Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost.

PubMed

Zhou, Zhen; Huang, Jingfeng; Wang, Jing; Zhang, Kangyu; Kuang, Zhaomin; Zhong, Shiquan; Song, Xiaodong

2015-01-01

Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited.

Chaotic genetic algorithm and Adaboost ensemble metamodeling approach for optimum resource planning in emergency departments.

PubMed

Yousefi, Milad; Yousefi, Moslem; Ferreira, Ricardo Poley Martins; Kim, Joong Hoon; Fogliatto, Flavio S

2018-01-01

Long length of stay and overcrowding in emergency departments (EDs) are two common problems in the healthcare industry. To decrease the average length of stay (ALOS) and tackle overcrowding, numerous resources, including the number of doctors, nurses and receptionists need to be adjusted, while a number of constraints are to be considered at the same time. In this study, an efficient method based on agent-based simulation, machine learning and the genetic algorithm (GA) is presented to determine optimum resource allocation in emergency departments. GA can effectively explore the entire domain of all 19 variables and identify the optimum resource allocation through evolution and mimicking the survival of the fittest concept. A chaotic mutation operator is used in this study to boost GA performance. A model of the system needs to be run several thousand times through the GA evolution process to evaluate each solution, hence the process is computationally expensive. To overcome this drawback, a robust metamodel is initially constructed based on an agent-based system simulation. The simulation exhibits ED performance with various resource allocations and trains the metamodel. The metamodel is created with an ensemble of the adaptive neuro-fuzzy inference system (ANFIS), feedforward neural network (FFNN) and recurrent neural network (RNN) using the adaptive boosting (AdaBoost) ensemble algorithm. The proposed GA-based optimization approach is tested in a public ED, and it is shown to decrease the ALOS in this ED case study by 14%. Additionally, the proposed metamodel shows a 26.6% improvement compared to the average results of ANFIS, FFNN and RNN in terms of mean absolute percentage error (MAPE). Copyright © 2017 Elsevier B.V. All rights reserved.

Mitosis detection using generic features and an ensemble of cascade adaboosts.

PubMed

Tek, F Boray

2013-01-01

Mitosis count is one of the factors that pathologists use to assess the risk of metastasis and survival of the patients, which are affected by the breast cancer. We investigate an application of a set of generic features and an ensemble of cascade adaboosts to the automated mitosis detection. Calculation of the features rely minimally on object-level descriptions and thus require minimal segmentation. The proposed work was developed and tested on International Conference on Pattern Recognition (ICPR) 2012 mitosis detection contest data. We plotted receiver operating characteristics curves of true positive versus false positive rates; calculated recall, precision, F-measure, and region overlap ratio measures. WE TESTED OUR FEATURES WITH TWO DIFFERENT CLASSIFIER CONFIGURATIONS: 1) An ensemble of single adaboosts, 2) an ensemble of cascade adaboosts. On the ICPR 2012 mitosis detection contest evaluation, the cascade ensemble scored 54, 62.7, and 58, whereas the non-cascade version scored 68, 28.1, and 39.7 for the recall, precision, and F-measure measures, respectively. Mostly used features in the adaboost classifier rules were a shape-based feature, which counted granularity and a color-based feature, which relied on Red, Green, and Blue channel statistics. The features, which express the granular structure and color variations, are found useful for mitosis detection. The ensemble of adaboosts performs better than the individual adaboost classifiers. Moreover, the ensemble of cascaded adaboosts was better than the ensemble of single adaboosts for mitosis detection.

RBOOST: RIEMANNIAN DISTANCE BASED REGULARIZED BOOSTING

PubMed Central

Liu, Meizhu; Vemuri, Baba C.

2011-01-01

Boosting is a versatile machine learning technique that has numerous applications including but not limited to image processing, computer vision, data mining etc. It is based on the premise that the classification performance of a set of weak learners can be boosted by some weighted combination of them. There have been a number of boosting methods proposed in the literature, such as the AdaBoost, LPBoost, SoftBoost and their variations. However, the learning update strategies used in these methods usually lead to overfitting and instabilities in the classification accuracy. Improved boosting methods via regularization can overcome such difficulties. In this paper, we propose a Riemannian distance regularized LPBoost, dubbed RBoost. RBoost uses Riemannian distance between two square-root densities (in closed form) – used to represent the distribution over the training data and the classification error respectively – to regularize the error distribution in an iterative update formula. Since this distance is in closed form, RBoost requires much less computational cost compared to other regularized Boosting algorithms. We present several experimental results depicting the performance of our algorithm in comparison to recently published methods, LP-Boost and CAVIAR, on a variety of datasets including the publicly available OASIS database, a home grown Epilepsy database and the well known UCI repository. Results depict that the RBoost algorithm performs better than the competing methods in terms of accuracy and efficiency. PMID:21927643

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

PubMed Central

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

NASA Astrophysics Data System (ADS)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

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

NASA Astrophysics Data System (ADS)

Lan, Qi; Xu, Zhiyong

2016-09-01

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

Cost-sensitive AdaBoost algorithm for ordinal regression based on extreme learning machine.

PubMed

Riccardi, Annalisa; Fernández-Navarro, Francisco; Carloni, Sante

2014-10-01

In this paper, the well known stagewise additive modeling using a multiclass exponential (SAMME) boosting algorithm is extended to address problems where there exists a natural order in the targets using a cost-sensitive approach. The proposed ensemble model uses an extreme learning machine (ELM) model as a base classifier (with the Gaussian kernel and the additional regularization parameter). The closed form of the derived weighted least squares problem is provided, and it is employed to estimate analytically the parameters connecting the hidden layer to the output layer at each iteration of the boosting algorithm. Compared to the state-of-the-art boosting algorithms, in particular those using ELM as base classifier, the suggested technique does not require the generation of a new training dataset at each iteration. The adoption of the weighted least squares formulation of the problem has been presented as an unbiased and alternative approach to the already existing ELM boosting techniques. Moreover, the addition of a cost model for weighting the patterns, according to the order of the targets, enables the classifier to tackle ordinal regression problems further. The proposed method has been validated by an experimental study by comparing it with already existing ensemble methods and ELM techniques for ordinal regression, showing competitive results.

Going beyond a First Reader: A Machine Learning Methodology for Optimizing Cost and Performance in Breast Ultrasound Diagnosis.

PubMed

Venkatesh, Santosh S; Levenback, Benjamin J; Sultan, Laith R; Bouzghar, Ghizlane; Sehgal, Chandra M

2015-12-01

The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two independent feature sets consisting of visual features based on a radiologist's interpretation of images and computer-extracted features when used as first and second readers and combined by adaptive boosting (AdaBoost) and a pruning classifier resulted in a very high level of diagnostic performance (area under the receiver operating characteristic curve = 0.98) at a cost of pruning a fraction (20%) of the cases for further evaluation by independent methods. AdaBoost also improved the diagnostic performance of the individual human observers and increased the agreement between their analyses. Pairing AdaBoost with selective pruning is a principled methodology for achieving high diagnostic performance without the added cost of an additional reader for differentiating solid breast masses by ultrasound. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

Short-term wind speed prediction based on the wavelet transformation and Adaboost neural network

NASA Astrophysics Data System (ADS)

Hai, Zhou; Xiang, Zhu; Haijian, Shao; Ji, Wu

2018-03-01

The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability of the grid operation. Typically, the traditional forecasting method does not take into account the frequency characteristics of wind speed, which cannot reflect the nature of the wind speed signal changes result from the low generality ability of the model structure. AdaBoost neural network in combination with the multi-resolution and multi-scale decomposition of wind speed is proposed to design the model structure in order to improve the forecasting accuracy and generality ability. The experimental evaluation using the data from a real wind farm in Jiangsu province is given to demonstrate the proposed strategy can improve the robust and accuracy of the forecasted variable.

A prediction model of short-term ionospheric foF2 based on AdaBoost

NASA Astrophysics Data System (ADS)

Zhao, Xiukuan; Ning, Baiqi; Liu, Libo; Song, Gangbing

2014-02-01

In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer (foF2) one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years' foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years' data were used as a training dataset and the second eleven years' data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.

A prediction model of short-term ionospheric foF2 Based on AdaBoost

NASA Astrophysics Data System (ADS)

Zhao, Xiukuan; Liu, Libo; Ning, Baiqi

Accurate specifications of spatial and temporal variations of the ionosphere during geomagnetic quiet and disturbed conditions are critical for applications, such as HF communications, satellite positioning and navigation, power grids, pipelines, etc. Therefore, developing empirical models to forecast the ionospheric perturbations is of high priority in real applications. The critical frequency of the F2 layer, foF2, is an important ionospheric parameter, especially for radio wave propagation applications. In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years’ foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years’ data were used as a training dataset and the second eleven years’ data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.

Improving ensemble decision tree performance using Adaboost and Bagging

NASA Astrophysics Data System (ADS)

Hasan, Md. Rajib; Siraj, Fadzilah; Sainin, Mohd Shamrie

2015-12-01

Ensemble classifier systems are considered as one of the most promising in medical data classification and the performance of deceision tree classifier can be increased by the ensemble method as it is proven to be better than single classifiers. However, in a ensemble settings the performance depends on the selection of suitable base classifier. This research employed two prominent esemble s namely Adaboost and Bagging with base classifiers such as Random Forest, Random Tree, j48, j48grafts and Logistic Model Regression (LMT) that have been selected independently. The empirical study shows that the performance varries when different base classifiers are selected and even some places overfitting issue also been noted. The evidence shows that ensemble decision tree classfiers using Adaboost and Bagging improves the performance of selected medical data sets.

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Posture recognition associated with lifting of heavy objects using Kinect and Adaboost

NASA Astrophysics Data System (ADS)

Raut, Sayli; Navaneethakrishna, M.; Ramakrishnan, S.

2017-12-01

Lifting of heavy objects is the common task in the industries. Recent statistics from the Bureau of Labour indicate, back injuries account for one of every five injuries in the workplace. Eighty per cent of these injuries occur to the lower back and are associated with manual materials handling tasks. According to the Industrial ergonomic safety manual, Squatting is the correct posture for lifting a heavy object. In this work, an attempt has been made to monitor posture of the workers during squat and stoop using 3D motion capture and machine learning techniques. For this, Microsoft Kinect V2 is used for capturing the depth data. Further, Dynamic Time Warping and Euclidian distance algorithms are used for extraction of features. Ada-boost algorithm is used for classification of stoop and squat. The results show that the 3D image data is large and complex to analyze. The application of nonlinear and linear metrics captures the variation in the lifting pattern. Additionally, the features extracted from this metric resulted in a classification accuracy of 85% and 81% respectively. This framework may be put-upon to alert the workers in the industrial ergonomic environments.

Adaptive guidance for an aero-assisted boost vehicle

NASA Astrophysics Data System (ADS)

Pamadi, Bandu N.; Taylor, Lawrence W., Jr.; Price, Douglas B.

An adaptive guidance system incorporating dynamic pressure constraint is studied for a single stage to low earth orbit (LEO) aero-assist booster with thrust gimbal angle as the control variable. To derive an adaptive guidance law, cubic spline functions are used to represent the ascent profile. The booster flight to LEO is divided into initial and terminal phases. In the initial phase, the ascent profile is continuously updated to maximize the performance of the boost vehicle enroute. A linear feedback control is used in the terminal phase to guide the aero-assisted booster onto the desired LEO. The computer simulation of the vehicle dynamics considers a rotating spherical earth, inverse square (Newtonian) gravity field and an exponential model for the earth's atmospheric density. This adaptive guidance algorithm is capable of handling large deviations in both atmospheric conditions and modeling uncertainties, while ensuring maximum booster performance.

Real-time detection with AdaBoost-svm combination in various face orientation

NASA Astrophysics Data System (ADS)

Fhonna, R. P.; Nasution, M. K. M.; Tulus

2018-03-01

Most of the research has used algorithm AdaBoost-SVM for face detection. However, to our knowledge so far there is no research has been facing detection on real-time data with various orientations using the combination of AdaBoost and Support Vector Machine (SVM). Characteristics of complex and diverse face variations and real-time data in various orientations, and with a very complex application will slow down the performance of the face detection system this becomes a challenge in this research. Face orientation performed on the detection system, that is 900, 450, 00, -450, and -900. This combination method is expected to be an effective and efficient solution in various face orientations. The results showed that the highest average detection rate is on the face detection oriented 00 and the lowest detection rate is in the face orientation 900.

AdaBoost-based on-line signature verifier

NASA Astrophysics Data System (ADS)

Hongo, Yasunori; Muramatsu, Daigo; Matsumoto, Takashi

2005-03-01

Authentication of individuals is rapidly becoming an important issue. The authors previously proposed a Pen-input online signature verification algorithm. The algorithm considers a writer"s signature as a trajectory of pen position, pen pressure, pen azimuth, and pen altitude that evolve over time, so that it is dynamic and biometric. Many algorithms have been proposed and reported to achieve accuracy for on-line signature verification, but setting the threshold value for these algorithms is a problem. In this paper, we introduce a user-generic model generated by AdaBoost, which resolves this problem. When user- specific models (one model for each user) are used for signature verification problems, we need to generate the models using only genuine signatures. Forged signatures are not available because imposters do not give forged signatures for training in advance. However, we can make use of another's forged signature in addition to the genuine signatures for learning by introducing a user generic model. And Adaboost is a well-known classification algorithm, making final decisions depending on the sign of the output value. Therefore, it is not necessary to set the threshold value. A preliminary experiment is performed on a database consisting of data from 50 individuals. This set consists of western-alphabet-based signatures provide by a European research group. In this experiment, our algorithm gives an FRR of 1.88% and an FAR of 1.60%. Since no fine-tuning was done, this preliminary result looks very promising.

A boosted optimal linear learner for retinal vessel segmentation

NASA Astrophysics Data System (ADS)

Poletti, E.; Grisan, E.

2014-03-01

Ocular fundus images provide important information about retinal degeneration, which may be related to acute pathologies or to early signs of systemic diseases. An automatic and quantitative assessment of vessel morphological features, such as diameters and tortuosity, can improve clinical diagnosis and evaluation of retinopathy. At variance with available methods, we propose a data-driven approach, in which the system learns a set of optimal discriminative convolution kernels (linear learner). The set is progressively built based on an ADA-boost sample weighting scheme, providing seamless integration between linear learner estimation and classification. In order to capture the vessel appearance changes at different scales, the kernels are estimated on a pyramidal decomposition of the training samples. The set is employed as a rotating bank of matched filters, whose response is used by the boosted linear classifier to provide a classification of each image pixel into the two classes of interest (vessel/background). We tested the approach fundus images available from the DRIVE dataset. We show that the segmentation performance yields an accuracy of 0.94.

Peculiarities of use of ECOC and AdaBoost based classifiers for thematic processing of hyperspectral data

NASA Astrophysics Data System (ADS)

Dementev, A. O.; Dmitriev, E. V.; Kozoderov, V. V.; Egorov, V. D.

2017-10-01

Hyperspectral imaging is up-to-date promising technology widely applied for the accurate thematic mapping. The presence of a large number of narrow survey channels allows us to use subtle differences in spectral characteristics of objects and to make a more detailed classification than in the case of using standard multispectral data. The difficulties encountered in the processing of hyperspectral images are usually associated with the redundancy of spectral information which leads to the problem of the curse of dimensionality. Methods currently used for recognizing objects on multispectral and hyperspectral images are usually based on standard base supervised classification algorithms of various complexity. Accuracy of these algorithms can be significantly different depending on considered classification tasks. In this paper we study the performance of ensemble classification methods for the problem of classification of the forest vegetation. Error correcting output codes and boosting are tested on artificial data and real hyperspectral images. It is demonstrates, that boosting gives more significant improvement when used with simple base classifiers. The accuracy in this case in comparable the error correcting output code (ECOC) classifier with Gaussian kernel SVM base algorithm. However the necessity of boosting ECOC with Gaussian kernel SVM is questionable. It is demonstrated, that selected ensemble classifiers allow us to recognize forest species with high enough accuracy which can be compared with ground-based forest inventory data.

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

Automatic Boosted Flood Mapping from Satellite Data

NASA Technical Reports Server (NTRS)

Coltin, Brian; McMichael, Scott; Smith, Trey; Fong, Terrence

2016-01-01

Numerous algorithms have been proposed to map floods from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, most require human input to succeed, either to specify a threshold value or to manually annotate training data. We introduce a new algorithm based on Adaboost which effectively maps floods without any human input, allowing for a truly rapid and automatic response. The Adaboost algorithm combines multiple thresholds to achieve results comparable to state-of-the-art algorithms which do require human input. We evaluate Adaboost, as well as numerous previously proposed flood mapping algorithms, on multiple MODIS flood images, as well as on hundreds of non-flood MODIS lake images, demonstrating its effectiveness across a wide variety of conditions.

[State Recognition of Solid Fermentation Process Based on Near Infrared Spectroscopy with Adaboost and Spectral Regression Discriminant Analysis].

PubMed

Yu, Shuang; Liu, Guo-hai; Xia, Rong-sheng; Jiang, Hui

2016-01-01

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris II), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct

An efficient ensemble learning method for gene microarray classification.

PubMed

Osareh, Alireza; Shadgar, Bita

2013-01-01

The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

Adaptive fractional order sliding mode control for Boost converter in the Battery/Supercapacitor HESS

PubMed Central

Xu, Dan; Zhou, Huan; Zhou, Tao

2018-01-01

In this paper, an adaptive fractional order sliding mode control (AFSMC) scheme is designed for the current tracking control of the Boost-type converter in a Battery/Supercapacitor hybrid energy storage system (HESS). In order to stabilize the current, the adaptation rules based on state-observer and Lyapunov function are being designed. A fractional order sliding surface function is defined based on the tracking current error and adaptive rules. Furthermore, through fractional order analysis, the stability of the fractional order control system is proven, and the value of the fractional order (λ) is being investigated. In addition, the effectiveness of the proposed AFSMC strategy is being verified by numerical simulations. The advantages of good transient response and robustness to uncertainty are being indicated by this design, when compared with a conventional integer order sliding mode control system. PMID:29702696

Adaptive fractional order sliding mode control for Boost converter in the Battery/Supercapacitor HESS.

PubMed

Wang, Jianlin; Xu, Dan; Zhou, Huan; Zhou, Tao

2018-01-01

In this paper, an adaptive fractional order sliding mode control (AFSMC) scheme is designed for the current tracking control of the Boost-type converter in a Battery/Supercapacitor hybrid energy storage system (HESS). In order to stabilize the current, the adaptation rules based on state-observer and Lyapunov function are being designed. A fractional order sliding surface function is defined based on the tracking current error and adaptive rules. Furthermore, through fractional order analysis, the stability of the fractional order control system is proven, and the value of the fractional order (λ) is being investigated. In addition, the effectiveness of the proposed AFSMC strategy is being verified by numerical simulations. The advantages of good transient response and robustness to uncertainty are being indicated by this design, when compared with a conventional integer order sliding mode control system.

Designing boosting ensemble of relational fuzzy systems.

PubMed

Scherer, Rafał

2010-10-01

A method frequently used in classification systems for improving classification accuracy is to combine outputs of several classifiers. Among various types of classifiers, fuzzy ones are tempting because of using intelligible fuzzy if-then rules. In the paper we build an AdaBoost ensemble of relational neuro-fuzzy classifiers. Relational fuzzy systems bond input and output fuzzy linguistic values by a binary relation; thus, fuzzy rules have additional, comparing to traditional fuzzy systems, weights - elements of a fuzzy relation matrix. Thanks to this the system is better adjustable to data during learning. In the paper an ensemble of relational fuzzy systems is proposed. The problem is that such an ensemble contains separate rule bases which cannot be directly merged. As systems are separate, we cannot treat fuzzy rules coming from different systems as rules from the same (single) system. In the paper, the problem is addressed by a novel design of fuzzy systems constituting the ensemble, resulting in normalization of individual rule bases during learning. The method described in the paper is tested on several known benchmarks and compared with other machine learning solutions from the literature.

Automatic detection of apical roots in oral radiographs

NASA Astrophysics Data System (ADS)

Wu, Yi; Xie, Fangfang; Yang, Jie; Cheng, Erkang; Megalooikonomou, Vasileios; Ling, Haibin

2012-03-01

The apical root regions play an important role in analysis and diagnosis of many oral diseases. Automatic detection of such regions is consequently the first step toward computer-aided diagnosis of these diseases. In this paper we propose an automatic method for periapical root region detection by using the state-of-theart machine learning approaches. Specifically, we have adapted the AdaBoost classifier for apical root detection. One challenge in the task is the lack of training cases especially for diseased ones. To handle this problem, we boost the training set by including more root regions that are close to the annotated ones and decompose the original images to randomly generate negative samples. Based on these training samples, the Adaboost algorithm in combination with Haar wavelets is utilized in this task to train an apical root detector. The learned detector usually generates a large amount of true and false positives. In order to reduce the number of false positives, a confidence score for each candidate detection result is calculated for further purification. We first merge the detected regions by combining tightly overlapped detected candidate regions and then we use the confidence scores from the Adaboost detector to eliminate the false positives. The proposed method is evaluated on a dataset containing 39 annotated digitized oral X-Ray images from 21 patients. The experimental results show that our approach can achieve promising detection accuracy.

Using Temporal Covariance of Motion and Geometric Features via Boosting for Human Fall Detection.

PubMed

Ali, Syed Farooq; Khan, Reamsha; Mahmood, Arif; Hassan, Malik Tahir; Jeon, And Moongu

2018-06-12

Fall induced damages are serious incidences for aged as well as young persons. A real-time automatic and accurate fall detection system can play a vital role in timely medication care which will ultimately help to decrease the damages and complications. In this paper, we propose a fast and more accurate real-time system which can detect people falling in videos captured by surveillance cameras. Novel temporal and spatial variance-based features are proposed which comprise the discriminatory motion, geometric orientation and location of the person. These features are used along with ensemble learning strategy of boosting with J48 and Adaboost classifiers. Experiments have been conducted on publicly available standard datasets including Multiple Cameras Fall ( with 2 classes and 3 classes ) and UR Fall Detection achieving percentage accuracies of 99.2, 99.25 and 99.0, respectively. Comparisons with nine state-of-the-art methods demonstrate the effectiveness of the proposed approach on both datasets.

Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools

NASA Astrophysics Data System (ADS)

Ouyang, Qin; Chen, Quansheng; Zhao, Jiewen

2016-02-01

The approach presented herein reports the application of near infrared (NIR) spectroscopy, in contrast with human sensory panel, as a tool for estimating Chinese rice wine quality; concretely, to achieve the prediction of the overall sensory scores assigned by the trained sensory panel. Back propagation artificial neural network (BPANN) combined with adaptive boosting (AdaBoost) algorithm, namely BP-AdaBoost, as a novel nonlinear algorithm, was proposed in modeling. First, the optimal spectra intervals were selected by synergy interval partial least square (Si-PLS). Then, BP-AdaBoost model based on the optimal spectra intervals was established, called Si-BP-AdaBoost model. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient (Rp) and root mean square error of prediction (RMSEP) in prediction set. Si-BP-AdaBoost showed excellent performance in comparison with other models. The best Si-BP-AdaBoost model was achieved with Rp = 0.9180 and RMSEP = 2.23 in the prediction set. It was concluded that NIR spectroscopy combined with Si-BP-AdaBoost was an appropriate method for the prediction of the sensory quality in Chinese rice wine.

Risk-adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Kim, Yusung

Currently, there is great interest in integrating biological information into intensity-modulated radiotherapy (IMRT) treatment planning with the aim of boosting high-risk tumor subvolumes. Selective boosting of tumor subvolumes can be accomplished without violating normal tissue complication constraints using information from functional imaging. In this work we have developed a risk-adaptive optimization-framework that utilizes a nonlinear biological objective function. Employing risk-adaptive radiotherapy for prostate cancer, it is possible to increase the equivalent uniform dose (EUD) by up to 35.4 Gy in tumor subvolumes having the highest risk classification without increasing normal tissue complications. Subsequently, we have studied the impact of functional imaging accuracy, and found on the one hand that loss in sensitivity had a large impact on expected local tumor control, which was maximal when a low-risk classification for the remaining low risk PTV was chosen. While on the other hand loss in specificity appeared to have a minimal impact on normal tissue sparing. Therefore, it appears that in order to improve the therapeutic ratio a functional imaging technique with a high sensitivity, rather than specificity, is needed. Last but not least a comparison study between selective boosting IMRT strategies and uniform-boosting IMRT strategies yielding the same EUD to the overall PTV was carried out, and found that selective boosting IMRT considerably improves expected TCP compared to uniform-boosting IMRT, especially when lack of control of the high-risk tumor subvolumes is the cause of expected therapy failure. Furthermore, while selective boosting IMRT, using physical dose-volume objectives, did yield similar rectal and bladder sparing when compared its equivalent uniform-boosting IMRT plan, risk-adaptive radiotherapy, utilizing biological objective functions, did yield a 5.3% reduction in NTCP for the rectum. Hence, in risk-adaptive radiotherapy the

Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools.

PubMed

Ouyang, Qin; Chen, Quansheng; Zhao, Jiewen

2016-02-05

The approach presented herein reports the application of near infrared (NIR) spectroscopy, in contrast with human sensory panel, as a tool for estimating Chinese rice wine quality; concretely, to achieve the prediction of the overall sensory scores assigned by the trained sensory panel. Back propagation artificial neural network (BPANN) combined with adaptive boosting (AdaBoost) algorithm, namely BP-AdaBoost, as a novel nonlinear algorithm, was proposed in modeling. First, the optimal spectra intervals were selected by synergy interval partial least square (Si-PLS). Then, BP-AdaBoost model based on the optimal spectra intervals was established, called Si-BP-AdaBoost model. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient (Rp) and root mean square error of prediction (RMSEP) in prediction set. Si-BP-AdaBoost showed excellent performance in comparison with other models. The best Si-BP-AdaBoost model was achieved with Rp=0.9180 and RMSEP=2.23 in the prediction set. It was concluded that NIR spectroscopy combined with Si-BP-AdaBoost was an appropriate method for the prediction of the sensory quality in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping

NASA Astrophysics Data System (ADS)

Naghibi, Seyed Amir; Moghaddam, Davood Davoodi; Kalantar, Bahareh; Pradhan, Biswajeet; Kisi, Ozgur

2017-05-01

In recent years, application of ensemble models has been increased tremendously in various types of natural hazard assessment such as landslides and floods. However, application of this kind of robust models in groundwater potential mapping is relatively new. This study applied four data mining algorithms including AdaBoost, Bagging, generalized additive model (GAM), and Naive Bayes (NB) models to map groundwater potential. Then, a novel frequency ratio data mining ensemble model (FREM) was introduced and evaluated. For this purpose, eleven groundwater conditioning factors (GCFs), including altitude, slope aspect, slope angle, plan curvature, stream power index (SPI), river density, distance from rivers, topographic wetness index (TWI), land use, normalized difference vegetation index (NDVI), and lithology were mapped. About 281 well locations with high potential were selected. Wells were randomly partitioned into two classes for training the models (70% or 197) and validating them (30% or 84). AdaBoost, Bagging, GAM, and NB algorithms were employed to get groundwater potential maps (GPMs). The GPMs were categorized into potential classes using natural break method of classification scheme. In the next stage, frequency ratio (FR) value was calculated for the output of the four aforementioned models and were summed, and finally a GPM was produced using FREM. For validating the models, area under receiver operating characteristics (ROC) curve was calculated. The ROC curve for prediction dataset was 94.8, 93.5, 92.6, 92.0, and 84.4% for FREM, Bagging, AdaBoost, GAM, and NB models, respectively. The results indicated that FREM had the best performance among all the models. The better performance of the FREM model could be related to reduction of over fitting and possible errors. Other models such as AdaBoost, Bagging, GAM, and NB also produced acceptable performance in groundwater modelling. The GPMs produced in the current study may facilitate groundwater exploitation

Application of adaptive boosting to EP-derived multilayer feed-forward neural networks (MLFN) to improve benign/malignant breast cancer classification

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Masters, Timothy D.; Lo, Joseph Y.; McKee, Dan

2001-07-01

A new neural network technology was developed for improving the benign/malignant diagnosis of breast cancer using mammogram findings. A new paradigm, Adaptive Boosting (AB), uses a markedly different theory in solutioning Computational Intelligence (CI) problems. AB, a new machine learning paradigm, focuses on finding weak learning algorithm(s) that initially need to provide slightly better than random performance (i.e., approximately 55%) when processing a mammogram training set. Then, by successive development of additional architectures (using the mammogram training set), the adaptive boosting process improves the performance of the basic Evolutionary Programming derived neural network architectures. The results of these several EP-derived hybrid architectures are then intelligently combined and tested using a similar validation mammogram data set. Optimization focused on improving specificity and positive predictive value at very high sensitivities, where an analysis of the performance of the hybrid would be most meaningful. Using the DUKE mammogram database of 500 biopsy proven samples, on average this hybrid was able to achieve (under statistical 5-fold cross-validation) a specificity of 48.3% and a positive predictive value (PPV) of 51.8% while maintaining 100% sensitivity. At 97% sensitivity, a specificity of 56.6% and a PPV of 55.8% were obtained.

Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier

PubMed Central

Min, Yang; Zhu, Dingju

2014-01-01

Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier. PMID:25003153

Obscenity detection using haar-like features and Gentle Adaboost classifier.

PubMed

Mustafa, Rashed; Min, Yang; Zhu, Dingju

2014-01-01

Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

NASA Astrophysics Data System (ADS)

Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

2013-10-01

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

Robust boosting via convex optimization

NASA Astrophysics Data System (ADS)

Rätsch, Gunnar

2001-12-01

In this work we consider statistical learning problems. A learning machine aims to extract information from a set of training examples such that it is able to predict the associated label on unseen examples. We consider the case where the resulting classification or regression rule is a combination of simple rules - also called base hypotheses. The so-called boosting algorithms iteratively find a weighted linear combination of base hypotheses that predict well on unseen data. We address the following issues: o The statistical learning theory framework for analyzing boosting methods. We study learning theoretic guarantees on the prediction performance on unseen examples. Recently, large margin classification techniques emerged as a practical result of the theory of generalization, in particular Boosting and Support Vector Machines. A large margin implies a good generalization performance. Hence, we analyze how large the margins in boosting are and find an improved algorithm that is able to generate the maximum margin solution. o How can boosting methods be related to mathematical optimization techniques? To analyze the properties of the resulting classification or regression rule, it is of high importance to understand whether and under which conditions boosting converges. We show that boosting can be used to solve large scale constrained optimization problems, whose solutions are well characterizable. To show this, we relate boosting methods to methods known from mathematical optimization, and derive convergence guarantees for a quite general family of boosting algorithms. o How to make Boosting noise robust? One of the problems of current boosting techniques is that they are sensitive to noise in the training sample. In order to make boosting robust, we transfer the soft margin idea from support vector learning to boosting. We develop theoretically motivated regularized algorithms that exhibit a high noise robustness. o How to adapt boosting to regression problems

Computer simulations of optimum boost and buck-boost converters

NASA Technical Reports Server (NTRS)

Rahman, S.

1982-01-01

The development of mathematicl models suitable for minimum weight boost and buck-boost converter designs are presented. The facility of an augumented Lagrangian (ALAG) multiplier-based nonlinear programming technique is demonstrated for minimum weight design optimizations of boost and buck-boost power converters. ALAG-based computer simulation results for those two minimum weight designs are discussed. Certain important features of ALAG are presented in the framework of a comprehensive design example for boost and buck-boost power converter design optimization. The study provides refreshing design insight of power converters and presents such information as weight annd loss profiles of various semiconductor components and magnetics as a function of the switching frequency.

Full Intelligent Cancer Classification of Thermal Breast Images to Assist Physician in Clinical Diagnostic Applications

PubMed Central

Lashkari, AmirEhsan; Pak, Fatemeh; Firouzmand, Mohammad

2016-01-01

, different classifiers such as AdaBoost, Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naïve Bayes (NB) and probability Neural Network (PNN) are assessed to find the best suitable one. These steps are applied on different thermogram images degrees. The results obtained on native database showed the best and significant performance of the proposed algorithm in comprise to the similar studies. According to experimental results, GA combined with AdaBoost with the mean accuracy of 85.33% and 87.42% on the left and right breast images with 0 degree, GA combined with AdaBoost with mean accuracy of 85.17% on the left breast images with 45 degree and mRMR combined with AdaBoost with mean accuracy of 85.15% on the right breast images with 45 degree, and also GA combined with AdaBoost with a mean accuracy of 84.67% and 86.21%, on the left and right breast images with 90 degree, are the best combinations of feature selection and classifier for evaluation of breast images. PMID:27014608

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

PubMed Central

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-01-01

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

PubMed

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-07-19

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

Sliding mode control of direct coupled interleaved boost converter for fuel cell

NASA Astrophysics Data System (ADS)

Wang, W. Y.; Ding, Y. H.; Ke, X.; Ma, X.

2017-12-01

A three phase direct coupled interleaved boost converter (TP-DIBC) was recommended in this paper. This converter has a small unbalance current sharing among the branches of TP-DIBC. An adaptive control law sliding mode control (SMC) is designed for the TP-DIBC. The aim is to 1) reduce ripple output voltage, inductor current and regulate output voltage tightly 2) The total current carried by direct coupled interleaved boost converter (DIBC) must be equally shared between different parallel branches. The efficacy and robustness of the proposed TP-DIBC and adaptive SMC is confirmed via computer simulations using Matlab SimPower System Tools. The simulation result is in line with the expectation.

Component Pin Recognition Using Algorithms Based on Machine Learning

NASA Astrophysics Data System (ADS)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

MACE prediction of acute coronary syndrome via boosted resampling classification using electronic medical records.

PubMed

Huang, Zhengxing; Chan, Tak-Ming; Dong, Wei

2017-02-01

Major adverse cardiac events (MACE) of acute coronary syndrome (ACS) often occur suddenly resulting in high mortality and morbidity. Recently, the rapid development of electronic medical records (EMR) provides the opportunity to utilize the potential of EMR to improve the performance of MACE prediction. In this study, we present a novel data-mining based approach specialized for MACE prediction from a large volume of EMR data. The proposed approach presents a new classification algorithm by applying both over-sampling and under-sampling on minority-class and majority-class samples, respectively, and integrating the resampling strategy into a boosting framework so that it can effectively handle imbalance of MACE of ACS patients analogous to domain practice. The method learns a new and stronger MACE prediction model each iteration from a more difficult subset of EMR data with wrongly predicted MACEs of ACS patients by a previous weak model. We verify the effectiveness of the proposed approach on a clinical dataset containing 2930 ACS patient samples with 268 feature types. While the imbalanced ratio does not seem extreme (25.7%), MACE prediction targets pose great challenge to traditional methods. As these methods degenerate dramatically with increasing imbalanced ratios, the performance of our approach for predicting MACE remains robust and reaches 0.672 in terms of AUC. On average, the proposed approach improves the performance of MACE prediction by 4.8%, 4.5%, 8.6% and 4.8% over the standard SVM, Adaboost, SMOTE, and the conventional GRACE risk scoring system for MACE prediction, respectively. We consider that the proposed iterative boosting approach has demonstrated great potential to meet the challenge of MACE prediction for ACS patients using a large volume of EMR. Copyright © 2017 Elsevier Inc. All rights reserved.

Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition

NASA Astrophysics Data System (ADS)

Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa

A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.

Gender classification of running subjects using full-body kinematics

NASA Astrophysics Data System (ADS)

Williams, Christina M.; Flora, Jeffrey B.; Iftekharuddin, Khan M.

2016-05-01

This paper proposes novel automated gender classification of subjects while engaged in running activity. The machine learning techniques include preprocessing steps using principal component analysis followed by classification with linear discriminant analysis, and nonlinear support vector machines, and decision-stump with AdaBoost. The dataset consists of 49 subjects (25 males, 24 females, 2 trials each) all equipped with approximately 80 retroreflective markers. The trials are reflective of the subject's entire body moving unrestrained through a capture volume at a self-selected running speed, thus producing highly realistic data. The classification accuracy using leave-one-out cross validation for the 49 subjects is improved from 66.33% using linear discriminant analysis to 86.74% using the nonlinear support vector machine. Results are further improved to 87.76% by means of implementing a nonlinear decision stump with AdaBoost classifier. The experimental findings suggest that the linear classification approaches are inadequate in classifying gender for a large dataset with subjects running in a moderately uninhibited environment.

Boosted ARTMAP: modifications to fuzzy ARTMAP motivated by boosting theory.

PubMed

Verzi, Stephen J; Heileman, Gregory L; Georgiopoulos, Michael

2006-05-01

In this paper, several modifications to the Fuzzy ARTMAP neural network architecture are proposed for conducting classification in complex, possibly noisy, environments. The goal of these modifications is to improve upon the generalization performance of Fuzzy ART-based neural networks, such as Fuzzy ARTMAP, in these situations. One of the major difficulties of employing Fuzzy ARTMAP on such learning problems involves over-fitting of the training data. Structural risk minimization is a machine-learning framework that addresses the issue of over-fitting by providing a backbone for analysis as well as an impetus for the design of better learning algorithms. The theory of structural risk minimization reveals a trade-off between training error and classifier complexity in reducing generalization error, which will be exploited in the learning algorithms proposed in this paper. Boosted ART extends Fuzzy ART by allowing the spatial extent of each cluster formed to be adjusted independently. Boosted ARTMAP generalizes upon Fuzzy ARTMAP by allowing non-zero training error in an effort to reduce the hypothesis complexity and hence improve overall generalization performance. Although Boosted ARTMAP is strictly speaking not a boosting algorithm, the changes it encompasses were motivated by the goals that one strives to achieve when employing boosting. Boosted ARTMAP is an on-line learner, it does not require excessive parameter tuning to operate, and it reduces precisely to Fuzzy ARTMAP for particular parameter values. Another architecture described in this paper is Structural Boosted ARTMAP, which uses both Boosted ART and Boosted ARTMAP to perform structural risk minimization learning. Structural Boosted ARTMAP will allow comparison of the capabilities of off-line versus on-line learning as well as empirical risk minimization versus structural risk minimization using Fuzzy ARTMAP-based neural network architectures. Both empirical and theoretical results are presented to

Pan-Influenza A Protection by Prime-Boost Vaccination with Cold-Adapted Live-Attenuated Influenza Vaccine in a Mouse Model.

PubMed

Jang, Yo Han; Kim, Joo Young; Byun, Young Ho; Son, Ahyun; Lee, Jeong-Yoon; Lee, Yoon Jae; Chang, Jun; Seong, Baik Lin

2018-01-01

Influenza virus infections continually pose a major public health threat with seasonal epidemics and sporadic pandemics worldwide. While currently licensed influenza vaccines provide only strain-specific protection, antigenic drift and shift occasionally render the viruses resistant to the host immune responses, which highlight the need for a vaccine that provides broad protection against multiple subtypes. In this study, we suggest a vaccination strategy using cold-adapted, live attenuated influenza vaccines (CAIVs) to provide a broad, potent, and safe cross-protection covering antigenically distinct hemagglutinin (HA) groups 1 and 2 influenza viruses. Using a mouse model, we tested different prime-boost combinations of CAIVs for their ability to induce humoral and T-cell responses, and protective efficacy against H1 and H5 (HA group 1) as well as H3 and H7 (HA group 2) influenza viruses. Notably, even in the absence of antibody-mediated neutralizing activity or HA inhibitory activity in vitro , CAIVs provided a potent protection against heterologous and heterosubtypic lethal challenges in vivo . Heterologous combination of prime (H1)-boost (H5) vaccine strains showed the most potent cross-protection efficacy. In vivo depletion experiments demonstrated not only that T cells and natural killer cells contributed to the cross-protection, but also the involvement of antibody-dependent mechanisms for the cross-protection. Vaccination-induced antibodies did not enhance the infectivity of heterologous viruses, and prime vaccination did not interfere with neutralizing antibody generation by the boost vaccination, allaying vaccine safety concerns associated with heterogeneity between the vaccines and challenge strains. Our data show that CAIV-based strategy can serve as a simple but powerful option for developing a "truly" universal influenza vaccine providing pan-influenza A protection, which has not been achieved yet by other vaccine strategies. The promising results

Pan-Influenza A Protection by Prime–Boost Vaccination with Cold-Adapted Live-Attenuated Influenza Vaccine in a Mouse Model

PubMed Central

Jang, Yo Han; Kim, Joo Young; Byun, Young Ho; Son, Ahyun; Lee, Jeong-Yoon; Lee, Yoon Jae; Chang, Jun; Seong, Baik Lin

2018-01-01

Influenza virus infections continually pose a major public health threat with seasonal epidemics and sporadic pandemics worldwide. While currently licensed influenza vaccines provide only strain-specific protection, antigenic drift and shift occasionally render the viruses resistant to the host immune responses, which highlight the need for a vaccine that provides broad protection against multiple subtypes. In this study, we suggest a vaccination strategy using cold-adapted, live attenuated influenza vaccines (CAIVs) to provide a broad, potent, and safe cross-protection covering antigenically distinct hemagglutinin (HA) groups 1 and 2 influenza viruses. Using a mouse model, we tested different prime–boost combinations of CAIVs for their ability to induce humoral and T-cell responses, and protective efficacy against H1 and H5 (HA group 1) as well as H3 and H7 (HA group 2) influenza viruses. Notably, even in the absence of antibody-mediated neutralizing activity or HA inhibitory activity in vitro, CAIVs provided a potent protection against heterologous and heterosubtypic lethal challenges in vivo. Heterologous combination of prime (H1)–boost (H5) vaccine strains showed the most potent cross-protection efficacy. In vivo depletion experiments demonstrated not only that T cells and natural killer cells contributed to the cross-protection, but also the involvement of antibody-dependent mechanisms for the cross-protection. Vaccination-induced antibodies did not enhance the infectivity of heterologous viruses, and prime vaccination did not interfere with neutralizing antibody generation by the boost vaccination, allaying vaccine safety concerns associated with heterogeneity between the vaccines and challenge strains. Our data show that CAIV-based strategy can serve as a simple but powerful option for developing a “truly” universal influenza vaccine providing pan-influenza A protection, which has not been achieved yet by other vaccine strategies. The promising

Adaptive super-twisting sliding mode control for a three-phase single-stage grid-connected differential boost inverter based photovoltaic system.

PubMed

Pati, Akshaya K; Sahoo, N C

2017-07-01

This paper presents an adaptive super-twisting sliding mode control (STC) along with double-loop control for voltage tracking performance of three-phase differential boost inverter and DC-link capacitor voltage regulation in grid-connected PV system. The effectiveness of the proposed control strategies are demonstrated under realistic scenarios such as variations in solar insolation, load power demand, grid voltage, and transition from grid-connected to standalone mode etc. Additional supplementary power quality control functions such as harmonic compensation, and reactive power management are also investigated with the proposed control strategy. The results are compared with conventional proportional-integral controller, and PWM sliding mode controller. The system performance is evaluated in simulation and in real-time. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear program based optimization of boost and buck-boost converter designs

NASA Astrophysics Data System (ADS)

Rahman, S.; Lee, F. C.

The facility of an Augmented Lagrangian (ALAG) multiplier based nonlinear programming technique is demonstrated for minimum-weight design optimizations of boost and buck-boost power converters. Certain important features of ALAG are presented in the framework of a comprehensive design example for buck-boost power converter design optimization. The study provides refreshing design insight of power converters and presents such information as weight and loss profiles of various semiconductor components and magnetics as a function of the switching frequency.

SemiBoost: boosting for semi-supervised learning.

PubMed

Mallapragada, Pavan Kumar; Jin, Rong; Jain, Anil K; Liu, Yi

2009-11-01

Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We call this as the Semi-supervised improvement problem, to distinguish the proposed approach from the existing approaches. We design a metasemi-supervised learning algorithm that wraps around the underlying supervised algorithm and improves its performance using unlabeled data. This problem is particularly important when we need to train a supervised learning algorithm with a limited number of labeled examples and a multitude of unlabeled examples. We present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages of the proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with a multitude of unlabeled data, 2) efficient computation by the iterative boosting algorithm, and 3) exploiting both manifold and cluster assumption in training classification models. An empirical study on 16 different data sets and text categorization demonstrates that the proposed framework improves the performance of several commonly used supervised learning algorithms, given a large number of unlabeled examples. We also show that the performance of the proposed algorithm, SemiBoost, is comparable to the state-of-the-art semi-supervised learning algorithms.

Can you boost your metabolism?

MedlinePlus

Weight-loss boost metabolism; Obesity - boost metabolism; Overweight - boost metabolism ... Cowley MA, Brown WA, Considine RV. Obesity. In: Jameson JL, De Groot ... and Pediatric . 7th ed. Philadelphia, PA: Elsevier Saunders; ...

Video to Text (V2T) in Wide Area Motion Imagery

DTIC Science & Technology

2015-09-01

microtext) or a document (e.g., using Sphinx or Apache NLP ) as an automated approach [102]. Previous work in natural language full-text searching...language processing ( NLP ) based module. The heart of the structured text processing module includes the following seven key word banks...Features Tracker MHT Multiple Hypothesis Tracking MIL Multiple Instance Learning NLP Natural Language Processing OAB Online AdaBoost OF Optic Flow

G and C boost and abort study summary, exhibit B

NASA Technical Reports Server (NTRS)

Backman, H. D.

1972-01-01

A six degree of freedom simulation of rigid vehicles was developed to study space shuttle vehicle boost-abort guidance and control techniques. The simulation was described in detail as an all digital program and as a hybrid program. Only the digital simulation was implemented. The equations verified in the digital simulation were adapted for use in the hybrid simulation. Study results were obtained from four abort cases using the digital program.

Shrinkage Degree in $L_{2}$ -Rescale Boosting for Regression.

PubMed

Xu, Lin; Lin, Shaobo; Wang, Yao; Xu, Zongben

2017-08-01

L 2 -rescale boosting ( L 2 -RBoosting) is a variant of L 2 -Boosting, which can essentially improve the generalization performance of L 2 -Boosting. The key feature of L 2 -RBoosting lies in introducing a shrinkage degree to rescale the ensemble estimate in each iteration. Thus, the shrinkage degree determines the performance of L 2 -RBoosting. The aim of this paper is to develop a concrete analysis concerning how to determine the shrinkage degree in L 2 -RBoosting. We propose two feasible ways to select the shrinkage degree. The first one is to parameterize the shrinkage degree and the other one is to develop a data-driven approach. After rigorously analyzing the importance of the shrinkage degree in L 2 -RBoosting, we compare the pros and cons of the proposed methods. We find that although these approaches can reach the same learning rates, the structure of the final estimator of the parameterized approach is better, which sometimes yields a better generalization capability when the number of sample is finite. With this, we recommend to parameterize the shrinkage degree of L 2 -RBoosting. We also present an adaptive parameter-selection strategy for shrinkage degree and verify its feasibility through both theoretical analysis and numerical verification. The obtained results enhance the understanding of L 2 -RBoosting and give guidance on how to use it for regression tasks.

Milne boost from Galilean gauge theory

NASA Astrophysics Data System (ADS)

Banerjee, Rabin; Mukherjee, Pradip

2018-03-01

Physical origin of Milne boost invariance of the Newton Cartan spacetime is traced to the effect of local Galilean boosts in its metric structure, using Galilean gauge theory. Specifically, we do not require any gauge field to understand Milne boost invariance.

Modeling the effect of boost timing in murine irradiated sporozoite prime-boost vaccines

PubMed Central

Zhang, Min; Herrero, Miguel A.; Acosta, Francisco J.; Tsuji, Moriya

2018-01-01

Vaccination with radiation-attenuated sporozoites has been shown to induce CD8+ T cell-mediated protection against pre-erythrocytic stages of malaria. Empirical evidence suggests that successive inoculations often improve the efficacy of this type of vaccines. An initial dose (prime) triggers a specific cellular response, and subsequent inoculations (boost) amplify this response to create a robust CD8+ T cell memory. In this work we propose a model to analyze the effect of T cell dynamics on the performance of prime-boost vaccines. This model suggests that boost doses and timings should be selected according to the T cell response elicited by priming. Specifically, boosting during late stages of clonal contraction would maximize T cell memory production for vaccines using lower doses of irradiated sporozoites. In contrast, single-dose inoculations would be indicated for higher vaccine doses. Experimental data have been obtained that support theoretical predictions of the model. PMID:29329308

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Attentional load and attentional boost: a review of data and theory.

PubMed

Swallow, Khena M; Jiang, Yuhong V

2013-01-01

Both perceptual and cognitive processes are limited in capacity. As a result, attention is selective, prioritizing items and tasks that are important for adaptive behavior. However, a number of recent behavioral and neuroimaging studies suggest that, at least under some circumstances, increasing attention to one task can enhance performance in a second task (e.g., the attentional boost effect). Here we review these findings and suggest a new theoretical framework, the dual-task interaction model, that integrates these findings with current views of attentional selection. To reconcile the attentional boost effect with the effects of attentional load, we suggest that temporal selection results in a temporally specific enhancement across modalities, tasks, and spatial locations. Moreover, the effects of temporal selection may be best observed when the attentional system is optimally tuned to the temporal dynamics of incoming stimuli. Several avenues of research motivated by the dual-task interaction model are then discussed.

Attentional Load and Attentional Boost: A Review of Data and Theory

PubMed Central

Swallow, Khena M.; Jiang, Yuhong V.

2013-01-01

Both perceptual and cognitive processes are limited in capacity. As a result, attention is selective, prioritizing items and tasks that are important for adaptive behavior. However, a number of recent behavioral and neuroimaging studies suggest that, at least under some circumstances, increasing attention to one task can enhance performance in a second task (e.g., the attentional boost effect). Here we review these findings and suggest a new theoretical framework, the dual-task interaction model, that integrates these findings with current views of attentional selection. To reconcile the attentional boost effect with the effects of attentional load, we suggest that temporal selection results in a temporally specific enhancement across modalities, tasks, and spatial locations. Moreover, the effects of temporal selection may be best observed when the attentional system is optimally tuned to the temporal dynamics of incoming stimuli. Several avenues of research motivated by the dual-task interaction model are then discussed. PMID:23730294

Ascent Guidance for a Winged Boost Vehicle. M.S. Thesis

NASA Technical Reports Server (NTRS)

Corvin, Michael Alexander

1988-01-01

The objective of the advanced ascent guidance study was to investigate guidance concepts which could contribute to increased autonomy during ascent operations in a winged boost vehicle such as the proposed Shuttle II. The guidance scheme was required to yield near a full-optimal ascent in the presence of vehicle system and environmental dispersions. The study included consideration of trajectory shaping issues, trajectory design, closed loop and predictive adaptive guidance techniques and control of dynamic pressure by throttling. An extensive ascent vehicle simulation capability was developed for use in the study.

Antimicrobial resistance prediction in PATRIC and RAST

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

Davis, James J.; Boisvert, Sebastien; Brettin, Thomas

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned bymore » their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.« less

Antimicrobial Resistance Prediction in PATRIC and RAST.

PubMed

Davis, James J; Boisvert, Sébastien; Brettin, Thomas; Kenyon, Ronald W; Mao, Chunhong; Olson, Robert; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R; Will, Rebecca; Xia, Fangfang; Stevens, Rick

2016-06-14

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.

Antimicrobial resistance prediction in PATRIC and RAST

DOE PAGES

Davis, James J.; Boisvert, Sebastien; Brettin, Thomas; ...

2016-06-14

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned bymore » their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.« less

A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

NASA Astrophysics Data System (ADS)

Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

2018-04-01

Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods

More pain, more gain: Blocking the opioid system boosts adaptive cognitive control.

PubMed

van Steenbergen, Henk; Weissman, Daniel H; Stein, Dan J; Malcolm-Smith, Susan; van Honk, Jack

2017-06-01

The ability to adaptively increase cognitive control in response to cognitive challenges is crucial for goal-directed behavior. Recent findings suggest that aversive arousal triggers adaptive increases of control, but the neurochemical mechanisms underlying these effects remain unclear. Given the known contributions of the opioid system to hedonic states, we investigated whether blocking this system increases adaptive control modulations. To do so, we conducted a double-blind, placebo-controlled psychopharmacological study (n=52 females) involving a Stroop-like task. Specifically, we assessed the effect of naltrexone, an opioid blocker most selective to the mu-opioid system, on two measures of adaptive control that are thought to depend differentially on aversive arousal: post-error slowing and conflict adaptation. Consistent with our hypothesis, relative to placebo, naltrexone increased post-error slowing without influencing conflict adaptation. This finding not only supports the view that aversive arousal triggers adaptive control but also reveals a novel role for the opioid system in modulating such effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

PubMed

Zheng, Qi; Grice, Elizabeth A

2016-10-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.

Heterologous Prime-Boost Immunisation Regimens Against Infectious Diseases

DTIC Science & Technology

2006-08-01

of these cells by boosting. DNA vaccines are good priming agents since they are internalised by antigen presenting cells and can induce antigen...presentation via both MHC class I and class II, thereby inducing both cytotoxic T lymphocytes and type 1-helper T lymphocytes. Successful boosting agents ...assessing prime-boost vaccine combinations for protection against infectious agents . • In a number of prime - boost studies, the inclusion of growth

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multifractal texture estimation for detection and segmentation of brain tumors.

PubMed

Islam, Atiq; Reza, Syed M S; Iftekharuddin, Khan M

2013-11-01

A stochastic model for characterizing tumor texture in brain magnetic resonance (MR) images is proposed. The efficacy of the model is demonstrated in patient-independent brain tumor texture feature extraction and tumor segmentation in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain tumor texture is formulated using a multiresolution-fractal model known as multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm model and corresponding novel algorithm to extract spatially varying multifractal features are proposed. A multifractal feature-based brain tumor segmentation method is developed next. To evaluate efficacy, tumor segmentation performance using proposed multifractal feature is compared with that using Gabor-like multiscale texton feature. Furthermore, novel patient-independent tumor segmentation scheme is proposed by extending the well-known AdaBoost algorithm. The modification of AdaBoost algorithm involves assigning weights to component classifiers based on their ability to classify difficult samples and confidence in such classification. Experimental results for 14 patients with over 300 MRIs show the efficacy of the proposed technique in automatic segmentation of tumors in brain MRIs. Finally, comparison with other state-of-the art brain tumor segmentation works with publicly available low-grade glioma BRATS2012 dataset show that our segmentation results are more consistent and on the average outperforms these methods for the patients where ground truth is made available.

Multifractal Texture Estimation for Detection and Segmentation of Brain Tumors

PubMed Central

Islam, Atiq; Reza, Syed M. S.

2016-01-01

A stochastic model for characterizing tumor texture in brain magnetic resonance (MR) images is proposed. The efficacy of the model is demonstrated in patient-independent brain tumor texture feature extraction and tumor segmentation in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain tumor texture is formulated using a multiresolution-fractal model known as multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm model and corresponding novel algorithm to extract spatially varying multifractal features are proposed. A multifractal feature-based brain tumor segmentation method is developed next. To evaluate efficacy, tumor segmentation performance using proposed multifractal feature is compared with that using Gabor-like multiscale texton feature. Furthermore, novel patient-independent tumor segmentation scheme is proposed by extending the well-known AdaBoost algorithm. The modification of AdaBoost algorithm involves assigning weights to component classifiers based on their ability to classify difficult samples and confidence in such classification. Experimental results for 14 patients with over 300 MRIs show the efficacy of the proposed technique in automatic segmentation of tumors in brain MRIs. Finally, comparison with other state-of-the art brain tumor segmentation works with publicly available low-grade glioma BRATS2012 dataset show that our segmentation results are more consistent and on the average outperforms these methods for the patients where ground truth is made available. PMID:23807424

Proposed hybrid-classifier ensemble algorithm to map snow cover area

NASA Astrophysics Data System (ADS)

Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir

2018-01-01

Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.

