical Tibetan document images based on block projections. The task of text extraction is considered as text area detection and location problem. The images are divided equally into blocks and the blocks are filtered by the information of the categories of connected components and corner point density. By analyzing the filtered blocks' projections, the approximate text areas can be located, and the text regions are extracted. Experiments on the dataset of historical Tibetan documents demonstrate the effectiveness of the proposed method.
SERS-based application in food analytics (Conference Presentation)
NASA Astrophysics Data System (ADS)
Cialla-May, Dana; Radu, Andreea; Jahn, Martin; Weber, Karina; Popp, Jürgen
2017-02-01
To establish detection schemes in life science applications, specific and sensitive methods allowing for fast detection times are required. Due to the interaction of molecules with strong electromagnetic fields excited at metallic nanostructures, the molecular fingerprint specific Raman spectrum is increased by several orders of magnitude. This effect is described as surface-enhanced Raman spectroscopy (SERS) and became a very powerful analytical tool in many fields of application. Within this presentation, we will introduce innovative bottom-up strategies to prepare SERS-active nanostructures coated with a lipophilic sensor layer. To do so, the food colorant Sudan III, an indirect carcinogen substance found in chili powder, palm oil or spice mixtures, is detected quantitatively in the background of the competitor riboflavin as well as paprika powder extracts. The SERS-based detection of azorubine (E122) in commercial available beverages with different complexity (e.g. sugar content, alcohol concentration) illustrates the strong potential of SERS as a qualitative as well as semiquantitative prescan method in food analytics. Here, a good agreement between the estimated concentration employing SERS as well as the gold standard technique HPLC, a highly laborious method, is found. Finally, SERS is applied to detect vitamin B2 and B12 in cereals as well as the estimate the ratio of lycopene and β-carotene in tomatoes. Acknowledgement: Funding the projects "QuantiSERS" and "Jenaer Biochip Initiative 2.0" within the framework "InnoProfile Transfer - Unternehmen Region" the Federal Ministry of Education and Research, Germany (BMBF) is gratefully acknowledged.
Cammilleri, Gaetano; Chetta, Michele; Costa, Antonella; Graci, Stefania; Collura, Rosaria; Buscemi, Maria Drussilla; Cusimano, Maria; Alongi, Angelina; Principato, Deborah; Giangrosso, Giuseppe; Vella, Antonio; Ferrantelli, Vincenzo
2016-03-01
Anisakis and other parasites belonging to the Anisakidae family are organisms of interest for human health, because of their high zoonotic potential. Parasites belonging to this family can cause Anisakiasis, a parasitological disease caused by the ingestion of raw, infested fish products. Furthermore, evidence from the EFSA (European Food Safety Authority; EFSA 2010) has highlighted the allergological potential of nematodes belonging to the Anisakis genre. The detection and identification of Anisakidae larvae in fish products requires an initial visual inspection of the fish sample, as well as other techniques such as candling, UV illumination and artificial digestion. The digestion method consists of the simulation of digestive mechanics, which is made possible by the utilization of HCl and pepsin, according to EC Regulation 2075/2005. In this study, a new Anisakidae larvae detection method using a mechanical digestion system called Trichineasy® was developed. A total of 142 fish samples, belonging to 14 different species, were examined to validate the method. A reaction mixture with 100 g of sample, 10 g of pepsin (1:10000 NF) and 50 ml of 10% HCl at 36 ± 1°C for 20 minutes was evaluated to be the best condition for the digestion of fish samples. These parameters have also allowed the detection of viable larvae after digestion. The results confirm this instrumentation as a valuable and safe tool for the detection of Anisakidae larvae in fishery products.
Chenais, Erika; Sternberg-Lewerin, Susanna; Boqvist, Sofia; Emanuelson, Ulf; Aliro, Tonny; Tejler, Emma; Cocca, Giampaolo; Masembe, Charles; Ståhl, Karl
2015-01-01
Animal diseases impact negatively on households and on national economies. In low-income countries, this pertains especially to socio-economic effects on household level. To control animal diseases and mitigate their impact, it is necessary to understand the epidemiology of the disease in its local context. Such understanding, gained through disease surveillance, is often lacking in resource-poor settings. Alternative surveillance methods have been developed to overcome some of the hurdles obstructing surveillance. The objective of this study was to evaluate and qualitatively compare three methods for surveillance of acute infectious diseases using African swine fever in northern Uganda as an example. Report-driven outbreak investigations, participatory rural appraisals (PRAs), and a household survey using a smartphone application were evaluated. All three methods had good disease-detecting capacity, and each of them detected many more outbreaks compared to those reported to the World Organization for Animal Health during the same time period. Apparent mortality rates were similar for the three methods although highest for the report-driven outbreak investigations, followed by the PRAs, and then the household survey. The three methods have different characteristics and the method of choice will depend on the surveillance objective. The optimal situation might be achieved by a combination of the methods: outbreak detection via smartphone-based real-time surveillance, outbreak investigation for collection of biological samples, and a PRA for a better understanding of the epidemiology of the specific outbreak. All three methods require initial investments and continuous efforts. The sustainability of the surveillance system should, therefore, be carefully evaluated before making such investments.
Evaluation of permeable fractures in rock aquifers
NASA Astrophysics Data System (ADS)
Bok Lee, Hang
2015-04-01
In this study, the practical usefulness and fundamental applicability of a self-potential (SP) method for identifying the permeable fractures were evaluated by a comparison of SP methods with other geophysical logging methods and hydraulic tests. At a 10 m-shallow borehole in the study site, the candidates of permeable fractures crossing the borehole were first determined by conventional geophysical methods such as an acoustic borehole televiwer, temperature, electrical conductivity and gamma-gamma loggings, which was compared to the analysis by the SP method. Constant pressure injection and recovery tests were conducted for verification of the hydraulic properties of the fractures identified by various logging methods. The acoustic borehole televiwer and gamma-gamma loggings detected the open space or weathering zone within the borehole, but they cannot prove the possibility of a groundwater flow through the detected fractures. The temperature and electrical conductivity loggings had limitations to detect the fractured zones where groundwater in the borehole flows out to the surrounding rock aquifers. Comparison of results from different methods showed that there is a best correlation between the distribution of hydraulic conductivity and the variation of the SP signals, and the SP logging can estimate accurately the hydraulic activity as well as the location of permeable fractures. Based on the results, the SP method is recommended for determining the hydraulically-active fractures rather than other conventional geophysical loggings. This self-potential method can be effectively applied in the initial stage of a site investigation which selects the optimal location and evaluates the hydrogeological property of fractures in target sites for the underground structure including the geothermal reservoir and radioactive waste disposal.
Automatic Detection of Seizures with Applications
NASA Technical Reports Server (NTRS)
Olsen, Dale E.; Harris, John C.; Cutchis, Protagoras N.; Cristion, John A.; Lesser, Ronald P.; Webber, W. Robert S.
1993-01-01
There are an estimated two million people with epilepsy in the United States. Many of these people do not respond to anti-epileptic drug therapy. Two devices can be developed to assist in the treatment of epilepsy. The first is a microcomputer-based system designed to process massive amounts of electroencephalogram (EEG) data collected during long-term monitoring of patients for the purpose of diagnosing seizures, assessing the effectiveness of medical therapy, or selecting patients for epilepsy surgery. Such a device would select and display important EEG events. Currently many such events are missed. A second device could be implanted and would detect seizures and initiate therapy. Both of these devices require a reliable seizure detection algorithm. A new algorithm is described. It is believed to represent an improvement over existing seizure detection algorithms because better signal features were selected and better standardization methods were used.
Detection of bacterial growth by gas absorption.
Waters, J R
1992-05-01
When 24 different aerobic organisms were grown in a shaken culture, all were found to first absorb gas from the headspace. In a rudimentary medium, such as tryptic soy broth, 16 of the 24 organisms did not produce gas following the initial gas absorption. We have developed a simple, noninvasive method for detecting both gas absorption and production in multiple culture vials. The time to positivity was compared with that obtained by the BACTEC 460 blood culture system. For nearly all of these organisms, there was no difference. For some of those organisms that did not produce gas, e.g. Staphylococcus epidermidis, Moraxella osloensis, and Neisseria meningitidis, detection by gas absorption was a few hours faster. Gas absorption appears to be a promising technique for a new automated blood culture system because of its simplicity and because medium without special additives can be used to detect organisms that do not produce gas.
Automatic Fatigue Detection of Drivers through Yawning Analysis
NASA Astrophysics Data System (ADS)
Azim, Tayyaba; Jaffar, M. Arfan; Ramzan, M.; Mirza, Anwar M.
This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The focus of the paper is on how to detect yawning which is an important cue for determining driver's fatigue. Initially, the face is located through Viola-Jones face detection method in a video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. The degree of mouth openness is extracted on the basis of mouth features, to determine driver's yawning state. If the yawning state of the driver persists for several consecutive frames, the system concludes that the driver is non-vigilant due to fatigue and is thus warned through an alarm. The system reinitializes when occlusion or misdetection occurs. Experiments were carried out using real data, recorded in day and night lighting conditions, and with users belonging to different race and gender.
Feuerstein, Marco; Reichl, Tobias; Vogel, Jakob; Traub, Joerg; Navab, Nassir
2009-06-01
Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.