A machine learned classifier for RR Lyrae in the VVV survey

NASA Astrophysics Data System (ADS)

Elorrieta, Felipe; Eyheramendy, Susana; Jordán, Andrés; Dékány, István; Catelan, Márcio; Angeloni, Rodolfo; Alonso-García, Javier; Contreras-Ramos, Rodrigo; Gran, Felipe; Hajdu, Gergely; Espinoza, Néstor; Saito, Roberto K.; Minniti, Dante

2016-11-01

Variable stars of RR Lyrae type are a prime tool with which to obtain distances to old stellar populations in the Milky Way. One of the main aims of the Vista Variables in the Via Lactea (VVV) near-infrared survey is to use them to map the structure of the Galactic Bulge. Owing to the large number of expected sources, this requires an automated mechanism for selecting RR Lyrae, and particularly those of the more easily recognized type ab (I.e., fundamental-mode pulsators), from the 106-107 variables expected in the VVV survey area. In this work we describe a supervised machine-learned classifier constructed for assigning a score to a Ks-band VVV light curve that indicates its likelihood of being ab-type RR Lyrae. We describe the key steps in the construction of the classifier, which were the choice of features, training set, selection of aperture, and family of classifiers. We find that the AdaBoost family of classifiers give consistently the best performance for our problem, and obtain a classifier based on the AdaBoost algorithm that achieves a harmonic mean between false positives and false negatives of ≈7% for typical VVV light-curve sets. This performance is estimated using cross-validation and through the comparison to two independent datasets that were classified by human experts.

Series Connected Buck-Boost Regulator

NASA Technical Reports Server (NTRS)

Birchenough, Arthur G. (Inventor)

2006-01-01

A Series Connected Buck-Boost Regulator (SCBBR) that switches only a fraction of the input power, resulting in relatively high efficiencies. The SCBBR has multiple operating modes including a buck, a boost, and a current limiting mode, so that an output voltage of the SCBBR ranges from below the source voltage to above the source voltage.

Riemann curvature of a boosted spacetime geometry

NASA Astrophysics Data System (ADS)

Battista, Emmanuele; Esposito, Giampiero; Scudellaro, Paolo; Tramontano, Francesco

2016-10-01

The ultrarelativistic boosting procedure had been applied in the literature to map the metric of Schwarzschild-de Sitter spacetime into a metric describing de Sitter spacetime plus a shock-wave singularity located on a null hypersurface. This paper evaluates the Riemann curvature tensor of the boosted Schwarzschild-de Sitter metric by means of numerical calculations, which make it possible to reach the ultrarelativistic regime gradually by letting the boost velocity approach the speed of light. Thus, for the first time in the literature, the singular limit of curvature, through Dirac’s δ distribution and its derivatives, is numerically evaluated for this class of spacetimes. Moreover, the analysis of the Kretschmann invariant and the geodesic equation shows that the spacetime possesses a “scalar curvature singularity” within a 3-sphere and it is possible to define what we here call “boosted horizon”, a sort of elastic wall where all particles are surprisingly pushed away, as numerical analysis demonstrates. This seems to suggest that such “boosted geometries” are ruled by a sort of “antigravity effect” since all geodesics seem to refuse to enter the “boosted horizon” and are “reflected” by it, even though their initial conditions are aimed at driving the particles toward the “boosted horizon” itself. Eventually, the equivalence with the coordinate shift method is invoked in order to demonstrate that all δ2 terms appearing in the Riemann curvature tensor give vanishing contribution in distributional sense.

Boosting Learning Algorithm for Stock Price Forecasting

NASA Astrophysics Data System (ADS)

Wang, Chengzhang; Bai, Xiaoming

2018-03-01

To tackle complexity and uncertainty of stock market behavior, more studies have introduced machine learning algorithms to forecast stock price. ANN (artificial neural network) is one of the most successful and promising applications. We propose a boosting-ANN model in this paper to predict the stock close price. On the basis of boosting theory, multiple weak predicting machines, i.e. ANNs, are assembled to build a stronger predictor, i.e. boosting-ANN model. New error criteria of the weak studying machine and rules of weights updating are adopted in this study. We select technical factors from financial markets as forecasting input variables. Final results demonstrate the boosting-ANN model works better than other ones for stock price forecasting.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework

PubMed Central

Zheng, Qi; Grice, Elizabeth A.

2016-01-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost’s algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost. PMID:27706155

Boosted one dimensional fermionic superfluids on a lattice

NASA Astrophysics Data System (ADS)

Ray, Sayonee; Mukerjee, Subroto; Shenoy, Vijay B.

2017-09-01

We study the effect of a boost (Fermi sea displaced by a finite momentum) on one dimensional systems of lattice fermions with short-ranged interactions. In the absence of a boost such systems with attractive interactions possess algebraic superconducting order. Motivated by physics in higher dimensions, one might naively expect a boost to weaken and ultimately destroy superconductivity. However, we show that for one dimensional systems the effect of the boost can be to strengthen the algebraic superconducting order by making correlation functions fall off more slowly with distance. This phenomenon can manifest in interesting ways, for example, a boost can produce a Luther-Emery phase in a system with both charge and spin gaps by engendering the destruction of the former.

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

Resolving boosted jets with XCone

DOE PAGES

Thaler, Jesse; Wilkason, Thomas F.

2015-12-01

We show how the recently proposed XCone jet algorithm smoothly interpolates between resolved and boosted kinematics. When using standard jet algorithms to reconstruct the decays of hadronic resonances like top quarks and Higgs bosons, one typically needs separate analysis strategies to handle the resolved regime of well-separated jets and the boosted regime of fat jets with substructure. XCone, by contrast, is an exclusive cone jet algorithm that always returns a fixed number of jets, so jet regions remain resolved even when (sub)jets are overlapping in the boosted regime. In this paper, we perform three LHC case studies $-$ dijet resonances,more » Higgs decays to bottom quarks, and all-hadronic top pairs$-$ that demonstrate the physics applications of XCone over a wide kinematic range.« less

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

2016-08-01

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

Boosting multi-state models.

PubMed

Reulen, Holger; Kneib, Thomas

2016-04-01

One important goal in multi-state modelling is to explore information about conditional transition-type-specific hazard rate functions by estimating influencing effects of explanatory variables. This may be performed using single transition-type-specific models if these covariate effects are assumed to be different across transition-types. To investigate whether this assumption holds or whether one of the effects is equal across several transition-types (cross-transition-type effect), a combined model has to be applied, for instance with the use of a stratified partial likelihood formulation. Here, prior knowledge about the underlying covariate effect mechanisms is often sparse, especially about ineffectivenesses of transition-type-specific or cross-transition-type effects. As a consequence, data-driven variable selection is an important task: a large number of estimable effects has to be taken into account if joint modelling of all transition-types is performed. A related but subsequent task is model choice: is an effect satisfactory estimated assuming linearity, or is the true underlying nature strongly deviating from linearity? This article introduces component-wise Functional Gradient Descent Boosting (short boosting) for multi-state models, an approach performing unsupervised variable selection and model choice simultaneously within a single estimation run. We demonstrate that features and advantages in the application of boosting introduced and illustrated in classical regression scenarios remain present in the transfer to multi-state models. As a consequence, boosting provides an effective means to answer questions about ineffectiveness and non-linearity of single transition-type-specific or cross-transition-type effects.

Online Bagging and Boosting

NASA Technical Reports Server (NTRS)

Oza, Nikunji C.

2005-01-01

Bagging and boosting are two of the most well-known ensemble learning methods due to their theoretical performance guarantees and strong experimental results. However, these algorithms have been used mainly in batch mode, i.e., they require the entire training set to be available at once and, in some cases, require random access to the data. In this paper, we present online versions of bagging and boosting that require only one pass through the training data. We build on previously presented work by presenting some theoretical results. We also compare the online and batch algorithms experimentally in terms of accuracy and running time.

Dynamics of multirate sampled data control systems. [for space shuttle boost vehicle

NASA Technical Reports Server (NTRS)

Naylor, J. R.; Hynes, R. J.; Molnar, D. O.

1974-01-01

The effect was investigated of the synthesis approach (single or multirate) on the machine requirements for a digital control system for the space shuttle boost vehicle. The study encompassed four major work areas: synthesis approach trades, machine requirements trades, design analysis requirements and multirate adaptive control techniques. The primary results are two multirate autopilot designs for the low Q and maximum Q flight conditions that exhibits equal or better performance than the analog and single rate system designs. Also, a preferred technique for analyzing and synthesizing multirate digital control systems is included.

Conditional Random Field (CRF)-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

PubMed Central

Yang, Ehwa; Gwak, Jeonghwan; Jeon, Moongu

2017-01-01

Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT). In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF) for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable. PMID:28304366

Tracking down hyper-boosted top quarks

DOE PAGES

Larkoski, Andrew J.; Maltoni, Fabio; Selvaggi, Michele

2015-06-05

The identification of hadronically decaying heavy states, such as vector bosons, the Higgs, or the top quark, produced with large transverse boosts has been and will continue to be a central focus of the jet physics program at the Large Hadron Collider (LHC). At a future hadron collider working at an order-of-magnitude larger energy than the LHC, these heavy states would be easily produced with transverse boosts of several TeV. At these energies, their decay products will be separated by angular scales comparable to individual calorimeter cells, making the current jet substructure identification techniques for hadronic decay modes not directlymore » employable. In addition, at the high energy and luminosity projected at a future hadron collider, there will be numerous sources for contamination including initial- and final-state radiation, underlying event, or pile-up which must be mitigated. We propose a simple strategy to tag such "hyper-boosted" objects that defines jets with radii that scale inversely proportional to their transverse boost and combines the standard calorimetric information with charged track-based observables. By means of a fast detector simulation, we apply it to top quark identification and demonstrate that our method efficiently discriminates hadronically decaying top quarks from light QCD jets up to transverse boosts of 20 TeV. Lastly, our results open the way to tagging heavy objects with energies in the multi-TeV range at present and future hadron colliders.« less

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

PubMed

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma.

PubMed

Zhang, Bin; He, Xin; Ouyang, Fusheng; Gu, Dongsheng; Dong, Yuhao; Zhang, Lu; Mo, Xiaokai; Huang, Wenhui; Tian, Jie; Zhang, Shuixing

2017-09-10

We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled 110 patients with advanced NPC. A total of 970 radiomic features were extracted from MRI images for each patient. Six feature selection methods and nine classification methods were evaluated in terms of their performance. We applied the 10-fold cross-validation as the criterion for feature selection and classification. We repeated each combination for 50 times to obtain the mean area under the curve (AUC) and test error. We observed that the combination methods Random Forest (RF) + RF (AUC, 0.8464 ± 0.0069; test error, 0.3135 ± 0.0088) had the highest prognostic performance, followed by RF + Adaptive Boosting (AdaBoost) (AUC, 0.8204 ± 0.0095; test error, 0.3384 ± 0.0097), and Sure Independence Screening (SIS) + Linear Support Vector Machines (LSVM) (AUC, 0.7883 ± 0.0096; test error, 0.3985 ± 0.0100). Our radiomics study identified optimal machine-learning methods for the radiomics-based prediction of local failure and distant failure in advanced NPC, which could enhance the applications of radiomics in precision oncology and clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.

Inelastic Boosted Dark Matter at direct detection experiments

NASA Astrophysics Data System (ADS)

Giudice, Gian F.; Kim, Doojin; Park, Jong-Chul; Shin, Seodong

2018-05-01

We explore a novel class of multi-particle dark sectors, called Inelastic Boosted Dark Matter (iBDM). These models are constructed by combining properties of particles that scatter off matter by making transitions to heavier states (Inelastic Dark Matter) with properties of particles that are produced with a large Lorentz boost in annihilation processes in the galactic halo (Boosted Dark Matter). This combination leads to new signals that can be observed at ordinary direct detection experiments, but require unconventional searches for energetic recoil electrons in coincidence with displaced multi-track events. Related experimental strategies can also be used to probe MeV-range boosted dark matter via their interactions with electrons inside the target material.

A PIPO Boost Converter with Low Ripple and Medium Current Application

NASA Astrophysics Data System (ADS)

Bandri, S.; Sofian, A.; Ismail, F.

2018-04-01

This paper presents a Parallel Input Parallel Output (PIPO) boost converter is proposed to gain power ability of converter, and reduce current inductors. The proposed technique will distribute current for n-parallel inductor and switching component. Four parallel boost converters implement on input voltage 20.5Vdc to generate output voltage 28.8Vdc. The PIPO boost converter applied phase shift pulse width modulation which will compare with conventional PIPO boost converters by using a similar pulse for every switching component. The current ripple reduction shows an advantage PIPO boost converter then conventional boost converter. Varies loads and duty cycle will be simulated and analyzed to verify the performance of PIPO boost converter. Finally, the unbalance of current inductor is able to be verified on four area of duty cycle in less than 0.6.

Modeling and sizing the coil in boost converters dedicated to photovoltaic sources

NASA Astrophysics Data System (ADS)

Atik, Lotfi; Fares, Mohammed Amine; Zaraket, Jean; Bachir, Ghalem; Aillerie, Michel

2018-05-01

The coil is a very important element in a wide range of power electrical systems as such as those used in converter or inverter dedicated to extract and to adapt the value and the shape of the intensity and the voltage delivered by renewable energy sources. Thus, knowing its behavior in converters is paramount to obtain a maximum conversion efficiency and reliability. In this context, this paper presents a global study of a DC/DC boost converter dedicated to photovoltaic sources based on the modeling of the behavior of the coil or the inductance as a function of the switching frequency.

Hypersonic Boost Glider

NASA Image and Video Library

1957-04-15

Hypersonic Boost Glider in 11 Inch Hypersonic Tunnel L57-1681 In 1957 Langley tested its HYWARDS design in the 11 Inch Hypersonic Tunnel. Photograph published in Engineer in Charge: A History of the Langley Aeronautical Laboratory, 1917-1958 by James R. Hansen. Page 369.

Using reconstructed IVUS images for coronary plaque classification.

PubMed

Caballero, Karla L; Barajas, Joel; Pujol, Oriol; Rodriguez, Oriol; Radeva, Petia

2007-01-01

Coronary plaque rupture is one of the principal causes of sudden death in western societies. Reliable diagnostic of the different plaque types are of great interest for the medical community the predicting their evolution and applying an effective treatment. To achieve this, a tissue classification must be performed. Intravascular Ultrasound (IVUS) represents a technique to explore the vessel walls and to observe its histological properties. In this paper, a method to reconstruct IVUS images from the raw Radio Frequency (RF) data coming from ultrasound catheter is proposed. This framework offers a normalization scheme to compare accurately different patient studies. The automatic tissue classification is based on texture analysis and Adapting Boosting (Adaboost) learning technique combined with Error Correcting Output Codes (ECOC). In this study, 9 in-vivo cases are reconstructed with 7 different parameter set. This method improves the classification rate based on images, yielding a 91% of well-detected tissue using the best parameter set. It also reduces the inter-patient variability compared with the analysis of DICOM images, which are obtained from the commercial equipment.

Boosted Schwarzschild metrics from a Kerr–Schild perspective

NASA Astrophysics Data System (ADS)

Mädler, Thomas; Winicour, Jeffrey

2018-02-01

The Kerr–Schild version of the Schwarzschild metric contains a Minkowski background which provides a definition of a boosted black hole. There are two Kerr–Schild versions corresponding to ingoing or outgoing principle null directions. We show that the two corresponding Minkowski backgrounds and their associated boosts have an unexpected difference. We analyze this difference and discuss the implications in the nonlinear regime for the gravitational memory effect resulting from the ejection of massive particles from an isolated system. We show that the nonlinear effect agrees with the linearized result based upon the retarded Green function only if the velocity of the ejected particle corresponds to a boost symmetry of the ingoing Minkowski background. A boost with respect to the outgoing Minkowski background is inconsistent with the absence of ingoing radiation from past null infinity.

Global Dirac bispinor entanglement under Lorentz boosts

NASA Astrophysics Data System (ADS)

Bittencourt, Victor A. S. V.; Bernardini, Alex E.; Blasone, Massimo

2018-03-01

The effects of Lorentz boosts on the quantum entanglement encoded by a pair of massive spin-1/2 particles are described according to the Lorentz covariant structure described by Dirac bispinors. The quantum system considered incorporates four degrees of freedom: two of them related to the bispinor intrinsic parity and the other two related to the bispinor spin projection, i.e., the Dirac particle helicity. Because of the natural multipartite structure involved, the Meyer-Wallach global measure of entanglement is preliminarily used for computing global quantum correlations, while the entanglement separately encoded by spin degrees of freedom is measured through the negativity of the reduced two-particle spin-spin state. A general framework to compute the changes on quantum entanglement induced by a boost is developed and then specialized to describe three particular antisymmetric two-particle states. According to the results obtained, two-particle spin-spin entanglement cannot be created by the action of a Lorentz boost in a spin-spin separable antisymmetric state. On the other hand, the maximal spin-spin entanglement encoded by antisymmetric superpositions is degraded by Lorentz boosts driven by high-speed frame transformations. Finally, the effects of boosts on chiral states are shown to exhibit interesting invariance properties, which can only be obtained through such a Lorentz covariant formulation of the problem.

Symmetry boost of the fidelity of Shor factoring

NASA Astrophysics Data System (ADS)

Nam, Y. S.; Blümel, R.

2018-05-01

In Shor's algorithm quantum subroutines occur with the structure F U F-1 , where F is a unitary transform and U is performing a quantum computation. Examples are quantum adders and subunits of quantum modulo adders. In this paper we show, both analytically and numerically, that if, in analogy to spin echoes, F and F-1 can be implemented symmetrically when executing Shor's algorithm on actual, imperfect quantum hardware, such that F and F-1 have the same hardware errors, a symmetry boost in the fidelity of the combined F U F-1 quantum operation results when compared to the case in which the errors in F and F-1 are independently random. Running the complete gate-by-gate implemented Shor algorithm, we show that the symmetry-induced fidelity boost can be as large as a factor 4. While most of our analytical and numerical results concern the case of over- and under-rotation of controlled rotation gates, in the numerically accessible case of Shor's algorithm with a small number of qubits, we show explicitly that the symmetry boost is robust with respect to more general types of errors. While, expectedly, additional error types reduce the symmetry boost, we show explicitly, by implementing general off-diagonal SU (N ) errors (N =2 ,4 ,8 ), that the boost factor scales like a Lorentzian in δ /σ , where σ and δ are the error strengths of the diagonal over- and underrotation errors and the off-diagonal SU (N ) errors, respectively. The Lorentzian shape also shows that, while the boost factor may become small with increasing δ , it declines slowly (essentially like a power law) and is never completely erased. We also investigate the effect of diagonal nonunitary errors, which, in analogy to unitary errors, reduce but never erase the symmetry boost. Going beyond the case of small quantum processors, we present analytical scaling results that show that the symmetry boost persists in the practically interesting case of a large number of qubits. We illustrate this result

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Transcriptomics of the Vaccine Immune Response: Priming With Adjuvant Modulates Recall Innate Responses After Boosting.

PubMed

Santoro, Francesco; Pettini, Elena; Kazmin, Dmitri; Ciabattini, Annalisa; Fiorino, Fabio; Gilfillan, Gregor D; Evenroed, Ida M; Andersen, Peter; Pozzi, Gianni; Medaglini, Donata

2018-01-01

Transcriptomic profiling of the immune response induced by vaccine adjuvants is of critical importance for the rational design of vaccination strategies. In this study, transcriptomics was employed to profile the effect of the vaccine adjuvant used for priming on the immune response following re-exposure to the vaccine antigen alone. Mice were primed with the chimeric vaccine antigen H56 of Mycobacterium tuberculosis administered alone or with the CAF01 adjuvant and boosted with the antigen alone. mRNA sequencing was performed on blood samples collected 1, 2, and 7 days after priming and after boosting. Gene expression analysis at day 2 after priming showed that the CAF01 adjuvanted vaccine induced a stronger upregulation of the innate immunity modules compared with the unadjuvanted formulation. The immunostimulant effect of the CAF01 adjuvant, used in the primary immunization, was clearly seen after a booster immunization with a low dose of antigen alone. One day after boost, we observed a strong upregulation of multiple genes in blood of mice primed with H56 + CAF01 compared with mice primed with the H56 alone. In particular, blood transcription modules related to innate immune response, such as monocyte and neutrophil recruitment, activation of antigen-presenting cells, and interferon response were activated. Seven days after boost, differential expression of innate response genes faded while a moderate differential expression of T cell activation modules was appreciable. Indeed, immunological analysis showed a higher frequency of H56-specific CD4+ T cells and germinal center B cells in draining lymph nodes, a strong H56-specific humoral response and a higher frequency of antibody-secreting cells in spleen of mice primed with H56 + CAF01. Taken together, these data indicate that the adjuvant used for priming strongly reprograms the immune response that, upon boosting, results in a stronger recall innate response essential for shaping the downstream

Boosted regression tree, table, and figure data

EPA Pesticide Factsheets

Spreadsheets are included here to support the manuscript Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition. This dataset is associated with the following publication:Golden , H., C. Lane , A. Prues, and E. D'Amico. Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition. JAWRA. American Water Resources Association, Middleburg, VA, USA, 52(5): 1251-1274, (2016).

Preprocessing of PHERMEX flash radiographic images with Haar and adaptive filtering

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

Brolley, J.E.

1978-11-01

Work on image preparation has continued with the application of high-sequency boosting via Haar filtering. This is useful in developing line or edge structures. Widrow LMS adaptive filtering has also been shown to be useful in developing edge structure in special problems. Shadow effects can be obtained with the latter which may be useful for some problems. Combined Haar and adaptive filtering is illustrated for a PHERMEX image.

Boosted Kaluza-Klein magnetic monopole

NASA Astrophysics Data System (ADS)

Hashemi, S. Sedigheh; Riazi, Nematollah

2018-06-01

We consider a Kaluza-Klein vacuum solution which is closely related to the Gross-Perry-Sorkin (GPS) magnetic monopole. The solution can be obtained from the Euclidean Taub-NUT solution with an extra compact fifth spatial dimension within the formalism of Kaluza-Klein reduction. We study its physical properties as appearing in (3 + 1) spacetime dimensions, which turns out to be a static magnetic monopole. We then boost the GPS magnetic monopole along the extra dimension, and perform the Kaluza-Klein reduction. The resulting four-dimensional spacetime is a rotating stationary system, with both electric and magnetic fields. In fact, after the boost the magnetic monopole turns into a string connected to a dyon.

Automated detection of new impact sites on Martian surface from HiRISE images

NASA Astrophysics Data System (ADS)

Xin, Xin; Di, Kaichang; Wang, Yexin; Wan, Wenhui; Yue, Zongyu

2017-10-01

In this study, an automated method for Martian new impact site detection from single images is presented. It first extracts dark areas in full high resolution image, then detects new impact craters within dark areas using a cascade classifier which combines local binary pattern features and Haar-like features trained by an AdaBoost machine learning algorithm. Experimental results using 100 HiRISE images show that the overall detection rate of proposed method is 84.5%, with a true positive rate of 86.9%. The detection rate and true positive rate in the flat regions are 93.0% and 91.5%, respectively.

Q-Boosted Optomechanical Resonators

DTIC Science & Technology

2015-11-18

Devices ( ORCHID ) Lead Organization: University of California at Berkeley Project Title: Q-Boosted Optomechanical Resonators Technical...be a PDF. Please do not password protect or secure the PDF . The maximum file size for the Report Document is 50MB. 150915 UCB Nguyen ORCHID

The Score-Boosting Game.

ERIC Educational Resources Information Center

Popham, W. James

2000-01-01

Teachers everywhere are playing the score-boosting game to raise scores on mandated standardized achievement tests, although five nationally recognized assessments compare student performance instead of measuring classroom learning. Since curriculum standards are often vague and misaligned with assessments, teachers sprinkle instruction with…

Centrifugal compressor design for electrically assisted boost

NASA Astrophysics Data System (ADS)

Y Yang, M.; Martinez-Botas, R. F.; Zhuge, W. L.; Qureshi, U.; Richards, B.

2013-12-01

Electrically assisted boost is a prominent method to solve the issues of transient lag in turbocharger and remains an optimized operation condition for a compressor due to decoupling from turbine. Usually a centrifugal compressor for gasoline engine boosting is operated at high rotational speed which is beyond the ability of an electric motor in market. In this paper a centrifugal compressor with rotational speed as 120k RPM and pressure ratio as 2.0 is specially developed for electrically assisted boost. A centrifugal compressor including the impeller, vaneless diffuser and the volute is designed by meanline method followed by 3D detailed design. Then CFD method is employed to predict as well as analyse the performance of the design compressor. The results show that the pressure ratio and efficiency at design point is 2.07 and 78% specifically.

14 CFR 27.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2013 CFR

2013-01-01

... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: NORMAL CATEGORY ROTORCRAFT Design and Construction Control Systems § 27.695 Power boost and power-operated control system. (a) If a power boost or power-operated... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Power boost and power-operated control...

14 CFR 29.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2013 CFR

2013-01-01

... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: TRANSPORT CATEGORY ROTORCRAFT Design and Construction Control Systems § 29.695 Power boost and power-operated control system. (a) If a power boost or power-operated... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Power boost and power-operated control...

Boosted Multivariate Trees for Longitudinal Data

PubMed Central

Pande, Amol; Li, Liang; Rajeswaran, Jeevanantham; Ehrlinger, John; Kogalur, Udaya B.; Blackstone, Eugene H.; Ishwaran, Hemant

2017-01-01

Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing P-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data. PMID:29249866

Centaur liquid oxygen boost pump vibration test

NASA Technical Reports Server (NTRS)

Tang, H. M.

1975-01-01

The Centaur LOX boost pump was subjected to both the simulated Titan Centaur proof flight and confidence demonstration vibration test levels. For each test level, both sinusoidal and random vibration tests were conducted along each of the three orthogonal axes of the pump and turbine assembly. In addition to these tests, low frequency longitudinal vibration tests for both levels were conducted. All tests were successfully completed without damage to the boost pump.

NTCP reduction for advanced head and neck cancer patients using proton therapy for complete or sequential boost treatment versus photon therapy.

PubMed

Jakobi, Annika; Stützer, Kristin; Bandurska-Luque, Anna; Löck, Steffen; Haase, Robert; Wack, Linda-Jacqueline; Mönnich, David; Thorwarth, Daniel; Perez, Damien; Lühr, Armin; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Perrin, Rosalind; Richter, Christian

2015-01-01

To determine by treatment plan comparison differences in toxicity risk reduction for patients with head and neck squamous cell carcinoma (HNSCC) from proton therapy either used for complete treatment or sequential boost treatment only. For 45 HNSCC patients, intensity-modulated photon (IMXT) and proton (IMPT) treatment plans were created including a dose escalation via simultaneous integrated boost with a one-step adaptation strategy after 25 fractions for sequential boost treatment. Dose accumulation was performed for pure IMXT treatment, pure IMPT treatment and for a mixed modality treatment with IMXT for the elective target followed by a sequential boost with IMPT. Treatment plan evaluation was based on modern normal tissue complication probability (NTCP) models for mucositis, xerostomia, aspiration, dysphagia, larynx edema and trismus. Individual NTCP differences between IMXT and IMPT (∆NTCPIMXT-IMPT) as well as between IMXT and the mixed modality treatment (∆NTCPIMXT-Mix) were calculated. Target coverage was similar in all three scenarios. NTCP values could be reduced in all patients using IMPT treatment. However, ∆NTCPIMXT-Mix values were a factor 2-10 smaller than ∆NTCPIMXT-IMPT. Assuming a threshold of ≥ 10% NTCP reduction in xerostomia or dysphagia risk as criterion for patient assignment to IMPT, less than 15% of the patients would be selected for a proton boost, while about 50% would be assigned to pure IMPT treatment. For mucositis and trismus, ∆NTCP ≥ 10% occurred in six and four patients, respectively, with pure IMPT treatment, while no such difference was identified with the proton boost. The use of IMPT generally reduces the expected toxicity risk while maintaining good tumor coverage in the examined HNSCC patients. A mixed modality treatment using IMPT solely for a sequential boost reduces the risk by 10% only in rare cases. In contrast, pure IMPT treatment may be reasonable for about half of the examined patient cohort considering

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

Tumour bed boost radiotherapy for women after breast-conserving surgery.

PubMed

Kindts, Isabelle; Laenen, Annouschka; Depuydt, Tom; Weltens, Caroline

2017-11-06

Breast-conserving therapy, involving breast-conserving surgery followed by whole-breast irradiation and optionally a boost to the tumour bed, is a standard therapeutic option for women with early-stage breast cancer. A boost to the tumour bed means that an extra dose of radiation is applied that covers the initial tumour site. The rationale for a boost of radiotherapy to the tumour bed is that (i) local recurrence occurs mostly at the site of the primary tumour because remaining microscopic tumour cells are most likely situated there; and (ii) radiation can eliminate these causative microscopic tumour cells. The boost continues to be used in women at high risk of local recurrence, but is less widely accepted for women at lower risk. Reasons for questioning the boost are twofold. Firstly, the boost brings higher treatment costs. Secondly, the potential adverse events are not negligible. In this Cochrane Review, we investigated the effect of the tumour bed boost on local control and side effects. To assess the effects of tumour bed boost radiotherapy after breast-conserving surgery and whole-breast irradiation for the treatment of breast cancer. We searched the Cochrane Breast Cancer Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (January 1966 to 1 March 2017), Embase (1980 to 1 March 2017), the World Health Organization International Clinical Trials Registry Platform, and ClinicalTrials.gov on 1 March 2017. We also searched the European Society of Radiotherapy and Oncology Annual Meeting, the St Gallen Oncology Conferences, and the American Society for Radiation Oncology Annual Meeting for abstracts. Randomised controlled trials comparing the addition and the omission of breast cancer tumour bed boost radiotherapy. Two review authors (IK and CW) performed data extraction and assessed risk of bias using Cochrane's 'Risk of bias' tool, resolving any disagreements through discussion. We entered data into Review Manager 5 for

14 CFR 27.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Systems § 27.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Power boost and power-operated control...

14 CFR 29.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Systems § 29.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Power boost and power-operated control...

14 CFR 29.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Systems § 29.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Power boost and power-operated control...

14 CFR 27.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Systems § 27.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Power boost and power-operated control...

14 CFR 29.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Systems § 29.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Power boost and power-operated control...

14 CFR 29.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Systems § 29.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Power boost and power-operated control...

14 CFR 27.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Systems § 27.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Power boost and power-operated control...

14 CFR 27.695 - Power boost and power-operated control system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Systems § 27.695 Power boost and power-operated control system. (a) If a power boost or power-operated... failure of all engines. (b) Each alternate system may be a duplicate power portion or a manually operated... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Power boost and power-operated control...

Alternative Fuels Data Center: Electric Trolley Boosts Business in

Science.gov Websites

Bakersfield, CaliforniaA> Electric Trolley Boosts Business in Bakersfield, California to someone Business in Bakersfield, California Discover how Bakersfield's electric trolley is giving a green boost to downtown businesses. For information about this project, contact San Joaquin Valley Clean Cities. Download

Nudging and Boosting: Steering or Empowering Good Decisions.

PubMed

Hertwig, Ralph; Grüne-Yanoff, Till

2017-11-01

In recent years, policy makers worldwide have begun to acknowledge the potential value of insights from psychology and behavioral economics into how people make decisions. These insights can inform the design of nonregulatory and nonmonetary policy interventions-as well as more traditional fiscal and coercive measures. To date, much of the discussion of behaviorally informed approaches has emphasized "nudges," that is, interventions designed to steer people in a particular direction while preserving their freedom of choice. Yet behavioral science also provides support for a distinct kind of nonfiscal and noncoercive intervention, namely, "boosts." The objective of boosts is to foster people's competence to make their own choices-that is, to exercise their own agency. Building on this distinction, we further elaborate on how boosts are conceptually distinct from nudges: The two kinds of interventions differ with respect to (a) their immediate intervention targets, (b) their roots in different research programs, (c) the causal pathways through which they affect behavior, (d) their assumptions about human cognitive architecture, (e) the reversibility of their effects, (f) their programmatic ambitions, and (g) their normative implications. We discuss each of these dimensions, provide an initial taxonomy of boosts, and address some possible misconceptions.

Boost breaking in the EFT of inflation

DOE PAGES

Delacrétaz, Luca V.; Noumi, Toshifumi; Senatore, Leonardo

2017-02-17

If time-translations are spontaneously broken, so are boosts. This symmetry breaking pattern can be non-linearly realized by either just the Goldstone boson of time translations, or by four Goldstone bosons associated with time translations and boosts. Here in this paper we extend the Effective Field Theory of Multifield Inflation to consider the case in which the additional Goldstone bosons associated with boosts are light and coupled to the Goldstone boson of time translations. The symmetry breaking pattern forces a coupling to curvature so that the mass of the additional Goldstone bosons is predicted to be equal to √2H in themore » vast majority of the parameter space where they are light. This pattern therefore offers a natural way of generating self-interacting particles with Hubble mass during inflation. After constructing the general effective Lagrangian, we study how these particles mix and interact with the curvature fluctuations, generating potentially detectable non-Gaussian signals.« less

Three-dimensional conformal simultaneously integrated boost technique for breast-conserving radiotherapy.

PubMed

van der Laan, Hans Paul; Dolsma, Wil V; Maduro, John H; Korevaar, Erik W; Hollander, Miranda; Langendijk, Johannes A

2007-07-15

To compare the target coverage and normal tissue dose with the simultaneously integrated boost (SIB) and the sequential boost technique in breast cancer, and to evaluate the incidence of acute skin toxicity in patients treated with the SIB technique. Thirty patients with early-stage left-sided breast cancer underwent breast-conserving radiotherapy using the SIB technique. The breast and boost planning target volumes (PTVs) were treated simultaneously (i.e., for each fraction, the breast and boost PTVs received 1.81 Gy and 2.3 Gy, respectively). Three-dimensional conformal beams with wedges were shaped and weighted using forward planning. Dose-volume histograms of the PTVs and organs at risk with the SIB technique, 28 x (1.81 + 0.49 Gy), were compared with those for the sequential boost technique, 25 x 2 Gy + 8 x 2 Gy. Acute skin toxicity was evaluated for 90 patients treated with the SIB technique according to Common Terminology Criteria for Adverse Events, version 3.0. PTV coverage was adequate with both techniques. With SIB, more efficiently shaped boost beams resulted in smaller irradiated volumes. The mean volume receiving > or =107% of the breast dose was reduced by 20%, the mean volume outside the boost PTV receiving > or =95% of the boost dose was reduced by 54%, and the mean heart and lung dose were reduced by 10%. Of the evaluated patients, 32.2% had Grade 2 or worse toxicity. The SIB technique is proposed for standard use in breast-conserving radiotherapy because of its dose-limiting capabilities, easy implementation, reduced number of treatment fractions, and relatively low incidence of acute skin toxicity.

The Lateral Decubitus Breast Boost: Description, Rationale, and Efficacy

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

Ludwig, Michelle S., E-mail: mludwig@mdanderson.or; McNeese, Marsha D.; Buchholz, Thomas A.

2010-01-15

Purpose: To describe and evaluate the modified lateral decubitus boost, a breast irradiation technique. Patients are repositioned and resimulated for electron boost to minimize the necessary depth for the electron beam and optimize target volume coverage. Methods and Materials: A total of 2,606 patients were treated with post-lumpectomy radiation at our institution between January 1, 2000, and February 1, 2008. Of these, 231 patients underwent resimulation in the lateral decubitus position with electron boost. Distance from skin to the maximal depth of target volume was measured in both the original and boost plans. Age, body mass index (BMI), boost electronmore » energy, and skin reaction were evaluated. Results: Resimulation in the lateral decubitus position reduced the distance from skin to maximal target volume depth in all patients. Average depth reduction by repositioning was 2.12 cm, allowing for an average electron energy reduction of approximately 7 MeV. Mean skin entrance dose was reduced from about 90% to about 85% (p < 0.001). Only 14 patients (6%) experienced moist desquamation in the boost field at the end of treatment. Average BMI of these patients was 30.4 (range, 17.8-50.7). BMI greater than 30 was associated with more depth reduction by repositioning and increased risk of moist desquamation. Conclusions: The lateral decubitus position allows for a decrease in the distance from the skin to the target volume depth, improving electron coverage of the tumor bed while reducing skin entrance dose. This is a well-tolerated regimen for a patient population with a high BMI or deep tumor location.« less

Local initiatives and adaptation to climate change.

PubMed

Blanco, Ana V Rojas

2006-03-01

Climate change is expected to lead to an increase in the number and strength of natural hazards produced by climatic events. This paper presents some examples of the experiences of community-based organisations (CBOs) and non-governmental organisations (NGOs) of variations in climate, and looks at how they have incorporated their findings into the design and implementation of local adaptation strategies. Local organisations integrate climate change and climatic hazards into the design and development of their projects as a means of adapting to their new climatic situation. Projects designed to boost the resilience of local livelihoods are good examples of local adaptation strategies. To upscale these adaptation initiatives, there is a need to improve information exchange between CBOs, NGOs and academia. Moreover, there is a need to bridge the gap between scientific and local knowledge in order to create projects capable of withstanding stronger natural hazards.

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

PubMed

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Retroperitoneal sarcoma (RPS) high risk gross tumor volume boost (HR GTV boost) contour delineation agreement among NRG sarcoma radiation and surgical oncologists.

PubMed

Baldini, Elizabeth H; Bosch, Walter; Kane, John M; Abrams, Ross A; Salerno, Kilian E; Deville, Curtiland; Raut, Chandrajit P; Petersen, Ivy A; Chen, Yen-Lin; Mullen, John T; Millikan, Keith W; Karakousis, Giorgos; Kendrick, Michael L; DeLaney, Thomas F; Wang, Dian

2015-09-01

Curative intent management of retroperitoneal sarcoma (RPS) requires gross total resection. Preoperative radiotherapy (RT) often is used as an adjuvant to surgery, but recurrence rates remain high. To enhance RT efficacy with acceptable tolerance, there is interest in delivering "boost doses" of RT to high-risk areas of gross tumor volume (HR GTV) judged to be at risk for positive resection margins. We sought to evaluate variability in HR GTV boost target volume delineation among collaborating sarcoma radiation and surgical oncologist teams. Radiation planning CT scans for three cases of RPS were distributed to seven paired radiation and surgical oncologist teams at six institutions. Teams contoured HR GTV boost volumes for each case. Analysis of contour agreement was performed using the simultaneous truth and performance level estimation (STAPLE) algorithm and kappa statistics. HRGTV boost volume contour agreement between the seven teams was "substantial" or "moderate" for all cases. Agreement was best on the torso wall posteriorly (abutting posterior chest abdominal wall) and medially (abutting ipsilateral para-vertebral space and great vessels). Contours varied more significantly abutting visceral organs due to differing surgical opinions regarding planned partial organ resection. Agreement of RPS HRGTV boost volumes between sarcoma radiation and surgical oncologist teams was substantial to moderate. Differences were most striking in regions abutting visceral organs, highlighting the importance of collaboration between the radiation and surgical oncologist for "individualized" target delineation on the basis of areas deemed at risk and planned resection.

Convergence and divergence of neurocognitive patterns in schizophrenia and depression.

PubMed

Liang, Sugai; Brown, Matthew R G; Deng, Wei; Wang, Qiang; Ma, Xiaohong; Li, Mingli; Hu, Xun; Juhas, Michal; Li, Xinmin; Greiner, Russell; Greenshaw, Andrew J; Li, Tao

2018-02-01

Neurocognitive impairments are frequently observed in schizophrenia and major depressive disorder (MDD). However, it remains unclear whether reported neurocognitive abnormalities could objectively identify an individual as having schizophrenia or MDD. The current study included 220 first-episode patients with schizophrenia, 110 patients with MDD and 240 demographically matched healthy controls (HC). All participants performed the short version of the Wechsler Adult Intelligence Scale-Revised in China; the immediate and delayed logical memory of the Wechsler Memory Scale-Revised in China; and seven tests from the computerized Cambridge Neurocognitive Test Automated Battery to evaluate neurocognitive performance. The three-class AdaBoost tree-based ensemble algorithm was employed to identify neurocognitive endophenotypes that may distinguish between subjects in the categories of schizophrenia, depression and HC. Hierarchical cluster analysis was applied to further explore the neurocognitive patterns in each group. The AdaBoost algorithm identified individual's diagnostic class with an average accuracy of 77.73% (80.81% for schizophrenia, 53.49% for depression and 86.21% for HC). The average area under ROC curve was 0.92 (0.96 in schizophrenia, 0.86 in depression and 0.92 in HC). Hierarchical cluster analysis revealed for MDD and schizophrenia, convergent altered neurocognition patterns related to shifting, sustained attention, planning, working memory and visual memory. Divergent neurocognition patterns for MDD and schizophrenia related to motor speed, general intelligence, perceptual sensitivity and reversal learning were identified. Neurocognitive abnormalities could predict whether the individual has schizophrenia, depression or neither with relatively high accuracy. Additionally, the neurocognitive features showed promise as endophenotypes for discriminating between schizophrenia and depression. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.

PubMed

Yan, Kang K; Zhao, Hongyu; Pang, Herbert

2017-12-06

High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provide a holistic understanding of human health and diseases, it is necessary to integrate multiple data sources. Several algorithms have been proposed so far, however, a comprehensive comparison of data integration algorithms for classification of binary traits is currently lacking. In this paper, we focus on two common classes of integration algorithms, graph-based that depict relationships with subjects denoted by nodes and relationships denoted by edges, and kernel-based that can generate a classifier in feature space. Our paper provides a comprehensive comparison of their performance in terms of various measurements of classification accuracy and computation time. Seven different integration algorithms, including graph-based semi-supervised learning, graph sharpening integration, composite association network, Bayesian network, semi-definite programming-support vector machine (SDP-SVM), relevance vector machine (RVM) and Ada-boost relevance vector machine are compared and evaluated with hypertension and two cancer data sets in our study. In general, kernel-based algorithms create more complex models and require longer computation time, but they tend to perform better than graph-based algorithms. The performance of graph-based algorithms has the advantage of being faster computationally. The empirical results demonstrate that composite association network, relevance vector machine, and Ada-boost RVM are the better performers. We provide recommendations on how to choose an appropriate algorithm for integrating data from multiple sources.

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

Prospective Study Delivering Simultaneous Integrated High-dose Tumor Boost (≤70 Gy) With Image Guided Adaptive Radiation Therapy for Radical Treatment of Localized Muscle-Invasive Bladder Cancer

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

Hafeez, Shaista, E-mail: Shaista.Hafeez@icr.ac.uk; The Royal Marsden National Health Service Foundation Trust, London; Warren-Oseni, Karole

Purpose: Image guided adaptive radiation therapy offers individualized solutions to improve target coverage and reduce normal tissue irradiation, allowing the opportunity to increase the radiation tumor dose and spare normal bladder tissue. Methods and Materials: A library of 3 intensity modulated radiation therapy plans were created (small, medium, and large) from planning computed tomography (CT) scans performed at 30 and 60 minutes; treating the whole bladder to 52 Gy and the tumor to 70 Gy in 32 fractions. A “plan of the day” approach was used for treatment delivery. A post-treatment cone beam CT (CBCT) scan was acquired weekly to assess intrafraction fillingmore » and coverage. Results: A total of 18 patients completed treatment to 70 Gy. The plan and treatment for 1 patient was to 68 Gy. Also, 1 patient's plan was to 70 Gy but the patient was treated to a total dose of 65.6 Gy because dose-limiting toxicity occurred before dose escalation. A total of 734 CBCT scans were evaluated. Small, medium, and large plans were used in 36%, 48%, and 16% of cases, respectively. The mean ± standard deviation rate of intrafraction filling at the start of treatment (ie, week 1) was 4.0 ± 4.8 mL/min (range 0.1-19.4) and at end of radiation therapy (ie, week 5 or 6) was 1.1 ± 1.6 mL/min (range 0.01-7.5; P=.002). The mean D{sub 98} (dose received by 98% volume) of the tumor boost and bladder as assessed on the post-treatment CBCT scan was 97.07% ± 2.10% (range 89.0%-104%) and 99.97% ± 2.62% (range 96.4%-112.0%). At a median follow-up period of 19 months (range 4-33), no muscle-invasive recurrences had developed. Two patients experienced late toxicity (both grade 3 cystitis) at 5.3 months (now resolved) and 18 months after radiation therapy. Conclusions: Image guided adaptive radiation therapy using intensity modulated radiation therapy to deliver a simultaneous integrated tumor boost to 70 Gy is feasible, with acceptable toxicity, and will be

[MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

PubMed

Chen, Zhiru; Hong, Wenxue

2016-02-01

Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning. Finally, the prediction of miRNA target integrated classifier is achieved with the combination of multiple weak classifiers through the voting mechanism. The experiment revealed that the SVM-IUSW, compared with other algorithms on unbalanced dataset collection, could not only improve the accuracy of positive targets and the overall effect of classification, but also enhance the generalization ability of miRNA target classifier.

Attention modulates visual size adaptation.

PubMed

Kreutzer, Sylvia; Fink, Gereon R; Weidner, Ralph

2015-01-01

The current study determined in healthy subjects (n = 16) whether size adaptation occurs at early, i.e., preattentive, levels of processing or whether higher cognitive processes such as attention can modulate the illusion. To investigate this issue, bottom-up stimulation was kept constant across conditions by using a single adaptation display containing both small and large adapter stimuli. Subjects' attention was directed to either the large or small adapter stimulus by means of a luminance detection task. When attention was directed toward the small as compared to the large adapter, the perceived size of the subsequent target was significantly increased. Data suggest that different size adaptation effects can be induced by one and the same stimulus depending on the current allocation of attention. This indicates that size adaptation is subject to attentional modulation. These findings are in line with previous research showing that transient as well as sustained attention modulates visual features, such as contrast sensitivity and spatial frequency, and influences adaptation in other contexts, such as motion adaptation (Alais & Blake, 1999; Lankheet & Verstraten, 1995). Based on a recently suggested model (Pooresmaeili, Arrighi, Biagi, & Morrone, 2013), according to which perceptual adaptation is based on local excitation and inhibition in V1, we conclude that guiding attention can boost these local processes in one or the other direction by increasing the weight of the attended adapter. In sum, perceptual adaptation, although reflected in changes of neural activity at early levels (as shown in the aforementioned study), is nevertheless subject to higher-order modulation.

Search for Boosted Dark Matter Interacting with Electrons in Super-Kamiokande

NASA Astrophysics Data System (ADS)

Kachulis, C.; Abe, K.; Bronner, C.; Hayato, Y.; Ikeda, M.; Iyogi, K.; Kameda, J.; Kato, Y.; Kishimoto, Y.; Marti, Ll.; Miura, M.; Moriyama, S.; Nakahata, M.; Nakano, Y.; Nakayama, S.; Okajima, Y.; Orii, A.; Pronost, G.; Sekiya, H.; Shiozawa, M.; Sonoda, Y.; Takeda, A.; Takenaka, A.; Tanaka, H.; Tasaka, S.; Tomura, T.; Akutsu, R.; Kajita, T.; Kaneyuki, K.; Nishimura, Y.; Okumura, K.; Tsui, K. M.; Labarga, L.; Fernandez, P.; Blaszczyk, F. d. M.; Gustafson, J.; Kearns, E.; Raaf, J. L.; Stone, J. L.; Sulak, L. R.; Berkman, S.; Tobayama, S.; Goldhaber, M.; Elnimr, M.; Kropp, W. R.; Mine, S.; Locke, S.; Weatherly, P.; Smy, M. B.; Sobel, H. W.; Takhistov, V.; Ganezer, K. S.; Hill, J.; Kim, J. Y.; Lim, I. T.; Park, R. G.; Himmel, A.; Li, Z.; O'Sullivan, E.; Scholberg, K.; Walter, C. W.; Ishizuka, T.; Nakamura, T.; Jang, J. S.; Choi, K.; Learned, J. G.; Matsuno, S.; Smith, S. N.; Amey, J.; Litchfield, R. P.; Ma, W. Y.; Uchida, Y.; Wascko, M. O.; Cao, S.; Friend, M.; Hasegawa, T.; Ishida, T.; Ishii, T.; Kobayashi, T.; Nakadaira, T.; Nakamura, K.; Oyama, Y.; Sakashita, K.; Sekiguchi, T.; Tsukamoto, T.; Abe, KE.; Hasegawa, M.; Suzuki, A. T.; Takeuchi, Y.; Yano, T.; Hayashino, T.; Hiraki, T.; Hirota, S.; Huang, K.; Jiang, M.; Nakamura, KE.; Nakaya, T.; Quilain, B.; Patel, N. D.; Wendell, R. A.; Anthony, L. H. V.; McCauley, N.; Pritchard, A.; Fukuda, Y.; Itow, Y.; Murase, M.; Muto, F.; Mijakowski, P.; Frankiewicz, K.; Jung, C. K.; Li, X.; Palomino, J. L.; Santucci, G.; Vilela, C.; Wilking, M. J.; Yanagisawa, C.; Ito, S.; Fukuda, D.; Ishino, H.; Kibayashi, A.; Koshio, Y.; Nagata, H.; Sakuda, M.; Xu, C.; Kuno, Y.; Wark, D.; Di Lodovico, F.; Richards, B.; Tacik, R.; Kim, S. B.; Cole, A.; Thompson, L.; Okazawa, H.; Choi, Y.; Ito, K.; Nishijima, K.; Koshiba, M.; Totsuka, Y.; Suda, Y.; Yokoyama, M.; Calland, R. G.; Hartz, M.; Martens, K.; Simpson, C.; Suzuki, Y.; Vagins, M. R.; Hamabe, D.; Kuze, M.; Yoshida, T.; Ishitsuka, M.; Martin, J. F.; Nantais, C. M.; Tanaka, H. A.; Konaka, A.; Chen, S.; Wan, L.; Zhang, Y.; Wilkes, R. J.; Minamino, A.; Super-Kamiokande Collaboration

2018-06-01

A search for boosted dark matter using 161.9 kt yr of Super-Kamiokande IV data is presented. We search for an excess of elastically scattered electrons above the atmospheric neutrino background, with a visible energy between 100 MeV and 1 TeV, pointing back to the Galactic center or the Sun. No such excess is observed. Limits on boosted dark matter event rates in multiple angular cones around the Galactic center and Sun are calculated. Limits are also calculated for a baseline model of boosted dark matter produced from cold dark matter annihilation or decay. This is the first experimental search for boosted dark matter from the Galactic center or the Sun interacting in a terrestrial detector.

Kill: boosting HIV-specific immune responses.

PubMed

Trautmann, Lydie

2016-07-01

Increasing evidence suggests that purging the latent HIV reservoir in virally suppressed individuals will require both the induction of viral replication from its latent state and the elimination of these reactivated HIV-infected cells ('Shock and Kill' strategy). Boosting potent HIV-specific CD8 T cells is a promising way to achieve an HIV cure. Recent studies provided the rationale for developing immune interventions to increase the numbers, function and location of HIV-specific CD8 T cells to purge HIV reservoirs. Multiple approaches are being evaluated including very early suppression of HIV replication in acute infection, adoptive cell transfer, therapeutic vaccination or use of immunomodulatory molecules. New assays to measure the killing and antiviral function of induced HIV-specific CD8 T cells have been developed to assess the efficacy of these new approaches. The strategies combining HIV reactivation and immunobased therapies to boost HIV-specific CD8 T cells can be tested in in-vivo and in-silico models to accelerate the design of new clinical trials. New immunobased strategies are explored to boost HIV-specific CD8 T cells able to purge the HIV-infected cells with the ultimate goal of achieving spontaneous control of viral replication without antiretroviral treatment.

Kill: Boosting HIV-specific immune responses

PubMed Central

Trautmann, Lydie

2016-01-01

Purpose of review Increasing evidences suggest that purging the latent HIV reservoir in virally-suppressed individuals will require both the induction of viral replication from its latent state and the elimination of these reactivated HIV infected cells (“Shock and Kill” strategy). Boosting potent HIV-specific CD8 T cells is a promising way to achieve an HIV cure. Recent findings Recent studies provided the rationale for developing immune interventions to increase the numbers, function and location of HIV-specific CD8 T cells to purge HIV reservoirs. Multiple approaches are being evaluated including very early suppression of HIV replication in acute infection, adoptive cell transfer, therapeutic vaccination or use of immunomodulatory molecules. New assays to measure the killing and antiviral function of induced HIV-specific CD8 T cells have been developed to assess the efficacy of these new approaches. The strategies combining HIV reactivation and immunobased therapies to boost HIV-specific CD8 T cells can be tested in in vivo and in silico models to accelerate the design of new clinical trials. Summary New immunobased strategies are explored to boost HIV-specific CD8 T cells able to purge the HIV-infected cells with the ultimate goal of achieving spontaneous control of viral replication without antiretroviral treatment. PMID:27054280

Brachytherapy Boost Utilization and Survival in Unfavorable-risk Prostate Cancer.

PubMed

Johnson, Skyler B; Lester-Coll, Nataniel H; Kelly, Jacqueline R; Kann, Benjamin H; Yu, James B; Nath, Sameer K

2017-11-01

There are limited comparative survival data for prostate cancer (PCa) patients managed with a low-dose rate brachytherapy (LDR-B) boost and dose-escalated external-beam radiotherapy (DE-EBRT) alone. To compare overall survival (OS) for men with unfavorable PCa between LDR-B and DE-EBRT groups. Using the National Cancer Data Base, we identified men with unfavorable PCa treated between 2004 and 2012 with androgen suppression (AS) and either EBRT followed by LDR-B or DE-EBRT (75.6-86.4Gy). Treatment selection was evaluated using logistic regression and annual percentage proportions. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards, and propensity score matching. We identified 25038 men between 2004 and 2012, during which LDR-B boost utilization decreased from 29% to 14%. LDR-B was associated with better OS on univariate (7-yr OS: 82% vs 73%; p<0.001) and multivariate analyses (hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.64-0.77). Propensity score matching verified an OS benefit associated with LDR-B boost (HR 0.74, 95% CI 0.66-0.89). The OS benefit of LDR-B boost persisted when limited to men aged <60 yr with no comorbidities. On subset analysis, there was no interaction between treatment and age, risk group, or radiation dose. Limitations include the retrospective design, nonrandomized selection bias, and the absence of treatment toxicity, hormone duration, and cancer-specific outcomes. Between 2004 and 2012, LDR-B boost utilization declined and was associated with better OS compared to DE-EBRT alone. LDR-B boost is probably the ideal treatment option for men with unfavorable PCa, pending long-term results of randomized trials. We compared radiotherapy utilization and survival for prostate cancer (PCa) patients using a national database. We found that low-dose rate brachytherapy (LDR-B) boost, a method being used less frequently, was associated with better overall survival when compared to dose-escalated external

Radiotherapy Breast Boost With Reduced Whole-Breast Dose Is Associated With Improved Cosmesis: The Results of a Comprehensive Assessment From the St. George and Wollongong Randomized Breast Boost Trial

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

Hau, Eric, E-mail: helloerico@yahoo.com; Browne, Lois H.; Khanna, Sam

Purpose: To evaluate comprehensively the effect of a radiotherapy boost on breast cosmetic outcomes after 5 years in patients treated with breast-conserving surgery. Methods: The St. George and Wollongong trial (NCT00138814) randomized 688 patients with histologically proven Tis-2, N 0-1, M0 carcinoma to the control arm of 50 Gy in 25 fractions (342 patients) and the boost arm of 45 Gy in 25 fractions to the whole breast followed by a 16 Gy in 8 fraction electron boost (346 patients). Five-year cosmetic outcomes were assessed by a panel subjectively in 385 patients and objectively using pBRA (relative breast retraction assessment).more » A subset of patients also had absolute BRA measurements. Clinician assessment and patient self-assessment of overall cosmetic and specific items as well as computer BCCT.core analysis were also performed. Results: The boost arm had improved cosmetic overall outcomes as scored by the panel and BCCT.core software with 79% (p = 0.016) and 81% (p = 0.004) excellent/good cosmesis respectively compared with 68% in no-boost arm. The boost arm also had lower pBRA and BRA values with a mean difference of 0.60 and 1.82 mm, respectively, but was not statistically significant. There was a very high proportion of overall excellent/good cosmetic outcome in 95% and 93% in the boost and no-boost arms using patient self-assessment. However, no difference in overall and specific items scored by clinician assessment and patient self-assessment was found. Conclusion: The results show the negative cosmetic effect of a 16-Gy boost is offset by a lower whole-breast dose of 45 Gy.« less

Ensemble Deep Learning for Biomedical Time Series Classification

PubMed Central

2016-01-01

Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost. PMID:27725828

Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

NASA Astrophysics Data System (ADS)

Borodinov, A. A.; Myasnikov, V. V.