Kusić, Dragana; Rösch, Petra; Popp, Jürgen
2016-03-01
Legionellae colonize biofilms, can form a biofilm by itself and multiply intracellularly within the protozoa commonly found in water distribution systems. Approximately half of the known species are pathogenic and have been connected to severe multisystem Legionnaires' disease. The detection methods for Legionella spp. in water samples are still based on cultivation, which is time consuming due to the slow growth of this bacterium. Here, we developed a cultivation-independent, label-free and fast detection method for legionellae in a biofilm matrix based on the Raman spectroscopic analysis of isolated single cells via immunomagnetic separation (IMS). A database comprising the Raman spectra of single bacterial cells captured and separated from the biofilms formed by each species was used to build the identification method based on a support vector machine (SVM) discriminative classifier. The complete method allows the detection of Legionella spp. in 100 min. Cross-reactivity of Legionella spp. specific immunomagnetic beads to the other studied genera was tested, where only small cell amounts of Pseudomonas aeruginosa, Klebsiella pneumoniae and Escherichia coli compared to the initial number of cells were isolated by the immunobeads. Nevertheless, the Raman spectra collected from isolated non-targeted bacteria were well-discriminated from the Raman spectra collected from isolated Legionella cells, whereby the Raman spectra of the independent dataset of Legionella strains were assigned with an accuracy of 98.6%. In addition, Raman spectroscopy was also used to differentiate between isolated Legionella species. Copyright © 2016 Elsevier GmbH. All rights reserved.
NASA Astrophysics Data System (ADS)
Boccara, A. Claude; Fedala, Yasmina; Voronkoff, Justine; Paffoni, Nina; Boccara, Martine
2017-03-01
Due to the huge abundance and the major role that viruses and membrane vesicles play in the seas or rivers ecosystems it is necessary to develop simple, sensitive, compact and reliable methods for their detection and characterization. Our approach is based on the measurement of the weak light level scattered by the biotic nanoparticles. We describe a new full-field, incoherently illuminated, shot-noise limited, common-path interferometric detection method coupled with the analysis of Brownian motion to detect, quantify, and differentiate biotic nanoparticles. The last developments take advantage of a new fast (700 Hz) camera with 2 Me- full well capacity that improves the signal to noise ratio and increases the precision of the Brownian motion characterization. We validated the method with calibrated nanoparticles and homogeneous DNA or RNA.viruses. The smallest virus size that we characterized with a suitable signal-to-noise ratio was around 30 nm in diameter with a target towards the numerous 20 nm diameter viruses. We show for the first time anisotropic trajectories for myoviruses meaning that there is a memory of the initial direction of their Brownian motions. Significant improvements have been made in the handling of the sample as well as in the statistical analysis for differentiating the various families of vesicles and virus. We further applied the method for vesicles detection and for analysis of coastal and oligotrophic samples from Tara Oceans circumnavigation as well of various rivers.
Georgsson, G; Martin, J R; Stoner, G L; Webster, H F
1987-01-01
Mice were infected by the vaginal route with the MS strain of herpes simplex virus type 2 (HSV-2). Serial vaginal cultures were used to confirm infection and to select mice for this study. Two mice were killed by perfusion on days 2-6 post infection (p.i.) and lumbar and sacral cord with cauda were fixed and embedded for electron microscopy. Semithin Epon-sections were stained for viral antigen using a rabbit anti-HSV-2 antiserum and the Avidin-Biotin (ABC) method. Thin sections from antigen-positive blocks were examined by electron microscopy, and the number and types of infected cells detected by these two methods were compared. A good correlation was found between detection of infected cells by these methods. Infected cells included neurons of dorsal root ganglia and spinal cord, satellite cells of dorsal root ganglia, non-myelinating Schwann cells, astrocytes, oligodendrocytes and arachnoidal cells. Infected cells were first detected in the cauda on day 3 p.i. and in the spinal cord on day 5 p.i. The temporal and spatial distribution of infected cells was consistent with neural spread to and within the CNS. The pathological lesions showed a good correlation with the distribution and number of infected cells and are probably due to a direct virus effect. The similar sensitivity of the Epon-ABC method to electron microscopy in detecting infected cells indicates that this method may have useful applications in both experimental and diagnostic work.
Otolith Trace Element Chemistry of Juvenile Black Rockfish
NASA Astrophysics Data System (ADS)
Hardin, W.; Bobko, S. J.; Jones, C. M.
2002-12-01
In the summer of 1997 we collected young-of -the-year (YOY) black rockfish, Sebastes melanops, from floating docks and seagrass beds in Newport and Coos Bay, Oregon. Otoliths were extracted from randomly selected fish, sectioned and polished under general laboratory conditions, and cleaned in a class 100 clean room. We used Laser Ablation - Inductively Coupled Mass Spectrometry (LA-ICPMS) to analyze elemental composition of the estuarine phase of the otoliths. While we observed differences in Mn/Ca ratios between the two estuaries, there was no statistical difference in otolith trace element chemistry ratios between estuaries using MANOVA. To determine if laboratory processing of otoliths might have impeded us from detecting differences in otolith chemistry, we conducted a second experiment. Right and left otoliths from 10 additional Coos Bay fish were randomly allocated to two processing methods. The first method was identical to our initial otolith processing, sectioning and polishing under normal laboratory conditions. In the second method, polishing was done in the clean room. For both methods otoliths went through a final cleaning in the clean room and analyzed with LA-ICPMS. While we did not detect statistical differences in element ratios between the two methods, otoliths polished outside the clean room had much higher variances. This increased variance might have lowered our ability to detect differences in otolith chemistry between estuaries. Based on our results, we recommend polishing otoliths under clean room conditions to reduce contamination.
Paar, Jack; Doolittle, Mark M; Varma, Manju; Siefring, Shawn; Oshima, Kevin; Haugland, Richard A
2015-05-01
A method, incorporating recently improved reverse transcriptase-PCR primer/probe assays and including controls for detecting interferences in RNA recovery and analysis, was developed for the direct, culture-independent detection of genetic markers from FRNA coliphage genogroups I, II & IV in water samples. Results were obtained from an initial evaluation of the performance of this method in analyses of waste water, ambient surface water and stormwater drain and outfall samples from predominantly urban locations. The evaluation also included a comparison of the occurrence of the FRNA genetic markers with genetic markers from general and human-related bacterial fecal indicators determined by current or pending EPA-validated qPCR methods. Strong associations were observed between the occurrence of the putatively human related FRNA genogroup II marker and the densities of the bacterial markers in the stormwater drain and outfall samples. However fewer samples were positive for FRNA coliphage compared to either the general bacterial fecal indicator or the human-related bacterial fecal indicator markers particularly for ambient water samples. Together, these methods show promise as complementary tools for the identification of contaminated storm water drainage systems as well as the determination of human and non-human sources of contamination. Published by Elsevier B.V.
Ban, Susumu; Kondo, Tomoko; Ishizuka, Mayumi; Sasaki, Seiko; Konishi, Kanae; Washino, Noriaki; Fujita, Syoichi; Kishi, Reiko
2007-05-01
The field of molecular biology currently faces the need for a comprehensive method of evaluating individual differences derived from genetic variation in the form of single nucleotide polymorphisms (SNPs). SNPs in human genes are generally considered to be very useful in determining inherited genetic disorders, susceptibility to certain diseases, and cancer predisposition. Quick and accurate discrimination of SNPs is the key characteristic of technology used in DNA diagnostics. For this study, we first developed a DNA microarray and then evaluated its efficacy by determining the detection ability and validity of this method. Using DNA obtained from 380 pregnant Japanese women, we examined 13 polymorphisms of 9 genes, which are associated with the metabolism of environmental chemical compounds found in high frequency among Japanese populations. The ability to detect CYP1A1 I462V, CYP1B1 L432V, GSTP1 I105V and AhR R554K gene polymorphisms was above 98%, and agreement rates when compared with real time PCR analysis methods (kappa values) showed high validity: 0.98 (0.96), 0.97 (0.93), 0.90 (0.81), 0.90 (0.91), respectively. While this DNA microarray analysis should prove important as a method for initial screening, it is still necessary that we find better methods for improving the detection of other gene polymorphisms not part of this study.
Brown, Jeffrey S.; Petronis, Kenneth R.; Bate, Andrew; Zhang, Fang; Dashevsky, Inna; Kulldorff, Martin; Avery, Taliser R.; Davis, Robert L.; Chan, K. Arnold; Andrade, Susan E.; Boudreau, Denise; Gunter, Margaret J.; Herrinton, Lisa; Pawloski, Pamala A.; Raebel, Marsha A.; Roblin, Douglas; Smith, David; Reynolds, Robert
2013-01-01
Background: Drug adverse event (AE) signal detection using the Gamma Poisson Shrinker (GPS) is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan). Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds. PMID:24300404
Christodoulides, Nicolaos; De La Garza, Richard; Simmons, Glennon W; McRae, Michael P; Wong, Jorge; Newton, Thomas F; Smith, Regina; Mahoney, James J; Hohenstein, Justin; Gomez, Sobeyda; Floriano, Pierre N; Talavera, Humberto; Sloan, Daniel J; Moody, David E; Andrenyak, David M; Kosten, Thomas R; Haque, Ahmed; McDevitt, John T
2015-08-01