2018-04-01

The present work is devoted to comparing the accuracy of the known qualification algorithms in the task of recognizing local objects on radar images for various image preprocessing methods. Preprocessing involves speckle noise filtering and normalization of the object orientation in the image by the method of image moments and by a method based on the Hough transform. In comparison, the following classification algorithms are used: Decision tree; Support vector machine, AdaBoost, Random forest. The principal component analysis is used to reduce the dimension. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.

AC to DC Bridgeless Boost Converter for Ultra Low Input Energy Harvesting

NASA Astrophysics Data System (ADS)

Dawam, A. H. A.; Muhamad, M.

2018-03-01

This paper presents design of circuit which converts low input AC voltage to a higher output DC voltage. A buck-boost topology and boost topology are combined to condition cycle of an AC input voltage. the unique integration of a combining circuit of buck-boost and boost circuit have been proposed in order to introduce a new direct ac-dc power converter topology without conventional diode bridge rectifier. The converter achieved to convert a milli-volt scale of input AC voltage into a volt scale of output DC voltages which is from 400mV to 3.3V.

Search for Boosted Dark Matter Interacting with Electrons in Super-Kamiokande.

PubMed

Kachulis, C; Abe, K; Bronner, C; Hayato, Y; Ikeda, M; Iyogi, K; Kameda, J; Kato, Y; Kishimoto, Y; Marti, Ll; Miura, M; Moriyama, S; Nakahata, M; Nakano, Y; Nakayama, S; Okajima, Y; Orii, A; Pronost, G; Sekiya, H; Shiozawa, M; Sonoda, Y; Takeda, A; Takenaka, A; Tanaka, H; Tasaka, S; Tomura, T; Akutsu, R; Kajita, T; Kaneyuki, K; Nishimura, Y; Okumura, K; Tsui, K M; Labarga, L; Fernandez, P; Blaszczyk, F D M; Gustafson, J; Kearns, E; Raaf, J L; Stone, J L; Sulak, L R; Berkman, S; Tobayama, S; Goldhaber, M; Elnimr, M; Kropp, W R; Mine, S; Locke, S; Weatherly, P; Smy, M B; Sobel, H W; Takhistov, V; Ganezer, K S; Hill, J; Kim, J Y; Lim, I T; Park, R G; Himmel, A; Li, Z; O'Sullivan, E; Scholberg, K; Walter, C W; Ishizuka, T; Nakamura, T; Jang, J S; Choi, K; Learned, J G; Matsuno, S; Smith, S N; Amey, J; Litchfield, R P; Ma, W Y; Uchida, Y; Wascko, M O; Cao, S; Friend, M; Hasegawa, T; Ishida, T; Ishii, T; Kobayashi, T; Nakadaira, T; Nakamura, K; Oyama, Y; Sakashita, K; Sekiguchi, T; Tsukamoto, T; Abe, K E; Hasegawa, M; Suzuki, A T; Takeuchi, Y; Yano, T; Hayashino, T; Hiraki, T; Hirota, S; Huang, K; Jiang, M; Nakamura, K E; Nakaya, T; Quilain, B; Patel, N D; Wendell, R A; Anthony, L H V; McCauley, N; Pritchard, A; Fukuda, Y; Itow, Y; Murase, M; Muto, F; Mijakowski, P; Frankiewicz, K; Jung, C K; Li, X; Palomino, J L; Santucci, G; Vilela, C; Wilking, M J; Yanagisawa, C; Ito, S; Fukuda, D; Ishino, H; Kibayashi, A; Koshio, Y; Nagata, H; Sakuda, M; Xu, C; Kuno, Y; Wark, D; Di Lodovico, F; Richards, B; Tacik, R; Kim, S B; Cole, A; Thompson, L; Okazawa, H; Choi, Y; Ito, K; Nishijima, K; Koshiba, M; Totsuka, Y; Suda, Y; Yokoyama, M; Calland, R G; Hartz, M; Martens, K; Simpson, C; Suzuki, Y; Vagins, M R; Hamabe, D; Kuze, M; Yoshida, T; Ishitsuka, M; Martin, J F; Nantais, C M; Tanaka, H A; Konaka, A; Chen, S; Wan, L; Zhang, Y; Wilkes, R J; Minamino, A

2018-06-01

A search for boosted dark matter using 161.9 kt yr of Super-Kamiokande IV data is presented. We search for an excess of elastically scattered electrons above the atmospheric neutrino background, with a visible energy between 100 MeV and 1 TeV, pointing back to the Galactic center or the Sun. No such excess is observed. Limits on boosted dark matter event rates in multiple angular cones around the Galactic center and Sun are calculated. Limits are also calculated for a baseline model of boosted dark matter produced from cold dark matter annihilation or decay. This is the first experimental search for boosted dark matter from the Galactic center or the Sun interacting in a terrestrial detector.

Comparison of composite prostate radiotherapy plan doses with dependent and independent boost phases.

PubMed

Narayanasamy, Ganesh; Avila, Gabrielle; Mavroidis, Panayiotis; Papanikolaou, Niko; Gutierrez, Alonso; Baacke, Diana; Shi, Zheng; Stathakis, Sotirios

2016-09-01

Prostate cases commonly consist of dual phase planning with a primary plan followed by a boost. Traditionally, the boost phase is planned independently from the primary plan with the risk of generating hot or cold spots in the composite plan. Alternatively, boost phase can be planned taking into account the primary dose. The aim of this study was to compare the composite plans from independently and dependently planned boosts using dosimetric and radiobiological metrics. Ten consecutive prostate patients previously treated at our institution were used to conduct this study on the Raystation™ 4.0 treatment planning system. For each patient, two composite plans were developed: a primary plan with an independently planned boost and a primary plan with a dependently planned boost phase. The primary plan was prescribed to 54 Gy in 30 fractions to the primary planning target volume (PTV1) which includes prostate and seminal vesicles, while the boost phases were prescribed to 24 Gy in 12 fractions to the boost planning target volume (PTV2) that targets only the prostate. PTV coverage, max dose, median dose, target conformity, dose homogeneity, dose to OARs, and probabilities of benefit, injury, and complication-free tumor control (P+) were compared. Statistical significance was tested using either a 2-tailed Student's t-test or Wilcoxon signed-rank test. Dosimetrically, the composite plan with dependent boost phase exhibited smaller hotspots, lower maximum dose to the target without any significant change to normal tissue dose. Radiobiologically, for all but one patient, the percent difference in the P+ values between the two methods was not significant. A large percent difference in P+ value could be attributed to an inferior primary plan. The benefits of considering the dose in primary plan while planning the boost is not significant unless a poor primary plan was achieved.

The gradient boosting algorithm and random boosting for genome-assisted evaluation in large data sets.

PubMed

González-Recio, O; Jiménez-Montero, J A; Alenda, R

2013-01-01

In the next few years, with the advent of high-density single nucleotide polymorphism (SNP) arrays and genome sequencing, genomic evaluation methods will need to deal with a large number of genetic variants and an increasing sample size. The boosting algorithm is a machine-learning technique that may alleviate the drawbacks of dealing with such large data sets. This algorithm combines different predictors in a sequential manner with some shrinkage on them; each predictor is applied consecutively to the residuals from the committee formed by the previous ones to form a final prediction based on a subset of covariates. Here, a detailed description is provided and examples using a toy data set are included. A modification of the algorithm called "random boosting" was proposed to increase predictive ability and decrease computation time of genome-assisted evaluation in large data sets. Random boosting uses a random selection of markers to add a subsequent weak learner to the predictive model. These modifications were applied to a real data set composed of 1,797 bulls genotyped for 39,714 SNP. Deregressed proofs of 4 yield traits and 1 type trait from January 2009 routine evaluations were used as dependent variables. A 2-fold cross-validation scenario was implemented. Sires born before 2005 were used as a training sample (1,576 and 1,562 for production and type traits, respectively), whereas younger sires were used as a testing sample to evaluate predictive ability of the algorithm on yet-to-be-observed phenotypes. Comparison with the original algorithm was provided. The predictive ability of the algorithm was measured as Pearson correlations between observed and predicted responses. Further, estimated bias was computed as the average difference between observed and predicted phenotypes. The results showed that the modification of the original boosting algorithm could be run in 1% of the time used with the original algorithm and with negligible differences in accuracy

Intensity modulated radiotherapy with simultaneous integrated boost vs. conventional radiotherapy with sequential boost for breast cancer - A preliminary result.

PubMed

Lee, Hsin-Hua; Hou, Ming-Feng; Chuang, Hung-Yi; Huang, Ming-Yii; Tsuei, Le-Ping; Chen, Fang-Ming; Ou-Yang, Fu; Huang, Chih-Jen

2015-10-01

This study was aimed to assess the acute dermatological adverse effect from two distinct RT techniques for breast cancer patients. We compared intensity-modulated radiotherapy with simultaneous integrated boost (IMRT-SIB) and conventional radiotherapy followed by sequential boost (CRT-SB). The study population was composed of 126 consecutive female breast cancer patients treated with breast conserving surgery. Sixty-six patients received IMRT-SIB to 2 dose levels simultaneously. They received 50.4 Gy at 1.8 Gy per fraction to the whole breast and 60.2 Gy at 2.15 Gy per fraction to the tumor bed by integral boost. Sixty patients in the CRT-SB group received 50 Gy in 25 fractions to the whole breast followed by a boost irradiation to tumor bed in 5-7 fractions to a total dose of 60-64 Gy. Acute skin toxicities were documented in agreement with the Common Terminology Criteria for Adverse Events version 3 (CTCAE v.3.0). Ninety-eight patients had grade 1 radiation dermatitis while 14 patients had grade 2. Among those with grade 2, there were 3 patients in IMRT-SIB group (4.5%) while 11 in CRT-SB group (18.3%). (P = 0.048) There was no patient with higher than grade 2 toxicity. Three year local control was 99.2%, 3-year disease free survival was 97.5% and 3-year overall survival was 99.2%. A significant reduction in the severity of acute radiation dermatitis from IMRT-SIB comparing with CRT-SB is demonstrated. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive Local Realignment of Protein Sequences.

PubMed

DeBlasio, Dan; Kececioglu, John

2018-06-11

While mutation rates can vary markedly over the residues of a protein, multiple sequence alignment tools typically use the same values for their scoring-function parameters across a protein's entire length. We present a new approach, called adaptive local realignment, that in contrast automatically adapts to the diversity of mutation rates along protein sequences. This builds upon a recent technique known as parameter advising, which finds global parameter settings for an aligner, to now adaptively find local settings. Our approach in essence identifies local regions with low estimated accuracy, constructs a set of candidate realignments using a carefully-chosen collection of parameter settings, and replaces the region if a realignment has higher estimated accuracy. This new method of local parameter advising, when combined with prior methods for global advising, boosts alignment accuracy as much as 26% over the best default setting on hard-to-align protein benchmarks, and by 6.4% over global advising alone. Adaptive local realignment has been implemented within the Opal aligner using the Facet accuracy estimator.

Improving performance of natural language processing part-of-speech tagging on clinical narratives through domain adaptation.

PubMed

Ferraro, Jeffrey P; Daumé, Hal; Duvall, Scott L; Chapman, Wendy W; Harkema, Henk; Haug, Peter J

2013-01-01

Natural language processing (NLP) tasks are commonly decomposed into subtasks, chained together to form processing pipelines. The residual error produced in these subtasks propagates, adversely affecting the end objectives. Limited availability of annotated clinical data remains a barrier to reaching state-of-the-art operating characteristics using statistically based NLP tools in the clinical domain. Here we explore the unique linguistic constructions of clinical texts and demonstrate the loss in operating characteristics when out-of-the-box part-of-speech (POS) tagging tools are applied to the clinical domain. We test a domain adaptation approach integrating a novel lexical-generation probability rule used in a transformation-based learner to boost POS performance on clinical narratives. Two target corpora from independent healthcare institutions were constructed from high frequency clinical narratives. Four leading POS taggers with their out-of-the-box models trained from general English and biomedical abstracts were evaluated against these clinical corpora. A high performing domain adaptation method, Easy Adapt, was compared to our newly proposed method ClinAdapt. The evaluated POS taggers drop in accuracy by 8.5-15% when tested on clinical narratives. The highest performing tagger reports an accuracy of 88.6%. Domain adaptation with Easy Adapt reports accuracies of 88.3-91.0% on clinical texts. ClinAdapt reports 93.2-93.9%. ClinAdapt successfully boosts POS tagging performance through domain adaptation requiring a modest amount of annotated clinical data. Improving the performance of critical NLP subtasks is expected to reduce pipeline error propagation leading to better overall results on complex processing tasks.

A methodology for boost-glide transport technology planning

NASA Technical Reports Server (NTRS)

Repic, E. M.; Olson, G. A.; Milliken, R. J.

1974-01-01

A systematic procedure is presented by which the relative economic value of technology factors affecting design, configuration, and operation of boost-glide transport can be evaluated. Use of the methodology results in identification of first-order economic gains potentially achievable by projected advances in each of the definable, hypersonic technologies. Starting with a baseline vehicle, the formulas, procedures and forms which are integral parts of this methodology are developed. A demonstration of the methodology is presented for one specific boost-glide system.

Modeling driver stop/run behavior at the onset of a yellow indication considering driver run tendency and roadway surface conditions.

PubMed

Elhenawy, Mohammed; Jahangiri, Arash; Rakha, Hesham A; El-Shawarby, Ihab

2015-10-01

The ability to model driver stop/run behavior at signalized intersections considering the roadway surface condition is critical in the design of advanced driver assistance systems. Such systems can reduce intersection crashes and fatalities by predicting driver stop/run behavior. The research presented in this paper uses data collected from two controlled field experiments on the Smart Road at the Virginia Tech Transportation Institute (VTTI) to model driver stop/run behavior at the onset of a yellow indication for different roadway surface conditions. The paper offers two contributions. First, it introduces a new predictor related to driver aggressiveness and demonstrates that this measure enhances the modeling of driver stop/run behavior. Second, it applies well-known artificial intelligence techniques including: adaptive boosting (AdaBoost), random forest, and support vector machine (SVM) algorithms as well as traditional logistic regression techniques on the data in order to develop a model that can be used by traffic signal controllers to predict driver stop/run decisions in a connected vehicle environment. The research demonstrates that by adding the proposed driver aggressiveness predictor to the model, there is a statistically significant increase in the model accuracy. Moreover the false alarm rate is significantly reduced but this reduction is not statistically significant. The study demonstrates that, for the subject data, the SVM machine learning algorithm performs the best in terms of optimum classification accuracy and false positive rates. However, the SVM model produces the best performance in terms of the classification accuracy only. Copyright © 2015 Elsevier Ltd. All rights reserved.

Notch-Boosted Domain Wall Propagation in Magnetic Nanowires

NASA Astrophysics Data System (ADS)

Wang, Xiang Rong; Yuan, Hauiyang

Magnetic domain wall (DW) motion along a nanowire underpins many proposals of spintronic devices. High DW propagation velocity is obviously important because it determines the device speed. Thus it is interesting to search for effective control knobs of DW dynamics. We report a counter-intuitive finding that notches in an otherwise homogeneous magnetic nanowire can boost current-induced domain wall (DW) propagation. DW motion in notch-modulated wires can be classified into three phases: 1) A DW is pinned around a notch when the current density is below the depinning current density. 2) DW propagation velocity above the depinning current density is boosted by notches when non-adiabatic spin-transfer torque strength is smaller than the Gilbert damping constant. The boost can be many-fold. 3) DW propagation velocity is hindered when non-adiabatic spin-transfer torque strength is larger than the Gilbert damping constant. This work was supported by Hong Kong GRF Grants (Nos. 163011151 and 605413) and the Grant from NNSF of China (No. 11374249).

Engineering report: Oxygen boost compressor study

NASA Technical Reports Server (NTRS)

Tera, L. S.

1974-01-01

An oxygen boost compressor is described which supports a self-contained life support system. A preliminary analysis of the compressor is presented along with performance test results, and recommendations for follow-on efforts.

Complexified boost invariance and holographic heavy ion collisions

DOE PAGES

Gubser, Steven S.; van der Schee, Wilke

2015-01-08

At strong coupling holographic studies have shown that heavy ion collisions do not obey normal boost invariance. Here we study a modified boost invariance through a complex shift in time, and show that this leads to surprisingly good agreement with numerical holographic computations. When including perturbations the agreement becomes even better, both in the hydrodynamic and the far-from-equilibrium regime. Finally, one of the main advantages is an analytic formulation of the stress-energy tensor of the longitudinal dynamics of holographic heavy ion collisions.

A Study of 4-level DC-DC Boost Inverter with Passive Component Reduction Consideration

NASA Astrophysics Data System (ADS)

Kasiran, A. N.; Ponniran, A.; Harimon, M. A.; Hamzah, H. H.

2018-04-01

This study is to analyze design principles of boost inductor and capacitor used in the 4-level DC-DC boost converter to realize size reduction of passive component referring to their attributes. The important feature of this circuit is that most of the boost-up energy is transferred from the capacitor-clamped to the output side which the small inductance can be used at the input side. The inductance of the boost inductor is designed by referring the inductor current ripple. On the other hand, the capacitance of the capacitor-clamped is designed by considering voltage stress on semiconductor devices and also the used switching frequency. Besides that, according to the design specifications, the required inductance in 4-level DC-DC boost converter is decreased compared to a conventional conventional DC-DC boost converter. Meanwhile, voltage stress on semiconductor device is depending on the maximum voltage ripple of the capacitor-clamped. A 50 W 4-level DC-DC boost converter prototype has been constructed. The results show that the inductor current ripple was 1.15 A when the inductors, 1 mH and 0.11 mH were used in the conventional and 4-level DC-DC boost converters, respectively. Thus, based on the experimental results, it shows that the reduction of passive components by referring to their attributes in 4-level DC-DC boost converter is achieved. Moreover, the decreasing of voltage stress on the semiconductor devices is an advantage for the selection of low ON-resistance of the devices which will contribute to the reduction of the semiconductor conduction loss. The integration result of boost converter and H-bridge inverter is also shown.

Two-inductor boost and buck converters

NASA Astrophysics Data System (ADS)

White, J. L.; Muldoon, W. J.

The derivation, analysis and design of a coupled inductor boost converter is presented. Aspects of the qualitative ac behavior of coupled inductor converters are discussed. Considerations for the design of the magnetics for such converters are addressed.

Multiview boosting digital pathology analysis of prostate cancer.

PubMed

Kwak, Jin Tae; Hewitt, Stephen M

2017-04-01

Various digital pathology tools have been developed to aid in analyzing tissues and improving cancer pathology. The multi-resolution nature of cancer pathology, however, has not been fully analyzed and utilized. Here, we develop an automated, cooperative, and multi-resolution method for improving prostate cancer diagnosis. Digitized tissue specimen images are obtained from 5 tissue microarrays (TMAs). The TMAs include 70 benign and 135 cancer samples (TMA1), 74 benign and 89 cancer samples (TMA2), 70 benign and 115 cancer samples (TMA3), 79 benign and 82 cancer samples (TMA4), and 72 benign and 86 cancer samples (TMA5). The tissue specimen images are segmented using intensity- and texture-based features. Using the segmentation results, a number of morphological features from lumens and epithelial nuclei are computed to characterize tissues at different resolutions. Applying a multiview boosting algorithm, tissue characteristics, obtained from differing resolutions, are cooperatively combined to achieve accurate cancer detection. In segmenting prostate tissues, the multiview boosting method achieved≥ 0.97 AUC using TMA1. For detecting cancers, the multiview boosting method achieved an AUC of 0.98 (95% CI: 0.97-0.99) as trained on TMA2 and tested on TMA3, TMA4, and TMA5. The proposed method was superior to single-view approaches, utilizing features from a single resolution or merging features from all the resolutions. Moreover, the performance of the proposed method was insensitive to the choice of the training dataset. Trained on TMA3, TMA4, and TMA5, the proposed method obtained an AUC of 0.97 (95% CI: 0.96-0.98), 0.98 (95% CI: 0.96-0.99), and 0.97 (95% CI: 0.96-0.98), respectively. The multiview boosting method is capable of integrating information from multiple resolutions in an effective and efficient fashion and identifying cancers with high accuracy. The multiview boosting method holds a great potential for improving digital pathology tools and research

Exploiting tRNAs to Boost Virulence

PubMed Central

Albers, Suki; Czech, Andreas

2016-01-01

Transfer RNAs (tRNAs) are powerful small RNA entities that are used to translate nucleotide language of genes into the amino acid language of proteins. Their near-uniform length and tertiary structure as well as their high nucleotide similarity and post-transcriptional modifications have made it difficult to characterize individual species quantitatively. However, due to the central role of the tRNA pool in protein biosynthesis as well as newly emerging roles played by tRNAs, their quantitative assessment yields important information, particularly relevant for virus research. Viruses which depend on the host protein expression machinery have evolved various strategies to optimize tRNA usage—either by adapting to the host codon usage or encoding their own tRNAs. Additionally, several viruses bear tRNA-like elements (TLE) in the 5′- and 3′-UTR of their mRNAs. There are different hypotheses concerning the manner in which such structures boost viral protein expression. Furthermore, retroviruses use special tRNAs for packaging and initiating reverse transcription of their genetic material. Since there is a strong specificity of different viruses towards certain tRNAs, different strategies for recruitment are employed. Interestingly, modifications on tRNAs strongly impact their functionality in viruses. Here, we review those intersection points between virus and tRNA research and describe methods for assessing the tRNA pool in terms of concentration, aminoacylation and modification. PMID:26797637

Experimental Treatment for Duchenne Muscular Dystrophy Gets Boost from Existing Medication

MedlinePlus

... Boost from Existing Medication Spotlight on Research Experimental Treatment for Duchenne Muscular Dystrophy Gets Boost from Existing Medication By Colleen Labbe, M.S. | March 1, 2013 A mouse hanging on a wire during a test of muscle strength. Mice with a mutant dystrophin gene, which ...

Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

NASA Astrophysics Data System (ADS)

Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

PubMed

Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

2017-11-02

Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

Frequential versus spatial colour textons for breast TMA classification.

PubMed

Fernández-Carrobles, M Milagro; Bueno, Gloria; Déniz, Oscar; Salido, Jesús; García-Rojo, Marcial; Gonzández-López, Lucía

2015-06-01

Advances in digital pathology are generating huge volumes of whole slide (WSI) and tissue microarray images (TMA) which are providing new insights into the causes of cancer. The challenge is to extract and process effectively all the information in order to characterize all the heterogeneous tissue-derived data. This study aims to identify an optimal set of features that best separates different classes in breast TMA. These classes are: stroma, adipose tissue, benign and benign anomalous structures and ductal and lobular carcinomas. To this end, we propose an exhaustive assessment on the utility of textons and colour for automatic classification of breast TMA. Frequential and spatial texton maps from eight different colour models were extracted and compared. Then, in a novel way, the TMA is characterized by the 1st and 2nd order Haralick statistical descriptors obtained from the texton maps with a total of 241 × 8 features for each original RGB image. Subsequently, a feature selection process is performed to remove redundant information and therefore to reduce the dimensionality of the feature vector. Three methods were evaluated: linear discriminant analysis, correlation and sequential forward search. Finally, an extended bank of classifiers composed of six techniques was compared, but only three of them could significantly improve accuracy rates: Fisher, Bagging Trees and AdaBoost. Our results reveal that the combination of different colour models applied to spatial texton maps provides the most efficient representation of the breast TMA. Specifically, we found that the best colour model combination is Hb, Luv and SCT for all classifiers and the classifier that performs best for all colour model combinations is the AdaBoost. On a database comprising 628 TMA images, classification yields an accuracy of 98.1% and a precision of 96.2% with a total of 316 features on spatial textons maps. Copyright © 2014 Elsevier Ltd. All rights reserved.

Classification of intramural metastases and lymph node metastases of esophageal cancer from gene expression based on boosting and projective adaptive resonance theory.

PubMed

Takahashi, Hiro; Aoyagi, Kazuhiko; Nakanishi, Yukihiro; Sasaki, Hiroki; Yoshida, Teruhiko; Honda, Hiroyuki

2006-07-01

Esophageal cancer is a well-known cancer with poorer prognosis than other cancers. An optimal and individualized treatment protocol based on accurate diagnosis is urgently needed to improve the treatment of cancer patients. For this purpose, it is important to develop a sophisticated algorithm that can manage a large amount of data, such as gene expression data from DNA microarrays, for optimal and individualized diagnosis. Marker gene selection is essential in the analysis of gene expression data. We have already developed a combination method of the use of the projective adaptive resonance theory and that of a boosted fuzzy classifier with the SWEEP operator denoted PART-BFCS. This method is superior to other methods, and has four features, namely fast calculation, accurate prediction, reliable prediction, and rule extraction. In this study, we applied this method to analyze microarray data obtained from esophageal cancer patients. A combination method of PART-BFCS and the U-test was also investigated. It was necessary to use a specific type of BFCS, namely, BFCS-1,2, because the esophageal cancer data were very complexity. PART-BFCS and PART-BFCS with the U-test models showed higher performances than two conventional methods, namely, k-nearest neighbor (kNN) and weighted voting (WV). The genes including CDK6 could be found by our methods and excellent IF-THEN rules could be extracted. The genes selected in this study have a high potential as new diagnosis markers for esophageal cancer. These results indicate that the new methods can be used in marker gene selection for the diagnosis of cancer patients.

Breast conserving treatment for breast cancer: dosimetric comparison of sequential versus simultaneous integrated photon boost.

PubMed

Van Parijs, Hilde; Reynders, Truus; Heuninckx, Karina; Verellen, Dirk; Storme, Guy; De Ridder, Mark

2014-01-01

Breast conserving surgery followed by whole breast irradiation is widely accepted as standard of care for early breast cancer. Addition of a boost dose to the initial tumor area further reduces local recurrences. We investigated the dosimetric benefits of a simultaneously integrated boost (SIB) compared to a sequential boost to hypofractionate the boost volume, while maintaining normofractionation on the breast. For 10 patients 4 treatment plans were deployed, 1 with a sequential photon boost, and 3 with different SIB techniques: on a conventional linear accelerator, helical TomoTherapy, and static TomoDirect. Dosimetric comparison was performed. PTV-coverage was good in all techniques. Conformity was better with all SIB techniques compared to sequential boost (P = 0.0001). There was less dose spilling to the ipsilateral breast outside the PTVboost (P = 0.04). The dose to the organs at risk (OAR) was not influenced by SIB compared to sequential boost. Helical TomoTherapy showed a higher mean dose to the contralateral breast, but less than 5 Gy for each patient. SIB showed less dose spilling within the breast and equal dose to OAR compared to sequential boost. Both helical TomoTherapy and the conventional technique delivered acceptable dosimetry. SIB seems a safe alternative and can be implemented in clinical routine.

Preferential Targeting of Conserved Gag Regions after Vaccination with a Heterologous DNA Prime-Modified Vaccinia Virus Ankara Boost HIV-1 Vaccine Regimen.

PubMed

Bauer, Asli; Podola, Lilli; Mann, Philipp; Missanga, Marco; Haule, Antelmo; Sudi, Lwitiho; Nilsson, Charlotta; Kaluwa, Bahati; Lueer, Cornelia; Mwakatima, Maria; Munseri, Patricia J; Maboko, Leonard; Robb, Merlin L; Tovanabutra, Sodsai; Kijak, Gustavo; Marovich, Mary; McCormack, Sheena; Joseph, Sarah; Lyamuya, Eligius; Wahren, Britta; Sandström, Eric; Biberfeld, Gunnel; Hoelscher, Michael; Bakari, Muhammad; Kroidl, Arne; Geldmacher, Christof

2017-09-15

given immunogen in prime-boost vaccination strategies is one approach that aims to improve coverage for global virus variants, the immunologic consequences of this strategy have been poorly defined so far. It is unclear whether inclusion of multiple variants in prime-boost vaccination strategies improves recognition of variant viruses by T cells and by which mechanisms this would be achieved, either by improved cross-recognition of multiple variants for a given antigenic region or through preferential targeting of antigenic regions more conserved between prime and boost. Engineering vaccines to induce adaptive immune responses that preferentially target conserved antigenic regions of viral vulnerability might facilitate better immune control after preventive and therapeutic vaccination for HIV and for other variable viruses. Copyright © 2017 American Society for Microbiology.

Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance

DTIC Science & Technology

2003-07-21

Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance Vincent A. Cicirello CMU-RI-TR-03-27 Submitted in partial fulfillment...AND SUBTITLE Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...lead to the development of a search control framework, called QD-BEACON that uses online -generated statistical models of search performance to

Boosting Manufacturing through Modular Chemical Process Intensification

ScienceCinema

None

2018-06-12

Manufacturing USA's Rapid Advancement in Process Intensification Deployment Institute will focus on developing breakthrough technologies to boost domestic energy productivity and energy efficiency by 20 percent in five years through manufacturing processes.

Boosting Manufacturing through Modular Chemical Process Intensification

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

None

2016-12-09

Manufacturing USA's Rapid Advancement in Process Intensification Deployment Institute will focus on developing breakthrough technologies to boost domestic energy productivity and energy efficiency by 20 percent in five years through manufacturing processes.

Adaptive fuzzy sliding control of single-phase PV grid-connected inverter

PubMed Central

Zhu, Yunkai

2017-01-01

In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV) grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with adaptive step is adopted to track the maximum power point (MPP) by controlling the duty cycle of the controllable power switch of the boost DC-DC converter. An adaptive fuzzy sliding mode controller with an integral sliding surface is developed for the grid-connected inverter where a fuzzy system is used to approach the upper bound of the system nonlinearities. The proposed strategy has strong robustness for the sliding mode control can be designed independently and disturbances can be adaptively compensated. Simulation results of a PV grid-connected system verify the effectiveness of the proposed method, demonstrating the satisfactory robustness and performance. PMID:28797060

Adaptive fuzzy sliding control of single-phase PV grid-connected inverter.

PubMed

Fei, Juntao; Zhu, Yunkai

2017-01-01

In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV) grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with adaptive step is adopted to track the maximum power point (MPP) by controlling the duty cycle of the controllable power switch of the boost DC-DC converter. An adaptive fuzzy sliding mode controller with an integral sliding surface is developed for the grid-connected inverter where a fuzzy system is used to approach the upper bound of the system nonlinearities. The proposed strategy has strong robustness for the sliding mode control can be designed independently and disturbances can be adaptively compensated. Simulation results of a PV grid-connected system verify the effectiveness of the proposed method, demonstrating the satisfactory robustness and performance.

Early boost and slow consolidation in motor skill learning.

PubMed

Hotermans, Christophe; Peigneux, Philippe; Maertens de Noordhout, Alain; Moonen, Gustave; Maquet, Pierre

2006-01-01

Motorskill learning is a dynamic process that continues covertly after training has ended and eventually leads to delayed increments in performance. Current theories suggest that this off-line improvement takes time and appears only after several hours. Here we show an early transient and short-lived boost in performance, emerging as early as 5-30 min after training but no longer observed 4 h later. This early boost is predictive of the performance achieved 48 h later, suggesting its functional relevance for memory processes.

Breast Conserving Treatment for Breast Cancer: Dosimetric Comparison of Sequential versus Simultaneous Integrated Photon Boost

PubMed Central

Reynders, Truus; Heuninckx, Karina; Verellen, Dirk; Storme, Guy; De Ridder, Mark

2014-01-01

Background. Breast conserving surgery followed by whole breast irradiation is widely accepted as standard of care for early breast cancer. Addition of a boost dose to the initial tumor area further reduces local recurrences. We investigated the dosimetric benefits of a simultaneously integrated boost (SIB) compared to a sequential boost to hypofractionate the boost volume, while maintaining normofractionation on the breast. Methods. For 10 patients 4 treatment plans were deployed, 1 with a sequential photon boost, and 3 with different SIB techniques: on a conventional linear accelerator, helical TomoTherapy, and static TomoDirect. Dosimetric comparison was performed. Results. PTV-coverage was good in all techniques. Conformity was better with all SIB techniques compared to sequential boost (P = 0.0001). There was less dose spilling to the ipsilateral breast outside the PTVboost (P = 0.04). The dose to the organs at risk (OAR) was not influenced by SIB compared to sequential boost. Helical TomoTherapy showed a higher mean dose to the contralateral breast, but less than 5 Gy for each patient. Conclusions. SIB showed less dose spilling within the breast and equal dose to OAR compared to sequential boost. Both helical TomoTherapy and the conventional technique delivered acceptable dosimetry. SIB seems a safe alternative and can be implemented in clinical routine. PMID:25162031

Boosted dark matter signals uplifted with self-interaction

DOE PAGES

Kong, Kyoungchul; Mohlabeng, Gopolang; Park, Jong -Chul

2015-04-01

We explore detection prospects of a non-standard dark sector in the context of boosted dark matter. We focus on a scenario with two dark matter particles of a large mass difference, where the heavier candidate is secluded and interacts with the standard model particles only at loops, escaping existing direct and indirect detection bounds. Yet its pair annihilation in the galactic center or in the Sun may produce boosted stable particles, which could be detected as visible Cherenkov light in large volume neutrino detectors. In such models with multiple candidates, self-interaction of dark matter particles is naturally utilized in themore » assisted freeze-out mechanism and is corroborated by various cosmological studies such as N-body simulations of structure formation, observations of dwarf galaxies, and the small scale problem. We show that self-interaction of the secluded (heavier) dark matter greatly enhances the capture rate in the Sun and results in promising signals at current and future experiments. We perform a detailed analysis of the boosted dark matter events for Super-Kamiokande, Hyper-Kamiokande and PINGU, including notable effects such as evaporation due to self-interaction and energy loss in the Sun.« less

Boosted dark matter signals uplifted with self-interaction

NASA Astrophysics Data System (ADS)

Kong, Kyoungchul; Mohlabeng, Gopolang; Park, Jong-Chul

2015-04-01

We explore detection prospects of a non-standard dark sector in the context of boosted dark matter. We focus on a scenario with two dark matter particles of a large mass difference, where the heavier candidate is secluded and interacts with the standard model particles only at loops, escaping existing direct and indirect detection bounds. Yet its pair annihilation in the galactic center or in the Sun may produce boosted stable particles, which could be detected as visible Cherenkov light in large volume neutrino detectors. In such models with multiple candidates, self-interaction of dark matter particles is naturally utilized in the assisted freeze-out mechanism and is corroborated by various cosmological studies such as N-body simulations of structure formation, observations of dwarf galaxies, and the small scale problem. We show that self-interaction of the secluded (heavier) dark matter greatly enhances the capture rate in the Sun and results in promising signals at current and future experiments. We perform a detailed analysis of the boosted dark matter events for Super-Kamiokande, Hyper-Kamiokande and PINGU, including notable effects such as evaporation due to self-interaction and energy loss in the Sun.

Whole genome sequencing of turbot (Scophthalmus maximus; Pleuronectiformes): a fish adapted to demersal life

PubMed Central

Figueras, Antonio; Robledo, Diego; Corvelo, André; Hermida, Miguel; Pereiro, Patricia; Rubiolo, Juan A.; Gómez-Garrido, Jèssica; Carreté, Laia; Bello, Xabier; Gut, Marta; Gut, Ivo Glynne; Marcet-Houben, Marina; Forn-Cuní, Gabriel; Galán, Beatriz; García, José Luis; Abal-Fabeiro, José Luis; Pardo, Belen G.; Taboada, Xoana; Fernández, Carlos; Vlasova, Anna; Hermoso-Pulido, Antonio; Guigó, Roderic; Álvarez-Dios, José Antonio; Gómez-Tato, Antonio; Viñas, Ana; Maside, Xulio; Gabaldón, Toni; Novoa, Beatriz; Bouza, Carmen; Alioto, Tyler; Martínez, Paulino

2016-01-01

The turbot is a flatfish (Pleuronectiformes) with increasing commercial value, which has prompted active genomic research aimed at more efficient selection. Here we present the sequence and annotation of the turbot genome, which represents a milestone for both boosting breeding programmes and ascertaining the origin and diversification of flatfish. We compare the turbot genome with model fish genomes to investigate teleost chromosome evolution. We observe a conserved macrosyntenic pattern within Percomorpha and identify large syntenic blocks within the turbot genome related to the teleost genome duplication. We identify gene family expansions and positive selection of genes associated with vision and metabolism of membrane lipids, which suggests adaptation to demersal lifestyle and to cold temperatures, respectively. Our data indicate a quick evolution and diversification of flatfish to adapt to benthic life and provide clues for understanding their controversial origin. Moreover, we investigate the genomic architecture of growth, sex determination and disease resistance, key traits for understanding local adaptation and boosting turbot production, by mapping candidate genes and previously reported quantitative trait loci. The genomic architecture of these productive traits has allowed the identification of candidate genes and enriched pathways that may represent useful information for future marker-assisted selection in turbot. PMID:26951068

Analytic boosted boson discrimination

DOE PAGES

Larkoski, Andrew J.; Moult, Ian; Neill, Duff

2016-05-20

Observables which discriminate boosted topologies from massive QCD jets are of great importance for the success of the jet substructure program at the Large Hadron Collider. Such observables, while both widely and successfully used, have been studied almost exclusively with Monte Carlo simulations. In this paper we present the first all-orders factorization theorem for a two-prong discriminant based on a jet shape variable, D 2, valid for both signal and background jets. Our factorization theorem simultaneously describes the production of both collinear and soft subjets, and we introduce a novel zero-bin procedure to correctly describe the transition region between thesemore » limits. By proving an all orders factorization theorem, we enable a systematically improvable description, and allow for precision comparisons between data, Monte Carlo, and first principles QCD calculations for jet substructure observables. Using our factorization theorem, we present numerical results for the discrimination of a boosted Z boson from massive QCD background jets. We compare our results with Monte Carlo predictions which allows for a detailed understanding of the extent to which these generators accurately describe the formation of two-prong QCD jets, and informs their usage in substructure analyses. In conclusion, our calculation also provides considerable insight into the discrimination power and calculability of jet substructure observables in general.« less

Lorentz-boosted evanescent waves

NASA Astrophysics Data System (ADS)

Bliokh, Konstantin Y.

2018-06-01

Polarization, spin, and helicity are important properties of electromagnetic waves. It is commonly believed that helicity is invariant under the Lorentz transformations. This is indeed so for plane waves and their localized superpositions. However, this is not the case for evanescent waves, which are well-defined only in a half-space, and are characterized by complex wave vectors. Here we describe transformations of evanescent electromagnetic waves and their polarization/spin/helicity properties under the Lorentz boosts along the three spatial directions.

Effect of pole zero location on system dynamics of boost converter for micro grid

NASA Astrophysics Data System (ADS)

Lavanya, A.; Vijayakumar, K.; Navamani, J. D.; Jayaseelan, N.

2018-04-01

Green clean energy like photo voltaic, wind energy, fuel cell can be brought together by microgrid.For low voltage sources like photovoltaic cell boost converter is very much essential. This paper explores the dynamic analysis of boost converter in a continuous conduction mode (CCM). The transient performance and stability analysis is carried out in this paper using time domain analysis and frequency domain analysis techniques. Boost converter is simulated using both PSIM and MATLAB software. Furthermore, state space model obtained and the transfer function is derived. The converter behaviour when a step input is applied is analyzed and stability of the converter is analyzed from bode plot frequency for open loop. Effect of the locations of poles and zeros in the transfer function of boost converter and how the performance parameters are affected is discussed in this paper. Closed loop performance with PI controller is also analyzed for boost converter.

Maximum power point tracking techniques for wind energy systems using three levels boost converter

NASA Astrophysics Data System (ADS)

Tran, Cuong Hung; Nollet, Frédéric; Essounbouli, Najib; Hamzaoui, Abdelaziz

2018-05-01

This paper presents modeling and simulation of three level Boost DC-DC converter in Wind Energy Conversion System (WECS). Three-level Boost converter has significant advantage compared to conventional Boost. A maximum power point tracking (MPPT) method for a variable speed wind turbine using permanent magnet synchronous generator (PMSG) is also presented. Simulation of three-level Boost converter topology with Perturb and Observe algorithm and Fuzzy Logic Control is implemented in MATLAB/SIMULINK. Results of this simulation show that the system with MPPT using fuzzy logic controller has better performance to the Perturb and Observe algorithm: fast response under changing conditions and small oscillation.

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

PubMed Central

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

PubMed

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Identification of vegetable diseases using neural network

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Tang, Jianjun; Li, Yao

2007-02-01

Vegetables are widely planted all over China, but they often suffer from the some diseases. A method of major technical and economical importance is introduced in this paper, which explores the feasibility of implementing fast and reliable automatic identification of vegetable diseases and their infection grades from color and morphological features of leaves. Firstly, leaves are plucked from clustered plant and pictures of the leaves are taken with a CCD digital color camera. Secondly, color and morphological characteristics are obtained by standard image processing techniques, for examples, Otsu thresholding method segments the region of interest, image opening following closing algorithm removes noise, Principal Components Analysis reduces the dimension of the original features. Then, a recently proposed boosting algorithm AdaBoost. M2 is applied to RBF networks for diseases classification based on the above features, where the kernel function of RBF networks is Gaussian form with argument taking Euclidean distance of the input vector from a center. Our experiment performs on the database collected by Chinese Academy of Agricultural Sciences, and result shows that Boosting RBF Networks classifies the 230 cucumber leaves into 2 different diseases (downy-mildew and angular-leaf-spot), and identifies the infection grades of each disease according to the infection degrees.

Avoiding Anemia: Boost Your Red Blood Cells

MedlinePlus

... Issues Subscribe January 2014 Print this issue Avoiding Anemia Boost Your Red Blood Cells En español Send ... Disease When Blood Cells Bend Wise Choices Preventing Anemia To prevent or treat iron-deficiency anemia: Eat ...

Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.

PubMed

Chen, Ke; Wang, Shihai

2011-01-01

Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into account during boosting learning. In this paper, we propose a novel cost functional consisting of the margin cost on labeled data and the regularization penalty on unlabeled data based on three fundamental semi-supervised assumptions. Thus, minimizing our proposed cost functional with a greedy yet stagewise functional optimization procedure leads to a generic boosting framework for semi-supervised learning. Extensive experiments demonstrate that our algorithm yields favorite results for benchmark and real-world classification tasks in comparison to state-of-the-art semi-supervised learning algorithms, including newly developed boosting algorithms. Finally, we discuss relevant issues and relate our algorithm to the previous work.

Boosting bonsai trees for handwritten/printed text discrimination

NASA Astrophysics Data System (ADS)

Ricquebourg, Yann; Raymond, Christian; Poirriez, Baptiste; Lemaitre, Aurélie; Coüasnon, Bertrand

2013-12-01

Boosting over decision-stumps proved its efficiency in Natural Language Processing essentially with symbolic features, and its good properties (fast, few and not critical parameters, not sensitive to over-fitting) could be of great interest in the numeric world of pixel images. In this article we investigated the use of boosting over small decision trees, in image classification processing, for the discrimination of handwritten/printed text. Then, we conducted experiments to compare it to usual SVM-based classification revealing convincing results with very close performance, but with faster predictions and behaving far less as a black-box. Those promising results tend to make use of this classifier in more complex recognition tasks like multiclass problems.

Application of Boosting Regression Trees to Preliminary Cost Estimation in Building Construction Projects

PubMed Central

2015-01-01

Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project. PMID:26339227

Application of Boosting Regression Trees to Preliminary Cost Estimation in Building Construction Projects.

PubMed

Shin, Yoonseok

2015-01-01

Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.

Solid state light source driver establishing buck or boost operation

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

Palmer, Fred

A solid state light source driver circuit that operates in either a buck convertor or a boost convertor configuration is provided. The driver circuit includes a controller, a boost switch circuit and a buck switch circuit, each coupled to the controller, and a feedback circuit, coupled to the light source. The feedback circuit provides feedback to the controller, representing a DC output of the driver circuit. The controller controls the boost switch circuit and the buck switch circuit in response to the feedback signal, to regulate current to the light source. The controller places the driver circuit in its boostmore » converter configuration when the DC output is less than a rectified AC voltage coupled to the driver circuit at an input node. The controller places the driver circuit in its buck converter configuration when the DC output is greater than the rectified AC voltage at the input node.« less

Centaur boost pump turbine icing investigation

NASA Technical Reports Server (NTRS)

Rollbuhler, R. J.

1976-01-01

An investigation was conducted to determine if ice formation in the Centaur vehicle liquid oxygen boost pump turbine could prevent rotation of the pump and whether or not this phenomenon could have been the failure mechanism for the Titan/Centaur vehicle TC-1. The investigation consisted of a series of tests done in the LeRC Space Power Chamber Facility to evaluate evaporative cooling behavior patterns in a turbine as a function of the quantity of water trapped in the turbine and as a function of the vehicle ascent pressure profile. It was found that evaporative freezing of water in the turbine housing, due to rapid depressurization within the turbine during vehicle ascent, could result in the formation of ice that would block the turbine and prevent rotation of the boost pump. But for such icing conditions to exist it would be necessary to have significant quantities of water in the turbine and/or its components, and the turbine housing temperature would have to be colder than 40 F at vehicle liftoff.

Separation of pulsar signals from noise using supervised machine learning algorithms

NASA Astrophysics Data System (ADS)

Bethapudi, S.; Desai, S.

2018-04-01

We evaluate the performance of four different machine learning (ML) algorithms: an Artificial Neural Network Multi-Layer Perceptron (ANN MLP), Adaboost, Gradient Boosting Classifier (GBC), and XGBoost, for the separation of pulsars from radio frequency interference (RFI) and other sources of noise, using a dataset obtained from the post-processing of a pulsar search pipeline. This dataset was previously used for the cross-validation of the SPINN-based machine learning engine, obtained from the reprocessing of the HTRU-S survey data (Morello et al., 2014). We have used the Synthetic Minority Over-sampling Technique (SMOTE) to deal with high-class imbalance in the dataset. We report a variety of quality scores from all four of these algorithms on both the non-SMOTE and SMOTE datasets. For all the above ML methods, we report high accuracy and G-mean for both the non-SMOTE and SMOTE cases. We study the feature importances using Adaboost, GBC, and XGBoost and also from the minimum Redundancy Maximum Relevance approach to report algorithm-agnostic feature ranking. From these methods, we find that the signal to noise of the folded profile to be the best feature. We find that all the ML algorithms report FPRs about an order of magnitude lower than the corresponding FPRs obtained in Morello et al. (2014), for the same recall value.

Suspicious Behavior Detection System for an Open Space Parking Based on Recognition of Human Elemental Actions

NASA Astrophysics Data System (ADS)

Inomata, Teppei; Kimura, Kouji; Hagiwara, Masafumi

Studies for video surveillance applications for preventing various crimes such as stealing and violence have become a hot topic. This paper proposes a new video surveillance system that can detect suspicious behaviors such as a car break-in and vandalization in an open space parking, and that is based on image processing. The proposed system has the following features: it 1)deals time series data flow, 2)recognizes “human elemental actions” using statistic features, and 3)detects suspicious behavior using Subspace method and AdaBoost. We conducted the experiments to test the performance of the proposed system using open space parking scenes. As a result, we obtained about 10.0% for false positive rate, and about 4.6% for false negative rate.

Face verification system for Android mobile devices using histogram based features

NASA Astrophysics Data System (ADS)

Sato, Sho; Kobayashi, Kazuhiro; Chen, Qiu

2016-07-01

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

Pornographic information of Internet views detection method based on the connected areas

NASA Astrophysics Data System (ADS)

Wang, Huibai; Fan, Ajie

2017-01-01

Nowadays online porn video broadcasting and downloading is very popular. In view of the widespread phenomenon of Internet pornography, this paper proposed a new method of pornographic video detection based on connected areas. Firstly, decode the video into a serious of static images and detect skin color on the extracted key frames. If the area of skin color reaches a certain threshold, use the AdaBoost algorithm to detect the human face. Judge the connectivity of the human face and the large area of skin color to determine whether detect the sensitive area finally. The experimental results show that the method can effectively remove the non-pornographic videos contain human who wear less. This method can improve the efficiency and reduce the workload of detection.

Whole genome sequencing of turbot (Scophthalmus maximus; Pleuronectiformes): a fish adapted to demersal life.

PubMed

Figueras, Antonio; Robledo, Diego; Corvelo, André; Hermida, Miguel; Pereiro, Patricia; Rubiolo, Juan A; Gómez-Garrido, Jèssica; Carreté, Laia; Bello, Xabier; Gut, Marta; Gut, Ivo Glynne; Marcet-Houben, Marina; Forn-Cuní, Gabriel; Galán, Beatriz; García, José Luis; Abal-Fabeiro, José Luis; Pardo, Belen G; Taboada, Xoana; Fernández, Carlos; Vlasova, Anna; Hermoso-Pulido, Antonio; Guigó, Roderic; Álvarez-Dios, José Antonio; Gómez-Tato, Antonio; Viñas, Ana; Maside, Xulio; Gabaldón, Toni; Novoa, Beatriz; Bouza, Carmen; Alioto, Tyler; Martínez, Paulino

2016-06-01

The turbot is a flatfish (Pleuronectiformes) with increasing commercial value, which has prompted active genomic research aimed at more efficient selection. Here we present the sequence and annotation of the turbot genome, which represents a milestone for both boosting breeding programmes and ascertaining the origin and diversification of flatfish. We compare the turbot genome with model fish genomes to investigate teleost chromosome evolution. We observe a conserved macrosyntenic pattern within Percomorpha and identify large syntenic blocks within the turbot genome related to the teleost genome duplication. We identify gene family expansions and positive selection of genes associated with vision and metabolism of membrane lipids, which suggests adaptation to demersal lifestyle and to cold temperatures, respectively. Our data indicate a quick evolution and diversification of flatfish to adapt to benthic life and provide clues for understanding their controversial origin. Moreover, we investigate the genomic architecture of growth, sex determination and disease resistance, key traits for understanding local adaptation and boosting turbot production, by mapping candidate genes and previously reported quantitative trait loci. The genomic architecture of these productive traits has allowed the identification of candidate genes and enriched pathways that may represent useful information for future marker-assisted selection in turbot. © The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Experimental Research in Boost Driver with EDLCs

NASA Astrophysics Data System (ADS)

Matsumoto, Hirokazu

The supply used in servo systems tends to have a high voltage in order to reduce loss and improve the response of motor drives. We propose a new boost motor driver that comprises EDLCs. The proposed driver has a simple structure, wherein the EDLCs are connected in series to the supply, and comprises a charge circuit to charge the EDLCs. The proposed driver has three advantages over conventional boost drivers. The first advantage is that the driver can easily attain the stable boost voltage. The second advantage is that the driver can reduce input power peaks. In a servo system, the input power peaks become greater than the rated power in order to accelerate the motor rapidly. This implies that the equipments that supply power to servo systems must have sufficient power capacity to satisfy the power peaks. The proposed driver can suppress the increase of the power capacity of supply facilities. The third advantage is that the driver can store almost all of the regenerative energy. Conventional drivers have a braking resistor to suppress the increase in the DC link voltage. This causes a considerable reduction in the efficiency. The proposed driver is more efficient than conventional drivers. In this study, the experimental results confirmed the effectiveness of the proposed driver and showed that the drive performance of the proposed driver is the same as that of a conventional driver. Furthermore, it was confirmed that the results of the simulation of a model of the EDLC module, whose capacitance is dependent on the frequency, correspond well with the experimental results.

Closed Loop Fuzzy Logic Controlled PV Based Cascaded Boost Five-Level Inverter System

NASA Astrophysics Data System (ADS)

Revana, Guruswamy; Kota, Venkata Reddy

2018-04-01

Recent developments in intelligent control methods and power electronics have produced PV based DC to AC converters related to AC drives. Cascaded boost converter and inverter find their way in interconnecting PV and Induction Motor. This paper deals with digital simulation and implementation of closed loop controlled five-level inverter based Photo-Voltaic (PV) system. The objective of this work is to reduce the harmonics using Multi Level Inverter based system. The DC output from the PV panel is boosted using cascaded-boost-converters. The DC output of these cascaded boost converters is applied to the bridges of the cascaded inverter. The AC output voltage is obtained by the series cascading of the output voltage of the two inverters. The investigations are done with Induction motor load. Cascaded boost-converter is proposed in the present work to produce the required DC Voltage at the input of the bridge inverter. A simple FLC is applied to CBFLIIM system. The FLC is proposed to reduce the steady state error. The simulation results are compared with the hardware results. The results of the comparison are made to show the improvement in dynamic response in terms of settling time and steady state error. Design procedure and control strategy are presented in detail.

Closed Loop Fuzzy Logic Controlled PV Based Cascaded Boost Five-Level Inverter System

NASA Astrophysics Data System (ADS)

Revana, Guruswamy; Kota, Venkata Reddy

2017-12-01

Recent developments in intelligent control methods and power electronics have produced PV based DC to AC converters related to AC drives. Cascaded boost converter and inverter find their way in interconnecting PV and Induction Motor. This paper deals with digital simulation and implementation of closed loop controlled five-level inverter based Photo-Voltaic (PV) system. The objective of this work is to reduce the harmonics using Multi Level Inverter based system. The DC output from the PV panel is boosted using cascaded-boost-converters. The DC output of these cascaded boost converters is applied to the bridges of the cascaded inverter. The AC output voltage is obtained by the series cascading of the output voltage of the two inverters. The investigations are done with Induction motor load. Cascaded boost-converter is proposed in the present work to produce the required DC Voltage at the input of the bridge inverter. A simple FLC is applied to CBFLIIM system. The FLC is proposed to reduce the steady state error. The simulation results are compared with the hardware results. The results of the comparison are made to show the improvement in dynamic response in terms of settling time and steady state error. Design procedure and control strategy are presented in detail.

Finding structure in data using multivariate tree boosting

PubMed Central

Miller, Patrick J.; Lubke, Gitta H.; McArtor, Daniel B.; Bergeman, C. S.

2016-01-01

Technology and collaboration enable dramatic increases in the size of psychological and psychiatric data collections, but finding structure in these large data sets with many collected variables is challenging. Decision tree ensembles such as random forests (Strobl, Malley, & Tutz, 2009) are a useful tool for finding structure, but are difficult to interpret with multiple outcome variables which are often of interest in psychology. To find and interpret structure in data sets with multiple outcomes and many predictors (possibly exceeding the sample size), we introduce a multivariate extension to a decision tree ensemble method called gradient boosted regression trees (Friedman, 2001). Our extension, multivariate tree boosting, is a method for nonparametric regression that is useful for identifying important predictors, detecting predictors with nonlinear effects and interactions without specification of such effects, and for identifying predictors that cause two or more outcome variables to covary. We provide the R package ‘mvtboost’ to estimate, tune, and interpret the resulting model, which extends the implementation of univariate boosting in the R package ‘gbm’ (Ridgeway et al., 2015) to continuous, multivariate outcomes. To illustrate the approach, we analyze predictors of psychological well-being (Ryff & Keyes, 1995). Simulations verify that our approach identifies predictors with nonlinear effects and achieves high prediction accuracy, exceeding or matching the performance of (penalized) multivariate multiple regression and multivariate decision trees over a wide range of conditions. PMID:27918183

GeoBoost: accelerating research involving the geospatial metadata of virus GenBank records.

PubMed

Tahsin, Tasnia; Weissenbacher, Davy; O'Connor, Karen; Magge, Arjun; Scotch, Matthew; Gonzalez-Hernandez, Graciela

2018-05-01

GeoBoost is a command-line software package developed to address sparse or incomplete metadata in GenBank sequence records that relate to the location of the infected host (LOIH) of viruses. Given a set of GenBank accession numbers corresponding to virus GenBank records, GeoBoost extracts, integrates and normalizes geographic information reflecting the LOIH of the viruses using integrated information from GenBank metadata and related full-text publications. In addition, to facilitate probabilistic geospatial modeling, GeoBoost assigns probability scores for each possible LOIH. Binaries and resources required for running GeoBoost are packed into a single zipped file and freely available for download at https://tinyurl.com/geoboost. A video tutorial is included to help users quickly and easily install and run the software. The software is implemented in Java 1.8, and supported on MS Windows and Linux platforms. gragon@upenn.edu. Supplementary data are available at Bioinformatics online.

Research on motion model for the hypersonic boost-glide aircraft

NASA Astrophysics Data System (ADS)

Xu, Shenda; Wu, Jing; Wang, Xueying

2015-11-01

A motion model for the hypersonic boost-glide aircraft(HBG) was proposed in this paper, which also analyzed the precision of model through simulation. Firstly the trajectory of HBG was analyzed, and a scheme which divide the trajectory into two parts then build the motion model on each part. Secondly a restrained model of boosting stage and a restrained model of J2 perturbation were established, and set up the observe model. Finally the analysis of simulation results show the feasible and high-accuracy of the model, and raise a expectation for intensive research.

Committee approves bill to boost NIH funding.

PubMed

2015-08-01

A U.S. House of Representatives committee approved the 21st Century Cures Act. If passed by Congress, the bill would boost funding for the NIH and FDA and introduce new strategies for accelerating the approval of drugs and devices. ©2015 American Association for Cancer Research.

Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data

PubMed Central

Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian

2015-01-01

In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213

The Attentional Boost Effect with Verbal Materials

ERIC Educational Resources Information Center

Mulligan, Neil W.; Spataro, Pietro; Picklesimer, Milton

2014-01-01

Study stimuli presented at the same time as unrelated targets in a detection task are better remembered than stimuli presented with distractors. This attentional boost effect (ABE) has been found with pictorial (Swallow & Jiang, 2010) and more recently verbal materials (Spataro, Mulligan, & Rossi-Arnaud, 2013). The present experiments…

Schools Enlisting Defense Industry to Boost STEM

ERIC Educational Resources Information Center

Trotter, Andrew

2008-01-01

Defense contractors Northrop Grumman Corp. and Lockheed Martin Corp. are joining forces in an innovative partnership to develop high-tech simulations to boost STEM--or science, technology, engineering, and mathematics--education in the Baltimore County schools. The Baltimore County partnership includes the local operations of two major military…

Heterologous Prime-Boost HIV-1 Vaccination Regimens in Pre-Clinical and Clinical Trials

PubMed Central

Brown, Scott A.; Surman, Sherri L.; Sealy, Robert; Jones, Bart G.; Slobod, Karen S.; Branum, Kristen; Lockey, Timothy D.; Howlett, Nanna; Freiden, Pamela; Flynn, Patricia; Hurwitz, Julia L.

2010-01-01

Currently, there are more than 30 million people infected with HIV-1 and thousands more are infected each day. Vaccination is the single most effective mechanism for prevention of viral disease, and after more than 25 years of research, one vaccine has shown somewhat encouraging results in an advanced clinical efficacy trial. A modified intent-to-treat analysis of trial results showed that infection was approximately 30% lower in the vaccine group compared to the placebo group. The vaccine was administered using a heterologous prime-boost regimen in which both target antigens and delivery vehicles were changed during the course of inoculations. Here we examine the complexity of heterologous prime-boost immunizations. We show that the use of different delivery vehicles in prime and boost inoculations can help to avert the inhibitory effects caused by vector-specific immune responses. We also show that the introduction of new antigens into boost inoculations can be advantageous, demonstrating that the effect of ‘original antigenic sin’ is not absolute. Pre-clinical and clinical studies are reviewed, including our own work with a three-vector vaccination regimen using recombinant DNA, virus (Sendai virus or vaccinia virus) and protein. Promising preliminary results suggest that the heterologous prime-boost strategy may possibly provide a foundation for the future prevention of HIV-1 infections in humans. PMID:20407589

Detecting opinion spams through supervised boosting approach.

PubMed

Hazim, Mohamad; Anuar, Nor Badrul; Ab Razak, Mohd Faizal; Abdullah, Nor Aniza

2018-01-01

Product reviews are the individual's opinions, judgement or belief about a certain product or service provided by certain companies. Such reviews serve as guides for these companies to plan and monitor their business ventures in terms of increasing productivity or enhancing their product/service qualities. Product reviews can also increase business profits by convincing future customers about the products which they have interest in. In the mobile application marketplace such as Google Playstore, reviews and star ratings are used as indicators of the application quality. However, among all these reviews, hereby also known as opinions, spams also exist, to disrupt the online business balance. Previous studies used the time series and neural network approach (which require a lot of computational power) to detect these opinion spams. However, the detection performance can be restricted in terms of accuracy because the approach focusses on basic, discrete and document level features only thereby, projecting little statistical relationships. Aiming to improve the detection of opinion spams in mobile application marketplace, this study proposes using statistical based features that are modelled through the supervised boosting approach such as the Extreme Gradient Boost (XGBoost) and the Generalized Boosted Regression Model (GBM) to evaluate two multilingual datasets (i.e. English and Malay language). From the evaluation done, it was found that the XGBoost is most suitable for detecting opinion spams in the English dataset while the GBM Gaussian is most suitable for the Malay dataset. The comparative analysis also indicates that the implementation of the proposed statistical based features had achieved a detection accuracy rate of 87.43 per cent on the English dataset and 86.13 per cent on the Malay dataset.

The Voltage Boost Enabled by Luminescence Extraction in Solar Cells

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

Ganapati, Vidya; Steiner, Myles A.; Yablonovitch, Eli

A new physical principle has emerged to produce record voltages and efficiencies in photovoltaic cells, 'luminescence extraction.' This is exemplified by the mantra 'a good solar cell should also be a good LED.' Luminescence extraction is the escape of internal photons out of the front surface of a solar cell. Basic thermodynamics says that the voltage boost should be related to concentration ratio, C, of a resource by ..delta..V=(kT/q)ln{C}. In light trapping, (i.e. when the solar cell is textured and has a perfect back mirror) the concentration ratio of photons C={4n2}, so one would expect a voltage boost of ..delta..V=kTmore » ln{4n2} over a solar cell with no texture and zero back reflectivity, where n is the refractive index. Nevertheless, there has been ambiguity over the voltage benefit to be expected from perfect luminescence extraction. Do we gain an open circuit voltage boost of ..delta..V=(kT/q)ln{n2}, ..delta..V=(kT/q)ln{2n2}, or ..delta..V=(kT/q)ln{4n2}? What is responsible for this voltage ambiguity ..delta..V=(kT/q)ln{4}=36mVolts? We show that different results come about, depending on whether the photovoltaic cell is optically thin or thick to its internal luminescence. In realistic intermediate cases of optical thickness the voltage boost falls in between; ln{n2}q..delta..V/kT)<;ln{4n2}.« less

An ensemble boosting model for predicting transfer to the pediatric intensive care unit.

PubMed

Rubin, Jonathan; Potes, Cristhian; Xu-Wilson, Minnan; Dong, Junzi; Rahman, Asif; Nguyen, Hiep; Moromisato, David

2018-04-01

Early deterioration indicators have the potential to alert hospital care staff in advance of adverse events, such as patients requiring an increased level of care, or the need for rapid response teams to be called. Our work focuses on the problem of predicting the transfer of pediatric patients from the general ward of a hospital to the pediatric intensive care unit. The development of a data-driven pediatric early deterioration indicator for use by clinicians with the purpose of predicting encounters where transfer from the general ward to the PICU is likely. Using data collected over 5.5 years from the electronic health records of two medical facilities, we develop machine learning classifiers based on adaptive boosting and gradient tree boosting. We further combine these learned classifiers into an ensemble model and compare its performance to a modified pediatric early warning score (PEWS) baseline that relies on expert defined guidelines. To gauge model generalizability, we perform an inter-facility evaluation where we train our algorithm on data from one facility and perform evaluation on a hidden test dataset from a separate facility. We show that improvements are witnessed over the modified PEWS baseline in accuracy (0.77 vs. 0.69), sensitivity (0.80 vs. 0.68), specificity (0.74 vs. 0.70) and AUROC (0.85 vs. 0.73). Data-driven, machine learning algorithms can improve PICU transfer prediction accuracy compared to expertly defined systems, such as a modified PEWS, but care must be taken in the training of such approaches to avoid inadvertently introducing bias into the outcomes of these systems. Copyright © 2018 Elsevier B.V. All rights reserved.

The effects of working memory resource depletion and training on sensorimotor adaptation

PubMed Central

Anguera, Joaquin A.; Bernard, Jessica A.; Jaeggi, Susanne M.; Buschkuehl, Martin; Benson, Bryan L.; Jennett, Sarah; Humfleet, Jennifer; Reuter-Lorenz, Patricia; Jonides, John; Seidler, Rachael D.

2011-01-01

We have recently demonstrated that visuospatial working memory performance predicts the rate of motor skill learning, particularly during the early phase of visuomotor adaptation. Here, we follow up these correlational findings with direct manipulations of working memory resources to determine the impact on visuomotor adaptation, a form of motor learning. We conducted two separate experiments. In the first one, we used a resource depletion strategy to investigate whether the rate of early visuomotor adaptation would be negatively affected by fatigue of spatial working memory resources. In the second study, we employed a dual n-back task training paradigm that has been shown to result in transfer effects [1] over five weeks to determine whether training-related improvements would boost the rate of early visuomotor adaptation. The depletion of spatial working memory resources negatively affected the rate of early visuomotor adaptation. However, enhancing working memory capacity via training did not lead to improved rates of visuomotor adaptation, suggesting that working memory capacity may not be the factor limiting maximal rate of visuomotor adaptation in young adults. These findings are discussed from a resource limitation / capacity framework with respect to current views of motor learning. PMID:22155489

Recombinant BCG prime and PPE protein boost provides potent protection against acute Mycobacterium tuberculosis infection in mice.

PubMed

Yang, Enzhuo; Gu, Jin; Wang, Feifei; Wang, Honghai; Shen, Hongbo; Chen, Zheng W

2016-04-01

Since BCG, the only vaccine widely used against tuberculosis (TB) in the world, provides varied protective efficacy and may not be effective for inducing long-term cellular immunity, it is in an urgent need to develop more effective vaccines and more potent immune strategies against TB. Prime-boost is proven to be a good strategy by inducing long-term protection. In this study, we tested the protective effect against Mycobacterium tuberculosis (Mtb) challenge of prime-boost strategy by recombinant BCG (rBCG) expressing PPE protein Rv3425 fused with Ag85B and Rv3425. Results showed that the prime-boost strategy could significantly increase the protective efficiency against Mtb infection, characterized by reduction of bacterial load in lung and spleen, attenuation of tuberculosis lesions in lung tissues. Importantly, we found that Rv3425 boost, superior to Ag85B boost, provided better protection against Mtb infection. Further research proved that rBCG prime-Rv3425 boost could obviously increase the expansion of lymphocytes, significantly induce IL-2 production by lymphocytes upon PPD stimulation, and inhibit IL-6 production at an early stage. It implied that rBCG prime-Rv3425 boost opted to induce Th1 immune response and provided a long-term protection against TB. These results implicated that rBCG prime-Rv3425 boost is a potent and promising strategy to prevent acute Mtb infection. Copyright © 2016 Elsevier Ltd. All rights reserved.

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012

DOE PAGES

Altheimer, A.; Arce, A.; Asquith, L.; ...

2014-03-21

This report of the BOOST2012 workshop presents the results of four working groups that studied key aspects of jet substructure. We discuss the potential of first-principle QCD calculations to yield a precise description of the substructure of jets and study the accuracy of state-of-the-art Monte Carlo tools. Limitations of the experiments’ ability to resolve substructure are evaluated, with a focus on the impact of additional (pile-up) proton proton collisions on jet substructure performance in future LHC operating scenarios. The final section summarizes the lessons learnt from jet substructure analyses in searches for new physics in the production of boosted topmore » quarks.« less

Boosted performance of a compression-ignition engine with a displaced piston

NASA Technical Reports Server (NTRS)

Moore, Charles S; Foster, Hampton H

1936-01-01

Performance tests were made using a rectangular displacer arranged so that the combustion air was forced through equal passages at either end of the displacer into the vertical-disk combustion chamber of a single-cylinder, four-stroke-cycle compression-ignition test engine. After making tests to determine optimum displacer height, shape, and fuel-spray arrangement, engine-performance tests were made at 1,500 and 2,000 r.p.m. for a range of boost pressures from 0 to 20 inches of mercury and for maximum cylinder pressures up to 1,150 pounds per square inch. The engine operation for boosted conditions was very smooth, there being no combustion shock even at the highest maximum cylinder pressures. Indicated mean effective pressures of 240 pounds per square inch for fuel consumptions of 0.39 pound per horsepower-hour have been readily reproduced during routine testing at 2,000 r.p.m. at a boost pressure of 20 inches of mercury.

Can we predict Acute Medical readmissions using the BOOST tool? A retrospective case note review.

PubMed

Lee, Geraldine A; Freedman, Daniel; Beddoes, Penelope; Lyness, Emily; Nixon, Imogen; Srivastava, Vivek

2016-01-01

Readmissions within 30-days of hospital discharge are a problem. The aim was to determine if the Better Outcomes for Older Adults through Safe Transitions (BOOST) risk assessment tool was applicable within the UK. Patients over 65 readmitted were identified retrospectively via a casenote review. BOOST assessment was applied with 1 point for each risk factor. 324 patients were readmitted (mean age 77 years) with a median of 7 days between discharge and readmission. The median BOOST score was 3 (IQR 2-4) with polypharmacy evident in 88% and prior hospitalisation in 70%. The tool correctly predicted 90% of readmissions using two or more risk factors and 99.1% if one risk factor was included. The BOOST assessment tool appears appropriate in predicting readmissions however further analysis is required to determine its precision.

Detecting boosted dark matter from the Sun with large volume neutrino detectors

NASA Astrophysics Data System (ADS)

Berger, Joshua; Cui, Yanou; Zhao, Yue

2015-02-01

We study novel scenarios where thermal dark matter (DM) can be efficiently captured in the Sun and annihilate into boosted dark matter. In models with semi-annihilating DM, where DM has a non-minimal stabilization symmetry, or in models with a multi-component DM sector, annihilations of DM can give rise to stable dark sector particles with moderate Lorentz boosts. We investigate both of these possibilities, presenting concrete models as proofs of concept. Both scenarios can yield viable thermal relic DM with masses O(1)-O(100) GeV. Taking advantage of the energetic proton recoils that arise when the boosted DM scatters off matter, we propose a detection strategy which uses large volume terrestrial detectors, such as those designed to detect neutrinos or proton decays. In particular, we propose a search for proton tracks pointing towards the Sun. We focus on signals at Cherenkov-radiation-based detectors such as Super-Kamiokande (SK) and its upgrade Hyper-Kamiokande (HK). We find that with spin-dependent scattering as the dominant DM-nucleus interaction at low energies, boosted DM can leave detectable signals at SK or HK, with sensitivity comparable to DM direct detection experiments while being consistent with current constraints. Our study provides a new search path for DM sectors with non-minimal structure.

Radiobiological and treatment planning study of a simultaneously integrated boost for canine nasal tumors using helical tomotherapy.

PubMed

Gutíerrez, Alonso N; Deveau, Michael; Forrest, Lisa J; Tomé, Wolfgang A; Mackie, Thomas R

2007-01-01

Feasibility of delivering a simultaneously integrated boost to canine nasal tumors using helical tomotherapy to improve tumor control probability (TCP) via an increase in total biological equivalent uniform dose (EUD) was evaluated. Eight dogs with varying size nasal tumors (5.8-110.9 cc) were replanned to 42 Gy to the nasal cavity and integrated dose boosts to gross disease of 45.2, 48.3, and 51.3 Gy in 10 fractions. EUD values were calculated for tumors and mean normalized total doses (NTD(mean)) for organs at risk (OAR). Normal Tissue Complication Probability (NTCP) values were obtained for OARs, and estimated TCP values were computed using a logistic dose-response model and based on deliverable EUD boost doses. Significant increases in estimated TCP to 54%, 74%, and 86% can be achieved with 10%, 23%, and 37% mean relative EUD boosts to the gross disease, respectively. NTCP values for blindness of either eye and for brain necrosis were < 0.01% for all boosts. Values for cataract development were 31%, 42%, and 46% for studied boost schemas, respectively. Average NTD(mean) to eyes and brain for mean EUD boosts were 10.2, 11.3, and 12.1 Gy3, and 7.5, 7.2, and 7.9 Gy2, respectively. Using helical tomotherapy, simultaneously integrated dose boosts can be delivered to increase the estimated TCP at 1-year without significantly increasing the NTD(mean) to eyes and brain. Delivery of these treatments in a prospective trial may allow quantification of a dose-response relationship in canine nasal tumors.

Cost-effectiveness assessment of lumpectomy cavity boost in elderly women with early stage estrogen receptor positive breast cancer receiving adjuvant radiotherapy.

PubMed

Lester-Coll, Nataniel H; Rutter, Charles E; Evans, Suzanne B

2016-04-01

Breast radiotherapy (RT) for elderly women with estrogen receptor positive early stage breast cancer (ER+ESBC) improves local recurrence (LR) rates without benefitting overall survival. Breast boost is a common practice, although the absolute benefit decreases with age. Consequently, an analysis of its cost-effectiveness in the elderly ESBC populations is warranted. A Markov model was used to compare cost-effectiveness of RT with or without a boost in elderly ER+ESBC patients. The ten-year probability of LR with boost was derived from the CALGB 9343 trial and adjusted by the hazard ratio for LR from boost radiotherapy trial data, yielding the LR rate without boost. Remaining parameters were estimated using published data. Boost RT was associated with an increase in mean cost ($7139 vs $6193) and effectiveness (5.66 vs 5.64 quality adjusted life years; QALYs) relative to no boost. The incremental cost-effectiveness ratio (ICER) for boost was $55,903 per QALY. On one-way sensitivity analysis, boost remained cost-effective if the hazard ratio of LR with boost was <0.67. Boost RT for ER+ESBC patients was cost-effective over a wide range of assumptions and inputs over commonly accepted willingness-to pay-thresholds, but particularly in women at higher risk for LR. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Spacecraft boost and abort guidance and control systems requirement study, boost dynamics and control analysis study. Exhibit A: Boost dynamics and control anlaysis

NASA Technical Reports Server (NTRS)

Williams, F. E.; Price, J. B.; Lemon, R. S.

1972-01-01

The simulation developments for use in dynamics and control analysis during boost from liftoff to orbit insertion are reported. Also included are wind response studies of the NR-GD 161B/B9T delta wing booster/delta wing orbiter configuration, the MSC 036B/280 inch solid rocket motor configuration, the MSC 040A/L0X-propane liquid injection TVC configuration, the MSC 040C/dual solid rocket motor configuration, and the MSC 049/solid rocket motor configuration. All of the latest math models (rigid and flexible body) developed for the MSC/GD Space Shuttle Functional Simulator, are included.

High Temperature Boost (HTB) Power Processing Unit (PPU) Formulation Study

NASA Technical Reports Server (NTRS)

Chen, Yuan; Bradley, Arthur T.; Iannello, Christopher J.; Carr, Gregory A.; Mohammad, Mojarradi M.; Hunter, Don J.; DelCastillo, Linda; Stell, Christopher B.

2013-01-01

This technical memorandum is to summarize the Formulation Study conducted during fiscal year 2012 on the High Temperature Boost (HTB) Power Processing Unit (PPU). The effort is authorized and supported by the Game Changing Technology Division, NASA Office of the Chief Technologist. NASA center participation during the formulation includes LaRC, KSC and JPL. The Formulation Study continues into fiscal year 2013. The formulation study has focused on the power processing unit. The team has proposed a modular, power scalable, and new technology enabled High Temperature Boost (HTB) PPU, which has 5-10X improvement in PPU specific power/mass and over 30% in-space solar electric system mass saving.

Dosimetric evaluation of simultaneous integrated boost during stereotactic body radiation therapy for pancreatic cancer

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

Yang, Wensha, E-mail: wensha.yang@cshs.org; Reznik, Robert; Fraass, Benedick A.

Stereotactic body radiation therapy (SBRT) provides a promising way to treat locally advanced pancreatic cancer and borderline resectable pancreatic cancer. A simultaneous integrated boost (SIB) to the region of vessel abutment or encasement during SBRT has the potential to downstage otherwise likely positive surgical margins. Despite the potential benefit of using SIB-SBRT, the ability to boost is limited by the local geometry of the organs at risk (OARs), such as stomach, duodenum, and bowel (SDB), relative to tumor. In this study, we have retrospectively replanned 20 patients with 25 Gy prescribed to the planning target volume (PTV) and 33~80 Gymore » to the boost target volume (BTV) using an SIB technique for all patients. The number of plans and patients able to satisfy a set of clinically established constraints is analyzed. The ability to boost vessels (within the gross target volume [GTV]) is shown to correlate with the overlap volume (OLV), defined to be the overlap between the GTV + a 1(OLV1)- or 2(OLV2)-cm margin with the union of SDB. Integral dose, boost dose contrast (BDC), biologically effective BDC, tumor control probability for BTV, and normal tissue complication probabilities are used to analyze the dosimetric results. More than 65% of the cases can deliver a boost to 40 Gy while satisfying all OAR constraints. An OLV2 of 100 cm{sup 3} is identified as the cutoff volume: for cases with OLV2 larger than 100 cm{sup 3}, it is very unlikely the case could achieve 25 Gy to the PTV while successfully meeting all the OAR constraints.« less

Dosimetric evaluation of simultaneous integrated boost during stereotactic body radiation therapy for pancreatic cancer.

PubMed

Yang, Wensha; Reznik, Robert; Fraass, Benedick A; Nissen, Nicholas; Hendifar, Andrew; Wachsman, Ashley; Sandler, Howard; Tuli, Richard

2015-01-01

Stereotactic body radiation therapy (SBRT) provides a promising way to treat locally advanced pancreatic cancer and borderline resectable pancreatic cancer. A simultaneous integrated boost (SIB) to the region of vessel abutment or encasement during SBRT has the potential to downstage otherwise likely positive surgical margins. Despite the potential benefit of using SIB-SBRT, the ability to boost is limited by the local geometry of the organs at risk (OARs), such as stomach, duodenum, and bowel (SDB), relative to tumor. In this study, we have retrospectively replanned 20 patients with 25Gy prescribed to the planning target volume (PTV) and 33~80Gy to the boost target volume (BTV) using an SIB technique for all patients. The number of plans and patients able to satisfy a set of clinically established constraints is analyzed. The ability to boost vessels (within the gross target volume [GTV]) is shown to correlate with the overlap volume (OLV), defined to be the overlap between the GTV + a 1(OLV1)- or 2(OLV2)-cm margin with the union of SDB. Integral dose, boost dose contrast (BDC), biologically effective BDC, tumor control probability for BTV, and normal tissue complication probabilities are used to analyze the dosimetric results. More than 65% of the cases can deliver a boost to 40Gy while satisfying all OAR constraints. An OLV2 of 100cm(3) is identified as the cutoff volume: for cases with OLV2 larger than 100cm(3), it is very unlikely the case could achieve 25Gy to the PTV while successfully meeting all the OAR constraints. Copyright © 2015 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

New Solar Cells to Boost Satellite Power

Science.gov Websites

New Solar Cells to Boost Satellite Power For more information contact: George Douglas (303) 275 much as doubled, each satellite and its services can be more economical and offer a greater return to satellite customers. The new cells will also have a longer useful life. Because of their construction they

The Attentional Boost Effect and Context Memory

ERIC Educational Resources Information Center

Mulligan, Neil W.; Smith, S. Adam; Spataro, Pietro

2016-01-01

Stimuli co-occurring with targets in a detection task are better remembered than stimuli co-occurring with distractors--the attentional boost effect (ABE). The ABE is of interest because it is an exception to the usual finding that divided attention during encoding impairs memory. The effect has been demonstrated in tests of item memory but it is…

L2-Boosting algorithm applied to high-dimensional problems in genomic selection.

PubMed

González-Recio, Oscar; Weigel, Kent A; Gianola, Daniel; Naya, Hugo; Rosa, Guilherme J M

2010-06-01

The L(2)-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm in a genomic selection context to make predictions of yet to be observed outcomes. Two data sets were used: (1) productive lifetime predicted transmitting abilities from 4702 Holstein sires genotyped for 32 611 single nucleotide polymorphisms (SNPs) derived from the Illumina BovineSNP50 BeadChip, and (2) progeny averages of food conversion rate, pre-corrected by environmental and mate effects, in 394 broilers genotyped for 3481 SNPs. Each of these data sets was split into training and testing sets, the latter comprising dairy or broiler sires whose ancestors were in the training set. Two weak learners, ordinary least squares (OLS) and non-parametric (NP) regression were used for the L2-Boosting algorithm, to provide a stringent evaluation of the procedure. This algorithm was compared with BL [Bayesian LASSO (least absolute shrinkage and selection operator)] and BayesA regression. Learning tasks were carried out in the training set, whereas validation of the models was performed in the testing set. Pearson correlations between predicted and observed responses in the dairy cattle (broiler) data set were 0.65 (0.33), 0.53 (0.37), 0.66 (0.26) and 0.63 (0.27) for OLS-Boosting, NP-Boosting, BL and BayesA, respectively. The smallest bias and mean-squared errors (MSEs) were obtained with OLS-Boosting in both the dairy cattle (0.08 and 1.08, respectively) and broiler (-0.011 and 0.006) data sets, respectively. In the dairy cattle data set, the BL was more accurate (bias=0.10 and MSE=1.10) than BayesA (bias=1.26 and MSE=2.81), whereas no differences between these two methods were found in the broiler data set. L2-Boosting with a suitable learner was found to be a competitive

WE-G-BRD-08: Motion Analysis for Rectal Cancer: Implications for Adaptive Radiotherapy On the MR-Linac

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

Kleijnen, J; Asselen, B van; Burbach, M

2015-06-15

Purpose: Purpose of this study is to find the optimal trade-off between adaptation interval and margin reduction and to define the implications of motion for rectal cancer boost radiotherapy on a MR-linac. Methods: Daily MRI scans were acquired of 16 patients, diagnosed with rectal cancer, prior to each radiotherapy fraction in one week (N=76). Each scan session consisted of T2-weighted and three 2D sagittal cine-MRI, at begin (t=0 min), middle (t=9:30 min) and end (t=18:00 min) of scan session, for 1 minute at 2 Hz temporal resolution. Tumor and clinical target volume (CTV) were delineated on each T2-weighted scan andmore » transferred to each cine-MRI. The start frame of the begin scan was used as reference and registered to frames at time-points 15, 30 and 60 seconds, 9:30 and 18:00 minutes and 1, 2, 3 and 4 days later. Per time-point, motion of delineated voxels was evaluated using the deformation vector fields of the registrations and the 95th percentile distance (dist95%) was calculated as measure of motion. Per time-point, the distance that includes 90% of all cases was taken as estimate of required planning target volume (PTV)-margin. Results: Highest motion reduction is observed going from 9:30 minutes to 60 seconds. We observe a reduction in margin estimates from 10.6 to 2.7 mm and 16.1 to 4.6 mm for tumor and CTV, respectively, when adapting every 60 seconds compared to not adapting treatment. A 75% and 71% reduction, respectively. Further reduction in adaptation time-interval yields only marginal motion reduction. For adaptation intervals longer than 18:00 minutes only small motion reductions are observed. Conclusion: The optimal adaptation interval for adaptive rectal cancer (boost) treatments on a MR-linac is 60 seconds. This results in substantial smaller PTV-margin estimates. Adaptation intervals of 18:00 minutes and higher, show little improvement in motion reduction.« less

Awards to Boost Research into Cheaper Solar Electricity

Science.gov Websites

Awards to Boost Research into Cheaper Solar Electricity For more information contact: George thin-film photovoltaic cells. Photovoltaics (solar cells) generate electricity directly from sunlight cut the cost of solar electricity," said Energy Secretary Spencer Abraham. "With lowered

Verification of charge sign for high-energy particles measured by magnetic tracking system of PAMELA spectrometer

NASA Astrophysics Data System (ADS)

Lukyanov, A. D.; Alekseev, V. V.; Bogomolov, Yu V.; Dunaeva, O. A.; Malakhov, V. V.; Mayorov, A. G.; Rodenko, S. A.

2017-01-01

Analysis of experimental data of primary positrons and antiprotons fluxes obtained by PAMELA spectrometer, recently confirmed by AMS-02 spectrometer, for some reasons is of big interest for scientific community, especially for energies higher than 100 GV, where appearance of signal coming from dark matter particles is possible. In this work we present a method for verification of charge sign for high-energy antiprotons, measured by magnetic tracking system of PAMELA spectrometer, which can be immitated by protons due to scattering or finite instrumental resolution at high energies (so-called “spillover”). We base our approach on developing2 a set of distinctive features represented by differently computed rigidities and training AdaBoost classifier, which shows good classification accuracy on Monte-Carlo simulation data of 98% for rigidity up to 600 GV.

Multiresolution texture models for brain tumor segmentation in MRI.

PubMed

Iftekharuddin, Khan M; Ahmed, Shaheen; Hossen, Jakir

2011-01-01

In this study we discuss different types of texture features such as Fractal Dimension (FD) and Multifractional Brownian Motion (mBm) for estimating random structures and varying appearance of brain tissues and tumors in magnetic resonance images (MRI). We use different selection techniques including KullBack - Leibler Divergence (KLD) for ranking different texture and intensity features. We then exploit graph cut, self organizing maps (SOM) and expectation maximization (EM) techniques to fuse selected features for brain tumors segmentation in multimodality T1, T2, and FLAIR MRI. We use different similarity metrics to evaluate quality and robustness of these selected features for tumor segmentation in MRI for real pediatric patients. We also demonstrate a non-patient-specific automated tumor prediction scheme by using improved AdaBoost classification based on these image features.

Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

PubMed Central

Bleris, Leonidas; Xie, Zhen; Glass, David; Adadey, Asa; Sontag, Eduardo; Benenson, Yaakov

2011-01-01

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network-coding genes. Gene product levels could potentially be decoupled from these changes via built-in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post-transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post-transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability. PMID:21811230

How do associative and phonemic overlap interact to boost illusory recollection?

PubMed

Hutchison, Keith A; Meade, Michelle L; Williams, Nikolas S; Manley, Krista D; McNabb, Jaimie C

2018-05-01

This project investigated the underlying mechanisms that boost false remember responses when participants receive study words that are both semantically and phonologically similar to a critical lure. Participants completed a memory task in which they were presented with a list of words all associated with a critical lure. Included within the list of semantic associates was a target that was either semantically associated (e.g., yawn) to the critical lure (e.g., sleep) or shared the initial (e.g., slam) or final (e.g., beep) phoneme(s) with the critical lure. After hearing the list, participants recalled each list item and indicated whether they just knew it was on the list or if they instead recollected specific contextual details of that item's presentation. We found that inserting an initial phonemic overlap target boosted experiences of recollection, but only when semantically related associates were presented beforehand. The results are consistent with models of spoken word recognition and show that established semantic context plus initial phonemic overlap play important roles in boosting false recollection.

DIRBoost-an algorithm for boosting deformable image registration: application to lung CT intra-subject registration.

PubMed

Muenzing, Sascha E A; van Ginneken, Bram; Viergever, Max A; Pluim, Josien P W

2014-04-01

We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. Copyright © 2014 Elsevier B.V. All rights reserved.

Detecting boosted dark matter from the Sun with large volume neutrino detectors

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

Berger, Joshua; Cui, Yanou; Zhao, Yue, E-mail: jberger@slac.stanford.edu, E-mail: ycui@perimeterinstitute.ca, E-mail: zhaoyue@stanford.edu

2015-02-01

We study novel scenarios where thermal dark matter (DM) can be efficiently captured in the Sun and annihilate into boosted dark matter. In models with semi-annihilating DM, where DM has a non-minimal stabilization symmetry, or in models with a multi-component DM sector, annihilations of DM can give rise to stable dark sector particles with moderate Lorentz boosts. We investigate both of these possibilities, presenting concrete models as proofs of concept. Both scenarios can yield viable thermal relic DM with masses O(1)-O(100) GeV. Taking advantage of the energetic proton recoils that arise when the boosted DM scatters off matter, we proposemore » a detection strategy which uses large volume terrestrial detectors, such as those designed to detect neutrinos or proton decays. In particular, we propose a search for proton tracks pointing towards the Sun. We focus on signals at Cherenkov-radiation-based detectors such as Super-Kamiokande (SK) and its upgrade Hyper-Kamiokande (HK). We find that with spin-dependent scattering as the dominant DM-nucleus interaction at low energies, boosted DM can leave detectable signals at SK or HK, with sensitivity comparable to DM direct detection experiments while being consistent with current constraints. Our study provides a new search path for DM sectors with non-minimal structure.« less

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

The Voltage Boost Enabled by Luminescence Extraction in Solar Cells

DOE PAGES

Ganapati, Vidya; Steiner, Myles A.; Yablonovitch, Eli

2016-07-01

Over the past few years, the application of the physical principle, i.e., 'luminescence extraction,' has produced record voltages and efficiencies in photovoltaic cells. Luminescence extraction is the use of optical design, such as a back mirror or textured surfaces, to help internal photons escape out of the front surface of a solar cell. The principle of luminescence extraction is exemplified by the mantra 'a good solar cell should also be a good LED.' Basic thermodynamics says that the voltage boost should be related to concentration ratio C of a resource by ΔV = (kT/q) ln{C}. In light trapping (i.e., when the solar cell is textured and has a perfect back mirror), the concentration ratio of photons C = {4n 2}; therefore, one would expect a voltage boost of ΔV = (kT/q) ln{4n 2} over a solar cell with no texture and zero back reflectivity, where n is the refractive index. Nevertheless, there has been ambiguity over the voltage benefit to be expected from perfect luminescence extraction. Do we gain an open-circuit voltage boost of ΔV = (kT/q) ln{n 2}, ΔV = (kT/q) ln{2 n 2}, or ΔV = (kT/q) ln{4 n 2}? What is responsible for this voltage ambiguity ΔV = (kT/q) ln{4}more » $${\\asymp}$$ 36 mV? Finally, we show that different results come about, depending on whether the photovoltaic cell is optically thin or thick to its internal luminescence. In realistic intermediate cases of optical thickness, the voltage boost falls in between: ln{n 2} < (qΔV/kT) < ln{4n 2}.« less

The Voltage Boost Enabled by Luminescence Extraction in Solar Cells

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

Ganapati, Vidya; Steiner, Myles A.; Yablonovitch, Eli

Over the past few years, the application of the physical principle, i.e., 'luminescence extraction,' has produced record voltages and efficiencies in photovoltaic cells. Luminescence extraction is the use of optical design, such as a back mirror or textured surfaces, to help internal photons escape out of the front surface of a solar cell. The principle of luminescence extraction is exemplified by the mantra 'a good solar cell should also be a good LED.' Basic thermodynamics says that the voltage boost should be related to concentration ratio C of a resource by ΔV = (kT/q) ln{C}. In light trapping (i.e., when the solar cell is textured and has a perfect back mirror), the concentration ratio of photons C = {4n 2}; therefore, one would expect a voltage boost of ΔV = (kT/q) ln{4n 2} over a solar cell with no texture and zero back reflectivity, where n is the refractive index. Nevertheless, there has been ambiguity over the voltage benefit to be expected from perfect luminescence extraction. Do we gain an open-circuit voltage boost of ΔV = (kT/q) ln{n 2}, ΔV = (kT/q) ln{2 n 2}, or ΔV = (kT/q) ln{4 n 2}? What is responsible for this voltage ambiguity ΔV = (kT/q) ln{4}more » $${\\asymp}$$ 36 mV? Finally, we show that different results come about, depending on whether the photovoltaic cell is optically thin or thick to its internal luminescence. In realistic intermediate cases of optical thickness, the voltage boost falls in between: ln{n 2} < (qΔV/kT) < ln{4n 2}.« less

Detection of chewing from piezoelectric film sensor signals using ensemble classifiers.

PubMed

Farooq, Muhammad; Sazonov, Edward

2016-08-01

Selection and use of pattern recognition algorithms is application dependent. In this work, we explored the use of several ensembles of weak classifiers to classify signals captured from a wearable sensor system to detect food intake based on chewing. Three sensor signals (Piezoelectric sensor, accelerometer, and hand to mouth gesture) were collected from 12 subjects in free-living conditions for 24 hrs. Sensor signals were divided into 10 seconds epochs and for each epoch combination of time and frequency domain features were computed. In this work, we present a comparison of three different ensemble techniques: boosting (AdaBoost), bootstrap aggregation (bagging) and stacking, each trained with 3 different weak classifiers (Decision Trees, Linear Discriminant Analysis (LDA) and Logistic Regression). Type of feature normalization used can also impact the classification results. For each ensemble method, three feature normalization techniques: (no-normalization, z-score normalization, and minmax normalization) were tested. A 12 fold cross-validation scheme was used to evaluate the performance of each model where the performance was evaluated in terms of precision, recall, and accuracy. Best results achieved here show an improvement of about 4% over our previous algorithms.

A boosted negative bit-line SRAM with write-assisted cell in 45 nm CMOS technology

NASA Astrophysics Data System (ADS)

Bhatnagar, Vipul; Kumar, Pradeep; Pandey, Neeta; Pandey, Sujata

2018-02-01

A new 11 T SRAM cell with write-assist is proposed to improve operation at low supply voltage. In this technique, a negative bit-line voltage is applied to one of the write bit-lines, while a boosted voltage is applied to the other write bit-line where transmission gate access is used in proposed 11 T cell. Supply voltage to one of the inverters is interrupted to weaken the feedback. Improved write feature is attributed to strengthened write access devices and weakened feedback loop of cell at the same time. Amount of boosting required for write performance improvement is also reduced due to feedback weakening, solving the persistent problem of half-selected cells and reliability reduction of access devices with the other suggested boosted and negative bit-line techniques. The proposed design improves write time by 79%, 63% and slower by 52% with respect to LP 10 T, WRE 8 T and 6 T cells respectively. It is found that write margin for the proposed cell is improved by about 4×, 2.4× and 5.37× compared to WRE8 T, LP10 T and 6 T respectively. The proposed cell with boosted negative bit line (BNBL) provides 47%, 31%, and 68.4% improvement in write margin with respect to no write-assist, negative bit line (NBL) and boosted bit line (BBL) write-assist respectively. Also, new sensing circuit with replica bit-line is proposed to give a more precise timing of applying boosted voltages for improved results. All simulations are done on TSMC 45 nm CMOS technology.

Boosting BCG-primed responses with a subunit Apa vaccine during the waning phase improves immunity and imparts protection against Mycobacterium tuberculosis.

PubMed

Nandakumar, Subhadra; Kannanganat, Sunil; Dobos, Karen M; Lucas, Megan; Spencer, John S; Amara, Rama Rao; Plikaytis, Bonnie B; Posey, James E; Sable, Suraj B

2016-05-13

Heterologous prime-boosting has emerged as a powerful vaccination approach against tuberculosis. However, optimal timing to boost BCG-immunity using subunit vaccines remains unclear in clinical trials. Here, we followed the adhesin Apa-specific T-cell responses in BCG-primed mice and investigated its BCG-booster potential. The Apa-specific T-cell response peaked 32-52 weeks after parenteral or mucosal BCG-priming but waned significantly by 78 weeks. A subunit-Apa-boost during the contraction-phase of BCG-response had a greater effect on the magnitude and functional quality of specific cellular and humoral responses compared to a boost at the peak of BCG-response. The cellular response increased following mucosal BCG-prime-Apa-subunit-boost strategy compared to Apa-subunit-prime-BCG-boost approach. However, parenteral BCG-prime-Apa-subunit-boost by a homologous route was the most effective strategy in-terms of enhancing specific T-cell responses during waning in the lung and spleen. Two Apa-boosters markedly improved waning BCG-immunity and significantly reduced Mycobacterium tuberculosis burdens post-challenge. Our results highlight the challenges of optimization of prime-boost regimens in mice where BCG drives persistent immune-activation and suggest that boosting with a heterologous vaccine may be ideal once the specific persisting effector responses are contracted. Our results have important implications for design of prime-boost regimens against tuberculosis in humans.

Boosting BCG-primed responses with a subunit Apa vaccine during the waning phase improves immunity and imparts protection against Mycobacterium tuberculosis

PubMed Central

Nandakumar, Subhadra; Kannanganat, Sunil; Dobos, Karen M.; Lucas, Megan; Spencer, John S.; Amara, Rama Rao; Plikaytis, Bonnie B.; Posey, James E.; Sable, Suraj B.

2016-01-01

Heterologous prime–boosting has emerged as a powerful vaccination approach against tuberculosis. However, optimal timing to boost BCG-immunity using subunit vaccines remains unclear in clinical trials. Here, we followed the adhesin Apa-specific T-cell responses in BCG-primed mice and investigated its BCG-booster potential. The Apa-specific T-cell response peaked 32–52 weeks after parenteral or mucosal BCG-priming but waned significantly by 78 weeks. A subunit-Apa-boost during the contraction-phase of BCG-response had a greater effect on the magnitude and functional quality of specific cellular and humoral responses compared to a boost at the peak of BCG-response. The cellular response increased following mucosal BCG-prime–Apa-subunit-boost strategy compared to Apa-subunit-prime–BCG-boost approach. However, parenteral BCG-prime–Apa-subunit-boost by a homologous route was the most effective strategy in-terms of enhancing specific T-cell responses during waning in the lung and spleen. Two Apa-boosters markedly improved waning BCG-immunity and significantly reduced Mycobacterium tuberculosis burdens post-challenge. Our results highlight the challenges of optimization of prime–boost regimens in mice where BCG drives persistent immune-activation and suggest that boosting with a heterologous vaccine may be ideal once the specific persisting effector responses are contracted. Our results have important implications for design of prime–boost regimens against tuberculosis in humans. PMID:27173443

CMOS single-stage input-powered bridge rectifier with boost switch and duty cycle control

NASA Astrophysics Data System (ADS)

Radzuan, Roskhatijah; Mohd Salleh, Mohd Khairul; Hamzah, Mustafar Kamal; Ab Wahab, Norfishah

2017-06-01

This paper presents a single-stage input-powered bridge rectifier with boost switch for wireless-powered devices such as biomedical implants and wireless sensor nodes. Realised using CMOS process technology, it employs a duty cycle switch control to achieve high output voltage using boost technique, leading to a high output power conversion. It has only six external connections with the boost inductance. The input frequency of the bridge rectifier is set at 50 Hz, while the switching frequency is 100 kHz. The proposed circuit is fabricated on a single 0.18-micron CMOS die with a space area of 0.024 mm2. The simulated and measured results show good agreement.

Boosting fire drill participation in hospital settings.

PubMed

Prosper, Darryl

2015-01-01

In a health system with over 100 sites in a geographically dispersed region, boosting fire drill participation to meet government requirements, according to the author, is a constant effort, both to achieve and to maintain. In this article, he describes a comprehensive approach that entails engagement of executive, site committees and local fire authorities, as well as comprehensive training and awareness campaigns.

Analysis of high voltage step-up nonisolated DC-DC boost converters

NASA Astrophysics Data System (ADS)

Alisson Alencar Freitas, Antônio; Lessa Tofoli, Fernando; Junior, Edilson Mineiro Sá; Daher, Sergio; Antunes, Fernando Luiz Marcelo

2016-05-01

A high voltage step-up nonisolated DC-DC converter based on coupled inductors suitable to photovoltaic (PV) systems applications is proposed in this paper. Considering that numerous approaches exist to extend the voltage conversion ratio of DC-DC converters that do not use transformers, a detailed comparison is also presented among the proposed converter and other popular topologies such as the conventional boost converter and the quadratic boost converter. The qualitative analysis of the coupled-inductor-based topology is developed so that a design procedure can be obtained, from which an experimental prototype is implemented to validate the theoretical assumptions.

Distinguishing Positive Selection From Neutral Evolution: Boosting the Performance of Summary Statistics

PubMed Central

Lin, Kao; Li, Haipeng; Schlötterer, Christian; Futschik, Andreas

2011-01-01

Summary statistics are widely used in population genetics, but they suffer from the drawback that no simple sufficient summary statistic exists, which captures all information required to distinguish different evolutionary hypotheses. Here, we apply boosting, a recent statistical method that combines simple classification rules to maximize their joint predictive performance. We show that our implementation of boosting has a high power to detect selective sweeps. Demographic events, such as bottlenecks, do not result in a large excess of false positives. A comparison to other neutrality tests shows that our boosting implementation performs well compared to other neutrality tests. Furthermore, we evaluated the relative contribution of different summary statistics to the identification of selection and found that for recent sweeps integrated haplotype homozygosity is very informative whereas older sweeps are better detected by Tajima's π. Overall, Watterson's θ was found to contribute the most information for distinguishing between bottlenecks and selection. PMID:21041556

Energy Management of Manned Boost-Glide Vehicles: A Historical Perspective

NASA Technical Reports Server (NTRS)

Day, Richard E.

2004-01-01

As flight progressed from propellers to jets to rockets, the propulsive energy grew exponentially. With the development of rocket-only boosted vehicles, energy management of these boost-gliders became a distinct requirement for the unpowered return to base, alternate landing site, or water-parachute landing, starting with the X-series rocket aircraft and terminating with the present-day Shuttle. The problem presented here consists of: speed (kinetic energy) - altitude (potential energy) - steep glide angles created by low lift-to-drag ratios (L/D) - distance to landing site - and the bothersome effects of the atmospheric characteristics varying with altitude. The primary discussion regards post-boost, stabilized glides; however, the effects of centrifugal and geopotential acceleration are discussed as well. The aircraft and spacecraft discussed here are the X-1, X-2, X-15, and the Shuttle; and to a lesser, comparative extent, Mercury, Gemini, Apollo, and lifting bodies. The footprints, landfalls, and methods developed for energy management are also described. The essential tools required for energy management - simulator planning, instrumentation, radar, telemetry, extended land or water range, Mission Control Center (with specialist controllers), and emergency alternate landing sites - were first established through development of early concepts and were then validated by research flight tests.

Voltage-Boosting Driver For Switching Regulator

NASA Technical Reports Server (NTRS)

Trump, Ronald C.

1990-01-01

Driver circuit assures availability of 10- to 15-V gate-to-source voltage needed to turn on n-channel metal oxide/semiconductor field-effect transistor (MOSFET) acting as switch in switching voltage regulator. Includes voltage-boosting circuit efficiently providing gate voltage 10 to 15 V above supply voltage. Contains no exotic parts and does not require additional power supply. Consists of NAND gate and dual voltage booster operating in conjunction with pulse-width modulator part of regulator.

68Ga-PSMA-PET/CT imaging of localized primary prostate cancer patients for intensity modulated radiation therapy treatment planning with integrated boost.

PubMed

Thomas, Lena; Kantz, Steffi; Hung, Arthur; Monaco, Debra; Gaertner, Florian C; Essler, Markus; Strunk, Holger; Laub, Wolfram; Bundschuh, Ralph A

2018-07-01

The purpose of our study was to show the feasibility and potential benefits of using 68 Ga-PSMA-PET/CT imaging for radiation therapy treatment planning of patients with primary prostate cancer using either integrated boost on the PET-positive volume or localized treatment of the PET-positive volume. The potential gain of such an approach, the improvement of tumor control, and reduction of the dose to organs-at-risk at the same time was analyzed using the QUANTEC biological model. Twenty-one prostate cancer patients (70 years average) without previous local therapy received 68 Ga-PSMA-PET/CT imaging. Organs-at-risk and standard prostate target volumes were manually defined on the obtained datasets. A PET active volume (PTV_PET) was segmented with a 40% of the maximum activity uptake in the lesion as threshold followed by manual adaption. Five different treatment plan variations were calculated for each patient. Analysis of derived treatment plans was done according to QUANTEC with in-house developed software. Tumor control probability (TCP) and normal tissue complication probability (NTCP) was calculated for all plan variations. Comparing the conventional plans to the plans with integrated boost and plans just treating the PET-positive tumor volume, we found that TCP increased to (95.2 ± 0.5%) for an integrated boost with 75.6 Gy, (98.1 ± 0.3%) for an integrated boost with 80 Gy, (94.7 ± 0.8%) for treatment of PET-positive volume with 75 Gy, and to (99.4 ± 0.1%) for treating PET-positive volume with 95 Gy (all p < 0.0001). For the integrated boost with 80 Gy, a significant increase of the median NTCP of the rectum was found, for all other plans no statistical significant increase in the NTCP neither of the rectum nor the bladder was found. Our study demonstrates that the use of 68 Ga-PSMA-PET/CT image information allows for more individualized prostate treatment planning. TCP values of identified active tumor volumes were increased, while

Serum Cytokine Profiles Associated with Specific Adjuvants Used in a DNA Prime-Protein Boost Vaccination Strategy

PubMed Central

Buglione-Corbett, Rachel; Pouliot, Kimberly; Marty-Roix, Robyn; West, Kim; Wang, Shixia; Lien, Egil; Lu, Shan

2013-01-01

In recent years, heterologous prime-boost vaccines have been demonstrated to be an effective strategy for generating protective immunity, consisting of both humoral and cell-mediated immune responses against a variety of pathogens including HIV-1. Previous reports of preclinical and clinical studies have shown the enhanced immunogenicity of viral vector or DNA vaccination followed by heterologous protein boost, compared to using either prime or boost components alone. With such approaches, the selection of an adjuvant for inclusion in the protein boost component is expected to impact the immunogenicity and safety of a vaccine. In this study, we examined in a mouse model the serum cytokine and chemokine profiles for several candidate adjuvants: QS-21, Al(OH)3, monophosphoryl lipid A (MPLA) and ISCOMATRIX™ adjuvant, in the context of a previously tested pentavalent HIV-1 Env DNA prime-protein boost formulation, DP6-001. Our data revealed that the candidate adjuvants in the context of the DP6-001 formulation are characterized by unique serum cytokine and chemokine profiles. Such information will provide valuable guidance in the selection of an adjuvant for future AIDS vaccine development, with the ultimate goal of enhancing immunogenicity while minimizing reactogenicity associated with the use of an adjuvant. More significantly, results reported here will add to the knowledge on how to include an adjuvant in the context of a heterologous prime-protein boost vaccination strategy in general. PMID:24019983

Culture First: Boosting Program Strength through Cultural Instruction

ERIC Educational Resources Information Center

Windham, Scott

2017-01-01

In recent years, cultural instruction has been touted as a way to help foreign language programs boost student learning outcomes, enrollments, and many other measures of program strength. In order to investigate the relationship between cultural instruction and program strength in a university-level German program, students in first- and…

Series-Connected Buck Boost Regulators

NASA Technical Reports Server (NTRS)

Birchenough, Arthur G.

2005-01-01

A series-connected buck boost regulator (SCBBR) is an electronic circuit that bucks a power-supply voltage to a lower regulated value or boosts it to a higher regulated value. The concept of the SCBBR is a generalization of the concept of the SCBR, which was reported in "Series-Connected Boost Regulators" (LEW-15918), NASA Tech Briefs, Vol. 23, No. 7 (July 1997), page 42. Relative to prior DC-voltage-regulator concepts, the SCBBR concept can yield significant reductions in weight and increases in power-conversion efficiency in many applications in which input/output voltage ratios are relatively small and isolation is not required, as solar-array regulation or battery charging with DC-bus regulation. Usually, a DC voltage regulator is designed to include a DC-to-DC converter to reduce its power loss, size, and weight. Advances in components, increases in operating frequencies, and improved circuit topologies have led to continual increases in efficiency and/or decreases in the sizes and weights of DC voltage regulators. The primary source of inefficiency in the DC-to-DC converter portion of a voltage regulator is the conduction loss and, especially at high frequencies, the switching loss. Although improved components and topology can reduce the switching loss, the reduction is limited by the fact that the converter generally switches all the power being regulated. Like the SCBR concept, the SCBBR concept involves a circuit configuration in which only a fraction of the power is switched, so that the switching loss is reduced by an amount that is largely independent of the specific components and circuit topology used. In an SCBBR, the amount of power switched by the DC-to-DC converter is only the amount needed to make up the difference between the input and output bus voltage. The remaining majority of the power passes through the converter without being switched. The weight and power loss of a DC-to-DC converter are determined primarily by the amount of power

Lorentz boosted frame simulation technique in Particle-in-cell methods

NASA Astrophysics Data System (ADS)

Yu, Peicheng

In this dissertation, we systematically explore the use of a simulation method for modeling laser wakefield acceleration (LWFA) using the particle-in-cell (PIC) method, called the Lorentz boosted frame technique. In the lab frame the plasma length is typically four orders of magnitude larger than the laser pulse length. Using this technique, simulations are performed in a Lorentz boosted frame in which the plasma length, which is Lorentz contracted, and the laser length, which is Lorentz expanded, are now comparable. This technique has the potential to reduce the computational needs of a LWFA simulation by more than four orders of magnitude, and is useful if there is no or negligible reflection of the laser in the lab frame. To realize the potential of Lorentz boosted frame simulations for LWFA, the first obstacle to overcome is a robust and violent numerical instability, called the Numerical Cerenkov Instability (NCI), that leads to unphysical energy exchange between relativistically drifting particles and their radiation. This leads to unphysical noise that dwarfs the real physical processes. In this dissertation, we first present a theoretical analysis of this instability, and show that the NCI comes from the unphysical coupling of the electromagnetic (EM) modes and Langmuir modes (both main and aliasing) of the relativistically drifting plasma. We then discuss the methods to eliminate them. However, the use of FFTs can lead to parallel scalability issues when there are many more cells along the drifting direction than in the transverse direction(s). We then describe an algorithm that has the potential to address this issue by using a higher order finite difference operator for the derivative in the plasma drifting direction, while using the standard second order operators in the transverse direction(s). The NCI for this algorithm is analyzed, and it is shown that the NCI can be eliminated using the same strategies that were used for the hybrid FFT

External beam boost versus interstitial high-dose-rate brachytherapy boost in the adjuvant radiotherapy following breast-conserving therapy in early-stage breast cancer: a dosimetric comparison

PubMed Central

Melchert, Corinna; Kovács, György

2016-01-01

Purpose This study aims to compare the dosimetric data of local tumor's bed dose escalation (boost) with photon beams (external beam radiation therapy – EBRT) versus high-dose-rate interstitial brachytherapy (HDR-BT) after breast-conserving treatment in women with early-stage breast cancer. Material and methods We analyzed the treatment planning data of 136 irradiated patients, treated between 2006 and 2013, who underwent breast-conserving surgery and adjuvant whole breast irradiation (WBI; 50.4 Gy) and boost (HDR-BT: 10 Gy in one fraction [n = 36]; EBRT: 10 Gy in five fractions [n = 100]). Organs at risk (OAR; heart, ipsilateral lung, skin, most exposed rib segment) were delineated. Dosimetric parameters were calculated with the aid of dose-volume histograms (DVH). A non-parametric test was performed to compare the two different boost forms. Results There was no difference for left-sided cancers regarding the maximum dose to the heart (HDR-BT 29.8% vs. EBRT 29.95%, p = 0.34). The maximum doses to the other OAR were significantly lower for HDR-BT (Dmax lung 47.12% vs. 87.7%, p < 0.01; rib 61.17% vs. 98.5%, p < 0.01; skin 57.1% vs. 94.75%, p < 0.01; in the case of right-sided breast irradiation, dose of the heart 6.00% vs. 16.75%, p < 0.01). Conclusions Compared to EBRT, local dose escalation with HDR-BT presented a significant dose reduction to the investigated OAR. Only left-sided irradiation showed no difference regarding the maximum dose to the heart. Reducing irradiation exposure to OAR could result in a reduction of long-term side effects. Therefore, from a dosimetric point of view, an interstitial boost complementary to WBI via EBRT seems to be more advantageous in the adjuvant radiotherapy of breast cancer. PMID:27648082

Boost Irradiation Integrated to Whole Brain Radiotherapy in the Management of Brain Metastases.