There is currently a gap in on-site drug of abuse monitoring. Current detection methods involve invasive sampling of blood and urine specimens, or collection of oral fluid, followed by qualitative screening tests using immunochromatographic cartridges. While remote laboratories then may provide confirmation and quantitative assessment of a presumptive positive, this instrumentation is expensive and decoupled from the initial sampling making the current drug-screening program inefficient and costly. The authors applied a noninvasive oral fluid sampling approach integrated with the in-development chip-based Programmable bio-nano-chip (p-BNC) platform for the detection of drugs of abuse. The p-BNC assay methodology was applied for the detection of tetrahydrocannabinol, morphine, amphetamine, methamphetamine, cocaine, methadone and benzodiazepines, initially using spiked buffered samples and, ultimately, using oral fluid specimen collected from consented volunteers. Rapid (∼10min), sensitive detection (∼ng/mL) and quantitation of 12 drugs of abuse was demonstrated on the p-BNC platform. Furthermore, the system provided visibility to time-course of select drug and metabolite profiles in oral fluids; for the drug cocaine, three regions of slope were observed that, when combined with concentration measurements from this and prior impairment studies, information about cocaine-induced impairment may be revealed. This chip-based p-BNC detection modality has significant potential to be used in the future by law enforcement officers for roadside drug testing and to serve a variety of other settings, including outpatient and inpatient drug rehabilitation centers, emergency rooms, prisons, schools, and in the workplace. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Zhu, Jing; Ding, Yongshun; Liu, Xingti; Wang, Lei; Jiang, Wei
2014-09-15
Highly sensitive and selective detection strategy for single-base mutations is essential for risk assessment of malignancy and disease prognosis. In this work, a fluorescent detection method for single-base mutation was proposed based on high selectivity of toehold-mediated strand displacement reaction (TSDR) and powerful signal amplification capability of isothermal DNA amplification. A discrimination probe was specially designed with a stem-loop structure and an overhanging toehold domain. Hybridization between the toehold domain and the perfect matched target initiated the TSDR along with the unfolding of the discrimination probe. Subsequently, the target sequence acted as a primer to initiate the polymerization and nicking reactions, which released a great abundant of short sequences. Finally, the released strands were annealed with the reporter probe, launching another polymerization and nicking reaction to produce lots of G-quadruplex DNA, which could bind the N-methyl mesoporphyrin IX to yield an enhanced fluorescence response. However, when there was even a single base mismatch in the target DNA, the TSDR was suppressed and so subsequent isothermal DNA amplification and fluorescence response process could not occur. The proposed approach has been successfully implemented for the identification of the single-base mutant sequences in the human KRAS gene with a detection limit of 1.8 pM. Furthermore, a recovery of 90% was obtained when detecting the target sequence in spiked HeLa cells lysate, demonstrating the feasibility of this detection strategy for single-base mutations in biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.
Hongwarittorrn, Irin; Chaichanawongsaroj, Nuntaree; Laiwattanapaisal, Wanida
2017-12-01
A distance-based paper analytical device (dPAD) for loop mediated isothermal amplification (LAMP) detection based on distance measurement was proposed. This approach relied on visual detection by the length of colour developed on the dPAD with reference to semi-quantitative determination of the initial amount of genomic DNA. In this communication, E. coli DNA was chosen as a template DNA for LAMP reaction. In accordance with the principle, the dPAD was immobilized by polyethylenimine (PEI), which is a strong cationic polymer, in the hydrophilic channel of the paper device. Hydroxynaphthol blue (HNB), a colourimetric indicator for monitoring the change of magnesium ion concentration in the LAMP reaction, was used to react with the immobilized PEI. The positive charges of PEI react with the negative charges of free HNB in the LAMP reaction, producing a blue colour deposit on the paper device. Consequently, the apparently visual distance appeared within 5min and length of distance correlated to the amount of DNA in the sample. The distance-based PAD for the visual detection of the LAMP reaction could quantify the initial concentration of genomic DNA as low as 4.14 × 10 3 copiesµL -1 . This distance-based visual semi-quantitative platform is suitable for choice of LAMP detection method, particular in resource-limited settings because of the advantages of low cost, simple fabrication and operation, disposability and portable detection of the dPAD device. Copyright © 2017 Elsevier B.V. All rights reserved.
An electromagnetic induction method for underground target detection and characterization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bartel, L.C.; Cress, D.H.
1997-01-01
An improved capability for subsurface structure detection is needed to support military and nonproliferation requirements for inspection and for surveillance of activities of threatening nations. As part of the DOE/NN-20 program to apply geophysical methods to detect and characterize underground facilities, Sandia National Laboratories (SNL) initiated an electromagnetic induction (EMI) project to evaluate low frequency electromagnetic (EM) techniques for subsurface structure detection. Low frequency, in this case, extended from kilohertz to hundreds of kilohertz. An EMI survey procedure had already been developed for borehole imaging of coal seams and had successfully been applied in a surface mode to detect amore » drug smuggling tunnel. The SNL project has focused on building upon the success of that procedure and applying it to surface and low altitude airborne platforms. Part of SNL`s work has focused on improving that technology through improved hardware and data processing. The improved hardware development has been performed utilizing Laboratory Directed Research and Development (LDRD) funding. In addition, SNL`s effort focused on: (1) improvements in modeling of the basic geophysics of the illuminating electromagnetic field and its coupling to the underground target (partially funded using LDRD funds) and (2) development of techniques for phase-based and multi-frequency processing and spatial processing to support subsurface target detection and characterization. The products of this project are: (1) an evaluation of an improved EM gradiometer, (2) an improved gradiometer concept for possible future development, (3) an improved modeling capability, (4) demonstration of an EM wave migration method for target recognition, and a demonstration that the technology is capable of detecting targets to depths exceeding 25 meters.« less
Detection methods for human enteric viruses in representative foods.