PubMed

Dobi, Ágnes; Fodor, Emese; Maráz, Anikó; Együd, Zsófia; Cserháti, Adrienne; Tiszlavicz, László; Reisz, Zita; Barzó, Pál; Varga, Zoltán; Hideghéty, Katalin

2018-01-17

Our retrospective analysis aimed to evaluate the clinical value of dose intensification schemes: WBRT and consecutive, delayed, or simultaneous integrated boost (SIB) in brain metastasis (BM) management. Clinical data and overall survival (OS) of 468 patients with BM from various primaries treated with 10 × 3 Gy WBRT (n = 195), WBRT+ 10 × 2 Gy boost (n = 125), or simultaneously 15 × 2.2 Gy WBRT+0.7 Gy boost (n = 148) during a 6-year period were statistically analysed. Significant difference in OS could be detected with additional boost to WBRT (3.3 versus 6.5 months) and this difference was confirmed for BMs of lung cancer and melanoma and both for oligo- and multiplex lesions. The OS was prolonged for the RPA 2 and RPA3 categories, if patients received escalated dose, 4.0 vs. 7.7 months; (p = 0.002) in class RPA2 and 2.6 vs. 4.2 months; (p < 0.0001) in the class RPA 3 respectively. The significant difference in OS was also achieved with SIB. The shortened overall treatment time of SIB with lower WBRT fraction dose exhibited survival benefit over WBRT alone, and could be applied for patients developing BM even with unfavourable prognostic factors. These results warrant for further study of this approach with dose escalation using the lately available solutions for hippocampus sparing and fractionated stereotactic irradiation. The simultaneous delivery of WBRT with reduced fraction dose and boost proved to be advantageous prolonging the OS with shortened treatment time and reduced probability for cognitive decline development even for patients with poor performance status and progressing extracranial disease.

Characterizing boosted dijet resonances with energy correlation functions

NASA Astrophysics Data System (ADS)

Chivukula, R. Sekhar; Mohan, Kirtimaan A.; Sengupta, Dipan; Simmons, Elizabeth H.

2018-03-01

Jet Energy Correlation Variables are powerful tools to study jet physics at LHC. We show that a class of such variables, known as Energy Correlation Functions can be used effectively to discover and distinguish a wide variety of boosted light dijet resonances at the LHC through sensitivity to their transverse momentum and color structures.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

A cosmetic evaluation of breast cancer treatment: A randomized study of radiotherapy boost technique

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

Vass, Sylvie; Bairati, Isabelle

2005-08-01

Purpose: To compare cosmetic results of two different radiotherapy (RT) boost techniques used in the treatment of breast cancer after whole breast radiotherapy and to identify factors affecting cosmetic outcomes. Methods and Materials: Between 1996 and 1998, 142 patients with Stage I and II breast cancer were treated with breast conservative surgery and adjuvant RT. Patients were then randomly assigned to receive a boost dose of 15 Gy delivered to the tumor bed either by iridium 192, or a combination of photons and electrons. Cosmetic evaluations were done on a 6-month basis, with a final evaluation at 36 months aftermore » RT. The evaluations were done using a panel of global and specific subjective scores, a digitized scoring system using the breast retraction assessment (BRA) measurement, and a patient's self-assessment evaluation. As cosmetic results were graded according to severity, the comparison of boost techniques was done using the ordinal logistic regression model. Adjusted odds ratios (OR) and their 95% confidence intervals (CI) are presented. Results: At 36 months of follow-up, there was no significant difference between the two groups with respect to the global subjective cosmetic outcome (OR = 1.40; 95%CI = 0.69-2.85, p = 0.35). Good to excellent scores were observed in 65% of implant patients and 62% of photon/electron patients. At 24 months and beyond, telangiectasia was more severe in the implant group with an OR of 9.64 (95%CI = 4.05-22.92, p < 0.0001) at 36 months. The only variable associated with a worse global cosmetic outcome was the presence of concomitant chemotherapy (OR = 3.87; 95%CI = 1.74-8.62). The BRA value once adjusted for age, concomitant chemotherapy, and boost volume showed a positive association with the boost technique. The BRA value was significantly greater in the implant group (p 0.03). There was no difference in the patient's final self-assessment score between the two groups. Three variables were statistically

A proposed adaptive step size perturbation and observation maximum power point tracking algorithm based on photovoltaic system modeling

NASA Astrophysics Data System (ADS)

Huang, Yu

Solar energy becomes one of the major alternative renewable energy options for its huge abundance and accessibility. Due to the intermittent nature, the high demand of Maximum Power Point Tracking (MPPT) techniques exists when a Photovoltaic (PV) system is used to extract energy from the sunlight. This thesis proposed an advanced Perturbation and Observation (P&O) algorithm aiming for relatively practical circumstances. Firstly, a practical PV system model is studied with determining the series and shunt resistances which are neglected in some research. Moreover, in this proposed algorithm, the duty ratio of a boost DC-DC converter is the object of the perturbation deploying input impedance conversion to achieve working voltage adjustment. Based on the control strategy, the adaptive duty ratio step size P&O algorithm is proposed with major modifications made for sharp insolation change as well as low insolation scenarios. Matlab/Simulink simulation for PV model, boost converter control strategy and various MPPT process is conducted step by step. The proposed adaptive P&O algorithm is validated by the simulation results and detail analysis of sharp insolation changes, low insolation condition and continuous insolation variation.

Can role models boost entrepreneurial attitudes?

PubMed

Fellnhofer, Katharina; Puumalainen, Kaisu

2017-01-01

This multi-country study used role models to boost perceptions of entrepreneurial feasibility and desirability. The results of a structural equation model based on a sample comprising 426 individuals who were primarily from Austria, Finland and Greece revealed a significant positive influence on perceived entrepreneurial desirability and feasibility. These findings support the argument for embedding entrepreneurial role models in entrepreneurship education courses to promote entrepreneurial activities. This direction is not only relevant for the academic community but also essential for nascent entrepreneurs, policymakers and society at large.

High static gain single-phase PFC based on a hybrid boost converter

NASA Astrophysics Data System (ADS)

Flores Cortez, Daniel; Maccarini, Marcello C.; Mussa, Samir A.; Barbi, Ivo

2017-05-01

In this paper, a single-phase unity power factor rectifier, based on a hybrid boost converter, resulting from the integration of a conventional dc-dc boost converter and a switched-capacitor voltage doubler is proposed, analysed, designed and tested. The high-power rectifier is controlled by two feedback loops with the same control strategy employed in the conventional boost-based rectifier. The main feature of the proposed rectifier is its ability to output a dc voltage larger than the double of the peak value of the input line voltage, while subjecting the power switches to half of the dc-link voltage, which contributes to reducing the cost and increasing the efficiency. Experimental data were obtained from a laboratory prototype with an input voltage of 220 Vrms, line frequency of 60 Hz, output voltage of 800 Vdc, load power of 1000 W and switching frequency of 50 kHz. The efficiency of the prototype, measured in the laboratory, was 96.5% for full load and 97% for half load.

Towards incorporating affective computing to virtual rehabilitation; surrogating attributed attention from posture for boosting therapy adaptation

NASA Astrophysics Data System (ADS)

Rivas, Jesús J.; Heyer, Patrick; Orihuela-Espina, Felipe; Sucar, Luis Enrique

2015-01-01

Virtual rehabilitation (VR) is a novel motor rehabilitation therapy in which the rehabilitation exercises occurs through interaction with bespoken virtual environments. These virtual environments dynamically adapt their activity to match the therapy progress. Adaptation should be guided by the cognitive and emotional state of the patient, none of which are directly observable. Here, we present our first steps towards inferring non-observable attentional state from unobtrusively observable seated posture, so that this knowledge can later be exploited by a VR platform to modulate its behaviour. The space of seated postures was discretized and 648 pictures of acted representations were exposed to crowd-evaluation to determine attributed state of attention. A semi-supervised classifier based on Na¨ıve Bayes with structural improvement was learnt to unfold a predictive relation between posture and attributed attention. Internal validity was established following a 2×5 cross-fold strategy. Following 4959 votes from crowd, classification accuracy reached a promissory 96.29% (µ±σ = 87.59±6.59) and F-measure reached 82.35% (µ ± σ = 69.72 ± 10.50). With the afforded rate of classification, we believe it is safe to claim posture as a reliable proxy for attributed attentional state. It follows that unobtrusively monitoring posture can be exploited for guiding an intelligent adaptation in a virtual rehabilitation platform. This study further helps to identify critical aspects of posture permitting inference of attention.

A multiview boosting approach to tissue segmentation

NASA Astrophysics Data System (ADS)

Kwak, Jin Tae; Xu, Sheng; Pinto, Peter A.; Turkbey, Baris; Bernardo, Marcelino; Choyke, Peter L.; Wood, Bradford J.

2014-04-01

Digitized histopathology images have a great potential for improving or facilitating current assessment tools in cancer pathology. In order to develop accurate and robust automated methods, the precise segmentation of histologic objects such epithelium, stroma, and nucleus is necessary, in the hopes of information extraction not otherwise obvious to the subjective eye. Here, we propose a multivew boosting approach to segment histology objects of prostate tissue. Tissue specimen images are first represented at different scales using a Gaussian kernel and converted into several forms such HSV and La*b*. Intensity- and texture-based features are extracted from the converted images. Adopting multiview boosting approach, we effectively learn a classifier to predict the histologic class of a pixel in a prostate tissue specimen. The method attempts to integrate the information from multiple scales (or views). 18 prostate tissue specimens from 4 patients were employed to evaluate the new method. The method was trained on 11 tissue specimens including 75,832 epithelial and 103,453 stroma pixels and tested on 55,319 epithelial and 74,945 stroma pixels from 7 tissue specimens. The technique showed 96.7% accuracy, and as summarized into a receiver operating characteristic (ROC) plot, the area under the ROC curve (AUC) of 0.983 (95% CI: 0.983-0.984) was achieved.

Design and dSpace interfacing of current fed high gain dc to dc boost converter for low voltage applications

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Debraj; Das, Subhrajit; Arunkumar, G.; Elangovan, D.; Ragunath, G.

2017-11-01

In this paper a current fed interleaved DC - DC boost converter which has an isolated topology and used for high voltage step up is proposed. A basic DC to DC boost converter converts uncontrolled DC voltage into controlled DC voltage of higher magnitude. Whereas this topology has the advantages of lower input current ripple, lesser output voltage, lesser stress on switches, faster transient response, improved reliability and much lesser electromagnetic emission over the conventional DC to DC boost converter. Most important benefit of this interleaved DC to DC boost converter is much higher efficiency. The input current is divided into two paths, substantially ohmic loss (I2R) and inductor ac loss gets reduced and finally the system achieves much higher efficiency. With recent mandates on energy saving interleaved DC to DC boost converter may be used as a very powerful tool to maintain good power density keeping the input current manageable. Higher efficiency also allows higher switching frequency and as a result the topology becomes more compact and cost friendly. The proposed topology boosts 48v DC to 200 V DC. Switching frequency is 100 kHz and PSIM 9.1 Platform has been used for the simulation.

Intranasal boosting with an adenovirus-vectored vaccine markedly enhances protection by parenteral Mycobacterium bovis BCG immunization against pulmonary tuberculosis.

PubMed

Santosuosso, Michael; McCormick, Sarah; Zhang, Xizhong; Zganiacz, Anna; Xing, Zhou

2006-08-01

Parenterally administered Mycobacterium bovis BCG vaccine confers only limited immune protection from pulmonary tuberculosis in humans. There is a need for developing effective boosting vaccination strategies. We examined a heterologous prime-boost regimen utilizing BCG as a prime vaccine and our recently described adenoviral vector expressing Ag85A (AdAg85A) as a boost vaccine. Since we recently demonstrated that a single intranasal but not intramuscular immunization with AdAg85A was able to induce potent protection from pulmonary Mycobacterium tuberculosis challenge in a mouse model, we compared the protective effects of parenteral and mucosal booster immunizations following subcutaneous BCG priming. Protection by BCG prime immunization was not effectively boosted by subcutaneous BCG or intramuscular AdAg85A. In contrast, protection by BCG priming was remarkably boosted by intranasal AdAg85A. Such enhanced protection by intranasal AdAg85A was correlated to the numbers of gamma interferon-positive CD4 and CD8 T cells residing in the airway lumen of the lung. Our study demonstrates that intranasal administration of AdAg85A represents an effective way to boost immune protection by parenteral BCG vaccination.

Phenotypic plasticity as an adaptation to a functional trade-off

PubMed Central

Yi, Xiao; Dean, Antony M

2016-01-01

We report the evolution of a phenotypically plastic behavior that circumvents the hardwired trade-off that exists when resources are partitioned between growth and motility in Escherichia coli. We propagated cultures in a cyclical environment, alternating between growth up to carrying capacity and selection for chemotaxis. Initial adaptations boosted overall swimming speed at the expense of growth. The effect of the trade-off was subsequently eased through a change in behavior; while individual cells reduced motility during exponential growth, the faction of the population that was motile increased as the carrying capacity was approached. This plastic behavior was produced by a single amino acid replacement in FliA, a regulatory protein central to the chemotaxis network. Our results illustrate how phenotypic plasticity potentiates evolvability by opening up new regions of the adaptive landscape. DOI: http://dx.doi.org/10.7554/eLife.19307.001 PMID:27692064

Action recognition via cumulative histogram of multiple features

NASA Astrophysics Data System (ADS)

Yan, Xunshi; Luo, Yupin

2011-01-01

Spatial-temporal interest points (STIPs) are popular in human action recognition. However, they suffer from difficulties in determining size of codebook and losing much information during forming histograms. In this paper, spatial-temporal interest regions (STIRs) are proposed, which are based on STIPs and are capable of marking the locations of the most ``shining'' human body parts. In order to represent human actions, the proposed approach takes great advantages of multiple features, including STIRs, pyramid histogram of oriented gradients and pyramid histogram of oriented optical flows. To achieve this, cumulative histogram is used to integrate dynamic information in sequences and to form feature vectors. Furthermore, the widely used nearest neighbor and AdaBoost methods are employed as classification algorithms. Experiments on public datasets KTH, Weizmann and UCF sports show that the proposed approach achieves effective and robust results.

Automatic choroid cells segmentation and counting in fluorescence microscopic image

NASA Astrophysics Data System (ADS)

Fei, Jianjun; Zhu, Weifang; Shi, Fei; Xiang, Dehui; Lin, Xiao; Yang, Lei; Chen, Xinjian

2016-03-01

In this paper, we proposed a method to automatically segment and count the rhesus choroid-retinal vascular endothelial cells (RF/6A) in fluorescence microscopic images which is based on shape classification, bottleneck detection and accelerated Dijkstra algorithm. The proposed method includes four main steps. First, a thresholding filter and morphological operations are applied to reduce the noise. Second, a shape classifier is used to decide whether a connected component is needed to be segmented. In this step, the AdaBoost classifier is applied with a set of shape features. Third, the bottleneck positions are found based on the contours of the connected components. Finally, the cells segmentation and counting are completed based on the accelerated Dijkstra algorithm with the gradient information between the bottleneck positions. The results show the feasibility and efficiency of the proposed method.

Disease Control and Ototoxicity Using Intensity-Modulated Radiation Therapy Tumor-Bed Boost for Medulloblastoma

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

Polkinghorn, William R.; Dunkel, Ira J.; Souweidane, Mark M.

2011-11-01

Purpose: We previously reported excellent local control for treating medulloblastoma with a limited boost to the tumor bed. In order to decrease ototoxicity, we subsequently implemented a tumor-bed boost using intensity-modulated radiation therapy (IMRT), the clinical results of which we report here. Patients and Methods: A total of 33 patients with newly diagnosed medulloblastoma, 25 with standard risk, and 8 with high risk, were treated on an IMRT tumor-bed boost following craniospinal irradiation (CSI). Six standard-risk patients were treated with an institutional protocol with 18 Gy CSI in conjunction with intrathecal iodine-131-labeled monoclonal antibody. The majority of patients received concurrentmore » vincristine and standard adjuvant chemotherapy. Pure-tone audiograms were graded according to National Cancer Institute Common Terminology Criteria for Adverse Events version 3.0. Results: Median age was 9 years old (range, 4-46 years old). Median follow-up was 63 months. Kaplan-Meier estimates of progression-free survival (PFS) and overall survival (OS) rates for standard-risk patients who received 23.4 or 36 Gy CSI (not including those who received 18 Gy CSI with radioimmunotherapy) were 81.4% and 88.4%, respectively, at 5 years; 5-year PFS and OS rates for high-risk patients were both 87.5%. There were no isolated posterior fossa failures outside of the boost volume. Posttreatment audiograms were available for 31 patients, of whom 6%, at a median follow-up of 19 months, had developed Grade 3 hearing loss. Conclusion: An IMRT tumor-bed boost results in excellent local control while delivering a low mean dose to the cochlea, resulting in a low rate of ototoxicity.« less

High-Dose Split-Course Radiation Therapy for Anal Cancer: Outcome Analysis Regarding the Boost Strategy (CORS-03 Study)

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

Hannoun-Levi, Jean-Michel, E-mail: jean-michel.hannoun-levi@nice.fnclcc.fr; Cercle des Oncologues Radiotherapeutes du Sud; Ortholan, Cecile

2011-07-01

Purpose: To retrospectively assess the clinical outcome in anal cancer patients treated with split-course radiation therapy and boosted through external-beam radiation therapy (EBRT) or brachytherapy (BCT). Methods and Materials: From January 2000 to December 2004, a selected group (162 patients) with invasive nonmetastatic anal squamous cell carcinoma was studied. Tumor staging reported was T1 = 31 patients (19%), T2 = 77 patients (48%), T3 = 42 patients (26%), and T4= 12 patients (7%). Lymph node status was N0-1 (86%) and N2-3 (14%). Patients underwent a first course of EBRT: mean dose 45.1 Gy (range, 39.5-50) followed by a boost: meanmore » dose 17.9 Gy (range, 8-25) using EBRT (76 patients, 47%) or BCT (86 patients, 53%). All characteristics of patients and tumors were well balanced between the BCT and EBRT groups. Results: The mean overall treatment time (OTT) was 82 days (range, 45-143) and 67 days (range, 37-128) for the EBRT and BCT groups, respectively (p < 0.001). The median follow-up was 62 months (range, 2-108). The 5-year cumulative rate of local recurrence (CRLR) was 21%. In the univariate analysis, the prognostic factors for CRLR were as follows: T stage (T1-2 = 15% vs. T3-4 = 36%, p = 0.03), boost technique (BCT = 12% vs. EBRT = 33%, p = 0.002) and OTT (OTT <80 days = 14%, OTT {>=}80 days = 34%, p = 0.005). In the multivariate analysis, BCT boost was the unique prognostic factor (hazard ratio = 0.62 (0.41-0.92). In the subgroup of patients with OTT <80 days, the 5-year CRLR was significantly increased with the BCT boost (BC = 9% vs. EBRT = 28%, p = 0.03). In the case of OTT {>=}80 days, the 5-year CRLR was not affected by the boost technique (BCT = 29% vs. EBRT = 38%, p = 0.21). Conclusion: In anal cancer, when OTT is <80 days, BCT boost is superior to EBRT boost for CRLR. These results suggest investigating the benefit of BCT boost in prospective trials.« less

Can role models boost entrepreneurial attitudes?

PubMed Central

Fellnhofer, Katharina; Puumalainen, Kaisu

2017-01-01

This multi-country study used role models to boost perceptions of entrepreneurial feasibility and desirability. The results of a structural equation model based on a sample comprising 426 individuals who were primarily from Austria, Finland and Greece revealed a significant positive influence on perceived entrepreneurial desirability and feasibility. These findings support the argument for embedding entrepreneurial role models in entrepreneurship education courses to promote entrepreneurial activities. This direction is not only relevant for the academic community but also essential for nascent entrepreneurs, policymakers and society at large. PMID:28458611

Congress OKs $2 Billion Boost for the NIH.

PubMed

2017-07-01

President Donald Trump last week signed a $1.1 trillion spending bill for fiscal year 2017, including a welcome $2 billion boost for the NIH that will support former Vice President Joe Biden's Cancer Moonshot initiative, among other priorities. However, researchers who rely heavily on NIH grant funding remain concerned about proposed cuts for 2018. ©2017 American Association for Cancer Research.

The quest for conditional independence in prospectivity modeling: weights-of-evidence, boost weights-of-evidence, and logistic regression

NASA Astrophysics Data System (ADS)

Schaeben, Helmut; Semmler, Georg

2016-09-01

The objective of prospectivity modeling is prediction of the conditional probability of the presence T = 1 or absence T = 0 of a target T given favorable or prohibitive predictors B, or construction of a two classes 0,1 classification of T. A special case of logistic regression called weights-of-evidence (WofE) is geologists' favorite method of prospectivity modeling due to its apparent simplicity. However, the numerical simplicity is deceiving as it is implied by the severe mathematical modeling assumption of joint conditional independence of all predictors given the target. General weights of evidence are explicitly introduced which are as simple to estimate as conventional weights, i.e., by counting, but do not require conditional independence. Complementary to the regression view is the classification view on prospectivity modeling. Boosting is the construction of a strong classifier from a set of weak classifiers. From the regression point of view it is closely related to logistic regression. Boost weights-of-evidence (BoostWofE) was introduced into prospectivity modeling to counterbalance violations of the assumption of conditional independence even though relaxation of modeling assumptions with respect to weak classifiers was not the (initial) purpose of boosting. In the original publication of BoostWofE a fabricated dataset was used to "validate" this approach. Using the same fabricated dataset it is shown that BoostWofE cannot generally compensate lacking conditional independence whatever the consecutively processing order of predictors. Thus the alleged features of BoostWofE are disproved by way of counterexamples, while theoretical findings are confirmed that logistic regression including interaction terms can exactly compensate violations of joint conditional independence if the predictors are indicators.

Study Of Boosted W-Jets And Higgs-Jets With the SiFCC Detector

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

Yu, Shin-Shan; Chekanov, Sergei; Gray, Lindsey

We study the detector performance in the reconstruction of hadronically-decaying W bosons and Higgs bosons at very high energy proton colliders using a full GEANT4 simulation of the SiFCC detector. The W and Higgs bosons carry transverse momentum in the multi-TeV range, which results in collimated decay products that are reconstructed as a single jet. We present a measurement of the energy response and resolution of boosted W-jets and Higgs-jets and show the separation of two sub-jets within the boosted boson jet.

Advanced Airfoils Boost Helicopter Performance

NASA Technical Reports Server (NTRS)

2007-01-01

Carson Helicopters Inc. licensed the Langley RC4 series of airfoils in 1993 to develop a replacement main rotor blade for their Sikorsky S-61 helicopters. The company's fleet of S-61 helicopters has been rebuilt to include Langley's patented airfoil design, and the helicopters are now able to carry heavier loads and fly faster and farther, and the main rotor blades have twice the previous service life. In aerial firefighting, the performance-boosting airfoils have helped the U.S. Department of Agriculture's Forest Service control the spread of wildfires. In 2003, Carson Helicopters signed a contract with Ducommun AeroStructures Inc., to manufacture the composite blades for Carson Helicopters to sell

Diversification and intensification of agricultural adaptation from global to local scales.

PubMed

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke; Läderach, Peter

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of

Diversification and intensification of agricultural adaptation from global to local scales

PubMed Central

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of

Chaos minimization in DC-DC boost converter using circuit parameter optimization

NASA Astrophysics Data System (ADS)

Sudhakar, N.; Natarajan, Rajasekar; Gourav, Kumar; Padmavathi, P.

2017-11-01

DC-DC converters are prone to several types of nonlinear phenomena including bifurcation, quasi periodicity, intermittency and chaos. These undesirable effects must be controlled for periodic operation of the converter to ensure the stability. In this paper an effective solution to control of chaos in solar fed DC-DC boost converter is proposed. Controlling of chaos is significantly achieved using optimal circuit parameters obtained through Bacterial Foraging Optimization Algorithm. The optimization renders the suitable parameters in minimum computational time. The obtained results are compared with the operation of traditional boost converter. Further the obtained results with BFA optimized parameter ensures the operations of the converter are within the controllable region. To elaborate the study of bifurcation analysis with optimized and unoptimized parameters are also presented.

Planning the Breast Boost: Comparison of Three Techniques and Evolution of Tumor Bed During Treatment

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

Hepel, Jaroslaw T.; Department of Radiation Oncology, Brown University, Rhode Island Hospital, Providence, RI; Evans, Suzanne B.

2009-06-01

Purpose: To evaluate the accuracy of two clinical techniques for electron boost planning compared with computed tomography (CT)-based planning. Additionally, we evaluated the tumor bed characteristics at whole breast planning and boost planning. Methods and Materials: A total of 30 women underwent tumor bed boost planning within 2 weeks of completing whole breast radiotherapy using three planning techniques: scar-based planning, palpation/clinical-based planning, and CT-based planning. The plans were analyzed for dosimetric coverage of the CT-delineated tumor bed. The cavity visualization score was used to define the CT-delineated tumor bed as well or poorly defined. Results: Scar-based planning resulted in inferiormore » tumor bed coverage compared with CT-based planning, with the minimal dose received by 90% of the target volume >90% in 53% and a geographic miss in 53%. The results of palpation/clinical-based planning were significantly better: 87% and 10% for the minimal dose received by 90% of the target volume >90% and geographic miss, respectively. Of the 30 tumor beds, 16 were poorly defined by the cavity visualization score. Of these 16, 8 were well demarcated by the surgical clips. The evaluation of the 22 well-defined tumor beds revealed similar results. A comparison of the tumor bed volume from the initial planning CT scan to the boost planning CT scan revealed a decrease in size in 77% of cases. The mean decrease in volume was 52%. Conclusion: The results of our study have shown that CT-based planning allows for optimal tumor bed coverage compared with clinical and scar-based approaches. However, in the setting of a poorly visualized cavity on CT without surgical clips, palpation/clinical-based planning can help delineate the appropriate target volumes and is superior to scar-based planning. CT simulation at boost planning could allow for a reduction in the boost volumes.« less

A boost and bounce theory of temporal attention.

PubMed

Olivers, Christian N L; Meeter, Martijn

2008-10-01

What is the time course of visual attention? Attentional blink studies have found that the 2nd of 2 targets is often missed when presented within about 500 ms from the 1st target, resulting in theories about relatively long-lasting capacity limitations or bottlenecks. Earlier studies, however, reported quite the opposite finding: Attention is transiently enhanced, rather than reduced, for several hundreds of milliseconds after a relevant event. The authors present a general theory, as well as a working computational model, that integrate these findings. There is no central role for capacity limitations or bottlenecks. Central is a rapidly responding gating system (or attentional filter) that seeks to enhance relevant and suppress irrelevant information. When items sufficiently match the target description, they elicit transient excitatory feedback activity (a "boost" function), meant to provide access to working memory. However, in the attentional blink task, the distractor after the target is accidentally boosted, resulting in subsequent strong inhibitory feedback response (a "bounce"), which, in effect, closes the gate to working memory. The theory explains many findings that are problematic for limited-capacity accounts, including a new experiment showing that the attentional blink can be postponed.

Post-translocational adaptation drives evolution through genetic selection and transcriptional shift in Saccharomyces cerevisiae.

PubMed

Tosato, Valentina; Sims, Jason; West, Nicole; Colombin, Martina; Bruschi, Carlo V

2017-05-01

Adaptation by natural selection might improve the fitness of an organism and its probability to survive in unfavorable environmental conditions. Decoding the genetic basis of adaptive evolution is one of the great challenges to deal with. To this purpose, Saccharomyces cerevisiae has been largely investigated because of its short division time, excellent aneuploidy tolerance and the availability of the complete sequence of its genome with a thorough genome database. In the past, we developed a system, named bridge-induced translocation, to trigger specific, non-reciprocal translocations, exploiting the endogenous recombination system of budding yeast. This technique allows users to generate a heterogeneous population of cells with different aneuploidies and increased phenotypic variation. In this work, we demonstrate that ad hoc chromosomal translocations might induce adaptation, fostering selection of thermo-tolerant yeast strains with improved phenotypic fitness. This "yeast eugenomics" correlates with a shift to enhanced expression of genes involved in stress response, heat shock as well as carbohydrate metabolism. We propose that the bridge-induced translocation is a suitable approach to generate adapted, physiologically boosted strains for biotechnological applications.

Experimental verification of internal parameter in magnetically coupled boost used as PV optimizer in parallel association

NASA Astrophysics Data System (ADS)

Sawicki, Jean-Paul; Saint-Eve, Frédéric; Petit, Pierre; Aillerie, Michel

2017-02-01

This paper presents results of experiments aimed to verify a formula able to compute duty cycle in the case of pulse width modulation control for a DC-DC converter designed and realized in laboratory. This converter, called Magnetically Coupled Boost (MCB) is sized to step up only one photovoltaic module voltage to supply directly grid inverters. Duty cycle formula will be checked in a first time by identifying internal parameter, auto-transformer ratio, and in a second time by checking stability of operating point on the side of photovoltaic module. Thinking on nature of generator source and load connected to converter leads to imagine additional experiments to decide if auto-transformer ratio parameter could be used with fixed value or on the contrary with adaptive value. Effects of load variations on converter behavior or impact of possible shading on photovoltaic module are also mentioned, with aim to design robust control laws, in the case of parallel association, designed to compensate unwanted effects due to output voltage coupling.

ASCENDE-RT: An Analysis of Treatment-Related Morbidity for a Randomized Trial Comparing a Low-Dose-Rate Brachytherapy Boost with a Dose-Escalated External Beam Boost for High- and Intermediate-Risk Prostate Cancer

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

Rodda, Sree; Tyldesley, Scott; Department of Surgery, University of British Columbia, Vancouver, British Columbia

Purpose: To report the genitourinary (GU) and gastrointestinal (GI) morbidity and erectile dysfunction in a randomized trial comparing 2 methods of dose escalation for high- and intermediate-risk prostate cancer. Methods and Materials: ASCENDE-RT (Androgen Suppression Combined with Elective Nodal and Dose Escalated Radiation Therapy) enrolled 398 men, median age 68 years, who were then randomized to either a standard arm that included 12 months of androgen deprivation therapy and pelvic irradiation to 46 Gy followed by a dose-escalated external beam radiation therapy (DE-EBRT) boost to 78 Gy, or an experimental arm that substituted a low-dose-rate prostate brachytherapy (LDR-PB) boost. At clinic visits, investigators recorded GUmore » and GI morbidity and information on urinary continence, catheter use, and erectile function. Exclusion of 15 who received nonprotocol treatment and correction of 14 crossover events left 195 men who actually received a DE-EBRT boost and 188, an LDR-PB boost. Median follow-up was 6.5 years. Results: The LDR-PB boost increased the risk of needing temporary catheterization and/or requiring incontinence pads. At 5 years the cumulative incidence of grade 3 GU events was 18.4% for LDR-PB, versus 5.2% for DE-EBRT (P<.001). Compared with the cumulative incidence, the 5-year prevalence of grade 3 GU morbidity was substantially lower for both arms (8.6% vs 2.2%, P=.058). The 5-year cumulative incidence of grade 3 GI events was 8.1% for LDR-PB, versus 3.2% for DE-EBRT (P=.124). The 5-year prevalence of grade 3 GI toxicity was lower than the cumulative incidence for both arms (1.0% vs 2.2%, respectively). Among men reporting adequate baseline erections, 45% of LDR-PB patients reported similar erectile function at 5 years, versus 37% after DE-EBRT (P=.30). Conclusions: The incidence of acute and late GU morbidity was higher after LDR-PB boost, and there was a nonsignificant trend for worse GI morbidity. No differences in the frequency of

Optical Coherence Tomography and Stent Boost Imaging Guided Bioresorbable Vascular Scaffold Overlapping for Coronary Chronic Total Occlusion Lesion

PubMed Central

Li, Hu; Choi, Cheol Ung; Oh, Dong Joo

2017-01-01

We report herein the optical coherence tomography (OCT) and stent boost imaging guided bioresorbable vascular scaffold (BVS) implantation for right coronary artery (RCA) chronic total occlusion (CTO) lesion. The gold standard for evaluating BVS expansion after percutaneous coronary intervention is OCT. However, stent boost imaging is a new technique that improves fluoroscopy-based assessments of stent overlapping, and the present case shows clinical usefulness of OCT and stent boost imaging guided ‘overlapping’ BVS implantation via antegrade approach for a typical RCA CTO lesion. PMID:28792157

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

PubMed

Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna

2015-01-27

To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

Ventriculogram segmentation using boosted decision trees

NASA Astrophysics Data System (ADS)

McDonald, John A.; Sheehan, Florence H.

2004-05-01

Left ventricular status, reflected in ejection fraction or end systolic volume, is a powerful prognostic indicator in heart disease. Quantitative analysis of these and other parameters from ventriculograms (cine xrays of the left ventricle) is infrequently performed due to the labor required for manual segmentation. None of the many methods developed for automated segmentation has achieved clinical acceptance. We present a method for semi-automatic segmentation of ventriculograms based on a very accurate two-stage boosted decision-tree pixel classifier. The classifier determines which pixels are inside the ventricle at key ED (end-diastole) and ES (end-systole) frames. The test misclassification rate is about 1%. The classifier is semi-automatic, requiring a user to select 3 points in each frame: the endpoints of the aortic valve and the apex. The first classifier stage is 2 boosted decision-trees, trained using features such as gray-level statistics (e.g. median brightness) and image geometry (e.g. coordinates relative to user supplied 3 points). Second stage classifiers are trained using the same features as the first, plus the output of the first stage. Border pixels are determined from the segmented images using dilation and erosion. A curve is then fit to the border pixels, minimizing a penalty function that trades off fidelity to the border pixels with smoothness. ED and ES volumes, and ejection fraction are estimated from border curves using standard area-length formulas. On independent test data, the differences between automatic and manual volumes (and ejection fractions) are similar in size to the differences between two human observers.

Boosting for detection of gene-environment interactions.

PubMed

Pashova, H; LeBlanc, M; Kooperberg, C

2013-01-30

In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.

Industrial Assessment Center Helps Boost Efficiency for Small and Medium Manufacturers

ScienceCinema

Johnson, Mark; Friedman, David

2018-06-12

The Industrial Assessment Center program helps small and medium manufacturers boost efficiency and save energy. It pairs companies with universities as students perform energy assessments and provide recommendations to improve their facilities.

Industrial Assessment Center Helps Boost Efficiency for Small and Medium Manufacturers

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

Johnson, Mark; Friedman, David

The Industrial Assessment Center program helps small and medium manufacturers boost efficiency and save energy. It pairs companies with universities as students perform energy assessments and provide recommendations to improve their facilities.

HIV-1 gp120 and Modified Vaccinia Virus Ankara (MVA) gp140 Boost Immunogens Increase Immunogenicity of a DNA/MVA HIV-1 Vaccine.

PubMed

Shen, Xiaoying; Basu, Rahul; Sawant, Sheetal; Beaumont, David; Kwa, Sue Fen; LaBranche, Celia; Seaton, Kelly E; Yates, Nicole L; Montefiori, David C; Ferrari, Guido; Wyatt, Linda S; Moss, Bernard; Alam, S Munir; Haynes, Barton F; Tomaras, Georgia D; Robinson, Harriet L

2017-12-15

An important goal of human immunodeficiency virus (HIV) vaccine design is identification of strategies that elicit effective antiviral humoral immunity. One novel approach comprises priming with DNA and boosting with modified vaccinia virus Ankara (MVA) expressing HIV-1 Env on virus-like particles. In this study, we evaluated whether the addition of a gp120 protein in alum or MVA-expressed secreted gp140 (MVAgp140) could improve immunogenicity of a DNA prime-MVA boost vaccine. Five rhesus macaques per group received two DNA primes at weeks 0 and 8 followed by three MVA boosts (with or without additional protein or MVAgp140) at weeks 18, 26, and 40. Both boost immunogens enhanced the breadth of HIV-1 gp120 and V1V2 responses, antibody-dependent cellular cytotoxicity (ADCC), and low-titer tier 1B and tier 2 neutralizing antibody responses. However, there were differences in antibody kinetics, linear epitope specificity, and CD4 T cell responses between the groups. The gp120 protein boost elicited earlier and higher peak responses, whereas the MVAgp140 boost resulted in improved antibody durability and comparable peak responses after the final immunization. Linear V3 specific IgG responses were particularly enhanced by the gp120 boost, whereas the MVAgp140 boost also enhanced responses to linear C5 and C2.2 epitopes. Interestingly, gp120, but not the MVAgp140 boost, increased peak CD4 + T cell responses. Thus, both gp120 and MVAgp140 can augment potential protection of a DNA/MVA vaccine by enhancing gp120 and V1/V2 antibody responses, whereas potential protection by gp120, but not MVAgp140 boosts, may be further impacted by increased CD4 + T cell responses. IMPORTANCE Prior immune correlate analyses with humans and nonhuman primates revealed the importance of antibody responses in preventing HIV-1 infection. A DNA prime-modified vaccinia virus Ankara (MVA) boost vaccine has proven to be potent in eliciting antibody responses. Here we explore the ability of boosts with

Cura Annonae-Chemically Boosting Crop Yields Through Metabolic Feeding of a Plant Signaling Precursor.

PubMed

Vocadlo, David J

2017-05-22

The cream of the crop: With the world facing a projected shortfall of crops by 2050, new approaches are needed to boost crop yields. Metabolic feeding of plants with photocaged trehalose-6-phosphate (Tre6P) can increase levels of the signaling metabolite Tre6P in the plant. Reprogramming of cellular metabolism by Tre6P stimulates a program of plant growth and enhanced crop yields, while boosting starch content. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

IMM tracking of a theater ballistic missile during boost phase

NASA Astrophysics Data System (ADS)

Hutchins, Robert G.; San Jose, Anthony

1998-09-01

Since the SCUD launches in the Gulf War, theater ballistic missile (TBM) systems have become a growing concern for the US military. Detection, tracking and engagement during boost phase or shortly after booster cutoff are goals that grow in importance with the proliferation of weapons of mass destruction. This paper addresses the performance of tracking algorithms for TBMs during boost phase and across the transition to ballistic flight. Three families of tracking algorithms are examined: alpha-beta-gamma trackers, Kalman-based trackers, and the interactive multiple model (IMM) tracker. In addition, a variation on the IMM to include prior knowledge of a booster cutoff parameter is examined. Simulated data is used to compare algorithms. Also, the IMM tracker is run on an actual ballistic missile trajectory. Results indicate that IMM trackers show significant advantage in tracking through the model transition represented by booster cutoff.

Using injectable hydrogel markers to assess resimulation for boost target volume definition in a patient undergoing whole-breast radiotherapy

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

Patel, Henal; Goyal, Sharad; Kim, Leonard, E-mail: kimlh@rutgers.edu

Several publications have recommended that patients undergoing whole-breast radiotherapy be resimulated for boost planning. The rationale for this is that the seroma may be smaller when compared with the initial simulation. However, the decision remains whether to use the earlier or later images to define an appropriate boost target volume. A patient undergoing whole-breast radiotherapy had new, injectable, temporary hydrogel fiducial markers placed 1 to 3 cm from the seroma at the time of initial simulation. The patient was resimulated 4.5 weeks later for conformal photon boost planning. Computed tomography (CT) scans acquired at the beginning and the end ofmore » whole-breast radiotherapy showed that shrinkage of the lumpectomy cavity was not matched by a corresponding reduction in the surrounding tissue volume, as demarcated by hydrogel markers. This observation called into question the usual interpretation of cavity shrinkage for boost target definition. For this patient, it was decided to define the boost target volume on the initial planning CT instead of the new CT.« less

How Citation Boosts Promote Scientific Paradigm Shifts and Nobel Prizes

PubMed Central

Mazloumian, Amin; Eom, Young-Ho; Helbing, Dirk; Lozano, Sergi; Fortunato, Santo

2011-01-01

Nobel Prizes are commonly seen to be among the most prestigious achievements of our times. Based on mining several million citations, we quantitatively analyze the processes driving paradigm shifts in science. We find that groundbreaking discoveries of Nobel Prize Laureates and other famous scientists are not only acknowledged by many citations of their landmark papers. Surprisingly, they also boost the citation rates of their previous publications. Given that innovations must outcompete the rich-gets-richer effect for scientific citations, it turns out that they can make their way only through citation cascades. A quantitative analysis reveals how and why they happen. Science appears to behave like a self-organized critical system, in which citation cascades of all sizes occur, from continuous scientific progress all the way up to scientific revolutions, which change the way we see our world. Measuring the “boosting effect” of landmark papers, our analysis reveals how new ideas and new players can make their way and finally triumph in a world dominated by established paradigms. The underlying “boost factor” is also useful to discover scientific breakthroughs and talents much earlier than through classical citation analysis, which by now has become a widespread method to measure scientific excellence, influencing scientific careers and the distribution of research funds. Our findings reveal patterns of collective social behavior, which are also interesting from an attention economics perspective. Understanding the origin of scientific authority may therefore ultimately help to explain how social influence comes about and why the value of goods depends so strongly on the attention they attract. PMID:21573229

How citation boosts promote scientific paradigm shifts and nobel prizes.

PubMed

Mazloumian, Amin; Eom, Young-Ho; Helbing, Dirk; Lozano, Sergi; Fortunato, Santo

2011-05-04

Nobel Prizes are commonly seen to be among the most prestigious achievements of our times. Based on mining several million citations, we quantitatively analyze the processes driving paradigm shifts in science. We find that groundbreaking discoveries of Nobel Prize Laureates and other famous scientists are not only acknowledged by many citations of their landmark papers. Surprisingly, they also boost the citation rates of their previous publications. Given that innovations must outcompete the rich-gets-richer effect for scientific citations, it turns out that they can make their way only through citation cascades. A quantitative analysis reveals how and why they happen. Science appears to behave like a self-organized critical system, in which citation cascades of all sizes occur, from continuous scientific progress all the way up to scientific revolutions, which change the way we see our world. Measuring the "boosting effect" of landmark papers, our analysis reveals how new ideas and new players can make their way and finally triumph in a world dominated by established paradigms. The underlying "boost factor" is also useful to discover scientific breakthroughs and talents much earlier than through classical citation analysis, which by now has become a widespread method to measure scientific excellence, influencing scientific careers and the distribution of research funds. Our findings reveal patterns of collective social behavior, which are also interesting from an attention economics perspective. Understanding the origin of scientific authority may therefore ultimately help to explain how social influence comes about and why the value of goods depends so strongly on the attention they attract.

Early Boost and Slow Consolidation in Motor Skill Learning

ERIC Educational Resources Information Center

Hotermans, Christophe; Peigneux, Philippe; de Noordhout, Alain Maertens; Moonen, Gustave; Maquet, Pierre

2006-01-01

Motor skill learning is a dynamic process that continues covertly after training has ended and eventually leads to delayed increments in performance. Current theories suggest that this off-line improvement takes time and appears only after several hours. Here we show an early transient and short-lived boost in performance, emerging as early as…

Boosting long-term memory via wakeful rest: intentional rehearsal is not necessary, consolidation is sufficient.

PubMed

Dewar, Michaela; Alber, Jessica; Cowan, Nelson; Della Sala, Sergio

2014-01-01

People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as 'foreign names in a bridge club abroad' and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is not dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is sufficient for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition.

Boosted protease inhibitor monotherapy versus boosted protease inhibitor plus lamivudine dual therapy as second-line maintenance treatment for HIV-1-infected patients in sub-Saharan Africa (ANRS12 286/MOBIDIP): a multicentre, randomised, parallel, open-label, superiority trial.

PubMed

Ciaffi, Laura; Koulla-Shiro, Sinata; Sawadogo, Adrien Bruno; Ndour, Cheik Tidiane; Eymard-Duvernay, Sabrina; Mbouyap, Pretty Rosereine; Ayangma, Liliane; Zoungrana, Jacques; Gueye, Ndeye Fatou Ngom; Diallo, Mohamadou; Izard, Suzanne; Bado, Guillaume; Kane, Coumba Toure; Aghokeng, Avelin Fobang; Peeters, Martine; Girard, Pierre Marie; Le Moing, Vincent; Reynes, Jacques; Delaporte, Eric

2017-09-01

Despite satisfactory efficacy of WHO-recommended second-line antiretroviral treatment for patients with HIV in low-income countries, the need for simplified, low-cost, and less-toxic maintenance strategies remains high. We compared boosted protease inhibitor monotherapy with dual therapy with boosted protease inhibitor plus lamivudine in patients on second-line antiretrovial therapy (ART). We did a multicentre, randomised, parallel, open-label, superiority, trial in the HIV services of five hospitals in sub-Saharan Africa (Yaoundé, Cameroon; Dakar, Senegal; and Bobo Dioulasso, Burkina Faso). We recruited patients from the long-term, post-trial cohort of the ANRS 12169/2LADY study that compared the efficacy of three second-line combinations based on boosted protease inhibitors. Participants for our study were HIV-1 infected with multiple mutations including M184V, at first-line failure, aged 18 years and older, on boosted protease inhibitor plus two nucleoside reverse transcriptase inhibitors (NRTI) for at least 48 weeks with at least 48 weeks follow-up in the 2LADY trial, with two viral load measurements of less than 200 copies per mL in the previous 6 months, CD4 counts of more than 100 cells per μL, adherence of at least 90%, and no change to ART in the past 3 months. We randomly assigned participants (1:1) to receive either monotherapy with their boosted protease inhibitor (once-daily darunavir 800 mg [two 400 mg tablets] boosted with ritonavir 100 mg [one tablet] or coformulation of lopinavir 200 mg with ritonavir 50 mg [two tablets taken twice per day]) or to boosted protease inhibitor plus once-daily lamivudine 300 mg (one 300 mg tablet or two 150 mg tablets). Computer-generated randomisation was stratified by study site and viral load at screening (< 50 copies per mL, and 50-200 copies per mL), and concealed from study personnel throughout the inclusion period. After randomisation, treatment allocation was not masked from clinicians or patients]. Patients

The Reduced Effectiveness of EGR to Mitigate Knock at High Loads in Boosted SI Engines

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

Szybist, James P.; Wagnon, Scott W.; Splitter, Derek A.

Numerous studies have demonstrated that exhaust gas recirculation (EGR) can attenuate knock propensity in spark ignition (SI) engines at naturally aspirated or lightly boosted conditions. In this paper, we investigate the role of cooled EGR under higher load conditions with multiple fuel compositions, where highly retarded combustion phasing typical of modern SI engines was used. It was found that under these conditions, EGR attenuation of knock is greatly reduced, where EGR doesn’t allow significant combustion phasing advance as it does under lighter load conditions. Detailed combustion analysis shows that when EGR is added, the polytropic coefficient increases causing the compressivemore » pressure and temperature to increase. At sufficiently highly boosted conditions, the increase in polytropic coefficient and additional trapped mass from EGR can sufficiently reduce fuel ignition delay to overcome knock attenuation effects. Kinetic modeling demonstrates that the effectiveness of EGR to mitigate knock is highly dependent on the pressure-temperature condition. Experiments at 2000 rpm have confirmed reduced fuel ignition delay under highly boosted conditions relevant to modern downsized boosted SI engines, where in-cylinder pressure is higher and the temperature is cooler. Finally, at these conditions, charge reactivity increases compared to naturally aspirated conditions, and attenuation of knock by EGR is reduced.« less

The Reduced Effectiveness of EGR to Mitigate Knock at High Loads in Boosted SI Engines

DOE PAGES

Szybist, James P.; Wagnon, Scott W.; Splitter, Derek A.; ...

2017-09-04

Numerous studies have demonstrated that exhaust gas recirculation (EGR) can attenuate knock propensity in spark ignition (SI) engines at naturally aspirated or lightly boosted conditions. In this paper, we investigate the role of cooled EGR under higher load conditions with multiple fuel compositions, where highly retarded combustion phasing typical of modern SI engines was used. It was found that under these conditions, EGR attenuation of knock is greatly reduced, where EGR doesn’t allow significant combustion phasing advance as it does under lighter load conditions. Detailed combustion analysis shows that when EGR is added, the polytropic coefficient increases causing the compressivemore » pressure and temperature to increase. At sufficiently highly boosted conditions, the increase in polytropic coefficient and additional trapped mass from EGR can sufficiently reduce fuel ignition delay to overcome knock attenuation effects. Kinetic modeling demonstrates that the effectiveness of EGR to mitigate knock is highly dependent on the pressure-temperature condition. Experiments at 2000 rpm have confirmed reduced fuel ignition delay under highly boosted conditions relevant to modern downsized boosted SI engines, where in-cylinder pressure is higher and the temperature is cooler. Finally, at these conditions, charge reactivity increases compared to naturally aspirated conditions, and attenuation of knock by EGR is reduced.« less

Boost-phase discrimination research

NASA Technical Reports Server (NTRS)

Langhoff, Stephen R.; Feiereisen, William J.

1993-01-01

The final report describes the combined work of the Computational Chemistry and Aerothermodynamics branches within the Thermosciences Division at NASA Ames Research Center directed at understanding the signatures of shock-heated air. Considerable progress was made in determining accurate transition probabilities for the important band systems of NO that account for much of the emission in the ultraviolet region. Research carried out under this project showed that in order to reproduce the observed radiation from the bow shock region of missiles in their boost phase it is necessary to include the Burnett terms in the constituent equation, account for the non-Boltzmann energy distribution, correctly model the NO formation and rotational excitation process, and use accurate transition probabilities for the NO band systems. This work resulted in significant improvements in the computer code NEQAIR that models both the radiation and fluid dynamics in the shock region.

Accelerating atomistic simulations through self-learning bond-boost hyperdynamics

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

Perez, Danny; Voter, Arthur F

2008-01-01

By altering the potential energy landscape on which molecular dynamics are carried out, the hyperdynamics method of Voter enables one to significantly accelerate the simulation state-to-state dynamics of physical systems. While very powerful, successful application of the method entails solving the subtle problem of the parametrization of the so-called bias potential. In this study, we first clarify the constraints that must be obeyed by the bias potential and demonstrate that fast sampling of the biased landscape is key to the obtention of proper kinetics. We then propose an approach by which the bond boost potential of Miron and Fichthorn canmore » be safely parametrized based on data acquired in the course of a molecular dynamics simulation. Finally, we introduce a procedure, the Self-Learning Bond Boost method, in which the parametrization is step efficiently carried out on-the-fly for each new state that is visited during the simulation by safely ramping up the strength of the bias potential up to its optimal value. The stability and accuracy of the method are demonstrated.« less

Hyperdynamics boost factor achievable with an ideal bias potential

DOE PAGES

Huang, Chen; Perez, Danny; Voter, Arthur F.

2015-08-20

Hyperdynamics is a powerful method to significantly extend the time scales amenable to molecular dynamics simulation of infrequent events. One outstanding challenge, however, is the development of the so-called bias potential required by the method. In this work, we design a bias potential using information about all minimum energy pathways (MEPs) out of the current state. While this approach is not suitable for use in an actual hyperdynamics simulation, because the pathways are generally not known in advance, it allows us to show that it is possible to come very close to the theoretical boost limit of hyperdynamics while maintainingmore » high accuracy. We demonstrate this by applying this MEP-based hyperdynamics (MEP-HD) to metallic surface diffusion systems. In most cases, MEP-HD gives boost factors that are orders of magnitude larger than the best existing bias potential, indicating that further development of hyperdynamics bias potentials could have a significant payoff. Lastly, we discuss potential practical uses of MEP-HD, including the possibility of developing MEP-HD into a true hyperdynamics.« less

RandomizEd controlled trial for pre-operAtive dose-escaLation BOOST in locally advanced rectal cancer (RECTAL BOOST study): study protocol for a randomized controlled trial.

PubMed

Burbach, J P Maarten; Verkooijen, Helena M; Intven, Martijn; Kleijnen, Jean-Paul J E; Bosman, Mirjam E; Raaymakers, Bas W; van Grevenstein, Wilhelmina M U; Koopman, Miriam; Seravalli, Enrica; van Asselen, Bram; Reerink, Onne

2015-02-22

Treatment for locally advanced rectal cancer (LARC) consists of chemoradiation therapy (CRT) and surgery. Approximately 15% of patients show a pathological complete response (pCR). Increased pCR-rates can be achieved through dose escalation, thereby increasing the number patients eligible for organ-preservation to improve quality of life (QoL). A randomized comparison of 65 versus 50Gy with external-beam radiation alone has not yet been performed. This trial investigates pCR rate, clinical response, toxicity, QoL and (disease-free) survival in LARC patients treated with 65Gy (boost + chemoradiation) compared with 50Gy standard chemoradiation (sCRT). This study follows the 'cohort multiple randomized controlled trial' (cmRCT) design: rectal cancer patients are included in a prospective cohort that registers clinical baseline, follow-up, survival and QoL data. At enrollment, patients are asked consent to offer them experimental interventions in the future. Eligible patients-histologically confirmed LARC (T3NxM0 <1 mm from mesorectal fascia, T4NxM0 or TxN2M0) located ≤10 cm from the anorectal transition who provided consent for experimental intervention offers-form a subcohort (n = 120). From this subcohort, a random sample is offered the boost prior to sCRT (n = 60), which they may accept or refuse. Informed consent is signed only after acceptance of the boost. Non-selected patients in the subcohort (n = 60) undergo sCRT alone and are not notified that they participate in the control arm until the trial is completed. sCRT consists of 50Gy (25 × 2Gy) with concomitant capecitabine. The boost (without chemotherapy) is given prior to sCRT and consists of 15 Gy (5 × 3Gy) delivered to the gross tumor volume (GTV). The primary endpoint is pCR (TRG 1). Secondary endpoints include acute grade 3-4 toxicity, good pathologic response (TRG 1-2), clinical response, surgical complications, QoL and (disease-free) survival. Data is analyzed by intention to treat. The boost is

An Optimal t-{Delta}v Guidance Law for Intercepting a Boosting Target

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

Ng, L.C.; Breitfeller, E.; Ledebuhr, A.G.

2002-06-30

Lawrence Livermore National Laboratory (LLNL) have developed a new missile guidance law for intercepting a missile during boost phase. Unlike other known missile guidance laws being used today, the new t-{Delta}v guidance law optimally trades an interceptor's onboard fuel capacity against time-to-go before impact. In particular, this guidance law allows a missile designer to program the interceptor to maximally impact a boosting missile before burnout or burn termination and thus negating its ability to achieve the maximum kinetic velocity. For an intercontinental range ballistic missile (ICBM), it can be shown that for every second of earlier intercept prior to burnout,more » the ICBM ground range is reduced by 350 km. Therefore, intercepting a mere 15 seconds earlier would result in amiss of 5,250 km from the intended target or approximately a distance across the continental US. This paper also shows how the t-{Delta}v guidance law can incorporate uncertainties in target burnout time, predicted intercept point (PIP) error, time-to-go error, and other track estimation errors. The authors believe that the t-{Delta}v guidance law is a step toward the development of a new and smart missile guidance law that would enhance the probability of achieving a boost phase intercept.« less

Boosted protease inhibitor monotherapy in HIV-infected adults: outputs from a pan-European expert panel meeting

PubMed Central

2013-01-01

While the introduction of combination highly active antiretroviral therapy (HAART) regimens represents an important advance in the management of human immunodeficiency virus (HIV)-infected patients, tolerability can be an issue and the use of several different agents may produce problems. The switch of combination HAART to ritonavir-boosted protease inhibitor (PI) monotherapy may offer the opportunity to maintain antiviral efficacy while reducing treatment complexity and the risks of toxicity. Current European AIDS Clinical Society (EACS) guidelines recognise ritonavir-boosted PI monotherapy with twice-daily lopinavir/ritonavir or once-daily darunavir/ritonavir as a possible option in patients who have intolerance to nucleoside reverse transcriptase inhibitors, or for treatment simplification. Clinical trials data for PI boosted monotherapy are encouraging, showing substantial efficacy in the majority of patients; however, further data are required before this approach can be recommended as a routine treatment. Available data indicate that the most suitable candidates for the use of boosted PI monotherapy are long-term virologically suppressed patients who have demonstrated good adherence to antiretroviral therapy, who do not have chronic hepatitis B, have no history of treatment failure on PIs and are able to tolerate low-dose ritonavir. PMID:23347595

Better imagined: Neural correlates of the episodic simulation boost to prospective memory performance.

PubMed

Spreng, R Nathan; Madore, Kevin P; Schacter, Daniel L

2018-05-01

Episodic simulation is an adaptive process that can support goal-directed activity and planning success. We investigated the neural architecture associated with the episodic simulation improvement to the likelihood of carrying out future actions by isolating the brain regions associated with this facilitation in a prospective memory paradigm. Participants performed a lexical decision task by making word/non-word judgments, with rarely occurring prospective memory target words requiring a pre-specified manual response. Prior to scanning, participants were given exposure to two lists of prospective memory targets: animals and tools. In a fully counterbalanced design, participants generated a rhyme to one target list and imagined their subsequent encounter (episodic simulation) with target words on the other list. Replicating prior behavioral work, episodic simulation improved subsequent prospective memory performance. Brain activation was assessed in a multivariate partial least squares analysis. Relative to lexical decision blocks with no prospective memory demand, sustained prospective memory replicated prior observations of frontal polar activation. Critically, maintaining the intention to respond to simulated targets, over and above rhyme targets, engaged middle frontal and angular gyri, and medial parietal and prefrontal cortices. Transient activity associated with prospective memory target hits revealed activation for simulated targets in medial prefrontal cortex, posterior cingulate, lateral temporal lobe and inferior parietal lobule. In contrast, rhyme target hits engaged more left lateralized dorsolateral prefrontal cortex and anterior insula. Episodic simulation, thus effectively shifts executive control strategy and boosts task performance. These results are consistent with a growing body of evidence implicating executive control and default network region interactions in adaptive, goal-directed behavior. Copyright © 2018 Elsevier Ltd. All rights reserved.

Responsivity boosting in FIR TiN LEKIDs using phonon recycling: simulations and array design

NASA Astrophysics Data System (ADS)

Fyhrie, Adalyn; McKenney, Christopher; Glenn, Jason; LeDuc, Henry G.; Gao, Jiansong; Day, Peter; Zmuidzinas, Jonas

2016-07-01

To characterize further the cosmic star formation history at high redshifts, a large-area survey by a cryogenic 4-6 meter class telescope with a focal plane populated by tens of thousands of far-infrared (FIR, 30-300 μm) detectors with broadband detector noise equivalent powers (NEPs) on the order of 3×10-9 W/√ Hz is needed. Ideal detectors for such a surveyor do not yet exist. As a demonstration of one technique for approaching the ultra-low NEPs required by this surveyor, we present the design of an array of 96 350 µm KIDs that utilize phonon recycling to boost responsivity. Our KID array is fabricated with TiN deposited on a silicon-on-insulator (SOI) wafer, which is a 2 μm thick layer of silicon bonded to a thicker slab of silicon by a thin oxide layer. The backside thick slab is etched away underneath the absorbers so that the inductors are suspended on just the 2 μm membrane. The intent is that quasiparticle recombination phonons are trapped in the thin membrane, thereby increasing their likelihood of being re-absorbed by the KID to break additional Cooper pairs and boost responsivity. We also present a Monte-Carlo simulation that predicts the amount of signal boost expected from phonon recycling given different detector geometries and illumination strategies. For our current array geometry, the simulation predicts a measurable 50% boost in responsivity.

DNA prime–protein boost increased the titer, avidity and persistence of anti-Aβ antibodies in wild-type mice

PubMed Central

Davtyan, H; Mkrtichyan, M; Movsesyan, N; Petrushina, I; Mamikonyan, G; Cribbs, DH; Agadjanyan, MG; Ghochikyan, A

2010-01-01

Recently, we reported that a DNA vaccine, composed of three copies of a self B cell epitope of amyloid-β (Aβ42) and the foreign T-cell epitope, Pan DR epitope (PADRE), generated strong anti-Aβ immune responses in wild-type and amyloid precursor protein transgenic animals. Although DNA vaccines have several advantages over peptide–protein vaccines, they induce lower immune responses in large animals and humans compared with those in mice. The focus of this study was to further enhance anti-Aβ11 immune responses by developing an improved DNA vaccination protocol of the prime–boost regimen, in which the priming step would use DNA and the boosting step would use recombinant protein. Accordingly, we generated DNA and recombinant protein-based epitope vaccines and showed that priming with DNA followed by boosting with a homologous recombinant protein vaccine significantly increases the anti-Aβ antibody responses and do not change the immunoglobulin G1 (IgG1) profile of humoral immune responses. Furthermore, the antibodies generated by this prime–boost regimen were long-lasting and possessed a higher avidity for binding with an Aβ42 peptide. Thus, we showed that a heterologous prime–boost regimen could be an effective protocol for developing a potent Alzheimer’s disease (AD) vaccine. PMID:19865176

Outcomes of uterine cervical cancer patients with pelvic lymph node metastases after radiotherapy without boost irradiation of metastases.

PubMed

Yoshizawa, Eriko; Koiwai, Keiichiro; Ina, Hironobu; Fukazawa, Ayumu; Sakai, Katsuya; Ozawa, Takesumi; Matsushita, Hirohide; Kadoya, Masumi

2017-04-01

The aim of this study was to evaluate the outcomes of uterine cervical cancer patients with pelvic lymph node (PLN) metastases after radiotherapy without boost irradiation of the metastases and to clarify the necessity of the boost irradiation of metastatic lesions. Thirty-two patients with uterine cervical cancer metastasizing only to the PLN were treated with definitive radiotherapy without boost irradiation of the metastases between 2008 and 2012 at our institution and were selected for this study. The pattern of progression, overall survival, and progression-free survival were analyzed. Ninety percent of the PLN metastases were controlled by radiotherapy. Twenty-two of 32 patients (69%) experienced progression. Distant metastases as initial progression were observed in 21 of these 22 patients (95%). Only two patients experienced failures in pre-treatment metastatic PLN as initial progression, along with other failures. Severe late lower gastrointestinal toxicities were not observed in any patients. Two-year cumulative overall survival and progression-free survival were 74% and 31%, respectively. Boost irradiation of PLN metastases is not necessarily indispensable. Further studies to examine the necessity of boost irradiation of PLN metastases in radiotherapy for uterine cervical cancer patients with metastases are required. © 2017 Japan Society of Obstetrics and Gynecology.

Boosting the Direct CP Measurement of the Higgs-Top Coupling.

PubMed

Buckley, Matthew R; Gonçalves, Dorival

2016-03-04

Characterizing the 125 GeV Higgs boson is a critical component of the physics program at the LHC Run II. In this Letter, we consider tt[over ¯]H associated production in the dileptonic mode. We demonstrate that the difference in azimuthal angle between the leptons from top decays can directly reveal the CP structure of the top-Higgs coupling with the sensitivity of the measurement substantially enhanced in the boosted Higgs regime. We first show how to access this channel via H→bb[over ¯] jet-substructure tagging, then demonstrate the ability of the new variable to measure CP. Our analysis includes all signal and background samples simulated via the MC@NLO algorithm including hadronization and underlying-event effects. Using a boosted Higgs substructure with dileptonic tops, we find that the top-Higgs coupling strength and the CP structure can be directly probed with achievable luminosity at the 13 TeV LHC.

Boosting the Light: X-ray Physics in Confinement

ScienceCinema

Rhisberger, Ralf [HASYLAB/ DESY

2017-12-09

Remarkable effects are observed if light is confined to dimensions comparable to the wavelength of the light. The lifetime of atomic resonances excited by the radiation is strongly reduced in photonic traps, such as cavities or waveguides. Moreover, one observes an anomalous boost of the intensity scattered from the resonant atoms. These phenomena results from the strong enhancement of the photonic density of states in such geometries. Many of these effects are currently being explored in the regime of vsible light due to their relevance for optical information processing. It is thus appealing to study these phenomena also for much shorter wavelengths. This talk illuminates recent experiments where synchrotron x-rays were trapped in planar waveguides to resonantly excite atomos ([57]Fe nuclei_ embedded in them. In fact, one observes that the radiative decay of these excited atoms is strongly accelerated. The temporal acceleration of the decay goes along with a strong boost of the radiation coherently scattered from the confined atmos. This can be exploited to obtain a high signal-to-noise ratio from tiny quantities of material, leading to manifold applications in the investigation of nanostructured materials. One application is the use of ultrathin probe layers to image the internal structure of magnetic layer systems.

Boosting Long-Term Memory via Wakeful Rest: Intentional Rehearsal Is Not Necessary, Consolidation Is Sufficient

PubMed Central

Dewar, Michaela; Alber, Jessica; Cowan, Nelson; Della Sala, Sergio

2014-01-01

People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as ‘foreign names in a bridge club abroad’ and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is not dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is sufficient for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition. PMID:25333957

Gradient boosting machine for modeling the energy consumption of commercial buildings

DOE PAGES

Touzani, Samir; Granderson, Jessica; Fernandes, Samuel

2017-11-26

Accurate savings estimations are important to promote energy efficiency projects and demonstrate their cost-effectiveness. The increasing presence of advanced metering infrastructure (AMI) in commercial buildings has resulted in a rising availability of high frequency interval data. These data can be used for a variety of energy efficiency applications such as demand response, fault detection and diagnosis, and heating, ventilation, and air conditioning (HVAC) optimization. This large amount of data has also opened the door to the use of advanced statistical learning models, which hold promise for providing accurate building baseline energy consumption predictions, and thus accurate saving estimations. The gradientmore » boosting machine is a powerful machine learning algorithm that is gaining considerable traction in a wide range of data driven applications, such as ecology, computer vision, and biology. In the present work an energy consumption baseline modeling method based on a gradient boosting machine was proposed. To assess the performance of this method, a recently published testing procedure was used on a large dataset of 410 commercial buildings. The model training periods were varied and several prediction accuracy metrics were used to evaluate the model's performance. The results show that using the gradient boosting machine model improved the R-squared prediction accuracy and the CV(RMSE) in more than 80 percent of the cases, when compared to an industry best practice model that is based on piecewise linear regression, and to a random forest algorithm.« less

Gradient boosting machine for modeling the energy consumption of commercial buildings

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

Touzani, Samir; Granderson, Jessica; Fernandes, Samuel

Accurate savings estimations are important to promote energy efficiency projects and demonstrate their cost-effectiveness. The increasing presence of advanced metering infrastructure (AMI) in commercial buildings has resulted in a rising availability of high frequency interval data. These data can be used for a variety of energy efficiency applications such as demand response, fault detection and diagnosis, and heating, ventilation, and air conditioning (HVAC) optimization. This large amount of data has also opened the door to the use of advanced statistical learning models, which hold promise for providing accurate building baseline energy consumption predictions, and thus accurate saving estimations. The gradientmore » boosting machine is a powerful machine learning algorithm that is gaining considerable traction in a wide range of data driven applications, such as ecology, computer vision, and biology. In the present work an energy consumption baseline modeling method based on a gradient boosting machine was proposed. To assess the performance of this method, a recently published testing procedure was used on a large dataset of 410 commercial buildings. The model training periods were varied and several prediction accuracy metrics were used to evaluate the model's performance. The results show that using the gradient boosting machine model improved the R-squared prediction accuracy and the CV(RMSE) in more than 80 percent of the cases, when compared to an industry best practice model that is based on piecewise linear regression, and to a random forest algorithm.« less

Learning Instance-Specific Predictive Models

PubMed Central

Visweswaran, Shyam; Cooper, Gregory F.

2013-01-01

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms. PMID:25045325

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

PubMed

Niu, Bing; Yuan, Xiao-Cheng; Roeper, Preston; Su, Qiang; Peng, Chun-Rong; Yin, Jing-Yuan; Ding, Juan; Li, HaiPeng; Lu, Wen-Cong

2013-03-01

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.

Designing of new structure PID controller of boost converter for solar photovoltaic stability

NASA Astrophysics Data System (ADS)

Shabrina, Hanifati Nur; Setiawan, Eko Adhi; Sabirin, Chip Rinaldi

2017-03-01

Nowadays, the utilization of renewable energy as the source on distributed generation system is increasing. It aims to reduce reliance and power losses from utility grid and improve power stability in near loads. One example of renewable energy technology that have been highly proven on the market is solar photovoltaic (PV). This technology converts photon from sunlight into electricity. However, the fluctuation of solar radiation that often occurs become the main problem for this system. Due to this condition, the power conversion is needed to convert the change frequently in photovoltaic panel into a stable voltage to the system. Developing control of boost converter has important role to keep ability of system stabilization. A conventional PID (Proportional, Integral, Derivative) control is mostly used to achieve this goal. In this research, a design of new structure PID controller of boost converter is offered to better optimize system stability comparing to the conventional PID. Parameters obtained from this PID structure have been successfully yield a stable boost converter output at 200 V with 10% overshoot, 1.5 seconds of settling time, and 1.5% of steady-state error.

Bayesian Mapping Reveals That Attention Boosts Neural Responses to Predicted and Unpredicted Stimuli.

PubMed

Garrido, Marta I; Rowe, Elise G; Halász, Veronika; Mattingley, Jason B

2018-05-01

Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between 2 alternative computational models. The "Opposition" model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the "Interaction" model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modeling showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.

Copper-boosting compounds: a novel concept for antimycobacterial drug discovery.

PubMed

Speer, Alexander; Shrestha, Tej B; Bossmann, Stefan H; Basaraba, Randall J; Harber, Gregory J; Michalek, Suzanne M; Niederweis, Michael; Kutsch, Olaf; Wolschendorf, Frank

2013-02-01

We and others recently identified copper resistance as important for virulence of Mycobacterium tuberculosis. Here, we introduce a high-throughput screening assay for agents that induce a copper hypersensitivity phenotype in M. tuberculosis and demonstrate that such copper-boosting compounds are effective against replicating and nonreplicating M. tuberculosis strains.

Dichroic subjettiness ratios to distinguish colour flows in boosted boson tagging

NASA Astrophysics Data System (ADS)

Salam, Gavin P.; Schunk, Lais; Soyez, Gregory

2017-03-01

N-subjettiness ratios are in wide use for tagging heavy boosted objects, in particular the ratio of 2-subjettiness to 1-subjettiness for tagging boosted electroweak bosons. In this article we introduce a new, dichroic ratio, which uses different regions of a jet to determine the two subjettiness measures, emphasising the hard substructure for the 1-subjettiness and the full colour radiation pattern for the 2-subjettiness. Relative to existing N -subjettiness ratios, the dichroic extension, combined with SoftDrop (pre-)grooming, makes it possible to increase the ultimate signal significance by about 25% (for 2 TeV jets), or to reduce non-perturbative effects by a factor of 2-3 at 50% signal efficiency while maintaining comparable background rejection. We motivate the dichroic approach through the study of Lund diagrams, supplemented with resummed analytical calculations.

Imputing data that are missing at high rates using a boosting algorithm

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

Cauthen, Katherine Regina; Lambert, Gregory; Ray, Jaideep

Traditional multiple imputation approaches may perform poorly for datasets with high rates of missingness unless many m imputations are used. This paper implements an alternative machine learning-based approach to imputing data that are missing at high rates. Here, we use boosting to create a strong learner from a weak learner fitted to a dataset missing many observations. This approach may be applied to a variety of types of learners (models). The approach is demonstrated by application to a spatiotemporal dataset for predicting dengue outbreaks in India from meteorological covariates. A Bayesian spatiotemporal CAR model is boosted to produce imputations, andmore » the overall RMSE from a k-fold cross-validation is used to assess imputation accuracy.« less

Modular high-voltage bias generator powered by dual-looped self-adaptive wireless power transmission.

PubMed

Xie, Kai; Huang, An-Feng; Li, Xiao-Ping; Guo, Shi-Zhong; Zhang, Han-Lu

2015-04-01

We proposed a modular high-voltage (HV) bias generator powered by a novel transmitter-sharing inductive coupled wireless power transmission technology, aimed to extend the generator's flexibility and configurability. To solve the problems caused through an uncertain number of modules, a dual-looped self-adaptive control method is proposed that is capable of tracking resonance frequency while maintaining a relatively stable induction voltage for each HV module. The method combines a phase-locked loop and a current feedback loop, which ensures an accurate resonance state and a relatively constant boost ratio for each module, simplifying the architecture of the boost stage and improving the total efficiency. The prototype was built and tested. The input voltage drop of each module is less than 14% if the module number varies from 3 to 10; resonance tracking is completed within 60 ms. The efficiency of the coupling structure reaches up to 95%, whereas the total efficiency approaches 73% for a rated output. Furthermore, this technology can be used in various multi-load wireless power supply applications.

Boosting of HIV-1 Neutralizing Antibody Responses by a Distally Related Retroviral Envelope Protein

PubMed Central

Uchtenhagen, Hannes; Schiffner, Torben; Bowles, Emma; Heyndrickx, Leo; LaBranche, Celia; Applequist, Steven E.; Jansson, Marianne; De Silva, Thushan; Back, Jaap Willem; Achour, Adnane; Scarlatti, Gabriella; Fomsgaard, Anders; Montefiori, David; Stewart-Jones, Guillaume; Spetz, Anna-Lena

2014-01-01

Our knowledge of the binding sites for neutralizing antibodies (NAbs) that recognize a broad range of HIV-1 strains (bNAb) has substantially increased in recent years. However, gaps remain in our understanding of how to focus B-cell responses to vulnerable conserved sites within the HIV-1 envelope glycoprotein (Env). Here we report an immunization strategy composed of a trivalent HIV-1 (clade B envs) DNA prime, followed by a SIVmac239 gp140 Env protein boost that aimed to focus the immune response to structurally conserved parts of the HIV-1 and SIV Envs. Heterologous NAb titres, primarily to tier 1 HIV-1 isolates, elicited during the trivalent HIV-1 env prime, were significantly increased by the SIVmac239 gp140 protein boost in rabbits. Epitope mapping of antibody binding reactivity revealed preferential recognition of the C1, C2, V2, V3 and V5 regions. These results provide a proof of concept that a distally related retroviral SIV Env protein boost can increase pre-existing NAb responses against HIV-1. PMID:24829409

Investigation of the charge boost technology for the efficiency increase of closed sorption thermal energy storage systems

NASA Astrophysics Data System (ADS)

Rohringer, C.; Engel, G.; Köll, R.; Wagner, W.; van Helden, W.

2017-10-01

The inclusion of solar thermal energy into energy systems requires storage possibilities to overcome the gap between supply and demand. Storage of thermal energy with closed sorption thermal energy systems has the advantage of low thermal losses and high energy density. However, the efficiency of these systems needs yet to be increased to become competitive on the market. In this paper, the so-called “charge boost technology” is developed and tested via experiments as a new concept for the efficiency increase of compact thermal energy storages. The main benefit of the charge boost technology is that it can reach a defined state of charge for sorption thermal energy storages at lower temperature levels than classic pure desorption processes. Experiments are conducted to provide a proof of principle for this concept. The results show that the charge boost technology does function as predicted and is a viable option for further improvement of sorption thermal energy storages. Subsequently, a new process application is developed by the author with strong focus on the utilization of the advantages of the charge boost technology over conventional desorption processes. After completion of the conceptual design, the theoretical calculations are validated via experiments.

Stratiform/convective rain delineation for TRMM microwave imager

NASA Astrophysics Data System (ADS)

Islam, Tanvir; Srivastava, Prashant K.; Dai, Qiang; Gupta, Manika; Wan Jaafar, Wan Zurina

2015-10-01

This article investigates the potential for using machine learning algorithms to delineate stratiform/convective (S/C) rain regimes for passive microwave imager taking calibrated brightness temperatures as only spectral parameters. The algorithms have been implemented for the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI), and calibrated as well as validated taking the Precipitation Radar (PR) S/C information as the target class variables. Two different algorithms are particularly explored for the delineation. The first one is metaheuristic adaptive boosting algorithm that includes the real, gentle, and modest versions of the AdaBoost. The second one is the classical linear discriminant analysis that includes the Fisher's and penalized versions of the linear discriminant analysis. Furthermore, prior to the development of the delineation algorithms, a feature selection analysis has been conducted for a total of 85 features, which contains the combinations of brightness temperatures from 10 GHz to 85 GHz and some derived indexes, such as scattering index, polarization corrected temperature, and polarization difference with the help of mutual information aided minimal redundancy maximal relevance criterion (mRMR). It has been found that the polarization corrected temperature at 85 GHz and the features derived from the "addition" operator associated with the 85 GHz channels have good statistical dependency to the S/C target class variables. Further, it has been shown how the mRMR feature selection technique helps to reduce the number of features without deteriorating the results when applying through the machine learning algorithms. The proposed scheme is able to delineate the S/C rain regimes with reasonable accuracy. Based on the statistical validation experience from the validation period, the Matthews correlation coefficients are in the range of 0.60-0.70. Since, the proposed method does not rely on any a priori information, this makes it very

The attentional boost effect and context memory.

PubMed

Mulligan, Neil W; Smith, S Adam; Spataro, Pietro

2016-04-01

Stimuli co-occurring with targets in a detection task are better remembered than stimuli co-occurring with distractors-the attentional boost effect (ABE). The ABE is of interest because it is an exception to the usual finding that divided attention during encoding impairs memory. The effect has been demonstrated in tests of item memory but it is unclear if context memory is likewise affected. Some accounts suggest enhanced perceptual encoding or associative binding, predicting an ABE on context memory, whereas other evidence suggests a more abstract, amodal basis of the effect. In Experiment 1, context memory was assessed in terms of an intramodal perceptual detail, the font and color of the study word. Experiment 2 examined context memory cross-modally, assessing memory for the modality (visual or auditory) of the study word. Experiments 3 and 4 assessed context memory with list discrimination, in which 2 study lists are presented and participants must later remember which list (if either) a test word came from. In all experiments, item (recognition) memory was also assessed and consistently displayed a robust ABE. In contrast, the attentional-boost manipulation did not enhance context memory, whether defined in terms of visual details, study modality, or list membership. There was some evidence that the mode of responding on the detection task (motoric response as opposed to covert counting of targets) may impact context memory but there was no evidence of an effect of target detection, per se. In sum, the ABE did not occur in context memory with verbal materials. (c) 2016 APA, all rights reserved).

Risk factors for pre-term birth in a Canadian cohort of HIV-positive women: role of ritonavir boosting?

PubMed Central

Kakkar, Fatima; Boucoiran, Isabelle; Lamarre, Valerie; Ducruet, Thierry; Amre, Devendra; Soudeyns, Hugo; Lapointe, Normand; Boucher, Marc

2015-01-01

Background The risk of pre-term birth (PTB) associated with the use of protease inhibitors (PIs) during pregnancy remains a subject of debate. Recent data suggest that ritonavir boosting of PIs may play a specific role in the initiation of PTB, through an effect on the maternal–fetal adrenal axis. The primary objective of this study is to compare the risk of PTB among women treated with boosted PI versus non-boosted PIs during pregnancy. Methods Between 1988 and 2011, 705 HIV-positive women were enrolled into the Centre Maternel et Infantile sur le SIDA mother–infant cohort at Centre Hospitalier Universitaire Sainte-Justine in Montreal, Canada. Inclusion criteria for the study were: 1) attendance at a minimum of two antenatal obstetric visits and 2) singleton live birth, at 24 weeks gestational or older. The association between PTB (defined as delivery at <37 weeks gestational age), antiretroviral drug exposure and maternal risk factors was assessed retrospectively using logistic regression. Results A total of 525 mother–infant pairs were included in the analysis. Among them, PI-based combination anti-retroviral therapy was used in 37.4%, boosted PI based in 24.4%, non-nucleoside reverse transcriptase inhibitor (NNRTI) or nucleoside reverse transcriptase inhibitor based in 28.1%, and no treatment was given in 10.0% of cases. Overall, 13.5% of women experienced PTB. Among women treated with antiretroviral therapy, the risk of PTB was significantly higher among women who received boosted versus non-boosted PI (OR 2.01, 95% CI 1.02–3.97). This remained significant after adjusting for maternal age, delivery CD4 count, hepatitis C co-infection, history of previous PTB, and parity (aOR 2.17, 95% CI 1.05–4.51). There was no increased risk of PTB with the use of unboosted PIs as compared to NNRTI- or NRTI-based regimens. Conclusion While previous studies on the association between PTB and PI use have generally considered all PIs the same, our results would

Whole-Brain Radiotherapy With Simultaneous Integrated Boost to Multiple Brain Metastases Using Volumetric Modulated Arc Therapy

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

Lagerwaard, Frank J.; Hoorn, Elles A.P. van der; Verbakel, Wilko

2009-09-01

Purpose: Volumetric modulated arc therapy (RapidArc [RA]; Varian Medical Systems, Palo Alto, CA) allows for the generation of intensity-modulated dose distributions by use of a single gantry rotation. We used RA to plan and deliver whole-brain radiotherapy (WBRT) with a simultaneous integrated boost in patients with multiple brain metastases. Methods and Materials: Composite RA plans were generated for 8 patients, consisting of WBRT (20 Gy in 5 fractions) with an integrated boost, also 20 Gy in 5 fractions, to Brain metastases, and clinically delivered in 3 patients. Summated gross tumor volumes were 1.0 to 37.5 cm{sup 3}. RA plans weremore » measured in a solid water phantom by use of Gafchromic films (International Specialty Products, Wayne, NJ). Results: Composite RA plans could be generated within 1 hour. Two arcs were needed to deliver the mean of 1,600 monitor units with a mean 'beam-on' time of 180 seconds. RA plans showed excellent coverage of planning target volume for WBRT and planning target volume for the boost, with mean volumes receiving at least 95% of the prescribed dose of 100% and 99.8%, respectively. The mean conformity index was 1.36. Composite plans showed much steeper dose gradients outside Brain metastases than plans with a conventional summation of WBRT and radiosurgery. Comparison of calculated and measured doses showed a mean gamma for double-arc plans of 0.30, and the area with a gamma larger than 1 was 2%. In-room times for clinical RA sessions were approximately 20 minutes for each patient. Conclusions: RA treatment planning and delivery of integrated plans of WBRT and boosts to multiple brain metastases is a rapid and accurate technique that has a higher conformity index than conventional summation of WBRT and radiosurgery boost.« less

Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

PubMed Central

Austin, Peter C; Lee, Douglas S

2011-01-01

Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

Marine reserves can mitigate and promote adaptation to climate change

PubMed Central

Roberts, Callum M.; O’Leary, Bethan C.; McCauley, Douglas J.; Cury, Philippe Maurice; Duarte, Carlos M.; Lubchenco, Jane; Pauly, Daniel; Sáenz-Arroyo, Andrea; Sumaila, Ussif Rashid; Wilson, Rod W.; Worm, Boris; Castilla, Juan Carlos

2017-01-01

Strong decreases in greenhouse gas emissions are required to meet the reduction trajectory resolved within the 2015 Paris Agreement. However, even these decreases will not avert serious stress and damage to life on Earth, and additional steps are needed to boost the resilience of ecosystems, safeguard their wildlife, and protect their capacity to supply vital goods and services. We discuss how well-managed marine reserves may help marine ecosystems and people adapt to five prominent impacts of climate change: acidification, sea-level rise, intensification of storms, shifts in species distribution, and decreased productivity and oxygen availability, as well as their cumulative effects. We explore the role of managed ecosystems in mitigating climate change by promoting carbon sequestration and storage and by buffering against uncertainty in management, environmental fluctuations, directional change, and extreme events. We highlight both strengths and limitations and conclude that marine reserves are a viable low-tech, cost-effective adaptation strategy that would yield multiple cobenefits from local to global scales, improving the outlook for the environment and people into the future. PMID:28584096

Marine reserves can mitigate and promote adaptation to climate change.

PubMed

Roberts, Callum M; O'Leary, Bethan C; McCauley, Douglas J; Cury, Philippe Maurice; Duarte, Carlos M; Lubchenco, Jane; Pauly, Daniel; Sáenz-Arroyo, Andrea; Sumaila, Ussif Rashid; Wilson, Rod W; Worm, Boris; Castilla, Juan Carlos

2017-06-13

Strong decreases in greenhouse gas emissions are required to meet the reduction trajectory resolved within the 2015 Paris Agreement. However, even these decreases will not avert serious stress and damage to life on Earth, and additional steps are needed to boost the resilience of ecosystems, safeguard their wildlife, and protect their capacity to supply vital goods and services. We discuss how well-managed marine reserves may help marine ecosystems and people adapt to five prominent impacts of climate change: acidification, sea-level rise, intensification of storms, shifts in species distribution, and decreased productivity and oxygen availability, as well as their cumulative effects. We explore the role of managed ecosystems in mitigating climate change by promoting carbon sequestration and storage and by buffering against uncertainty in management, environmental fluctuations, directional change, and extreme events. We highlight both strengths and limitations and conclude that marine reserves are a viable low-tech, cost-effective adaptation strategy that would yield multiple cobenefits from local to global scales, improving the outlook for the environment and people into the future.

Quality of Life in Women Undergoing Breast Irradiation in a Randomized, Controlled Clinical Trial Evaluating Different Tumor Bed Boost Fractionations

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

Finkel, Morgan A.; Cooper, Benjamin T.; Li, Xiaochun

Purpose: To identify differences in breast cancer patient-reported quality of life (QOL) between 2 radiation tumor bed boost dose regimens. Methods and Materials: Four hundred patients with stage 0, I, or II breast cancer who underwent segmental mastectomy with sentinel node biopsy and/or axillary node dissection were treated with either a daily or weekly boost. Patients were treated prone to 40.5 Gy/15 fractions to the whole breast, 5 days per week. Patients were randomized to a concomitant daily boost to the tumor bed of 0.5 Gy, or a weekly boost of 2 Gy on Friday. Patients completed 6 validated QOL survey instruments at baseline,more » last week of treatment (3 weeks), 45-60 days from the completion of radiation treatment, and at 2-year follow-up. Results: There were no statistically significance differences in responses to the 6 QOL instruments between the daily and weekly radiation boost regimens, even after adjustment for important covariates. However, several changes in responses over time occurred in both arms, including worsening functional status, cosmetic status, and breast-specific pain at the end of treatment as compared with before and 45 to 60 days after the conclusion of treatment. Conclusions: Whole-breast, prone intensity modulated radiation has similar outcomes in QOL measures whether given with a daily or weekly boost. This trial has generated the foundation for a current study of weekly versus daily radiation boost in women with early breast cancer in which 3-dimensional conformal radiation is allowed as a prospective stratification factor.« less

Historical and Current U.S. Strategies for Boosting Distributed Generation

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

Lowder, Travis; Schwabe, Paul; Zhou, Ella

2015-10-29

This report seeks to introduce a variety of top-down and bottom-up practices that, in concert with the macro-environment of cost-reduction globally and early adoption in Europe, helped boost the distributed generation photovoltaic market in the United States. These experiences may serve as a reference in China's quest to promote distributed renewable energy.

Degrees of Difficulty: Boosting College Success in New York City

ERIC Educational Resources Information Center

Hilliard, Tom

2017-01-01

This report, the latest in a series of studies by the Center for an Urban Future examining opportunities to expand economic mobility in New York City, takes an in-depth look at college readiness and success among the city's public high school students. It explores opportunities to dramatically boost the rate at which New York City's students enter…

How attentional boost interacts with reward: the effect of dopaminergic medications in Parkinson's disease.

PubMed

Kéri, Szabolcs; Nagy, Helga; Levy-Gigi, Einat; Kelemen, Oguz

2013-12-01

There is widespread evidence that dopamine is implicated in the regulation of reward and salience. However, it is less known how these processes interact with attention and recognition memory. To explore this question, we used the attentional boost test in patients with Parkinson's disease (PD) before and after the administration of dopaminergic medications. Participants performed a visual letter detection task (remembering rewarded target letters and ignoring distractor letters) while also viewing a series of photos of natural and urban scenes in the background of the letters. The aim of the game was to retrieve the target letter after each trial and to win as much virtual money as possible. The recognition of background scenes was not rewarded. We enrolled 26 drug-naïve, newly diagnosed patients with PD and 25 healthy controls who were evaluated at baseline and follow-up. Patients with PD received dopamine agonists (pramipexole, ropinirole, rotigotine) during the 12-week follow-up period. At baseline, we found intact attentional boost in patients with PD: they were able to recognize target-associated scenes similarly to controls. At follow-up, patients with PD outperformed controls for both target- and distractor-associated scenes, but not when scenes were presented without letters. The alerting, orienting and executive components of attention were intact in PD. Enhanced attentional boost was replicated in a smaller group of patients with PD (n = 15) receiving l-3,4-dihydroxyphenylalanine (L-DOPA). These results suggest that dopaminergic medications facilitate attentional boost for background information regardless of whether the central task (letter detection) is rewarded or not. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The Role of Concomitant Radiation Boost in Neoadjuvant Chemoradiotherapy for Locally Advanced Rectal Cancer.

PubMed

Badakhshi, Harun; Ismail, Mahmoud; Boskos, Christos; Zhao, Kuaile; Kaul, David

2017-06-01

This study analyzed the impact of concomitant boost on long-term clinical outcomes in locally advanced rectal cancer. A total of 141 patients (median age=61 years) were treated with neoadjuvant chemoradiotherapy. Median total dose was 50.4 Gy. Forty-three patients received a concomitant boost. Concurrent chemotherapy consisted of 5-fluorouracil (5-FU), given as a 24-h continuous infusion. Mean follow-up was 83.7 months. The 3, 5-, and 10-year overall survival (OS) rates were 91.9%, 84.6%, and 52.9%, respectively. Recurrence-free survival (RFS) rates at 3, 5, and 10 years were 91.4%, 88.9%, and 79.3%, respectively. Metastasis-free survival (MFS) rates at 3, 5, and 10 years were 84.6%, 75.4%, and 49.9%, respectively. Overall, 9.9% of all patients achieved pathological complete response. Down-staging of T- or N-stage was achieved in 55.1% and 41.5% of patients. Multivariate analysis revealed that female sex (p=0.011), concomitant boost-radiotherapy (p=0.014), and the presence of fewer than five positive lymph nodes (p<0.001) were positive predictors of OS. Fewer than five positive lymph nodes was also a positive predictor for RFS (p=0.019). Female gender (p=0.018) and fewer than five positive lymph nodes (p<0.001) were significant predictors for MFS. Our data support the efficacy of preoperative treatment for rectal cancer in terms of local outcomes. Intensified radiotherapy using a concomitant boost has a positive effect on OS. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

A boosting skin vaccination with dissolving microneedle patch encapsulating M2e vaccine broadens the protective efficacy of conventional influenza vaccines.

PubMed

Zhu, Wandi; Pewin, Winston; Wang, Chao; Luo, Yuan; Gonzalez, Gilbert X; Mohan, Teena; Prausnitz, Mark R; Wang, Bao-Zhong

2017-09-10

The biodegradable microneedle patch (MNP) is a novel technology for vaccine delivery that could improve the immunogenicity of vaccines. To broaden the protective efficiency of conventional influenza vaccines, a new 4M2e-tFliC fusion protein construct containing M2e sequences from different subtypes was generated. Purified fusion protein was encapsulate into MNPs with a biocompatible polymer for use as a boosting vaccine. The results demonstrated that mice receiving a conventional inactivated vaccine followed by a skin-applied dissolving 4M2e-tFliC MNP boost could better maintain the humoral antibody response than that by the conventional vaccine-prime alone. Compared with an intramuscular injection boost, mice receiving the MNP boost showed significantly enhanced cellular immune responses, hemagglutination-inhibition (HAI) titers, and neutralization titers. Increased frequency of antigen-specific plasma cells and long-lived bone marrow plasma cells was detected in the MNP boosted group as well, indicating that skin vaccination with 4M2e-tFliC facilitated a long-term antibody-mediated immunity. The 4M2e-tFliC MNP-boosted group also possessed enhanced protection against high lethal dose challenges against homologous A/PR/8/34 and A/Aichi/2/68 viruses and protection for a majority of immunized mice against a heterologous A/California/07/2009 H1N1 virus. High levels of M2e specific immune responses were observed in the 4M2e-tFliC MNP-boosted group as well. These results demonstrate that a skin-applied 4M2e-tFliC MNP boosting immunization to seasonal vaccine recipients may be a rapid approach for increasing the protective efficacy of seasonal vaccines in response to a significant drift seen in circulating viruses. The results also provide a new perspective for future exploration of universal influenza vaccines. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiratio fusion change detection with adaptive thresholding

NASA Astrophysics Data System (ADS)

Hytla, Patrick C.; Balster, Eric J.; Vasquez, Juan R.; Neuroth, Robert M.

2017-04-01

A ratio-based change detection method known as multiratio fusion (MRF) is proposed and tested. The MRF framework builds on other change detection components proposed in this work: dual ratio (DR) and multiratio (MR). The DR method involves two ratios coupled with adaptive thresholds to maximize detected changes and minimize false alarms. The use of two ratios is shown to outperform the single ratio case when the means of the image pairs are not equal. MR change detection builds on the DR method by including negative imagery to produce four total ratios with adaptive thresholds. Inclusion of negative imagery is shown to improve detection sensitivity and to boost detection performance in certain target and background cases. MRF further expands this concept by fusing together the ratio outputs using a routine in which detections must be verified by two or more ratios to be classified as a true changed pixel. The proposed method is tested with synthetically generated test imagery and real datasets with results compared to other methods found in the literature. DR is shown to significantly outperform the standard single ratio method. MRF produces excellent change detection results that exhibit up to a 22% performance improvement over other methods from the literature at low false-alarm rates.

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

EPA Science Inventory

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on ...

Boosting of HIV-1 neutralizing antibody responses by a distally related retroviral envelope protein.

PubMed

Uchtenhagen, Hannes; Schiffner, Torben; Bowles, Emma; Heyndrickx, Leo; LaBranche, Celia; Applequist, Steven E; Jansson, Marianne; De Silva, Thushan; Back, Jaap Willem; Achour, Adnane; Scarlatti, Gabriella; Fomsgaard, Anders; Montefiori, David; Stewart-Jones, Guillaume; Spetz, Anna-Lena

2014-06-15

Our knowledge of the binding sites for neutralizing Abs (NAb) that recognize a broad range of HIV-1 strains (bNAb) has substantially increased in recent years. However, gaps remain in our understanding of how to focus B cell responses to vulnerable conserved sites within the HIV-1 envelope glycoprotein (Env). In this article, we report an immunization strategy composed of a trivalent HIV-1 (clade B envs) DNA prime, followed by a SIVmac239 gp140 Env protein boost that aimed to focus the immune response to structurally conserved parts of the HIV-1 and simian immunodeficiency virus (SIV) Envs. Heterologous NAb titers, primarily to tier 1 HIV-1 isolates, elicited during the trivalent HIV-1 env prime, were significantly increased by the SIVmac239 gp140 protein boost in rabbits. Epitope mapping of Ab-binding reactivity revealed preferential recognition of the C1, C2, V2, V3, and V5 regions. These results provide a proof of concept that a distally related retroviral SIV Env protein boost can increase pre-existing NAb responses against HIV-1. Copyright © 2014 by The American Association of Immunologists, Inc.

Antibody responses to prime-boost vaccination with an HIV-1 gp145 envelope protein and chimpanzee adenovirus vectors expressing HIV-1 gp140.

PubMed

Emmer, Kristel L; Wieczorek, Lindsay; Tuyishime, Steven; Molnar, Sebastian; Polonis, Victoria R; Ertl, Hildegund C J

2016-10-23

Over 2 million individuals are infected with HIV type 1 (HIV-1) each year, yet an effective vaccine remains elusive. The most successful HIV-1 vaccine to date demonstrated 31% efficacy. Immune correlate analyses associated HIV-1 envelope (Env)-specific antibodies with protection, thus providing a path toward a more effective vaccine. We sought to test the antibody response from novel prime-boost vaccination with a chimpanzee-derived adenovirus (AdC) vector expressing a subtype C Env glycoprotein (gp)140 combined with either a serologically distinct AdC vector expressing gp140 of a different subtype C isolate or an alum-adjuvanted, partially trimeric gp145 from yet another subtype C isolate. Three different prime-boost regimens were tested in mice: AdC prime-protein boost, protein prime-AdC boost, and AdC prime-AdC boost. Each regimen was tested at two different doses of AdC vector in a total of six experimental groups. Sera were collected at various time points and evaluated by ELISA for Env-specific antibody binding, isotype, and avidity. Antibody functionality was assessed by pseudovirus neutralization assay. Priming with AdC followed by a protein boost or sequential immunizations with two AdC vectors induced HIV-1 Env-specific binding antibodies, including those to the variable region 2, whereas priming with protein followed by an AdC boost was relatively ineffective. Antibodies that cross-neutralized tier 1 HIV-1 from different subtypes were elicited with vaccine regimens that included immunizations with protein. Our study warrants further investigation of AdC vector and gp145 protein prime-boost vaccines and their ability to protect against acquisition in animal challenge studies.

An evaluation of a hubless inducer and a full flow hydraulic turbine driven inducer boost pump

NASA Technical Reports Server (NTRS)

Lindley, B. K.; Martinson, A. R.

1971-01-01

The purpose of the study was to compare the performance of several configurations of hubless inducers with a hydrodynamically similar conventional inducer and to demonstrate the performance of a full flow hydraulic turbine driven inducer boost pump using these inducers. A boost pump of this type consists of an inducer connected to a hydraulic turbine with a high speed rotor located in between. All the flow passes through the inducer, rotor, and hydraulic turbine, then into the main pump. The rotor, which is attached to the main pump shaft, provides the input power to drive the hydraulic turbine which, in turn, drives the inducer. The inducer, rotating at a lower speed, develops the necessary head to prevent rotor cavitation. The rotor speed is consistent with present main engine liquid hydrogen pump designs and the overall boost pump head rise is sufficient to provide adequate main pump suction head. This system would have the potential for operating at lower liquid hydrogen tank pressures.

Simulation comparison of proportional integral derivative and fuzzy logic in controlling AC-DC buck boost converter

NASA Astrophysics Data System (ADS)

Faisal, A.; Hasan, S.; Suherman

2018-03-01

AC-DC converter is widely used in the commercial industry even for daily purposes. The AC-DC converter is used to convert AC voltage into DC. In order to obtain the desired output voltage, the converter usually has a controllable regulator. This paper discusses buck boost regulator with a power MOSFET as switching component which is adjusted based on the duty cycle of pulse width modulation (PWM). The main problems of the buck boost converter at start up are the high overshoot, the long peak time and rise time. This paper compares the effectiveness of two control techniques: proportional integral derivative (PID) and fuzzy logic control in controlling the buck boost converter through simulations. The results show that the PID is more sensitive to voltage change than fuzzy logic. However, PID generates higher overshoot, long peak time and rise time. On the other hand, fuzzy logic generates no overshoot and shorter rise time.

Advocating a need for suitable breeding approaches to boost integrated pest management: a European perspective.

PubMed

Lamichhane, Jay Ram; Arseniuk, Edward; Boonekamp, Piet; Czembor, Jerzy; Decroocq, Veronique; Enjalbert, Jérome; Finckh, Maria R; Korbin, Małgorzata; Koppel, Mati; Kudsk, Per; Mesterhazy, Akos; Sosnowska, Danuta; Zimnoch-Guzowska, Ewa; Messéan, Antoine

2018-06-01

Currently, European farmers do not have access to sufficient numbers and diversity of crop species/varieties. This prevents them from designing cropping systems more resilient to abiotic and biotic stresses. Crop diversification is a key lever to reduce pest (pathogens, animal pests and weeds) pressures at all spatial levels from fields to landscapes. In this context, plant breeding should consist of: (1) increased efforts in the development of new or minor crop varieties to foster diversity in cropping systems, and (2) focus on more resilient varieties showing local adaptation. This new breeding paradigm, called here 'breeding for integrated pest management (IPM)', may boost IPM through the development of cultivars with tolerance or resistance to key pests, with the goal of reducing reliance on conventional pesticides. At the same time, this paradigm has legal and practical implications for future breeding programs, including those targeting sustainable agricultural systems. By putting these issues into the context, this article presents the key outcomes of a questionnaire survey and experts' views expressed during an EU workshop entitled 'Breeding for IPM in sustainable agricultural systems'. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The natural history of varicella zoster virus infection in Norway: Further insights on exogenous boosting and progressive immunity to herpes zoster

PubMed Central

Marangi, Luigi; Mirinaviciute, Grazina; Flem, Elmira; Scalia Tomba, Gianpaolo; Guzzetta, Giorgio; Freiesleben de Blasio, Birgitte; Manfredi, Piero

2017-01-01

We use age-structured models for VZV transmission and reactivation to reconstruct the natural history of VZV in Norway based on available pre-vaccination serological data, contact matrices, and herpes zoster incidence data. Depending on the hypotheses on contact and transmission patterns, the basic reproduction number of varicella in Norway ranges between 3.7 and 5.0, implying a vaccine coverage between 73 and 80% to effectively interrupt transmission with a 100% vaccine efficacy against infection. The varicella force of infection peaks during early childhood (3–5 yrs) and shows a prolonged phase of higher risk during the childbearing period, though quantitative variations can occur depending on contact patterns. By expressing the magnitude of exogenous boosting as a proportion of the force of infection, it is shown that reactivation is well described by a progressive immunity mechanism sustained by a large, though possibly below 100%, degree of exogenous boosting, in agreement with findings from other Nordic countries, implying large reproduction numbers of boosting. Moreover, magnitudes of exogenous boosting below 40% are robustly disconfirmed by data. These results bring further insight on the magnitude of immunity boosting and its relationship with reactivation. PMID:28545047

Boosted dibosons from mixed heavy top squarks

NASA Astrophysics Data System (ADS)

Ghosh, Diptimoy

2013-12-01

The lighter mass eigenstate (t˜1) of the two top squarks, the scalar superpartners of the top quark, is extremely difficult to discover if it is almost degenerate with the lightest neutralino (χ˜10), the lightest stable supersymmetric particle in the R-parity conserving supersymmetry. The current experimental bound on t˜1 mass in this scenario stands only around 200 GeV. For such a light t˜1, the heavier top squark (t˜2) can also be around the TeV scale. Moreover, the high value of the Higgs (h) mass prefers the left- and right-handed top squarks to be highly mixed, allowing the possibility of a considerable branching ratio for t˜2→t˜1h and t˜2→t˜1Z. In this paper, we explore the above possibility together with the pair production of t˜2 t˜2*, giving rise to the spectacular diboson+missing transverse energy final state. For an approximately 1 TeV t˜2 and a few hundred GeV t˜1 the final state particles can be moderately boosted, which encourages us to propose a novel search strategy employing the jet substructure technique to tag the boosted h and Z. The reconstruction of the h and Z momenta also allows us to construct the stransverse mass MT2, providing an additional efficient handle to fight the backgrounds. We show that a 4-5σ signal can be observed at the 14 TeV LHC for ˜1TeV t˜2 with 100fb-1 integrated luminosity.

Computing a Comprehensible Model for Spam Filtering

NASA Astrophysics Data System (ADS)

Ruiz-Sepúlveda, Amparo; Triviño-Rodriguez, José L.; Morales-Bueno, Rafael

In this paper, we describe the application of the Desicion Tree Boosting (DTB) learning model to spam email filtering.This classification task implies the learning in a high dimensional feature space. So, it is an example of how the DTB algorithm performs in such feature space problems. In [1], it has been shown that hypotheses computed by the DTB model are more comprehensible that the ones computed by another ensemble methods. Hence, this paper tries to show that the DTB algorithm maintains the same comprehensibility of hypothesis in high dimensional feature space problems while achieving the performance of other ensemble methods. Four traditional evaluation measures (precision, recall, F1 and accuracy) have been considered for performance comparison between DTB and others models usually applied to spam email filtering. The size of the hypothesis computed by a DTB is smaller and more comprehensible than the hypothesis computed by Adaboost and Naïve Bayes.

Organic cattle products: Authenticating production origin by analysis of serum mineral content.

PubMed

Rodríguez-Bermúdez, Ruth; Herrero-Latorre, Carlos; López-Alonso, Marta; Losada, David E; Iglesias, Roberto; Miranda, Marta

2018-10-30

An authentication procedure for differentiating between organic and non-organic cattle production on the basis of analysis of serum samples has been developed. For this purpose, the concentrations of fourteen mineral elements (As, Cd, Co, Cr, Cu, Fe, Hg, I, Mn, Mo, Ni, Pb, Se and Zn) in 522 serum samples from cows (341 from organic farms and 181 from non-organic farms), determined by inductively coupled plasma spectrometry, were used. The chemical information provided by serum analysis was employed to construct different pattern recognition classification models that predict the origin of each sample: organic or non-organic class. Among all classification procedures considered, the best results were obtained with the decision tree C5.0, Random Forest and AdaBoost neural networks, with hit levels close to 90% for both production types. The proposed method, involving analysis of serum samples, provided rapid, accurate in vivo classification of cattle according to organic and non-organic production type. Copyright © 2018 Elsevier Ltd. All rights reserved.

Building Diversified Multiple Trees for classification in high dimensional noisy biomedical data.

PubMed

Li, Jiuyong; Liu, Lin; Liu, Jixue; Green, Ryan

2017-12-01

It is common that a trained classification model is applied to the operating data that is deviated from the training data because of noise. This paper will test an ensemble method, Diversified Multiple Tree (DMT), on its capability for classifying instances in a new laboratory using the classifier built on the instances of another laboratory. DMT is tested on three real world biomedical data sets from different laboratories in comparison with four benchmark ensemble methods, AdaBoost, Bagging, Random Forests, and Random Trees. Experiments have also been conducted on studying the limitation of DMT and its possible variations. Experimental results show that DMT is significantly more accurate than other benchmark ensemble classifiers on classifying new instances of a different laboratory from the laboratory where instances are used to build the classifier. This paper demonstrates that an ensemble classifier, DMT, is more robust in classifying noisy data than other widely used ensemble methods. DMT works on the data set that supports multiple simple trees.

Dependence structure of the commodity and stock markets, and relevant multi-spread strategy

NASA Astrophysics Data System (ADS)

Kim, Min Jae; Kim, Sehyun; Jo, Yong Hwan; Kim, Soo Yong

2011-10-01

Understanding the dependence structure between the commodity and stock markets is a crucial issue in constructing a portfolio. It can also help us to discover new opportunities to implement spread trading using multiple assets classified in the two different markets. This study analyzed the dependence structure of the commodity and stock markets using the random matrix theory technique and network analysis. Our results show that the stock and commodity markets must be handled as completely separated asset classes except for the oil and gold markets, so the performance enhancement of the mean-variance portfolio is significant as expected. In light of the fact that WTI 1 month futures and four oil-related stocks are strongly correlated, they were selected as basic ingredients to complement the multi-spread convergence trading strategy using a machine learning technique called the AdaBoost algorithm. The performance of this strategy for non-myopic investors, who can endure short-term loss, can be enhanced significantly on a risk measurement basis.

A practical approach for writer-dependent symbol recognition using a writer-independent symbol recognizer.

PubMed

LaViola, Joseph J; Zeleznik, Robert C

2007-11-01

We present a practical technique for using a writer-independent recognition engine to improve the accuracy and speed while reducing the training requirements of a writer-dependent symbol recognizer. Our writer-dependent recognizer uses a set of binary classifiers based on the AdaBoost learning algorithm, one for each possible pairwise symbol comparison. Each classifier consists of a set of weak learners, one of which is based on a writer-independent handwriting recognizer. During online recognition, we also use the n-best list of the writer-independent recognizer to prune the set of possible symbols and thus reduce the number of required binary classifications. In this paper, we describe the geometric and statistical features used in our recognizer and our all-pairs classification algorithm. We also present the results of experiments that quantify the effect incorporating a writer-independent recognition engine into a writer-dependent recognizer has on accuracy, speed, and user training time.

Automated anatomical labeling of bronchial branches extracted from CT datasets based on machine learning and combination optimization and its application to bronchoscope guidance.

PubMed

Mori, Kensaku; Ota, Shunsuke; Deguchi, Daisuke; Kitasaka, Takayuki; Suenaga, Yasuhito; Iwano, Shingo; Hasegawa, Yosihnori; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi

2009-01-01

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

Androgen Suppression Combined with Elective Nodal and Dose Escalated Radiation Therapy (the ASCENDE-RT Trial): An Analysis of Survival Endpoints for a Randomized Trial Comparing a Low-Dose-Rate Brachytherapy Boost to a Dose-Escalated External Beam Boost for High- and Intermediate-risk Prostate Cancer

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

Morris, W. James, E-mail: jmorris@bccancer.bc.ca; BC Cancer Agency–Vancouver Centre, Vancouver, British Columbia; Tyldesley, Scott

Purpose: To report the primary endpoint of biochemical progression-free survival (b-PFS) and secondary survival endpoints from ASCENDE-RT, a randomized trial comparing 2 methods of dose escalation for intermediate- and high-risk prostate cancer. Methods and Materials: ASCENDE-RT enrolled 398 men, with a median age of 68 years; 69% (n=276) had high-risk disease. After stratification by risk group, the subjects were randomized to a standard arm with 12 months of androgen deprivation therapy, pelvic irradiation to 46 Gy, followed by a dose-escalated external beam radiation therapy (DE-EBRT) boost to 78 Gy, or an experimental arm that substituted a low-dose-rate prostate brachytherapy (LDR-PB) boost. Of the 398more » trial subjects, 200 were assigned to DE-EBRT boost and 198 to LDR-PB boost. The median follow-up was 6.5 years. Results: In an intent-to-treat analysis, men randomized to DE-EBRT were twice as likely to experience biochemical failure (multivariable analysis [MVA] hazard ratio [HR] 2.04; P=.004). The 5-, 7-, and 9-year Kaplan-Meier b-PFS estimates were 89%, 86%, and 83% for the LDR-PB boost versus 84%, 75%, and 62% for the DE-EBRT boost (log-rank P<.001). The LDR-PB boost benefited both intermediate- and high-risk patients. Because the b-PFS curves for the treatment arms diverge sharply after 4 years, the relative advantage of the LDR-PB should increase with longer follow-up. On MVA, the only variables correlated with reduced overall survival were age (MVA HR 1.06/y; P=.004) and biochemical failure (MVA HR 6.30; P<.001). Although biochemical failure was associated with increased mortality and randomization to DE-EBRT doubled the rate of biochemical failure, no significant overall survival difference was observed between the treatment arms (MVA HR 1.13; P=.62). Conclusions: Compared with 78 Gy EBRT, men randomized to the LDR-PB boost were twice as likely to be free of biochemical failure at a median follow-up of 6.5 years.« less

Adaptive radiotherapy for head and neck cancers: Fact or fallacy to improve therapeutic ratio?