Leggitt, P R; Jaykus, L A
2000-12-01
Although viral foodborne disease is a significant problem, foods are rarely tested for viral contamination, and when done, testing is limited to shellfish commodities. In this work, we report a method to extract and detect human enteric viruses from alternative food commodities using an elution-concentration approach followed by detection using reverse transcription-polymerase chain reaction (RT-PCR). Fifty-gram lettuce or hamburger samples were artificially inoculated with poliovirus type 1 (PV1), hepatitis A virus (HAV), or the Norwalk virus and processed by the sequential steps of homogenization, filtration, Freon extraction (hamburger), and polyethylene glycol (PEG) precipitation. To reduce volumes further and remove RT-PCR inhibitors, a secondary PEG precipitation was necessary, resulting in an overall 10- to 20-fold sample size reduction from 50 g to 3 to 5 ml. Virus recoveries in secondary PEG concentrates ranged from 10 to 70% for PV1 and 2 to 4% for HAV as evaluated by mammalian cell culture infectivity assay. Total RNA from PEG concentrates was extracted to a small volume (30 to 40 microl) and subjected to RT-PCR amplification of viral RNA sequences. Detection limit studies indicated that viral RNA was consistently detected by RT-PCR at initial inoculum levels > or =102 PFU/50-g food sample for PV1 and > or =10(3) PFU/50-g food sample for HAV. In similar studies with the Norwalk virus, detection at inoculum levels > or =1.5 X 10(3) PCR-amplifiable units/50-g sample for both food products was possible. All RT-PCR amplicons were confirmed by subsequent Southern hybridization. The procedure reported represents progress toward the development of methods to detect human enteric viral contamination in foods other than shellfish.
Using a high spatial resolution tactile sensor for intention detection.
Castellini, Claudio; Koiva, Risto
2013-06-01
Intention detection is the interpretation of biological signals with the aim of automatically, reliably and naturally understanding what a human subject desires to do. Although intention detection is not restricted to disabled people, such methods can be crucial in improving a patient's life, e.g., aiding control of a robotic wheelchair or of a self-powered prosthesis. Traditionally, intention detection is done using, e.g., gaze tracking, surface electromyography and electroencephalography. In this paper we present exciting initial results of an experiment aimed at intention detection using a high-spatial-resolution, high-dynamic-range tactile sensor. The tactile image of the ventral side of the forearm of 9 able-bodied participants was recorded during a variable-force task stimulated at the fingertip. Both the forces at the fingertip and at the forearm were synchronously recorded. We show that a standard dimensionality reduction technique (Principal Component Analysis) plus a Support Vector Machine attain almost perfect detection accuracy of the direction and the intensity of the intended force. This paves the way for high spatial resolution tactile sensors to be used as a means for intention detection.
Detection of z~2 Type IIn Supernovae
NASA Astrophysics Data System (ADS)
Cooke, Jeff; Sullivan, Mark; Barton, Elizabeth J.
2009-05-01
Type IIn supernovae (SNe IIn) result from the deaths of massive stars. The broad magnitude distribution of SNe IIn make these some of the most luminous SN events ever recorded. In addition, they are the most luminous SN type in the rest-frame UV which make them ideal targets for wide-field optical high redshift searches. We briefly describe our method to detect z~2 SNe IIn events that involves monitoring color-selected galaxies in deep stacked images and our program that applies this method to the CFHTLS survey. Initial results have detected four compelling photometric candidates from their subtracted images and light curves. SNe IIn spectra exhibit extremely bright narrow emission lines as a result of the interaction between the SN ejecta and the circumstellar material released in pre-explosion outbursts. These emission lines remain bright for years after outburst and are above the thresholds of current 8 m-class telescope sensitivities to z~3. The deep spectroscopy required to confirm z~2 host galaxies has the potential to detect the SN emission lines and measure their energies. Finally, planned deep, wide-field surveys have the capability to detect and confirm SNe IIn to z~6. The emission lines of such high-redshift events are expected to be above the sensitivity of future 30 m-class telescopes and the James Webb Space Telescope.
Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors
Hübl, Johannes; McArdell, Brian W.; Walter, Fabian
2018-01-01
The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. PMID:29789449
Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul
2011-01-01
Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238
Nomanpour, B; Ghodousi, A; Babaei, A; Abtahi, HR; Tabrizi, M; Feizabadi, MM
2011-01-01
Background and Objectives Pneumonia with Acinetobacter baumannii has a major therapeutic problem in health care settings. Decision to initiate correct antibiotic therapy requires rapid identification and quantification of organism. The aim of this study was to develop a rapid and sensitive method for direct detection of A. baumannii from respiratory specimens. Materials and Methods A Taqman real time PCR based on the sequence of bla oxa-51 was designed and used for direct detection of A. baumannii from 361 respiratory specimens of patients with pneumonia. All specimens were checked by conventional bacteriology in parallel. Results The new real time PCR could detect less than 200 cfu per ml of bacteria in specimens. There was agreement between the results of real time PCR and culture (Kappa value 1.0, p value<0.001). The sensitivity, specificity and predictive values of real time PCR were 100%. The prevalence of A. baumannii in pneumonia patients was 10.53 % (n=38). Poly-microbial infections were detected in 65.71% of specimens. Conclusion Acinetobacter baumannii is the third causative agent in nosocomial pneumonia after Pseudomonas aeroginosa (16%) and Staphylococcus aureus (13%) at Tehran hospitals. We recommend that 104 CFU be the threshold for definition of infection with A. baumannii using real time PCR. PMID:22530083
Hypervelocity Impact (HVI). Volume 6; WLE High Fidelity Specimen Fg(RCC)-2
NASA Technical Reports Server (NTRS)
Gorman, Michael R.; Ziola, Steven M.
2007-01-01
During 2003 and 2004, the Johnson Space Center's White Sands Testing Facility in Las Cruces, New Mexico conducted hypervelocity impact tests on the space shuttle wing leading edge. Hypervelocity impact tests were conducted to determine if Micro-Meteoroid/Orbital Debris impacts could be reliably detected and located using simple passive ultrasonic methods. The objective of Target Fg(RCC)-2 was to study hypervelocity impacts through the reinforced carbon-carbon (RCC) panels of the Wing Leading Edge. Fiberglass was used in place of RCC in the initial tests. Impact damage was detected using lightweight, low power instrumentation capable of being used in flight.
Hypervelocity Impact (HVI). Volume 4; WLE Small-Scale Fiberglass Panel Flat Target C-2
NASA Technical Reports Server (NTRS)
Gorman, Michael R.; Ziola, Steven M.
2007-01-01
During 2003 and 2004, the Johnson Space Center's White Sands Testing Facility in Las Cruces, New Mexico conducted hypervelocity impact tests on the space shuttle wing leading edge. Hypervelocity impact tests were conducted to determine if Micro-Meteoroid/Orbital Debris impacts could be reliably detected and located using simple passive ultrasonic methods. The objective of Target C-2 was to study impacts through the reinforced carboncarbon (RCC) panels of the Wing Leading Edge. Fiberglass was used in place of RCC in the initial tests. Impact damage was detected using lightweight, low power instrumentation capable of being used in flight.
Hypervelocity Impact (HVI). Volume 5; WLE High Fidelity Specimen Fg(RCC)-1
NASA Technical Reports Server (NTRS)
Gorman, Michael R.; Ziola, Steven M.
2007-01-01
During 2003 and 2004, the Johnson Space Center's White Sands Testing Facility in Las Cruces, New Mexico conducted hypervelocity impact tests on the space shuttle wing leading edge. Hypervelocity impact tests were conducted to determine if Micro-Meteoroid/Orbital Debris impacts could be reliably detected and located using simple passive ultrasonic methods. The objective of Target Fg(RCC)-1 was to study hypervelocity impacts through the reinforced carbon-carbon (RCC) panels of the Wing Leading Edge. Fiberglass was used in place of RCC in the initial tests. Impact damage was detected using lightweight, low power instrumentation capable of being used in flight.
Hypervelocity Impact (HVI). Volume 3; WLE Small-Scale Fiberglass Panel Flat Target C-1
NASA Technical Reports Server (NTRS)
Gorman, Michael R.; Ziola, Steven M.
2007-01-01
During 2003 and 2004, the Johnson Space Center's White Sands Testing Facility in Las Cruces, New Mexico conducted hypervelocity impact tests on the space shuttle wing leading edge. Hypervelocity impact tests were conducted to determine if Micro-Meteoroid/Orbital Debris impacts could be reliably detected and located using simple passive ultrasonic methods. The objective of Target C-1 was to study hypervelocity impacts on the reinforced carbon-carbon (RCC) panels of the Wing Leading Edge. Fiberglass was used in place of RCC in the initial tests. Impact damage was detected using lightweight, low power instrumentation capable of being used in flight.