PubMed

Li, Y Q; Tan, J S H; Wee, J T S; Chua, M L K

2018-04-23

Modern standards of precision radiotherapy, primarily driven by the technological advances of intensity modulation and image guidance, have led to increased versatility in radiotherapy planning and delivery. The ability to shape doses around critical normal organs, while simultaneously "painting" boost doses to the tumor have translated to substantial therapeutic gains in head and neck cancer patients. Recently, dose adaptation (or adaptive radiotherapy) has been proposed as a novel concept to enhance the therapeutic ratio of head and neck radiotherapy, facilitated in part by the onset of molecular and functional imaging. These contemporary imaging techniques have enabled visualisation of the spatial molecular architecture of the tumor. Daily cone-beam imaging, besides improving treatment accuracy, offers another unique angle to explore radiomics - a novel high throughput feature extraction and selection workflow, for adapting radiotherapy based on real-time tumor changes. Here, we review the existing evidence of molecular and functional imaging in head and neck cancers, as well as the current application of adaptive radiotherapy in the treatment of this tumor type. We propose that adaptive radiotherapy can be further exploited through a systematic application of molecular and functional imaging, including radiomics, at the different phases of planning and treatment. Copyright © 2018 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

HBV-Derived Synthetic Long Peptide Can Boost CD4+ and CD8+ T-Cell Responses in Chronic HBV Patients Ex Vivo

PubMed Central

Dou, Yingying; van Montfoort, Nadine; van den Bosch, Aniek; de Man, Robert A; Zom, Gijs G; Krebber, Willem-Jan; Melief, Cornelis J M; Buschow, Sonja I; Woltman, Andrea M

2018-01-01

Abstract Background Vaccination with synthetic long peptides (SLP) is a promising new treatment strategy for chronic hepatitis B virus (CHB). SLP can induce broad T-cell responses for all HLA types. Here we investigated the ability of a prototype HBV-core (HBc)-sequence-derived SLP to boost HBV-specific T cells in CHB patients ex vivo. Methods HBc-SLP was used to assess cross-presentation by monocyte-derived dendritic cells (moDC) and BDCA1+ blood myeloid DC (mDC) to engineered HBV-specific CD8+ T cells. Autologous SLP-loaded and toll-like receptor (TLR)-stimulated DC were used to activate patient HBc-specific CD8+ and CD4+ T cells. Results HBV-SLP was cross-presented by moDC, which was further enhanced by adjuvants. Patient-derived SLP-loaded moDC significantly increased autologous HBcAg18-27-specific CD8+ T cells and CD4+ T cells ex vivo. HBV-specific T cells were functional as they synthesized tumor necrosis factor-alpha and interferon-gamma. In 6/7 of patients blockade of PD-L1 further increased SLP effects. Also, importantly, patient-derived BDCA1+ mDC cross-presented and activated autologous T-cell responses ex vivo. Conclusions As a proof of concept, we showed a prototype HBc-SLP can boost T-cell responses in patients ex vivo. These results pave the way for the development of a therapeutic SLP-based vaccine to induce effective HBV-specific adaptive immune responses in CHB patients. PMID:29220492

Oxygen-boosted immunogenic photodynamic therapy with gold nanocages@manganese dioxide to inhibit tumor growth and metastases.

PubMed

Liang, Ruijing; Liu, Lanlan; He, Huamei; Chen, Zhikuan; Han, Zhiqun; Luo, Zhenyu; Wu, Zhihao; Zheng, Mingbin; Ma, Yifan; Cai, Lintao

2018-09-01

Metastatic triple-negative breast cancer (mTNBC) is an aggressive disease among women worldwide, characterized by high mortality and poor prognosis despite systemic therapy with radiation and chemotherapies. Photodynamic therapy (PDT) is an important strategy to eliminate the primary tumor, however its therapeutic efficacy against metastases and recurrence is still limited. Here, we employed a template method to develop the core-shell gold nanocage@manganese dioxide (AuNC@MnO 2 , AM) nanoparticles as tumor microenvironment responsive oxygen producers and near-infrared (NIR)-triggered reactive oxygen species (ROS) generators for oxygen-boosted immunogenic PDT against mTNBC. In this platform, MnO 2 shell degrades in acidic tumor microenvironment pH/H 2 O 2 conditions and generates massive oxygen to boost PDT effect of AM nanoparticles under laser irradiation. Fluorescence (FL)/photoacoustic (PA)/magnetic resonance (MR) multimodal imaging confirms the effective accumulation of AM nanoparticles with sufficient oxygenation in tumor site to ameliorate local hypoxia. Moreover, the oxygen-boosted PDT effect of AM not only destroys primary tumor effectively but also elicits immunogenic cell death (ICD) with damage-associated molecular patterns (DAMPs) release, which subsequently induces DC maturation and effector cells activation, thereby robustly evoking systematic antitumor immune responses against mTNBC. Hence, this oxygen-boosted immunogenic PDT nanosystem offers a promising approach to ablate primary tumor and simultaneously prevent tumor metastases via immunogenic abscopal effects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Intraoperative radiotherapy given as a boost for early breast cancer: Long-term clinical and cosmetic results

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

Lemanski, Claire; Azria, David; Thezenas, Simon

2006-04-01

Purpose: The standard radiotherapy (RT) of breast cancer consists of 50 Gy external beam RT (EBRT) to the whole breast followed by an electron boost of 10-16 Gy to the tumor bed, but this has several cosmetic disadvantages. Intraoperative radiotherapy (IORT) could be an alternative to overcome these. Methods and Materials: We evaluated 50 women with early breast cancer operated on in a dedicated IORT facility. Median dose of 10 Gy was delivered using 9-MeV electron beams. All patients received postoperative EBRT (50 Gy in 2 Gy fractions). Late toxicity and cosmetic results were assessed independently by two physicians accordingmore » to the Common Terminology Criteria for Adverse Event v3.0 grading system and the European Organization for Research and Treatment of Cancer questionnaires. Results: After a median follow-up of 9.1 years (range, 5-15 years), two local recurrences were observed within the primary tumor bed. At the time of analysis, 45 patients are alive with (n = 1) or without disease. Among the 42 disease-free remaining patients, 6 experienced Grade 2 late subcutaneous fibrosis within the boost area. Overall, the scores indicated a very good quality of life and cosmesis was good to excellent in the evaluated patients. Conclusion: Our results confirm that IORT given as a boost after breast-conserving surgery is a reliable alternative to conventional postoperative fractionated boost radiation.« less

Adaptive accelerated ReaxFF reactive dynamics with validation from simulating hydrogen combustion.

PubMed

Cheng, Tao; Jaramillo-Botero, Andrés; Goddard, William A; Sun, Huai

2014-07-02

We develop here the methodology for dramatically accelerating the ReaxFF reactive force field based reactive molecular dynamics (RMD) simulations through use of the bond boost concept (BB), which we validate here for describing hydrogen combustion. The bond order, undercoordination, and overcoordination concepts of ReaxFF ensure that the BB correctly adapts to the instantaneous configurations in the reactive system to automatically identify the reactions appropriate to receive the bond boost. We refer to this as adaptive Accelerated ReaxFF Reactive Dynamics or aARRDyn. To validate the aARRDyn methodology, we determined the detailed sequence of reactions for hydrogen combustion with and without the BB. We validate that the kinetics and reaction mechanisms (that is the detailed sequences of reactive intermediates and their subsequent transformation to others) for H2 oxidation obtained from aARRDyn agrees well with the brute force reactive molecular dynamics (BF-RMD) at 2498 K. Using aARRDyn, we then extend our simulations to the whole range of combustion temperatures from ignition (798 K) to flame temperature (2998K), and demonstrate that, over this full temperature range, the reaction rates predicted by aARRDyn agree well with the BF-RMD values, extrapolated to lower temperatures. For the aARRDyn simulation at 798 K we find that the time period for half the H2 to form H2O product is ∼538 s, whereas the computational cost was just 1289 ps, a speed increase of ∼0.42 trillion (10(12)) over BF-RMD. In carrying out these RMD simulations we found that the ReaxFF-COH2008 version of the ReaxFF force field was not accurate for such intermediates as H3O. Consequently we reoptimized the fit to a quantum mechanics (QM) level, leading to the ReaxFF-OH2014 force field that was used in the simulations.

Safety and immunogenicity of heterologous prime-boost immunization with viral-vectored malaria vaccines adjuvanted with Matrix-M™.

PubMed

Venkatraman, Navin; Anagnostou, Nicholas; Bliss, Carly; Bowyer, Georgina; Wright, Danny; Lövgren-Bengtsson, Karin; Roberts, Rachel; Poulton, Ian; Lawrie, Alison; Ewer, Katie; V S Hill, Adrian

2017-10-27

The use of viral vectors in heterologous prime-boost regimens to induce potent T cell responses in addition to humoral immunity is a promising vaccination strategy in the fight against malaria. We conducted an open-label, first-in-human, controlled Phase I study evaluating the safety and immunogenicity of Matrix-M adjuvanted vaccination with a chimpanzee adenovirus serotype 63 (ChAd63) prime followed by a modified vaccinia Ankara (MVA) boost eight weeks later, both encoding the malaria ME-TRAP antigenic sequence (a multiple epitope string fused to thrombospondin-related adhesion protein). Twenty-two healthy adults were vaccinated intramuscularly with either ChAd63-MVA ME-TRAP alone (n=6) or adjuvanted with 25μg (n=8) or 50μg (n=8) Matrix-M. Vaccinations appeared to be safe and generally well tolerated, with the majority of local and systemic adverse events being mild in nature. The addition of Matrix-M to the vaccine did not increase local reactogenicity; however, systemic adverse events were reported more frequently by volunteers who received adjuvanted vaccine in comparison to the control group. T cell ELISpot responses peaked at 7-days post boost vaccination with MVA ME-TRAP in all three groups. TRAP-specific IgG responses were highest at 28-days post boost with MVA ME-TRAP in all three groups. There were no differences in cellular and humoral immunogenicity at any of the time points between the control group and the adjuvanted groups. We demonstrate that Matrix-M can be safely used in combination with ChAd63-MVA ME-TRAP heterologous prime-boost immunization without any reduction in cellular or humoral immunogenicity. Clinical Trials Registration NCT01669512. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simultaneous integrated vs. sequential boost in VMAT radiotherapy of high-grade gliomas.

PubMed

Farzin, Mostafa; Molls, Michael; Astner, Sabrina; Rondak, Ina-Christine; Oechsner, Markus

2015-12-01

In 20 patients with high-grade gliomas, we compared two methods of planning for volumetric-modulated arc therapy (VMAT): simultaneous integrated boost (SIB) vs. sequential boost (SEB). The investigation focused on the analysis of dose distributions in the target volumes and the organs at risk (OARs). After contouring the target volumes [planning target volumes (PTVs) and boost volumes (BVs)] and OARs, SIB planning and SEB planning were performed. The SEB method consisted of two plans: in the first plan the PTV received 50 Gy in 25 fractions with a 2-Gy dose per fraction. In the second plan the BV received 10 Gy in 5 fractions with a dose per fraction of 2 Gy. The doses of both plans were summed up to show the total doses delivered. In the SIB method the PTV received 54 Gy in 30 fractions with a dose per fraction of 1.8 Gy, while the BV received 60 Gy in the same fraction number but with a dose per fraction of 2 Gy. All of the OARs showed higher doses (Dmax and Dmean) in the SEB method when compared with the SIB technique. The differences between the two methods were statistically significant in almost all of the OARs. Analysing the total doses of the target volumes we found dose distributions with similar homogeneities and comparable total doses. Our analysis shows that the SIB method offers advantages over the SEB method in terms of sparing OARs.

Simultaneous integrated intensity-modulated radiotherapy boost for locally advanced gynecological cancer: Radiobiological and dosimetric considerations

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

Guerrero, Mariana; Li, X. Allen; Ma Lijun

2005-07-01

Purpose: Whole-pelvis irradiation (WPI) followed by a boost to the tumor site is the standard of practice for the radiotherapeutic management of locally advanced gynecologic cancers. The boost is frequently administered by use of brachytherapy or, occasionally, external-beam radiotherapy (EBRT) when brachytherapy does not provide sufficient coverage because of the size of the tumor or the geometry of the patient. In this work, we propose using an intensity-modulated radiotherapy (IMRT) simultaneous integrated boost (SIB), which is a single-phase process, to replace the conventional two-phase process involving WPI plus a boost. Radiobiological modeling is used to design appropriate regimens for themore » IMRT SIB. To demonstrate feasibility, a dosimetric study is carried out on an example patient. Methods and Materials: The standard linear-quadratic (LQ) model is used to calculate the biologically effective dose (BED) and equivalent uniform dose (EUD). A series of regimens that are biologically equivalent to those conventional two-phase treatments is calculated for the proposed SIB. A commercial inverse planning system (Corvus) was used to generate IMRT SIB plans for a sample patient case that used the newly designed fractionations. The dose-volume histogram (DVH) and EUD of both the target and normal structures for conventional treatments and the SIB are compared. A sparing factor was introduced to characterize the sparing of normal structures. Results: Fractionation regimes that are equivalent to the conventional treatments and are suitable for the IMRT SIB are deduced. For example, a SIB plan with 25 x 3.1 Gy (77.5 Gy) to a tumor is equivalent to a conventional treatment of EBRT of 45 Gy to the whole pelvis in 25 fractions plus a high-dose rate (HDR) brachytherapy boost with 30 Gy in 5 fractions. The normal tissue BED is found to be lower for the SIB plan than for the whole-pelvis plus HDR scheme when a sparing factor for the critical structures is considered

Radiotherapy boost dose-escalation for invasive breast cancer after breast-conserving surgery: 2093 patients treated with a prospective margin-directed policy.

PubMed

Livi, Lorenzo; Meattini, Icro; Franceschini, Davide; Saieva, Calogero; Meacci, Fiammetta; Marrazzo, Livia; Gerlain, Elena; Desideri, Isacco; Scotti, Vieri; Nori, Jacopo; Sanchez, Luis Jose; Orzalesi, Lorenzo; Bonomo, Pierluigi; Greto, Daniela; Bianchi, Simonetta; Biti, Giampaolo

2013-08-01

To investigate the outcome of invasive early breast cancer patients that underwent breast-conserving surgery and adjuvant radiotherapy (RT), treated with a prospective margin-directed institutional policy for RT boost dose, based on final margins status (FMS). A total of 2093 patients were treated between 2000 and 2008. 10 Gy boost was prescribed in case of FMS>5mm; 16 Gy boost with FMS between 2 and 5mm; 20 Gy boost in case of FMS<2mm or positive. After a median follow up of 5.2 years, we recorded 41 local relapse (LR, 2%). Concerning LR free survival, age at diagnosis, nuclear grade, hormonal status, T-stage, adjuvant hormonal therapy and adjuvant chemotherapy emerged as significant parameters (p-values from log rank test <0.05). FMS, that directed the RT boost dose, did not have significant impact on LRFS (p=0.46). LR rates were 2.3% for FMS<2mm, 2.6% for 2-5mm FMS and 1.8% for FMS>5mm. At multivariate analysis, higher nuclear grade (p=0.045), triple negative subtype (p=0.036) and higher T-stage (p=0.02) resulted as the independent predictors of LR occurrence. Our experience showed that a margin-directed policy of RT boost dose-escalation seems to reduce the negative impact of FMS on LR, but it is not able to overcome the unfavorable effect of higher nuclear grade, higher T stage and triple negative subtype. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Effects of adaptive dynamical linking in networked games

NASA Astrophysics Data System (ADS)

Yang, Zhihu; Li, Zhi; Wu, Te; Wang, Long

2013-10-01

The role of dynamical topologies in the evolution of cooperation has received considerable attention, as some studies have demonstrated that dynamical networks are much better than static networks in terms of boosting cooperation. Here we study a dynamical model of evolution of cooperation on stochastic dynamical networks in which there are no permanent partners to each agent. Whenever a new link is created, its duration is randomly assigned without any bias or preference. We allow the agent to adaptively adjust the duration of each link during the evolution in accordance with the feedback from game interactions. By Monte Carlo simulations, we find that cooperation can be remarkably promoted by this adaptive dynamical linking mechanism both for the game of pairwise interactions, such as the Prisoner's Dilemma game (PDG), and for the game of group interactions, illustrated by the public goods game (PGG). And the faster the adjusting rate, the more successful the evolution of cooperation. We also show that in this context weak selection favors cooperation much more than strong selection does. What is particularly meaningful is that the prosperity of cooperation in this study indicates that the rationality and selfishness of a single agent in adjusting social ties can lead to the progress of altruism of the whole population.

Prime-boost vaccination using DNA and whole inactivated virus vaccines provides limited protection against virulent feline immunodeficiency virus.

PubMed

Dunham, Stephen P; Bruce, Jennifer; Klein, Dieter; Flynn, J Norman; Golder, Matthew C; MacDonald, Susan; Jarrett, Oswald; Neil, James C

2006-11-30

Protection against feline immunodeficiency virus (FIV) has been achieved using a variety of vaccines notably whole inactivated virus (WIV) and DNA. However protection against more virulent isolates, typical of those encountered in natural infections, has been difficult to achieve. In an attempt to improve protection against virulent FIV(GL8), we combined both DNA and WIV vaccines in a "prime-boost" approach. Thirty cats were divided into four groups receiving vaccinations and one unvaccinated control group. Following viral challenge, two vaccinated animals, one receiving DNA alone and one the prime-boost vaccine remained free of viraemia, whilst all controls became viraemic. Animals vaccinated with WIV showed apparent early enhancement of infection at 2 weeks post challenge (pc) with higher plasma viral RNA loads than control animals or cats immunised with DNA alone. Despite this, animals vaccinated with WIV or DNA alone showed significantly lower proviral loads in peripheral blood mononuclear cells and mesenteric lymph node cells, whilst those receiving the DNA-WIV prime-boost vaccine showed significantly lower proviral loads in PBMC, than control animals, at 35 weeks pc. Therefore both DNA and WIV vaccines conferred limited protection against viral challenge but the combination of WIV and DNA in a prime-boost approach appeared to offer no significant advantage over either vaccine alone.

A heterologous prime-boost Ebola virus vaccine regimen induces durable neutralizing antibody response and prevents Ebola virus-like particle entry in mice.

PubMed

Chen, Tan; Li, Dapeng; Song, Yufeng; Yang, Xi; Liu, Qingwei; Jin, Xia; Zhou, Dongming; Huang, Zhong

2017-09-01

Ebola virus (EBOV) is one of the most virulent pathogens known to humans. Neutralizing antibodies play a major role in the protection against EBOV infections. Thus, an EBOV vaccine capable of inducing a long-lasting neutralizing antibody response is highly desirable. We report here that a heterologous prime-boost vaccine regimen can elicit durable EBOV-neutralizing antibody response in mice. A chimpanzee serotype 7 adenovirus expressing EBOV GP (denoted AdC7-GP) was generated and used for priming. A truncated version of EBOV GP1 protein (denoted GP1t) was produced at high levels in Drosophila S2 cells and used for boosting. Mouse immunization studies showed that the AdC7-GP prime/GP1t boost vaccine regimen was more potent in eliciting neutralizing antibodies than either the AdC7-GP or GP1t alone. Neutralizing antibodies induced by the heterologous prime-boost regimen sustained at high titers for at least 18 weeks after immunization. Significantly, in vivo challenge studies revealed that the entry of reporter EBOV-like particles was efficiently blocked in mice receiving the heterologous prime-boost regimen even at 18 weeks after the final dose of immunization. These results suggest that this novel AdC7-GP prime/GP1t boost regimen represents an EBOV vaccine approach capable of establishing long-term protection, and therefore warrants further development. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in the TRMM Version-5 and Version-6 Precipitation Radar Products Due to Orbit Boost

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert

2010-01-01

The performance of the version-5 and version-6 Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) products before and after the satellite orbit boost is assessed through a series of comparisons with Weather Surveillance Radar (WSR)-88D ground-based radar in Melbourne, Florida. Analysis of the comparisons of radar reflectivity near the storm top from the ground radar and both versions of the PR indicates that the PR bias relative to the WSR radar at Melbourne is on the order of 1dB for both pre- and post-boost periods, indicating that the PR products maintain accurate calibration after the orbit boost. Comparisons with the WSR-88D near-surface reflectivity factors indicate that both versions of the PR products accurately correct for attenuation in stratiform rain. However, in convective rain, both versions exhibit negative biases in the near-surface radar reflectivity with version-6 products having larger negative biases than version-5. Rain rate comparisons between the ground and space radars show similar characteristics

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations.

PubMed

Sinko, William; de Oliveira, César Augusto F; Pierce, Levi C T; McCammon, J Andrew

2012-01-10

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

Successive Intramuscular Boosting with IFN-Alpha Protects Mycobacterium bovis BCG-Vaccinated Mice against M. lepraemurium Infection

PubMed Central

Guerrero, G. G.; Rangel-Moreno, J.; Islas-Trujillo, S.; Rojas-Espinosa, Ó.

2015-01-01

Leprosy caused by Mycobacterium leprae primarily affects the skin and peripheral nerves. As a human infectious disease, it is still a significant health and economic burden on developing countries. Although multidrug therapy is reducing the number of active cases to approximately 0.5 million, the number of cases per year is not declining. Therefore, alternative host-directed strategies should be addressed to improve treatment efficacy and outcome. In this work, using murine leprosy as a model, a very similar granulomatous skin lesion to human leprosy, we have found that successive IFN-alpha boosting protects BCG-vaccinated mice against M. lepraemurium infection. No difference in the seric isotype and all IgG subclasses measured, neither in the TH1 nor in the TH2 type cytokine production, was seen. However, an enhanced iNOS/NO production in BCG-vaccinated/i.m. IFN-alpha boosted mice was observed. The data provided in this study suggest a promising use for IFN-alpha boosting as a new prophylactic alternative to be explored in human leprosy by targeting host innate cell response. PMID:26484351

Probing TeV scale top-philic resonances with boosted top-tagging at the high luminosity LHC

DOE PAGES

Kim, Jeong Han; Kong, Kyoungchul; Lee, Seung J.; ...

2016-08-24

Here, we investigate the discovery potential of singly produced top-philic resonances at the high luminosity (HL) LHC in the four-top final state. Our analysis spans over the fully-hadronic, semi-leptonic, and same-sign dilepton channels where we present concrete search strategies adequate to a boosted kinematic regime and high jet-multiplicity environments. We utilize the Template Overlap Method (TOM) with newly developed template observables for tagging boosted top quarks, a large-radius jet variablemore » $$M_J$$ and customized b-tagging tactics for background discrimination. Our results show that the same-sign dilepton channel gives the best sensitivity among the considered channels, with an improvement of significance up to 10%-20% when combined with boosted-top tagging. Both the fully-hadronic and semi-leptonic channels yield comparable discovery potential and contribute to further enhancements in the sensitivity by combining all channels. Finally, we show the sensitivity of a top-philic resonance at the LHC and HL-LHC by showing the $$2\\sigma$$ exclusion limit and $$5\\sigma$$ discovery reach, including a combination of all three channels.« less

Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

PubMed

Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

2015-08-01

Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects.

PubMed

Brunellière, Angèle; Perre, Laetitia; Tran, ThiMai; Bonnotte, Isabelle

2017-09-01

In recent decades, many computational techniques have been developed to analyse the contextual usage of words in large language corpora. The present study examined whether the co-occurrence frequency obtained from large language corpora might boost purely semantic priming effects. Two experiments were conducted: one with conscious semantic priming, the other with subliminal semantic priming. Both experiments contrasted three semantic priming contexts: an unrelated priming context and two related priming contexts with word pairs that are semantically related and that co-occur either frequently or infrequently. In the conscious priming presentation (166-ms stimulus-onset asynchrony, SOA), a semantic priming effect was recorded in both related priming contexts, which was greater with higher co-occurrence frequency. In the subliminal priming presentation (66-ms SOA), no significant priming effect was shown, regardless of the related priming context. These results show that co-occurrence frequency boosts pure semantic priming effects and are discussed with reference to models of semantic network.

Optimization of heterologous DNA-prime, protein boost regimens and site of vaccination to enhance therapeutic immunity against human papillomavirus-associated disease.

PubMed

Peng, Shiwen; Qiu, Jin; Yang, Andrew; Yang, Benjamin; Jeang, Jessica; Wang, Joshua W; Chang, Yung-Nien; Brayton, Cory; Roden, Richard B S; Hung, Chien-Fu; Wu, T-C

2016-01-01

Human papillomavirus (HPV) has been identified as the primary etiologic factor of cervical cancer as well as subsets of anogenital and oropharyngeal cancers. The two HPV viral oncoproteins, E6 and E7, are uniquely and consistently expressed in all HPV infected cells and are therefore promising targets for therapeutic vaccination. Both recombinant naked DNA and protein-based HPV vaccines have been demonstrated to elicit HPV-specific CD8+ T cell responses that provide therapeutic effects against HPV-associated tumor models. Here we examine the immunogenicity in a preclinical model of priming with HPV DNA vaccine followed by boosting with filterable aggregates of HPV 16 L2E6E7 fusion protein (TA-CIN). We observed that priming twice with an HPV DNA vaccine followed by a single TA-CIN booster immunization generated the strongest antigen-specific CD8+ T cell response compared to other prime-boost combinations tested in C57BL/6 mice, whether naïve or bearing the HPV16 E6/E7 transformed syngeneic tumor model, TC-1. We showed that the magnitude of antigen-specific CD8+ T cell response generated by the DNA vaccine prime, TA-CIN protein vaccine boost combinatorial strategy is dependent on the dose of TA-CIN protein vaccine. In addition, we found that a single booster immunization comprising intradermal or intramuscular administration of TA-CIN after priming twice with an HPV DNA vaccine generated a comparable boost to E7-specific CD8+ T cell responses. We also demonstrated that the immune responses elicited by the DNA vaccine prime, TA-CIN protein vaccine boost strategy translate into potent prophylactic and therapeutic antitumor effects. Finally, as seen for repeat TA-CIN protein vaccination, we showed that the heterologous DNA prime and protein boost vaccination strategy is well tolerated by mice. Our results provide rationale for future clinical testing of HPV DNA vaccine prime, TA-CIN protein vaccine boost immunization regimen for the control of HPV-associated diseases.

Boosting jet power in black hole spacetimes.

PubMed

Neilsen, David; Lehner, Luis; Palenzuela, Carlos; Hirschmann, Eric W; Liebling, Steven L; Motl, Patrick M; Garrett, Travis

2011-08-02

The extraction of rotational energy from a spinning black hole via the Blandford-Znajek mechanism has long been understood as an important component in models to explain energetic jets from compact astrophysical sources. Here we show more generally that the kinetic energy of the black hole, both rotational and translational, can be tapped, thereby producing even more luminous jets powered by the interaction of the black hole with its surrounding plasma. We study the resulting Poynting jet that arises from single boosted black holes and binary black hole systems. In the latter case, we find that increasing the orbital angular momenta of the system and/or the spins of the individual black holes results in an enhanced Poynting flux.

Observer-Pattern Modeling and Slow-Scale Bifurcation Analysis of Two-Stage Boost Inverters

NASA Astrophysics Data System (ADS)

Zhang, Hao; Wan, Xiaojin; Li, Weijie; Ding, Honghui; Yi, Chuanzhi

2017-06-01

This paper deals with modeling and bifurcation analysis of two-stage Boost inverters. Since the effect of the nonlinear interactions between source-stage converter and load-stage inverter causes the “hidden” second-harmonic current at the input of the downstream H-bridge inverter, an observer-pattern modeling method is proposed by removing time variance originating from both fundamental frequency and hidden second harmonics in the derived averaged equations. Based on the proposed observer-pattern model, the underlying mechanism of slow-scale instability behavior is uncovered with the help of eigenvalue analysis method. Then eigenvalue sensitivity analysis is used to select some key system parameters of two-stage Boost inverter, and some behavior boundaries are given to provide some design-oriented information for optimizing the circuit. Finally, these theoretical results are verified by numerical simulations and circuit experiment.

Different levels of immunogenicity of two strains of Fowlpox virus as recombinant vaccine vectors eliciting T-cell responses in heterologous prime-boost vaccination strategies.

PubMed

Cottingham, Matthew G; van Maurik, Andre; Zago, Manola; Newton, Angela T; Anderson, Richard J; Howard, M Keith; Schneider, Jörg; Skinner, Michael A

2006-07-01

The FP9 strain of F has been described as a more immunogenic recombinant vaccine vector than the Webster FPV-M (FPW) strain (R. J. Anderson et al., J. Immunol. 172:3094-3100, 2004). This study expands the comparison to include two separate recombinant antigens and multiple, rather than single, independent viral clones derived from the two strains. Dual-poxvirus heterologous prime-boost vaccination regimens using individual clones of recombinant FP9 or FPW in combination with recombinant modified V Ankara expressing the same antigen were evaluated for their ability to elicit T-cell responses against recombinant antigens from Plasmodium berghei (circumsporozoite protein) or human immunodeficiency virus type 1 (a Gag-Pol-Nef fusion protein). Gamma interferon enzyme-linked immunospot assay and fluorescence-activated cell sorting assays of the responses to specific epitopes confirmed the approximately twofold-greater cellular immunogenicity of FP9 compared to FPW, when given as the priming or boosting immunization. Equality of transgene expression in mouse cells infected with the two strains in vitro was verified by Western blotting. Directed partial sequence analysis and PCR analysis of FPW and comparison to available whole-genome sequences revealed that many loci that are mutated in the highly attenuated and culture-adapted FP9 strain are wild type in FPW, including the seven multikilobase deletions. These "passage-specific" alterations are hypothesized to be involved in determining the immunogenicity of fowlpox virus as a recombinant vaccine vector.

Fractionated stereotactic radiotherapy boost for gynecologic tumors: An alternative to brachytherapy?

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

Molla, Meritxell; Escude, Lluis D.; Nouet, Philippe

2005-05-01

Purpose: A brachytherapy (BT) boost to the vaginal vault is considered standard treatment for many endometrial or cervical cancers. We aimed to challenge this treatment standard by using stereotactic radiotherapy (SRT) with a linac-based micromultileaf collimator technique. Methods and Materials: Since January 2002, 16 patients with either endometrial (9) or cervical (7) cancer have been treated with a final boost to the areas at higher risk for relapse. In 14 patients, the target volume included the vaginal vault, the upper vagina, the parametria, or (if not operated) the uterus (clinical target volume [CTV]). In 2 patients with local relapse, themore » CTV was the tumor in the vaginal stump. Margins of 6-10 mm were added to the CTV to define the planning target volume (PTV). Hypofractionated dynamic-arc or intensity-modulated radiotherapy techniques were used. Postoperative treatment was delivered in 12 patients (2 x 7 Gy to the PTV with a 4-7-day interval between fractions). In the 4 nonoperated patients, a dose of 4 Gy/fraction in 5 fractions with 2 to 3 days' interval was delivered. Patients were immobilized in a customized vacuum body cast and optimally repositioned with an infrared-guided system developed for extracranial SRT. To further optimize daily repositioning and target immobilization, an inflated rectal balloon was used during each treatment fraction. In 10 patients, CT resimulation was performed before the last boost fraction to assess for repositioning reproducibility via CT-to-CT registration and to estimate PTV safety margins around the CTV. Finally, a comparative treatment planning study between BT and SRT was performed in 2 patients with an operated endometrial Stage I cancer. Results: No patient developed severe acute urinary or low-intestinal toxicity. No patient developed urinary late effects (>6 months). One patient with a vaginal relapse previously irradiated to the pelvic region presented with Grade 3 rectal bleeding 18 months after

Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

PubMed Central

Huan-ling, Tang; Zhi-yong, An

2014-01-01

Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene. PMID:25013850

Ultrahigh Detective Heterogeneous Photosensor Arrays with In-Pixel Signal Boosting Capability for Large-Area and Skin-Compatible Electronics.

PubMed

Kim, Jaehyun; Kim, Jaekyun; Jo, Sangho; Kang, Jingu; Jo, Jeong-Wan; Lee, Myungwon; Moon, Juhyuk; Yang, Lin; Kim, Myung-Gil; Kim, Yong-Hoon; Park, Sung Kyu

2016-04-01

An ultra-thin and large-area skin-compatible heterogeneous organic/metal-oxide photosensor array is demonstrated which is capable of sensing and boosting signals with high detectivity and signal-to-noise ratio. For the realization of ultra-flexible and high-sensitive heterogeneous photosensor arrays on a polyimide substrate having organic sensor arrays and metal-oxide boosting circuitry, solution-processing and room-temperature alternating photochemical conversion routes are applied. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Orbiter aborts from boost: Presimulation report

NASA Technical Reports Server (NTRS)

Backman, H. D.; Brechka, K. G.

1972-01-01

A description of a hybrid simulation of the 040C orbiter aborting from boost to specified landing site is provided. The simulation starts when the abort is initiated and continues until a terminal energy state (associated with the selected landing site) is reached. At abort it is assumed that all SRM's are jettisoned with the external tank remaining with the orbiter. The simulation described has six degrees of freedom with the vehicle simulated as a rigid body. A conventional form of autopilot is provided to control engine gimbaling during powered flight. An ideal form of an autopilot is provided to test conventional autopilot function and provide pseudo RCS function during coasting flight. The simulation is proposed to provide means for studies of abort guidance function and to gain information concerning ability to control the abort trajectory.

Adaptation of amoebae to cooling tower biocides.

PubMed

Srikanth, S; Berk, S G

1994-05-01

Adaptation of amoebae to four cooling tower Biocides, which included a thiocarbamate compound, tributyltin neodecanoate mixed with quaternary ammonium compounds (TBT/QAC), another QAC alone, and an isothiazolin derivative, was studied. Previously we found that amoebae isolated from waters of cooling towers were more resistant to cooling tower biocides than amoebae from other habitats. Acanthamoeba hatchetti and Cochliopodium bilimbosum, obtained from American Type Culture Collection and used in the previous studies, were tested to determine whether they could adapt to cooling tower Biocides. A. hatchetti was preexposed to subinhibitory concentrations of the four Biocides for 72h, after which they were tested for their resistance to the same and other biocides. C. bilimbosum was exposed to only two biocides, as exposure to the other two was lethal after 72 h. Preexposure to the subinhibitory concentrations of the Biocides increased the resistance of the amoebae, as indicated by a significant increase in the minimum inhibitory concentration (up to 30-fold). In addition, cross-resistance was also observed, i.e., exposure to one biocide caused resistance to other biocides. These results show that amoebae can adapt to biocides in a short time. The phenomenon of cross-resistance indicates that regularly alternating biocides, as is done to control microbial growth in cooling towers, may not be effective in keeping amoeba populations in check. On the contrary, exposure to one biocide may boost the amoebae's resistance to a second biocide before the second biocide is used in the cooling tower. Since amoebae may harbor Legionella, or alone cause human diseases, these results may be important in designing effective strategies for controlling pathogens in cooling towers.

Boosted food web productivity through ocean acidification collapses under warming.

PubMed

Goldenberg, Silvan U; Nagelkerken, Ivan; Ferreira, Camilo M; Ullah, Hadayet; Connell, Sean D

2017-10-01

Future climate is forecast to drive bottom-up (resource driven) and top-down (consumer driven) change to food web dynamics and community structure. Yet, our predictive understanding of these changes is hampered by an over-reliance on simplified laboratory systems centred on single trophic levels. Using a large mesocosm experiment, we reveal how future ocean acidification and warming modify trophic linkages across a three-level food web: that is, primary (algae), secondary (herbivorous invertebrates) and tertiary (predatory fish) producers. Both elevated CO 2 and elevated temperature boosted primary production. Under elevated CO 2 , the enhanced bottom-up forcing propagated through all trophic levels. Elevated temperature, however, negated the benefits of elevated CO 2 by stalling secondary production. This imbalance caused secondary producer populations to decline as elevated temperature drove predators to consume their prey more rapidly in the face of higher metabolic demand. Our findings demonstrate how anthropogenic CO 2 can function as a resource that boosts productivity throughout food webs, and how warming can reverse this effect by acting as a stressor to trophic interactions. Understanding the shifting balance between the propagation of resource enrichment and its consumption across trophic levels provides a predictive understanding of future dynamics of stability and collapse in food webs and fisheries production. © 2017 John Wiley & Sons Ltd.

Effects of gasoline reactivity and ethanol content on boosted premixed and partially stratified low-temperature gasoline combustion (LTGC)

DOE PAGES

Dec, John E.; Yang, Yi; Ji, Chunsheng; ...

2015-04-14

Low-temperature gasoline combustion (LTGC), based on the compression ignition of a premixed or partially premixed dilute charge, can provide thermal efficiencies (TE) and maximum loads comparable to those of turbo-charged diesel engines, and ultra-low NOx and particulate emissions. Intake boosting is key to achieving high loads with dilute combustion, and it also enhances the fuel's autoignition reactivity, reducing the required intake heating or hot residuals. These effects have the advantages of increasing TE and charge density, allowing greater timing retard with good stability, and making the fuel Φ- sensitive so that partial fuel stratification (PFS) can be applied for highermore » loads and further TE improvements. However, at high boost the autoignition reactivity enhancement can become excessive, and substantial amounts of EGR are required to prevent overly advanced combustion. Accordingly, an experimental investigation has been conducted to determine how the tradeoff between the effects of intake boost varies with fuel-type and its impact on load range and TE. Five fuels are investigated: a conventional AKI=87 petroleum-based gasoline (E0), and blends of 10 and 20% ethanol with this gasoline to reduce its reactivity enhancement with boost (E10 and E20). Furthermore, a second zero-ethanol gasoline with AKI=93 (matching that of E20) was also investigated (CF-E0), and some neat ethanol data are also reported.« less

Dramatically Polarized Opinion on the Role of Brachytherapy Boost in Management of High-risk Prostate Cancer: A Survey of North American Genitourinary Expert Radiation Oncologists.

PubMed

McClelland, Shearwood; Sandler, Kiri A; Degnin, Catherine; Chen, Yiyi; Mitin, Timur

2018-06-01

Three randomized clinical trials have established brachytherapy (BT) boost in combination with external beam radiation therapy (EBRT) and androgen deprivation therapy (ADT) as superior to definitive EBRT and ADT alone in terms of biochemical control (but not overall survival) at the expense of increased toxicity in men with high-risk (HR) prostate cancer (PCa). The current view regarding these 2 treatment algorithms among North American genitourinary (GU) experts is not known. A survey was distributed to 88 practicing North American GU physicians serving on decision-making committees of cooperative group research organizations. Questions pertained to opinions regarding BT as monotherapy for low-risk PCa and BT boost for HR PCa. Responders were asked to self-identify as BT experts versus non-experts. Treatment recommendations were correlated with practice patterns using the Fisher exact test. Forty-two radiation oncologists completed the survey, of whom 23 (55%) recommend EBRT and ADT alone and 19 (45%) recommend addition of BT boost. Twenty-five participants (60%) identified themselves as BT experts. Nearly 90% of those recommending BT boost were BT experts versus approximately 10% of non-BT experts (P < .001). Responders who recommended BT monotherapy as first-choice treatment for low-risk PCa were more likely to recommend BT boost for HR PCa (P < .0001). There is a dramatic polarization in opinions regarding incorporation of BT boost into EBRT + ADT therapy for patients with HR PCa among North American GU radiation oncology experts, who serve on decision-making committees and influence the national treatment guidelines and future clinical trials. Those who identify themselves as BT experts are significantly more likely to recommend BT boost. These findings are likely to influence the national guidelines and implementation of BT boost in current and future North American PCa clinical studies. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Chen, Xiaojian; Qiao, Qiao; Department of Radiotherapy, First Hospital of China Medical University, Shenyang

Purpose: To evaluate the efficiency of standard image-guided radiation therapy (IGRT) to account for lumpectomy cavity (LC) variation during whole-breast irradiation (WBI) and propose an adaptive strategy to improve dosimetry if IGRT fails to address the interfraction LC variations. Methods and Materials: Daily diagnostic-quality CT data acquired during IGRT in the boost stage using an in-room CT for 19 breast cancer patients treated with sequential boost after WBI in the prone position were retrospectively analyzed. Contours of the LC, treated breast, ipsilateral lung, and heart were generated by populating contours from planning CTs to boost fraction CTs using an auto-segmentationmore » tool with manual editing. Three plans were generated on each fraction CT: (1) a repositioning plan by applying the original boost plan with the shift determined by IGRT; (2) an adaptive plan by modifying the original plan according to a fraction CT; and (3) a reoptimization plan by a full-scale optimization. Results: Significant variations were observed in LC. The change in LC volume at the first boost fraction ranged from a 70% decrease to a 50% increase of that on the planning CT. The adaptive and reoptimization plans were comparable. Compared with the repositioning plans, the adaptive plans led to an improvement in target coverage for an increased LC case (1 of 19, 7.5% increase in planning target volume evaluation volume V{sub 95%}), and breast tissue sparing for an LC decrease larger than 35% (3 of 19, 7.5% decrease in breast evaluation volume V{sub 50%}; P=.008). Conclusion: Significant changes in LC shape and volume at the time of boost that deviate from the original plan for WBI with sequential boost can be addressed by adaptive replanning at the first boost fraction.« less

Transcutaneous immunization with cross-reacting material CRM(197) of diphtheria toxin boosts functional antibody levels in mice primed parenterally with adsorbed diphtheria toxoid vaccine.

PubMed

Stickings, Paul; Peyre, Marisa; Coombes, Laura; Muller, Sylviane; Rappuoli, Rino; Del Giudice, Giuseppe; Partidos, Charalambos D; Sesardic, Dorothea

2008-04-01

Transcutaneous immunization (TCI) capitalizes on the accessibility and immunocompetence of the skin, elicits protective immunity, simplifies vaccine delivery, and may be particularly advantageous when frequent boosting is required. In this study we examined the potential of TCI to boost preexisting immune responses to diphtheria in mice. The cross-reacting material (CRM(197)) of diphtheria toxin was used as the boosting antigen and was administered alone or together with either one of two commonly used mucosal adjuvants, cholera toxin (CT) and a partially detoxified mutant of heat-labile enterotoxin of Escherichia coli (LTR72). We report that TCI with CRM(197) significantly boosted preexisting immune responses elicited after parenteral priming with aluminum hydroxide-adsorbed diphtheria toxoid (DTxd) vaccine. In the presence of LTR72 as an adjuvant, toxin-neutralizing antibody titers were significantly higher than those elicited by CRM(197) alone and were comparable to the functional antibody levels induced after parenteral booster immunization with the adsorbed DTxd vaccine. Time course study showed that high levels of toxin-neutralizing antibodies persisted for at least 14 weeks after the transcutaneous boost. In addition, TCI resulted in a vigorous antigen-specific proliferative response in all groups of mice boosted with the CRM(197) protein. These findings highlight the promising prospect of using booster administrations of CRM(197) via the transcutaneous route to establish good herd immunity against diphtheria.

Applying additive modeling and gradient boosting to assess the effects of watershed and reach characteristics on riverine assemblages

USGS Publications Warehouse

Maloney, Kelly O.; Schmid, Matthias; Weller, Donald E.

2012-01-01

Issues with ecological data (e.g. non-normality of errors, nonlinear relationships and autocorrelation of variables) and modelling (e.g. overfitting, variable selection and prediction) complicate regression analyses in ecology. Flexible models, such as generalized additive models (GAMs), can address data issues, and machine learning techniques (e.g. gradient boosting) can help resolve modelling issues. Gradient boosted GAMs do both. Here, we illustrate the advantages of this technique using data on benthic macroinvertebrates and fish from 1573 small streams in Maryland, USA.

Stereotactic Body Radiotherapy: A Promising Treatment Option for the Boost of Oropharyngeal Cancers Not Suitable for Brachytherapy: A Single-Institutional Experience

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

Al-Mamgani, Abrahim, E-mail: a.al-mamgani@erasmusmc.nl; Tans, Lisa; Teguh, David N.

2012-03-15

Purpose: To prospectively assess the outcome and toxicity of frameless stereotactic body radiotherapy (SBRT) as a treatment option for boosting primary oropharyngeal cancers (OPC) in patients who not suitable for the standard brachytherapy boost (BTB). Methods and Materials: Between 2005 and 2010, 51 patients with Stage I to IV biopsy-proven OPC who were not suitable for BTB received boosts by means of SBRT (3 times 5.5 Gy, prescribed to the 80% isodose line), after 46 Gy of IMRT to the primary tumor and neck (when indicated). Endpoints of the study were local control (LC), disease-free survival (DFS), overall survival (OS),more » and acute and late toxicity. Results: After a median follow-up of 18 months (range, 6-65 months), the 2-year actuarial rates of LC, DFS, and OS were 86%, 80%, and 82%, respectively, and the 3-year rates were 70%, 66%, and 54%, respectively. The treatment was well tolerated, as there were no treatment breaks and no Grade 4 or 5 toxicity reported, either acute or chronic. The overall 2-year cumulative incidence of Grade {>=}2 late toxicity was 28%. Of the patients with 2 years with no evidence of disease (n = 20), only 1 patient was still feeding tube dependent and 2 patients had Grade 3 xerostomia. Conclusions: According to our knowledge, this study is the first report of patients with primary OPC who received boosts by means of SBRT. Patients with OPC who are not suitable for the standard BTB can safely and effectively receive boosts by SBRT. With this radiation technique, an excellent outcome was achieved. Furthermore, the SBRT boost did not have a negative impact regarding acute and late side effects.« less

Boosting jet power in black hole spacetimes

PubMed Central

Neilsen, David; Lehner, Luis; Palenzuela, Carlos; Hirschmann, Eric W.; Liebling, Steven L.; Motl, Patrick M.; Garrett, Travis

2011-01-01

The extraction of rotational energy from a spinning black hole via the Blandford–Znajek mechanism has long been understood as an important component in models to explain energetic jets from compact astrophysical sources. Here we show more generally that the kinetic energy of the black hole, both rotational and translational, can be tapped, thereby producing even more luminous jets powered by the interaction of the black hole with its surrounding plasma. We study the resulting Poynting jet that arises from single boosted black holes and binary black hole systems. In the latter case, we find that increasing the orbital angular momenta of the system and/or the spins of the individual black holes results in an enhanced Poynting flux. PMID:21768341

Bidirectional buck boost converter

DOEpatents

Esser, Albert Andreas Maria

1998-03-31

A bidirectional buck boost converter and method of operating the same allows regulation of power flow between first and second voltage sources in which the voltage level at each source is subject to change and power flow is independent of relative voltage levels. In one embodiment, the converter is designed for hard switching while another embodiment implements soft switching of the switching devices. In both embodiments, first and second switching devices are serially coupled between a relatively positive terminal and a relatively negative terminal of a first voltage source with third and fourth switching devices serially coupled between a relatively positive terminal and a relatively negative terminal of a second voltage source. A free-wheeling diode is coupled, respectively, in parallel opposition with respective ones of the switching devices. An inductor is coupled between a junction of the first and second switching devices and a junction of the third and fourth switching devices. Gating pulses supplied by a gating circuit selectively enable operation of the switching devices for transferring power between the voltage sources. In the second embodiment, each switching device is shunted by a capacitor and the switching devices are operated when voltage across the device is substantially zero.

Bidirectional buck boost converter

DOEpatents

Esser, A.A.M.

1998-03-31

A bidirectional buck boost converter and method of operating the same allows regulation of power flow between first and second voltage sources in which the voltage level at each source is subject to change and power flow is independent of relative voltage levels. In one embodiment, the converter is designed for hard switching while another embodiment implements soft switching of the switching devices. In both embodiments, first and second switching devices are serially coupled between a relatively positive terminal and a relatively negative terminal of a first voltage source with third and fourth switching devices serially coupled between a relatively positive terminal and a relatively negative terminal of a second voltage source. A free-wheeling diode is coupled, respectively, in parallel opposition with respective ones of the switching devices. An inductor is coupled between a junction of the first and second switching devices and a junction of the third and fourth switching devices. Gating pulses supplied by a gating circuit selectively enable operation of the switching devices for transferring power between the voltage sources. In the second embodiment, each switching device is shunted by a capacitor and the switching devices are operated when voltage across the device is substantially zero. 20 figs.

An Automatic User-Adapted Physical Activity Classification Method Using Smartphones.

PubMed

Li, Pengfei; Wang, Yu; Tian, Yu; Zhou, Tian-Shu; Li, Jing-Song

2017-03-01

In recent years, an increasing number of people have become concerned about their health. Most chronic diseases are related to lifestyle, and daily activity records can be used as an important indicator of health. Specifically, using advanced technology to automatically monitor actual activities can effectively prevent and manage chronic diseases. The data used in this paper were obtained from acceleration sensors and gyroscopes integrated in smartphones. We designed an efficient Adaboost-Stump running on a smartphone to classify five common activities: cycling, running, sitting, standing, and walking and achieved a satisfactory classification accuracy of 98%. We designed an online learning method, and the classification model requires continuous training with actual data. The parameters in the model then become increasingly fitted to the specific user, which allows the classification accuracy to reach 95% under different use environments. In addition, this paper also utilized the OpenCL framework to design the program in parallel. This process can enhance the computing efficiency approximately ninefold.

Medicaid plan, health centers reveal secrets to boosting HEDIS scores, quality of care.

PubMed

1999-07-01

How to do well on HEDIS measurement and boost quality of care for your Medicaid members. Neighborhood Health Plan in Boston, MA, attributes its top performance on Medicaid HEDIS measures to providers' care models, a commitment to quality, and the quest for performance data.

Optimizing HIV-1-specific CD8+ T-cell induction by recombinant BCG in prime-boost regimens with heterologous viral vectors.

PubMed

Hopkins, Richard; Bridgeman, Anne; Bourne, Charles; Mbewe-Mvula, Alice; Sadoff, Jerald C; Both, Gerald W; Joseph, Joan; Fulkerson, John; Hanke, Tomáš

2011-12-01

The desire to induce HIV-1-specific responses soon after birth to prevent breast milk transmission of HIV-1 led us to propose a vaccine regimen which primes HIV-1-specific T cells using a recombinant Mycobacterium bovis bacillus Calmette-Guérin (rBCG) vaccine. Because attenuated live bacterial vaccines are typically not sufficiently immunogenic as stand-alone vaccines, rBCG-primed T cells will likely require boost immunization(s). Here, we compared modified Danish (AERAS-401) and Pasteur lysine auxotroph (222) strains of BCG expressing the immunogen HIVA for their potency to prime HIV-1-specific responses in adult BALB/c mice and examined four heterologous boosting HIVA vaccines for their immunogenic synergy. We found that both BCG.HIVA(401) and BCG.HIVA(222) primed HIV-1-specific CD8(+) T-cell-mediated responses. The strongest boosts were delivered by human adenovirus-vectored HAdV5.HIVA and sheep atadenovirus-vectored OAdV7.HIVA vaccines, followed by poxvirus MVA.HIVA; the weakest was plasmid pTH.HIVA DNA. The prime-boost regimens induced T cells capable of efficient in vivo killing of sensitized target cells. We also observed that the BCG.HIVA(401) and BCG.HIVA(222) vaccines have broadly similar immunologic properties, but display a number of differences mainly detected through distinct profiles of soluble intercellular signaling molecules produced by immune splenocytes in response to both HIV-1- and BCG-specific stimuli. These results encourage further development of the rBCG prime-boost regimen. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.

PubMed

Pérez-Castillo, Yunierkis; Lazar, Cosmin; Taminau, Jonatan; Froeyen, Mathy; Cabrera-Pérez, Miguel Ángel; Nowé, Ann

2012-09-24

Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic Algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic Algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic Algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

Intranasal mucosal boosting with an adenovirus-vectored vaccine markedly enhances the protection of BCG-primed guinea pigs against pulmonary tuberculosis.

PubMed

Xing, Zhou; McFarland, Christine T; Sallenave, Jean-Michel; Izzo, Angelo; Wang, Jun; McMurray, David N

2009-06-10

Recombinant adenovirus-vectored (Ad) tuberculosis (TB) vaccine platform has demonstrated great potential to be used either as a stand-alone or a boost vaccine in murine models. However, Ad TB vaccine remains to be evaluated in a more relevant and sensitive guinea pig model of pulmonary TB. Many vaccine candidates shown to be effective in murine models have subsequently failed to pass the test in guinea pig models. Specific pathogen-free guinea pigs were immunized with BCG, AdAg85A intranasally (i.n), AdAg85A intramuscularly (i.m), BCG boosted with AdAg85A i.n, BCG boosted with AdAg85A i.m, or treated only with saline. The animals were then infected by a low-dose aerosol of M. tuberculosis (M.tb). At the specified times, the animals were sacrificed and the levels of infection in the lung and spleen were assessed. In separate studies, the long-term disease outcome of infected animals was monitored until the termination of this study. Immunization with Ad vaccine alone had minimal beneficial effects. Immunization with BCG alone and BCG prime-Ad vaccine boost regimens significantly reduced the level of M.tb infection in the tissues to a similar extent. However, while BCG alone prolonged the survival of infected guinea pigs, the majority of BCG-immunized animals succumbed by 53 weeks post-M.tb challenge. In contrast, intranasal or intramuscular Ad vaccine boosting of BCG-primed animals markedly improved the survival rate with 60% of BCG/Ad i.n- and 40% of BCG/Ad i.m-immunized guinea pigs still surviving by 74 weeks post-aerosol challenge. Boosting, particularly via the intranasal mucosal route, with AdAg85A vaccine is able to significantly enhance the long-term survival of BCG-primed guinea pigs following pulmonary M.tb challenge. Our results thus support further evaluation of this viral-vectored TB vaccine in clinical trials.

Scaling Trends and Tradeoffs between Short Channel Effect and Channel Boosting Characteristics in Sub-20 nm Bulk/Silicon-on-Insulator NAND Flash Memory

NASA Astrophysics Data System (ADS)

Miyaji, Kousuke; Hung, Chinglin; Takeuchi, Ken

2012-04-01

The scaling trends and limitation in sub-20 nm a bulk and silicon-on-insulator (SOI) NAND flash memory is studied by the three-dimensional (3D) device simulation focusing on short channel effects (SCE), channel boost leakage and channel voltage boosting characteristics during the program-inhibit operation. Although increasing punch-through stopper doping concentration is effective for suppressing SCE in bulk NAND cells, the generation of junction leakage becomes serious. On the other hand, SCE can be suppressed by thinning the buried oxide (BOX) in SOI NAND cells. However, the boosted channel voltage decreases by the higher BOX capacitance. It is concluded that the scaling limitation is dominated by the junction leakage and channel boosting capability for bulk and SOI NAND flash cells, respectively, and the scaling limit is decreased to 9 nm using SOI NAND flash memory cells from 13 nm in bulk NAND flash memory cells.

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

Targeting the genital tract mucosa with a lipopeptide/recombinant adenovirus prime/boost vaccine induces potent and long-lasting CD8+ T cell immunity against herpes: importance of MyD88.

PubMed

Zhang, Xiuli; Dervillez, Xavier; Chentoufi, Aziz Alami; Badakhshan, Tina; Bettahi, Ilham; Benmohamed, Lbachir

2012-11-01

Targeting of the mucosal immune system of the genital tract with subunit vaccines has failed to induce potent and durable local CD8(+) T cell immunity, which is crucial for protection against many sexually transmitted viral pathogens, including HSV type 2 (HSV-2), which causes genital herpes. In this study, we aimed to investigate the potential of a novel lipopeptide/adenovirus type 5 (Lipo/rAdv5) prime/boost mucosal vaccine for induction of CD8(+) T cell immunity to protect the female genital tract from herpes. The lipopeptide vaccine and the rAdv5 vaccine express the immunodominant HSV-2 CD8(+) T cell epitope (gB(498-505)), and both were delivered intravaginally in the progesterone-induced B6 mouse model of genital herpes. Compared with mice immunized with the homologous lipopeptide/lipopeptide (Lipo/Lipo) vaccine, the Lipo/rAdv5 prime/boost immunized mice 1) developed potent and sustained HSV-specific CD8(+) T cells, detected in both the genital tract draining nodes and in the vaginal mucosa; 2) had significantly lower virus titers; 3) had decreased overt signs of genital herpes disease; and 4) did not succumb to lethal infection (p < 0.005) after intravaginal HSV-2 challenge. Polyfunctional CD8(+) T cells, producing IFN-γ, TNF-α, and IL-2 and exhibiting cytotoxic activity, were associated with protection (p < 0.005). The protective CD8(+) T cell response was significantly compromised in the absence of the adapter MyD88 (p = 0.0001). Taken together, these findings indicate that targeting of the vaginal mucosa with a Lipo/rAdv5 prime/boost vaccine elicits a potent, MyD88-dependent, and long-lasting mucosal CD8(+) T cell protective immunity against sexually transmitted herpes infection and disease.