Next Generation Programmable Bio-Nano-Chip System for On-Site Detection in Oral Fluids.
Christodoulides, Nicolaos; De La Garza, Richard; Simmons, Glennon W; McRae, Michael P; Wong, Jorge; Newton, Thomas F; Kosten, Thomas R; Haque, Ahmed; McDevitt, John T
2015-11-23
Current on-site drug of abuse detection methods involve invasive sampling of blood and urine specimens, or collection of oral fluid, followed by qualitative screening tests using immunochromatographic cartridges. Test confirmation and quantitative assessment of a presumptive positive are then provided by remote laboratories, an inefficient and costly process decoupled from the initial sampling. Recently, a new noninvasive oral fluid sampling approach that is integrated with the chip-based Programmable Bio-Nano-Chip (p-BNC) platform has been developed for the rapid (~ 10 minutes), sensitive detection (~ ng/ml) and quantitation of 12 drugs of abuse. Furthermore, the system can provide the time-course of select drug and metabolite profiles in oral fluids. For cocaine, we observed three slope components were correlated with cocaine-induced impairment using this chip-based p-BNC detection modality. Thus, this p-BNC has significant potential for roadside drug testing by law enforcement officers. Initial work reported on chip-based drug detection was completed using 'macro' or "chip in the lab" prototypes, that included metal encased "flow cells", external peristaltic pumps and a bench-top analyzer system instrumentation. We now describe the next generation miniaturized analyzer instrumentation along with customized disposables and sampling devices. These tools will offer real-time oral fluid drug monitoring capabilities, to be used for roadside drug testing as well as testing in clinical settings as a non-invasive, quantitative, accurate and sensitive tool to verify patient adherence to treatment.
Defeating crypsis: detection and learning of camouflage strategies.
Troscianko, Jolyon; Lown, Alice E; Hughes, Anna E; Stevens, Martin
2013-01-01
Camouflage is perhaps the most widespread defence against predators in nature and an active area of interdisciplinary research. Recent work has aimed to understand what camouflage types exist (e.g. background matching, disruptive, and distractive patterns) and their effectiveness. However, work has almost exclusively focused on the efficacy of these strategies in preventing initial detection, despite the fact that predators often encounter the same prey phenotype repeatedly, affording them opportunities to learn to find those prey more effectively. The overall value of a camouflage strategy may, therefore, reflect both its ability to prevent detection by predators and resist predator learning. We conducted four experiments with humans searching for hidden targets of different camouflage types (disruptive, distractive, and background matching of various contrast levels) over a series of touch screen trials. As with previous work, disruptive coloration was the most successful method of concealment overall, especially with relatively high contrast patterns, whereas potentially distractive markings were either neutral or costly. However, high contrast patterns incurred faster decreases in detection times over trials compared to other stimuli. In addition, potentially distractive markings were sometimes learnt more slowly than background matching markings, despite being found more readily overall. Finally, learning effects were highly dependent upon the experimental paradigm, including the number of prey types seen and whether subjects encountered targets simultaneously or sequentially. Our results show that the survival advantage of camouflage strategies reflects both their ability to avoid initial detection (sensory mechanisms) and predator learning (perceptual mechanisms).
Compact binary merger rates: Comparison with LIGO/Virgo upper limits
Belczynski, Krzysztof; Repetto, Serena; Holz, Daniel E.; ...
2016-03-03
Here, we compare evolutionary predictions of double compact object merger rate densities with initial and forthcoming LIGO/Virgo upper limits. We find that: (i) Due to the cosmological reach of advanced detectors, current conversion methods of population synthesis predictions into merger rate densities are insufficient. (ii) Our optimistic models are a factor of 18 below the initial LIGO/Virgo upper limits for BH–BH systems, indicating that a modest increase in observational sensitivity (by a factor of ~2.5) may bring the first detections or first gravitational wave constraints on binary evolution. (iii) Stellar-origin massive BH–BH mergers should dominate event rates in advanced LIGO/Virgo and can be detected out to redshift z sime 2 with templates including inspiral, merger, and ringdown. Normal stars (more » $$\\lt 150\\;{M}_{\\odot }$$) can produce such mergers with total redshifted mass up to $${M}_{{\\rm{tot,z}}}\\simeq 400\\;{M}_{\\odot }$$. (iv) High black hole (BH) natal kicks can severely limit the formation of massive BH–BH systems (both in isolated binary and in dynamical dense cluster evolution), and thus would eliminate detection of these systems even at full advanced LIGO/Virgo sensitivity. We find that low and high BH natal kicks are allowed by current observational electromagnetic constraints. (v) The majority of our models yield detections of all types of mergers (NS–NS, BH–NS, BH–BH) with advanced detectors. Numerous massive BH–BH merger detections will indicate small (if any) natal kicks for massive BHs.« less