50 Sure Fire Ideas for Boosting Morale and Creating a Can-Do Culture.

ERIC Educational Resources Information Center

Baker, John; And Others

This three-part pamphlet presents 52 ideas contributed by 19 administrators at California community colleges for boosting the morale and performance of college administrators and staff. Following a list of contributors, the first part provides 39 suggestions for acknowledging contributions and encouraging staff members, including writing short…

Integrated bioethanol production to boost low-concentrated cellulosic ethanol without sacrificing ethanol yield.

PubMed

Xu, Youjie; Zhang, Meng; Roozeboom, Kraig; Wang, Donghai

2018-02-01

Four integrated designs were proposed to boost cellulosic ethanol titer and yield. Results indicated co-fermentation of corn flour with hydrolysate liquor from saccharified corn stover was the best integration scheme and able to boost ethanol titers from 19.9 to 123.2 g/L with biomass loading of 8% and from 36.8 to 130.2 g/L with biomass loadings of 16%, respectively, while meeting the minimal ethanol distillation requirement of 40 g/L and achieving high ethanol yields of above 90%. These results indicated integration of first and second generation ethanol production could significantly accelerate the commercialization of cellulosic biofuel production. Co-fermentation of starchy substrate with hydrolysate liquor from saccharified biomass is able to significantly enhance ethanol concentration to reduce energy cost for distillation without sacrificing ethanol yields. This novel method could be extended to any pretreatment of biomass from low to high pH pretreatment as demonstrated in this study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of the Educational Boost Your Brain and Memory Program Among Senior Living Residents.

PubMed

Nicholson, Roscoe; O'Brien, Catherine

2017-12-01

This random assignment waitlist control intervention study examined an implementation of the educational Boost Your Brain and Memory cognitive fitness intervention in 12 senior living organizations. Older adult participants ( n = 166) completed measures of brain health knowledge, use of memory techniques, physical and intellectual activity, and mindfulness, at baseline and after the intervention group's completion of the course. Changes in knowledge scores and in self-reported physical and intellectual activity increased significantly more for intervention participants than for waitlist controls at the conclusion of the course. There were no significant changes between the groups in mindfulness or use of memory techniques. This suggests that in senior living settings Boost Your Brain and Memory is effective in educating participants about brain healthy behaviors and in motivating behavioral change in the areas of physical and intellectual activity.

Boosting the pentose phosphate pathway restores cardiac progenitor cell availability in diabetes.

PubMed

Katare, Rajesh; Oikawa, Atsuhiko; Cesselli, Daniela; Beltrami, Antonio P; Avolio, Elisa; Muthukrishnan, Deepti; Munasinghe, Pujika Emani; Angelini, Gianni; Emanueli, Costanza; Madeddu, Paolo

2013-01-01

Diabetes impinges upon mechanisms of cardiovascular repair. However, the biochemical adaptation of cardiac stem cells to sustained hyperglycaemia remains largely unknown. Here, we investigate the molecular targets of high glucose-induced damage in cardiac progenitor cells (CPCs) from murine and human hearts and attempt safeguarding CPC viability and function through reactivation of the pentose phosphate pathway. Type-1 diabetes was induced by streptozotocin. CPC abundance was determined by flow cytometry. Proliferating CPCs were identified in situ by immunostaining for the proliferation marker Ki67. Diabetic hearts showed marked reduction in CPC abundance and proliferation when compared with controls. Moreover, Sca-1(pos) CPCs isolated from hearts of diabetic mice displayed reduced activity of key enzymes of the pentose phosphate pathway, glucose-6-phosphate dehydrogenase (G6PD), and transketolase, increased levels of superoxide and advanced glucose end-products (AGE), and inhibition of the Akt/Pim-1/Bcl-2 signalling pathway. Similarly, culture of murine CPCs or human CD105(pos) progenitor cells in high glucose inhibits the pentose phosphate and pro-survival signalling pathways, leading to the activation of apoptosis. In vivo and in vitro supplementation with benfotiamine reactivates the pentose phosphate pathway and rescues CPC availability and function. This benefit is abrogated by either G6PD silencing by small interfering RNA (siRNA) or Akt inhibition by dominant-negative Akt. We provide new evidence of the negative impact of diabetes and high glucose on mechanisms controlling CPC redox state and survival. Boosting the pentose phosphate pathway might represent a novel mechanistic target for protection of CPC integrity.

Boosting mediated electron transfer in bioelectrochemical systems with tailored defined microbial cocultures.

PubMed

Schmitz, Simone; Rosenbaum, Miriam A

2018-05-19

Bioelectrochemical systems (BES) hold great promise for sustainable energy generation via a microbial catalyst from organic matter, for example, from wastewater. To improve current generation in BES, understanding the underlying microbiology of the electrode community is essential. Electron mediator producing microorganism like Pseudomonas aeruginosa play an essential role in efficient electricity generation in BES. These microbes enable even nonelectroactive microorganism like Enterobacter aerogenes to contribute to current production. Together they form a synergistic coculture, where both contribute to community welfare. To use microbial co-operation in BES, the physical and chemical environments provided in the natural habitats of the coculture play a crucial role. Here, we show that synergistic effects in defined cocultures of P. aeruginosa and E. aerogenes can be strongly enhanced toward high current production by adapting process parameters, like pH, temperature, oxygen demand, and substrate requirements. Especially, oxygen was identified as a major factor influencing coculture behavior and optimization of its supply could enhance electric current production over 400%. Furthermore, operating the coculture in fed-batch mode enabled us to obtain very high current densities and to harvest electrical energy for 1 month. In this optimized condition, the coulombic efficiency of the process was boosted to 20%, which is outstanding for mediator-based electron transfer. This study lays the foundation for a rationally designed utilization of cocultures in BES for bioenergy generation from specific wastewaters or for bioprocess sensing and for benefiting from their synergistic effects under controlled bioprocess condition. © 2018 Wiley Periodicals, Inc.

Research procedure for buck-boost converter for small electric vehicles

NASA Astrophysics Data System (ADS)

Vacheva, Gergana; Hinov, Nikolay; Penev, Dimitar

2017-12-01

In the current paper is developed a mathematical model realized in Matlab for describing a buck-boost converter for control of small electric vehicle. The model is presented with differential equations which describes the processes in the converter. Through the research of this model it can be accomplished the optimal work mode of a small electric vehicles. The proposed converter can be used in a wide range of applications like small electric vehicles, smart grids and different systems for energy storage.

Modeling evolution of dark matter substructure and annihilation boost

NASA Astrophysics Data System (ADS)

Hiroshima, Nagisa; Ando, Shin'ichiro; Ishiyama, Tomoaki

2018-06-01

We study evolution of dark matter substructures, especially how they lose mass and change density profile after they fall in gravitational potential of larger host halos. We develop an analytical prescription that models the subhalo mass evolution and calibrate it to results of N -body numerical simulations of various scales from very small (Earth size) to large (galaxies to clusters) halos. We then combine the results with halo accretion histories and calculate the subhalo mass function that is physically motivated down to Earth-mass scales. Our results—valid for arbitrary host masses and redshifts—have reasonable agreement with those of numerical simulations at resolved scales. Our analytical model also enables self-consistent calculations of the boost factor of dark matter annihilation, which we find to increase from tens of percent at the smallest (Earth) and intermediate (dwarfs) masses to a factor of several at galaxy size, and to become as large as a factor of ˜10 for the largest halos (clusters) at small redshifts. Our analytical approach can accommodate substructures in the subhalos (sub-subhalos) in a consistent framework, which we find to give up to a factor of a few enhancements to the annihilation boost. The presence of the subhalos enhances the intensity of the isotropic gamma-ray background by a factor of a few, and as the result, the measurement by the Fermi Large Area Telescope excludes the annihilation cross section greater than ˜4 ×10-26 cm3 s-1 for dark matter masses up to ˜200 GeV .

Diesel Combustion and Emission Using High Boost and High Injection Pressure in a Single Cylinder Engine

NASA Astrophysics Data System (ADS)

Aoyagi, Yuzo; Kunishima, Eiji; Asaumi, Yasuo; Aihara, Yoshiaki; Odaka, Matsuo; Goto, Yuichi

Heavy-duty diesel engines have adopted numerous technologies for clean emissions and low fuel consumption. Some are direct fuel injection combined with high injection pressure and adequate in-cylinder air motion, turbo-intercooler systems, and strong steel pistons. Using these technologies, diesel engines have achieved an extremely low CO2 emission as a prime mover. However, heavy-duty diesel engines with even lower NOx and PM emission levels are anticipated. This study achieved high-boost and lean diesel combustion using a single cylinder engine that provides good engine performance and clean exhaust emission. The experiment was done under conditions of intake air quantity up to five times that of a naturally aspirated (NA) engine and 200MPa injection pressure. The adopted pressure booster is an external supercharger that can control intake air temperature. In this engine, the maximum cylinder pressure was increased and new technologies were adopted, including a monotherm piston for endurance of Pmax =30MPa. Moreover, every engine part is newly designed. As the boost pressure increases, the rate of heat release resembles the injection rate and becomes sharper. The combustion and brake thermal efficiency are improved. This high boost and lean diesel combustion creates little smoke; ISCO and ISTHC without the ISNOx increase. It also yields good thermal efficiency.

Ag85A-specific CD4+ T cell lines derived after boosting BCG-vaccinated cattle with Ad5-85A possess both mycobacterial growth inhibition and anti-inflammatory properties.

PubMed

Metcalfe, Hannah J; Biffar, Lucia; Steinbach, Sabine; Guzman, Efrain; Connelley, Tim; Morrison, Ivan; Vordermeier, H Martin; Villarreal-Ramos, Bernardo

2018-05-11

There is a need to improve the efficacy of the BCG vaccine against human and bovine tuberculosis. Previous data showed that boosting bacilli Calmette-Guerin (BCG)-vaccinated cattle with a recombinant attenuated human type 5 adenovirally vectored subunit vaccine (Ad5-85A) increased BCG protection and was associated with increased frequency of Ag85A-specific CD4 + T cells post-boosting. Here, the capacity of Ag85A-specific CD4 + T cell lines - derived before and after viral boosting - to interact with BCG-infected macrophages was evaluated. No difference before and after boosting was found in the capacity of these Ag85A-specific CD4 + T cell lines to restrict mycobacterial growth, but the secretion of IL-10 in vitro post-boost increased significantly. Furthermore, cell lines derived post-boost had no statistically significant difference in the secretion of pro-inflammatory cytokines (IL-1β, IL-12, IFNγ or TNFα) compared to pre-boost lines. In conclusion, the protection associated with the increased number of Ag85A-specific CD4 + T cells restricting mycobacterial growth may be associated with anti-inflammatory properties to limit immune-pathology. Copyright © 2018 Department for Environment Food and Rural Affairs. Published by Elsevier Ltd.. All rights reserved.

Dimensional Representation and Gradient Boosting for Seismic Event Classification

NASA Astrophysics Data System (ADS)

Semmelmayer, F. C.; Kappedal, R. D.; Magana-Zook, S. A.

2017-12-01

In this research, we conducted experiments of representational structures on 5009 seismic signals with the intent of finding a method to classify signals as either an explosion or an earthquake in an automated fashion. We also applied a gradient boosted classifier. While perfect classification was not attained (approximately 88% was our best model), some cases demonstrate that many events can be filtered out as very high probability being explosions or earthquakes, diminishing subject-matter experts'(SME) workload for first stage analysis. It is our hope that these methods can be refined, further increasing the classification probability.

Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm.

PubMed

Kamath, Uday; Domeniconi, Carlotta; De Jong, Kenneth

2018-01-01

Many real-world problems involve massive amounts of data. Under these circumstances learning algorithms often become prohibitively expensive, making scalability a pressing issue to be addressed. A common approach is to perform sampling to reduce the size of the dataset and enable efficient learning. Alternatively, one customizes learning algorithms to achieve scalability. In either case, the key challenge is to obtain algorithmic efficiency without compromising the quality of the results. In this article we discuss a meta-learning algorithm (PSBML) that combines concepts from spatially structured evolutionary algorithms (SSEAs) with concepts from ensemble and boosting methodologies to achieve the desired scalability property. We present both theoretical and empirical analyses which show that PSBML preserves a critical property of boosting, specifically, convergence to a distribution centered around the margin. We then present additional empirical analyses showing that this meta-level algorithm provides a general and effective framework that can be used in combination with a variety of learning classifiers. We perform extensive experiments to investigate the trade-off achieved between scalability and accuracy, and robustness to noise, on both synthetic and real-world data. These empirical results corroborate our theoretical analysis, and demonstrate the potential of PSBML in achieving scalability without sacrificing accuracy.

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

Eads, Damian Ryan; Rosten, Edward; Helmbold, David

The authors present BEAMER: a new spatially exploitative approach to learning object detectors which shows excellent results when applied to the task of detecting objects in greyscale aerial imagery in the presence of ambiguous and noisy data. There are four main contributions used to produce these results. First, they introduce a grammar-guided feature extraction system, enabling the exploration of a richer feature space while constraining the features to a useful subset. This is specified with a rule-based generative grammer crafted by a human expert. Second, they learn a classifier on this data using a newly proposed variant of AdaBoost whichmore » takes into account the spatially correlated nature of the data. Third, they perform another round of training to optimize the method of converting the pixel classifications generated by boosting into a high quality set of (x,y) locations. lastly, they carefully define three common problems in object detection and define two evaluation criteria that are tightly matched to these problems. Major strengths of this approach are: (1) a way of randomly searching a broad feature space, (2) its performance when evaluated on well-matched evaluation criteria, and (3) its use of the location prediction domain to learn object detectors as well as to generate detections that perform well on several tasks: object counting, tracking, and target detection. They demonstrate the efficacy of BEAMER with a comprehensive experimental evaluation on a challenging data set.« less

Automatic detection of regions of interest in mammographic images

NASA Astrophysics Data System (ADS)

Cheng, Erkang; Ling, Haibin; Bakic, Predrag R.; Maidment, Andrew D. A.; Megalooikonomou, Vasileios

2011-03-01

This work is a part of our ongoing study aimed at comparing the topology of anatomical branching structures with the underlying image texture. Detection of regions of interest (ROIs) in clinical breast images serves as the first step in development of an automated system for image analysis and breast cancer diagnosis. In this paper, we have investigated machine learning approaches for the task of identifying ROIs with visible breast ductal trees in a given galactographic image. Specifically, we have developed boosting based framework using the AdaBoost algorithm in combination with Haar wavelet features for the ROI detection. Twenty-eight clinical galactograms with expert annotated ROIs were used for training. Positive samples were generated by resampling near the annotated ROIs, and negative samples were generated randomly by image decomposition. Each detected ROI candidate was given a confidences core. Candidate ROIs with spatial overlap were merged and their confidence scores combined. We have compared three strategies for elimination of false positives. The strategies differed in their approach to combining confidence scores by summation, averaging, or selecting the maximum score.. The strategies were compared based upon the spatial overlap with annotated ROIs. Using a 4-fold cross-validation with the annotated clinical galactographic images, the summation strategy showed the best performance with 75% detection rate. When combining the top two candidates, the selection of maximum score showed the best performance with 96% detection rate.

Evaluation of Machine Learning Algorithms for Classification of Primary Biological Aerosol using a new UV-LIF spectrometer

NASA Astrophysics Data System (ADS)

Ruske, S. T.; Topping, D. O.; Foot, V. E.; Kaye, P. H.; Stanley, W. R.; Morse, A. P.; Crawford, I.; Gallagher, M. W.

2016-12-01

Characterisation of bio-aerosols has important implications within Environment and Public Health sectors. Recent developments in Ultra-Violet Light Induced Fluorescence (UV-LIF) detectors such as the Wideband Integrated bio-aerosol Spectrometer (WIBS) and the newly introduced Multiparameter bio-aerosol Spectrometer (MBS) has allowed for the real time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal Spores and pollen. This new generation of instruments has enabled ever-larger data sets to be compiled with the aim of studying more complex environments, yet the algorithms used for specie classification remain largely invalidated. It is therefore imperative that we validate the performance of different algorithms that can be used for the task of classification, which is the focus of this study. For unsupervised learning we test Hierarchical Agglomerative Clustering with various different linkages. For supervised learning, ten methods were tested; including decision trees, ensemble methods: Random Forests, Gradient Boosting and AdaBoost; two implementations for support vector machines: libsvm and liblinear; Gaussian methods: Gaussian naïve Bayesian, quadratic and linear discriminant analysis and finally the k-nearest neighbours algorithm. The methods were applied to two different data sets measured using a new Multiparameter bio-aerosol Spectrometer. We find that clustering, in general, performs slightly worse than the supervised learning methods correctly classifying, at best, only 72.7 and 91.1 percent for the two data sets. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 88.1 and 97.8 percent of the testing data respectively across the two data sets. We discuss the wider relevance of these results with regards to challenging existing classification in real-world environments.

Noninvasive differential diagnosis of dental periapical lesions in cone-beam CT scans.

PubMed

Okada, Kazunori; Rysavy, Steven; Flores, Arturo; Linguraru, Marius George

2015-04-01

This paper proposes a novel application of computer-aided diagnosis (CAD) to an everyday clinical dental challenge: the noninvasive differential diagnosis of periapical lesions between periapical cysts and granulomas. A histological biopsy is the most reliable method currently available for this differential diagnosis; however, this invasive procedure prevents the lesions from healing noninvasively despite a report that they may heal without surgical treatment. A CAD using cone-beam computed tomography (CBCT) offers an alternative noninvasive diagnostic tool which helps to avoid potentially unnecessary surgery and to investigate the unknown healing process and rate for the lesions. The proposed semiautomatic solution combines graph-based random walks segmentation with machine learning-based boosted classifiers and offers a robust clinical tool with minimal user interaction. As part of this CAD framework, the authors provide two novel technical contributions: (1) probabilistic extension of the random walks segmentation with likelihood ratio test and (2) LDA-AdaBoost: a new integration of weighted linear discriminant analysis to AdaBoost. A dataset of 28 CBCT scans is used to validate the approach and compare it with other popular segmentation and classification methods. The results show the effectiveness of the proposed method with 94.1% correct classification rate and an improvement of the performance by comparison with the Simon's state-of-the-art method by 17.6%. The authors also compare classification performances with two independent ground-truth sets from the histopathology and CBCT diagnoses provided by endodontic experts. Experimental results of the authors show that the proposed CAD system behaves in clearer agreement with the CBCT ground-truth than with histopathology, supporting the Simon's conjecture that CBCT diagnosis can be as accurate as histopathology for differentiating the periapical lesions.

Noninvasive differential diagnosis of dental periapical lesions in cone-beam CT scans

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

Okada, Kazunori, E-mail: kazokada@sfsu.edu; Rysavy, Steven; Flores, Arturo

Purpose: This paper proposes a novel application of computer-aided diagnosis (CAD) to an everyday clinical dental challenge: the noninvasive differential diagnosis of periapical lesions between periapical cysts and granulomas. A histological biopsy is the most reliable method currently available for this differential diagnosis; however, this invasive procedure prevents the lesions from healing noninvasively despite a report that they may heal without surgical treatment. A CAD using cone-beam computed tomography (CBCT) offers an alternative noninvasive diagnostic tool which helps to avoid potentially unnecessary surgery and to investigate the unknown healing process and rate for the lesions. Methods: The proposed semiautomatic solutionmore » combines graph-based random walks segmentation with machine learning-based boosted classifiers and offers a robust clinical tool with minimal user interaction. As part of this CAD framework, the authors provide two novel technical contributions: (1) probabilistic extension of the random walks segmentation with likelihood ratio test and (2) LDA-AdaBoost: a new integration of weighted linear discriminant analysis to AdaBoost. Results: A dataset of 28 CBCT scans is used to validate the approach and compare it with other popular segmentation and classification methods. The results show the effectiveness of the proposed method with 94.1% correct classification rate and an improvement of the performance by comparison with the Simon’s state-of-the-art method by 17.6%. The authors also compare classification performances with two independent ground-truth sets from the histopathology and CBCT diagnoses provided by endodontic experts. Conclusions: Experimental results of the authors show that the proposed CAD system behaves in clearer agreement with the CBCT ground-truth than with histopathology, supporting the Simon’s conjecture that CBCT diagnosis can be as accurate as histopathology for differentiating the periapical lesions.« less

Single multivalent vaccination boosted by trickle larval infection confers protection against experimental lymphatic filariasis

PubMed Central

Joseph, SK; Ramaswamy, K

2013-01-01

The multivalent vaccine BmHAT, consisting of the Brugia malayi infective larval (L3) antigens heat shock protein12.6 (HSP12.6), abundant larval transcript-2 (ALT-2) and tetraspanin large extra cellular loop (TSP-LEL), was shown to be protective in rodent models from our laboratory. We hypothesize that since these antigens were identified using protective antibodies from immune endemic normal individuals, the multivalent vaccine can be augmented by natural L3 infections providing protection to the vaccinated host. This hypothesis was tested using single dose of DNA and Protein or Protein alone of the BmHAT vaccination in gerbils followed by live trickle L3 infection as booster dose. Vaccine-induced protection in gerbils was determined by worm establishment, micropore chamber assay and by antibody dependant cell cytotoxicity (ADCC) assay. Results were compared with the traditional prime-boost vaccination regimen. Gerbils vaccinated with BmHAT and boosted with L3 trickle infection were protected 51% (BmHAT DNA-Protein) and 48% (BmHAT Protein) respectively. BmHAT vaccination plus L3 trickle booster generated significant titer of antigen-specific IgG antibodies comparable to the traditional prime boost vaccination approach. BmHAT vaccination plus L3 trickle booster also generated antigen-specific cells in the spleen of vaccinated animals and these cells secreted predominantly IFN-γ and IL-4 in response to the vaccine antigens. These studies thus show that single dose of BmHAT multivalent vaccination followed by L3 trickle booster infection can confer significant protection against lymphatic filariasis. PMID:23735679

Sterile Protection against Plasmodium knowlesi in Rhesus Monkeys from a Malaria Vaccine: Comparison of Heterologous Prime Boost Strategies

PubMed Central

Jiang, George; Shi, Meng; Conteh, Solomon; Richie, Nancy; Banania, Glenna; Geneshan, Harini; Valencia, Anais; Singh, Priti; Aguiar, Joao; Limbach, Keith; Kamrud, Kurt I.; Rayner, Jonathan; Smith, Jonathan; Bruder, Joseph T.; King, C. Richter; Tsuboi, Takafumi; Takeo, Satoru; Endo, Yaeta; Doolan, Denise L.; Richie, Thomas L.; Weiss, Walter R.

2009-01-01

Using newer vaccine platforms which have been effective against malaria in rodent models, we tested five immunization regimens against Plasmodium knowlesi in rhesus monkeys. All vaccines included the same four P. knowlesi antigens: the pre-erythrocytic antigens CSP, SSP2, and erythrocytic antigens AMA1, MSP1. We used four vaccine platforms for prime or boost vaccinations: plasmids (DNA), alphavirus replicons (VRP), attenuated adenovirus serotype 5 (Ad), or attenuated poxvirus (Pox). These four platforms combined to produce five different prime/boost vaccine regimens: Pox alone, VRP/Pox, VRP/Ad, Ad/Pox, and DNA/Pox. Five rhesus monkeys were immunized with each regimen, and five Control monkeys received a mock vaccination. The time to complete vaccinations was 420 days. All monkeys were challenged twice with 100 P. knowlesi sporozoites given IV. The first challenge was given 12 days after the last vaccination, and the monkeys receiving the DNA/Pox vaccine were the best protected, with 3/5 monkeys sterilely protected and 1/5 monkeys that self-cured its parasitemia. There was no protection in monkeys that received Pox malaria vaccine alone without previous priming. The second sporozoite challenge was given 4 months after the first. All 4 monkeys that were protected in the first challenge developed malaria in the second challenge. DNA, VRP and Ad5 vaccines all primed monkeys for strong immune responses after the Pox boost. We discuss the high level but short duration of protection in this experiment and the possible benefits of the long interval between prime and boost. PMID:19668343

Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection

DTIC Science & Technology

2015-02-01

multi-resolution stacking (MRS), which is a stack of ensemble classifiers. Each classifier in a building block inputs the concatenation of the predictions ...a base classifier in MRS, named boosted deep neural network (bDNN). bDNN first generates multiple base predictions from different contexts of a single...frame by only one DNN and then aggregates the base predictions for a better prediction of the frame, and it is different from computationally

Transcriptome Analysis in Tardigrade Species Reveals Specific Molecular Pathways for Stress Adaptations

PubMed Central

Förster, Frank; Beisser, Daniela; Grohme, Markus A.; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C.; Shkumatov, Alexander V.; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O.; Frohme, Marcus; Dandekar, Thomas

2012-01-01

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant. PMID:22563243

Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations.

PubMed

Förster, Frank; Beisser, Daniela; Grohme, Markus A; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C; Shkumatov, Alexander V; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O; Frohme, Marcus; Dandekar, Thomas

2012-01-01

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant.

Puncture initial data for black-hole binaries with high spins and high boosts

NASA Astrophysics Data System (ADS)

Ruchlin, Ian; Healy, James; Lousto, Carlos O.; Zlochower, Yosef

2017-01-01

We solve the Hamiltonian and momentum constraints of general relativity for two black holes with nearly extremal spins and relativistic boosts in the puncture formalism. We use a non-conformally-flat ansatz with an attenuated superposition of two Lorentz-boosted, conformally Kerr or conformally Schwarzschild 3-metrics and their corresponding extrinsic curvatures. We compare evolutions of these data with the standard Bowen-York conformally flat ansatz (technically limited to intrinsic spins χ =S /MADM2=0.928 and boosts P /MADM=0.897 ), finding, typically, an order of magnitude smaller burst of spurious radiation and agreement with inspiral and merger. As a first case study, we evolve two equal-mass black holes from rest with an initial separation of d =12 M and spins χi=Si/mi2=0.99 , compute the waveforms produced by the collision, the energy and angular momentum radiated, and the recoil of the final remnant black hole. We find that the black-hole trajectories curve at close separations, leading to the radiation of angular momentum. We also study orbiting nonspinning and moderate-spin black-hole binaries and compare these with standard Bowen-York data. We find a substantial reduction in the nonphysical initial burst of radiation which leads to cleaner waveforms. Finally, we study the case of orbiting binary black-hole systems with spin magnitude χi=0.95 in an aligned configuration and compare waveform and final remnant results with those of the SXS Collaboration [54 A. H. Mroue et al., Phys. Rev. Lett. 111, 241104 (2013)., 10.1103/PhysRevLett.111.241104], finding excellent agreement. This represents the first moving puncture evolution of orbiting and spinning black holes exceeding the Bowen-York limit. Finally, we study different choices of the initial lapse and lapse evolution equation in the moving puncture approach to improve the accuracy and efficiency of the simulations.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy.

PubMed

Kim, Yusung; Tomé, Wolfgang A

2008-01-01

Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy

PubMed Central

Kim, Yusung; Tomé, Wolfgang A.

2010-01-01

Summary Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans. PMID:21151734

Using Boosting Decision Trees in Gravitational Wave Searches triggered by Gamma-ray Bursts

NASA Astrophysics Data System (ADS)

Zuraw, Sarah; LIGO Collaboration

2015-04-01

The search for gravitational wave bursts requires the ability to distinguish weak signals from background detector noise. Gravitational wave bursts are characterized by their transient nature, making them particularly difficult to detect as they are similar to non-Gaussian noise fluctuations in the detector. The Boosted Decision Tree method is a powerful machine learning algorithm which uses Multivariate Analysis techniques to explore high-dimensional data sets in order to distinguish between gravitational wave signal and background detector noise. It does so by training with known noise events and simulated gravitational wave events. The method is tested using waveform models and compared with the performance of the standard gravitational wave burst search pipeline for Gamma-ray Bursts. It is shown that the method is able to effectively distinguish between signal and background events under a variety of conditions and over multiple Gamma-ray Burst events. This example demonstrates the usefulness and robustness of the Boosted Decision Tree and Multivariate Analysis techniques as a detection method for gravitational wave bursts. LIGO, UMass, PREP, NEGAP.

A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem.

PubMed

Dehzangi, Abdollah; Paliwal, Kuldip; Sharma, Alok; Dehzangi, Omid; Sattar, Abdul

2013-01-01

Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches to solve this problem, it still remains as an unsolved issue for bioinformatics that demands more attention and exploration. In this study, we propose a novel feature extraction model that incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation-based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, naive Bayes, multilayer perceptron (MLP), and support vector machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks.

Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study

NASA Astrophysics Data System (ADS)

Taroni, Paola; Paganoni, Anna Maria; Ieva, Francesca; Pifferi, Antonio; Quarto, Giovanna; Abbate, Francesca; Cassano, Enrico; Cubeddu, Rinaldo

2017-01-01

Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635-1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient’s anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation.

Improving Prediction Accuracy of “Central Line-Associated Blood Stream Infections” Using Data Mining Models

PubMed Central

Noaman, Amin Y.; Jamjoom, Arwa; Al-Abdullah, Nabeela; Nasir, Mahreen; Ali, Anser G.

2017-01-01

Prediction of nosocomial infections among patients is an important part of clinical surveillance programs to enable the related personnel to take preventive actions in advance. Designing a clinical surveillance program with capability of predicting nosocomial infections is a challenging task due to several reasons, including high dimensionality of medical data, heterogenous data representation, and special knowledge required to extract patterns for prediction. In this paper, we present details of six data mining methods implemented using cross industry standard process for data mining to predict central line-associated blood stream infections. For our study, we selected datasets of healthcare-associated infections from US National Healthcare Safety Network and consumer survey data from Hospital Consumer Assessment of Healthcare Providers and Systems. Our experiments show that central line-associated blood stream infections (CLABSIs) can be successfully predicted using AdaBoost method with an accuracy up to 89.7%. This will help in implementing effective clinical surveillance programs for infection control, as well as improving the accuracy detection of CLABSIs. Also, this reduces patients' hospital stay cost and maintains patients' safety. PMID:29085836

Prediction of cancer class with majority voting genetic programming classifier using gene expression data.

PubMed

Paul, Topon Kumar; Iba, Hitoshi

2009-01-01

In order to get a better understanding of different types of cancers and to find the possible biomarkers for diseases, recently, many researchers are analyzing the gene expression data using various machine learning techniques. However, due to a very small number of training samples compared to the huge number of genes and class imbalance, most of these methods suffer from overfitting. In this paper, we present a majority voting genetic programming classifier (MVGPC) for the classification of microarray data. Instead of a single rule or a single set of rules, we evolve multiple rules with genetic programming (GP) and then apply those rules to test samples to determine their labels with majority voting technique. By performing experiments on four different public cancer data sets, including multiclass data sets, we have found that the test accuracies of MVGPC are better than those of other methods, including AdaBoost with GP. Moreover, some of the more frequently occurring genes in the classification rules are known to be associated with the types of cancers being studied in this paper.

A High Efficiency Boost Converter with MPPT Scheme for Low Voltage Thermoelectric Energy Harvesting

NASA Astrophysics Data System (ADS)

Guan, Mingjie; Wang, Kunpeng; Zhu, Qingyuan; Liao, Wei-Hsin

2016-11-01

Using thermoelectric elements to harvest energy from heat has been of great interest during the last decade. This paper presents a direct current-direct current (DC-DC) boost converter with a maximum power point tracking (MPPT) scheme for low input voltage thermoelectric energy harvesting applications. Zero current switch technique is applied in the proposed MPPT scheme. Theoretical analysis on the converter circuits is explored to derive the equations for parameters needed in the design of the boost converter. Simulations and experiments are carried out to verify the theoretical analysis and equations. A prototype of the designed converter is built using discrete components and a low-power microcontroller. The results show that the designed converter can achieve a high efficiency at low input voltage. The experimental efficiency of the designed converter is compared with a commercial converter solution. It is shown that the designed converter has a higher efficiency than the commercial solution in the considered voltage range.

Testing for boosting at the Paralympic games: policies, results and future directions.

PubMed

Blauwet, Cheri A; Benjamin-Laing, Harry; Stomphorst, Jaap; Van de Vliet, Peter; Pit-Grosheide, Pia; Willick, Stuart E

2013-09-01

'Boosting' is defined as the intentional induction of autonomic dysreflexia (AD) by athletes with a spinal cord injury (SCI) at or above the level of T6 for the purpose of improving sports performance. Boosting has been shown to confer up to a 9.7% improvement in race time. Additionally, to compete in a hazardous dysreflexic state, whether intentional or unintentional, would present an extreme health risk to the athlete. For these reasons, the International Paralympic Committee strictly bans the practice of boosting, and has developed a protocol to test for its presence. Testing was performed at three major international Paralympic events. Education regarding the dangers of AD was provided to athletes and team staff. Testing was conducted on athletes from the relevant sport classes: Athletics (wheelchair racing classes T51/T52/T53) and Handcycling (H1). Key parameters included the athlete's demographics (gender, country of origin), classification and blood pressure measurements. An extremely elevated blood pressure was considered to be a proxy maker for AD, and a systolic blood pressure of ≥180 mm Hg was considered a positive test. A total of 78 tests for the presence of AD were performed during the three games combined. No athlete tested positive. The number of athletes tested, by classification, was: 6 in Athletics T51, 47 in Athletics T52, 9 in Athletics T53 and 16 in Handcycling H1. Of those tested, the average systolic and diastolic blood pressures were 135 mm Hg (range 98-178) and 82 mm Hg (range 44-112), respectively. All athletes were compliant with testing. No athletes were withdrawn from competition due to the presence of AD. Testing for the presence of AD in paralympic athletes with SCI prior to competition has been carried out for the first time at three major international paralympic competitions. There have been no positive tests thus far. Knowledge gained during these early testing experiences will be used to guide ongoing refinement of the testing

Vaccine strategies against Babesia bovis based on prime-boost immunizations in mice with modified vaccinia Ankara vector and recombinant proteins.

PubMed

Jaramillo Ortiz, José Manuel; Del Médico Zajac, María Paula; Zanetti, Flavia Adriana; Molinari, María Paula; Gravisaco, María José; Calamante, Gabriela; Wilkowsky, Silvina Elizabeth

2014-08-06

In this study, a recombinant modified vaccinia virus Ankara vector expressing a chimeric multi-antigen was obtained and evaluated as a candidate vaccine in homologous and heterologous prime-boost immunizations with a recombinant protein cocktail. The chimeric multi-antigen comprises immunodominant B and T cell regions of three Babesia bovis proteins. Humoral and cellular immune responses were evaluated in mice to compare the immunogenicity induced by different immunization schemes. The best vaccination scheme was achieved with a prime of protein cocktail and a boost with the recombinant virus. This scheme induced high level of specific IgG antibodies and secreted IFN and a high degree of activation of IFNγ(+) CD4(+) and CD8(+) specific T cells. This is the first report in which a novel vaccine candidate was constructed based on a rationally designed multi-antigen and evaluated in a prime-boost regime, optimizing the immune response necessary for protection against bovine babesiosis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Clinical outcomes of whole pelvis radiotherapy and stereotactic body radiotherapy boost for intermediate- and high-risk prostate cancer.

PubMed

Kim, Hun Jung; Phak, Jeong Hoon; Kim, Woo Chul

2017-10-01

We report our experience with Cyberknife to deliver hypofractionated stereotactic body radiotherapy (SBRT) boost combined with whole pelvis radiotherapy (WPRT) to patients with intermediate- to high-risk prostate cancer. From March 2008 to July 2014, 39 patients with newly diagnosed, intermediate- and high-risk (National Comprehensive Cancer Network definition) localized prostate cancer were treated with WPRT and SBRT boost. The whole pelvis dose was 45 Gy (25 fractions of 1.8 Gy) and the SBRT boost dose was 21 Gy (3 fractions of 7 Gy). No one received androgen deprivation therapy before biochemical relapse. The acute and late toxicities were recorded using the Radiation Therapy Oncology Group scale. Prostate-specific antigen (PSA) response was monitored. Thirty-nine patients with a median 53.6 months (range 14-74 months) follow-up were analyzed. The median pretreatment PSA was 15.97 ng/mL. The estimated 5-year biochemical failure (BCF)-free survival was 94.7%. Two BCFs were observed in only high-risk group. The median PSA nadir was 0.30 ng/mL at median 36 months and PSA bounce occurred in 15.4% (n = 6) of patients at median 12 months. No grade 3 acute toxicity was noted. A total of 23% of the patients had grade 2 acute genitourinary (GU) toxicities and 21% had grade 2 acute gastrointestinal (GI) toxicities. At 2 months, most complications had returned to baseline. GU and GI toxicities were observed. WPRT followed by SBRT boost using Cyberknife in intermediate- and high-risk prostate cancer is feasible with minimal toxicity and encouraging BCF-free survival. © 2016 John Wiley & Sons Australia, Ltd.

Blocking Junctional Adhesion Molecule C Enhances Dendritic Cell Migration and Boosts the Immune Responses against Leishmania major

PubMed Central

Ballet, Romain; Emre, Yalin; Jemelin, Stéphane; Charmoy, Mélanie; Tacchini-Cottier, Fabienne; Imhof, Beat A.

2014-01-01

The recruitment of dendritic cells to sites of infections and their migration to lymph nodes is fundamental for antigen processing and presentation to T cells. In the present study, we showed that antibody blockade of junctional adhesion molecule C (JAM-C) on endothelial cells removed JAM-C away from junctions and increased vascular permeability after L. major infection. This has multiple consequences on the output of the immune response. In resistant C57BL/6 and susceptible BALB/c mice, we found higher numbers of innate immune cells migrating from blood to the site of infection. The subsequent migration of dendritic cells (DCs) from the skin to the draining lymph node was also improved, thereby boosting the induction of the adaptive immune response. In C57BL/6 mice, JAM-C blockade after L. major injection led to an enhanced IFN-γ dominated T helper 1 (Th1) response with reduced skin lesions and parasite burden. Conversely, anti JAM-C treatment increased the IL-4-driven T helper 2 (Th2) response in BALB/c mice with disease exacerbation. Overall, our results show that JAM-C blockade can finely-tune the innate cell migration and accelerate the consequent immune response to L. major without changing the type of the T helper cell response. PMID:25474593

SIRT1 Gain of Function Does Not Mimic or Enhance the Adaptations to Intermittent Fasting.

PubMed

Boutant, Marie; Kulkarni, Sameer S; Joffraud, Magali; Raymond, Frédéric; Métairon, Sylviane; Descombes, Patrick; Cantó, Carles

2016-03-08

Caloric restriction (CR) has been shown to prevent the onset of insulin resistance and to delay age-related physiological decline in mammalian organisms. SIRT1, a NAD(+)-dependent deacetylase enzyme, has been suggested to mediate the adaptive responses to CR, leading to the speculation that SIRT1 activation could be therapeutically used as a CR-mimetic strategy. Here, we used a mouse model of moderate SIRT1 overexpression to test whether SIRT1 gain of function could mimic or boost the metabolic benefits induced by every-other-day feeding (EODF). Our results indicate that SIRT1 transgenesis does not affect the ability of EODF to decrease adiposity and improve insulin sensitivity. Transcriptomic analyses revealed that SIRT1 transgenesis and EODF promote very distinct adaptations in individual tissues, some of which can be even be metabolically opposite, as in brown adipose tissue. Therefore, whereas SIRT1 overexpression and CR both improve glucose metabolism and insulin sensitivity, the etiologies of these benefits are largely different. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Boosting the pentose phosphate pathway restores cardiac progenitor cell availability in diabetes

PubMed Central

Katare, Rajesh; Oikawa, Atsuhiko; Cesselli, Daniela; Beltrami, Antonio P.; Avolio, Elisa; Muthukrishnan, Deepti; Munasinghe, Pujika Emani; Angelini, Gianni; Emanueli, Costanza; Madeddu, Paolo

2013-01-01

Aims Diabetes impinges upon mechanisms of cardiovascular repair. However, the biochemical adaptation of cardiac stem cells to sustained hyperglycaemia remains largely unknown. Here, we investigate the molecular targets of high glucose-induced damage in cardiac progenitor cells (CPCs) from murine and human hearts and attempt safeguarding CPC viability and function through reactivation of the pentose phosphate pathway. Methods and results Type-1 diabetes was induced by streptozotocin. CPC abundance was determined by flow cytometry. Proliferating CPCs were identified in situ by immunostaining for the proliferation marker Ki67. Diabetic hearts showed marked reduction in CPC abundance and proliferation when compared with controls. Moreover, Sca-1pos CPCs isolated from hearts of diabetic mice displayed reduced activity of key enzymes of the pentose phosphate pathway, glucose-6-phosphate dehydrogenase (G6PD), and transketolase, increased levels of superoxide and advanced glucose end-products (AGE), and inhibition of the Akt/Pim-1/Bcl-2 signalling pathway. Similarly, culture of murine CPCs or human CD105pos progenitor cells in high glucose inhibits the pentose phosphate and pro-survival signalling pathways, leading to the activation of apoptosis. In vivo and in vitro supplementation with benfotiamine reactivates the pentose phosphate pathway and rescues CPC availability and function. This benefit is abrogated by either G6PD silencing by small interfering RNA (siRNA) or Akt inhibition by dominant-negative Akt. Conclusion We provide new evidence of the negative impact of diabetes and high glucose on mechanisms controlling CPC redox state and survival. Boosting the pentose phosphate pathway might represent a novel mechanistic target for protection of CPC integrity. PMID:22997160

DNA Prime/Adenovirus Boost Malaria Vaccine Encoding P. falciparum CSP and AMA1 Induces Sterile Protection Associated with Cell-Mediated Immunity

PubMed Central

Chuang, Ilin; Sedegah, Martha; Cicatelli, Susan; Spring, Michele; Polhemus, Mark; Tamminga, Cindy; Patterson, Noelle; Guerrero, Melanie; Bennett, Jason W.; McGrath, Shannon; Ganeshan, Harini; Belmonte, Maria; Farooq, Fouzia; Abot, Esteban; Banania, Jo Glenna; Huang, Jun; Newcomer, Rhonda; Rein, Lisa; Litilit, Dianne; Richie, Nancy O.; Wood, Chloe; Murphy, Jittawadee; Sauerwein, Robert; Hermsen, Cornelus C.; McCoy, Andrea J.; Kamau, Edwin; Cummings, James; Komisar, Jack; Sutamihardja, Awalludin; Shi, Meng; Epstein, Judith E.; Maiolatesi, Santina; Tosh, Donna; Limbach, Keith; Angov, Evelina; Bergmann-Leitner, Elke; Bruder, Joseph T.; Doolan, Denise L.; King, C. Richter; Carucci, Daniel; Dutta, Sheetij; Soisson, Lorraine; Diggs, Carter; Hollingdale, Michael R.; Ockenhouse, Christian F.; Richie, Thomas L.

2013-01-01

Background Gene-based vaccination using prime/boost regimens protects animals and humans against malaria, inducing cell-mediated responses that in animal models target liver stage malaria parasites. We tested a DNA prime/adenovirus boost malaria vaccine in a Phase 1 clinical trial with controlled human malaria infection. Methodology/Principal Findings The vaccine regimen was three monthly doses of two DNA plasmids (DNA) followed four months later by a single boost with two non-replicating human serotype 5 adenovirus vectors (Ad). The constructs encoded genes expressing P. falciparum circumsporozoite protein (CSP) and apical membrane antigen-1 (AMA1). The regimen was safe and well-tolerated, with mostly mild adverse events that occurred at the site of injection. Only one AE (diarrhea), possibly related to immunization, was severe (Grade 3), preventing daily activities. Four weeks after the Ad boost, 15 study subjects were challenged with P. falciparum sporozoites by mosquito bite, and four (27%) were sterilely protected. Antibody responses by ELISA rose after Ad boost but were low (CSP geometric mean titer 210, range 44–817; AMA1 geometric mean micrograms/milliliter 11.9, range 1.5–102) and were not associated with protection. Ex vivo IFN-γ ELISpot responses after Ad boost were modest (CSP geometric mean spot forming cells/million peripheral blood mononuclear cells 86, range 13–408; AMA1 348, range 88–1270) and were highest in three protected subjects. ELISpot responses to AMA1 were significantly associated with protection (p = 0.019). Flow cytometry identified predominant IFN-γ mono-secreting CD8+ T cell responses in three protected subjects. No subjects with high pre-existing anti-Ad5 neutralizing antibodies were protected but the association was not statistically significant. Significance The DNA/Ad regimen provided the highest sterile immunity achieved against malaria following immunization with a gene-based subunit vaccine (27%). Protection was

How Spreadsheets Boost Productivity.

ERIC Educational Resources Information Center

Ross, James

1988-01-01

Explains the use of computerized bookkeeping systems called spreadsheets to perform mathematical and accounting functions such as totaling expenditures, averaging test grades, and transferring funds. Advises about adapting spreadsheet programs and discusses several essential features, including linkage, macro functions, and sharing capabilities.…

Historical and Current U.S. Strategies for Boosting Distributed Generation (Chinese Translation)

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

Lowder, Travis; Schwabe, Paul; Zhou, Ella

2015-08-01

This is the Chinese translation of NREL/TP-6A20-64843. This report seeks to introduce a variety of top-down and bottom-up practices that, in concert with the macro-environment of cost-reduction globally and early adoption in Europe, helped boost the distributed generation photovoltaic market in the United States. These experiences may serve as a reference in China's quest to promote distributed renewable energy.

Impact of tumour bed boost integration on acute and late toxicity in patients with breast cancer: A systematic review.

PubMed

Hamilton, Daniel George; Bale, Rebecca; Jones, Claire; Fitzgerald, Emma; Khor, Richard; Knight, Kellie; Wasiak, Jason

2016-06-01

The purpose of this systematic review was to summarise the evidence from studies investigating the integration of tumour bed boosts into whole breast irradiation for patients with Stage 0-III breast cancer, with a focus on its impact on acute and late toxicities. A comprehensive systematic electronic search through the Ovid MEDLINE, EMBASE and PubMed databases from January 2000 to January 2015 was conducted. Studies were considered eligible if they investigated the efficacy of hypo- or normofractionated whole breast irradiation with the inclusion of a daily concurrent boost. The primary outcomes of interest were the degree of observed acute and late toxicity following radiotherapy treatment. Methodological quality assessment was performed on all included studies using either the Newcastle-Ottawa Scale or a previously published investigator-derived quality instrument. The search identified 35 articles, of which 17 satisfied our eligibility criteria. Thirteen and eleven studies reported on acute and late toxicities respectively. Grade 3 acute skin toxicity ranged from 1 to 7% whilst moderate to severe fibrosis and telangiectasia were both limited to 9%. Reported toxicity profiles were comparable to historical data at similar time-points. Studies investigating the delivery of concurrent boosts with whole breast radiotherapy courses report safe short to medium-term toxicity profiles and cosmesis rates. Whilst the quality of evidence and length of follow-up supporting these findings is low, sufficient evidence has been generated to consider concurrent boost techniques as an alternative to conventional sequential techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optical diagnosis of cervical cancer by higher order spectra and boosting

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Barman, Ritwik; Pratiher, Souvik; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-03-01

In this contribution, we report the application of higher order statistical moments using decision tree and ensemble based learning methodology for the development of diagnostic algorithms for optical diagnosis of cancer. The classification results were compared to those obtained with an independent feature extractors like linear discriminant analysis (LDA). The performance and efficacy of these methodology using higher order statistics as a classifier using boosting has higher specificity and sensitivity while being much faster as compared to other time-frequency domain based methods.

In vivo dosimetry and acute toxicity in breast cancer patients undergoing intraoperative radiotherapy as boost

PubMed Central

Lee, Jason Joon Bock; Choi, Jinhyun; Ahn, Sung Gwe; Jeong, Joon; Lee, Ik Jae; Park, Kwangwoo; Kim, Kangpyo; Kim, Jun Won

2017-01-01

Purpose To report the results of a correlation analysis of skin dose assessed by in vivo dosimetry and the incidence of acute toxicity. This is a phase 2 trial evaluating the feasibility of intraoperative radiotherapy (IORT) as a boost for breast cancer patients. Materials and Methods Eligible patients were treated with IORT of 20 Gy followed by whole breast irradiation (WBI) of 46 Gy. A total of 55 patients with a minimum follow-up of 1 month after WBI were evaluated. Optically stimulated luminescence dosimeter (OSLD) detected radiation dose delivered to the skin during IORT. Acute toxicity was recorded according to the Common Terminology Criteria for Adverse Events v4.0. Clinical parameters were correlated with seroma formation and maximum skin dose. Results Median follow-up after IORT was 25.9 weeks (range, 12.7 to 50.3 weeks). Prior to WBI, only one patient developed acute toxicity. Following WBI, 30 patients experienced grade 1 skin toxicity and three patients had grade 2 skin toxicity. Skin dose during IORT exceeded 5 Gy in two patients: with grade 2 complications around the surgical scar in one patient who received 8.42 Gy. Breast volume on preoperative images (p = 0.001), ratio of applicator diameter and breast volume (p = 0.002), and distance between skin and tumor (p = 0.003) showed significant correlations with maximum skin dose. conclusions IORT as a boost was well-tolerated among Korean women without severe acute complication. In vivo dosimetry with OSLD can help ensure safe delivery of IORT as a boost. PMID:28712278

In vivo dosimetry and acute toxicity in breast cancer patients undergoing intraoperative radiotherapy as boost.

PubMed

Lee, Jason Joon Bock; Choi, Jinhyun; Ahn, Sung Gwe; Jeong, Joon; Lee, Ik Jae; Park, Kwangwoo; Kim, Kangpyo; Kim, Jun Won

2017-06-01

To report the results of a correlation analysis of skin dose assessed by in vivo dosimetry and the incidence of acute toxicity. This is a phase 2 trial evaluating the feasibility of intraoperative radiotherapy (IORT) as a boost for breast cancer patients. Eligible patients were treated with IORT of 20 Gy followed by whole breast irradiation (WBI) of 46 Gy. A total of 55 patients with a minimum follow-up of 1 month after WBI were evaluated. Optically stimulated luminescence dosimeter (OSLD) detected radiation dose delivered to the skin during IORT. Acute toxicity was recorded according to the Common Terminology Criteria for Adverse Events v4.0. Clinical parameters were correlated with seroma formation and maximum skin dose. Median follow-up after IORT was 25.9 weeks (range, 12.7 to 50.3 weeks). Prior to WBI, only one patient developed acute toxicity. Following WBI, 30 patients experienced grade 1 skin toxicity and three patients had grade 2 skin toxicity. Skin dose during IORT exceeded 5 Gy in two patients: with grade 2 complications around the surgical scar in one patient who received 8.42 Gy. Breast volume on preoperative images (p = 0.001), ratio of applicator diameter and breast volume (p = 0.002), and distance between skin and tumor (p = 0.003) showed significant correlations with maximum skin dose. IORT as a boost was well-tolerated among Korean women without severe acute complication. In vivo dosimetry with OSLD can help ensure safe delivery of IORT as a boost.

Comparison of the immunogenicity and protection against bovine tuberculosis following immunization by BCG-priming and boosting with adenovirus or protein based vaccines.

PubMed

Dean, G; Whelan, A; Clifford, D; Salguero, F J; Xing, Z; Gilbert, S; McShane, H; Hewinson, R G; Vordermeier, M; Villarreal-Ramos, B

2014-03-05

There is a requirement for vaccines or vaccination strategies that confer better protection against TB than the current live attenuated Mycobacterium bovis Bacillus Calmette-Guerin (BCG) vaccine for use in cattle. Boosting with recombinant viral vectors expressing mycobacterial proteins, such as Ag85A, has shown a degree of promise as a strategy for improving on the protection afforded by BCG. Experiments in small animal models have indicated that broadening the immune response to include mycobacterial antigens other than Ag85A, such as Rv0288, induced by boosting with Ad5 constructs has a direct effect on the protection afforded against TB. Here, we compared the immunogenicity and protection against challenge with M. bovis afforded by boosting BCG-vaccinated cattle with a human type 5 (Ad5)-based vaccine expressing the mycobacterial antigens Ag85A (Ad5-85A); or Ag85A, Rv0251, Rv0287 and Rv0288 (Ad5-TBF); or with protein TBF emulsified in adjuvant (Adj-TBF). Boosting with TBF broaden the immune response. The kinetics of Ad5-TBF and Adj-TBF were shown to be different, with effector T cell responses from the latter developing more slowly but being more durable than those induced by Ad5-TBF. No increase in protection compared to BCG alone was afforded by Ad5-TBF or Adj-TBF by gross pathology or bacteriology. Using histopathology, as a novel parameter of protection, we show that boosting BCG vaccinated cattle with Ad5-85A induced significantly better protection than BCG alone. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Esophageal cancer dose escalation using a simultaneous integrated boost technique.

PubMed

Welsh, James; Palmer, Matthew B; Ajani, Jaffer A; Liao, Zhongxing; Swisher, Steven G; Hofstetter, Wayne L; Allen, Pamela K; Settle, Steven H; Gomez, Daniel; Likhacheva, Anna; Cox, James D; Komaki, Ritsuko

2012-01-01

We previously showed that 75% of radiation therapy (RT) failures in patients with unresectable esophageal cancer are in the gross tumor volume (GTV). We performed a planning study to evaluate if a simultaneous integrated boost (SIB) technique could selectively deliver a boost dose of radiation to the GTV in patients with esophageal cancer. Treatment plans were generated using four different approaches (two-dimensional conformal radiotherapy [2D-CRT] to 50.4 Gy, 2D-CRT to 64.8 Gy, intensity-modulated RT [IMRT] to 50.4 Gy, and SIB-IMRT to 64.8 Gy) and optimized for 10 patients with distal esophageal cancer. All plans were constructed to deliver the target dose in 28 fractions using heterogeneity corrections. Isodose distributions were evaluated for target coverage and normal tissue exposure. The 50.4 Gy IMRT plan was associated with significant reductions in mean cardiac, pulmonary, and hepatic doses relative to the 50.4 Gy 2D-CRT plan. The 64.8 Gy SIB-IMRT plan produced a 28% increase in GTV dose and comparable normal tissue doses as the 50.4 Gy IMRT plan; compared with the 50.4 Gy 2D-CRT plan, the 64.8 Gy SIB-IMRT produced significant dose reductions to all critical structures (heart, lung, liver, and spinal cord). The use of SIB-IMRT allowed us to selectively increase the dose to the GTV, the area at highest risk of failure, while simultaneously reducing the dose to the normal heart, lung, and liver. Clinical implications warrant systematic evaluation. Copyright © 2012 Elsevier Inc. All rights reserved.

Esophageal Cancer Dose Escalation using a Simultaneous Integrated Boost Technique

PubMed Central

Welsh, James; Palmer, Matthew B.; Ajani, Jaffer A.; Liao, Zhongxing; Swisher, Steven G.; Hofstetter, Wayne L.; Allen, Pamela K.; Settle, Steven H.; Gomez, Daniel; Likhacheva, Anna; Cox, James D.; Komaki, Ritsuko

2014-01-01

Purpose We previously showed that 75% of radiation therapy (RT) failures in patients with unresectable esophageal cancer are in the gross tumor volume (GTV). We performed a planning study to evaluate if a simultaneous integrated boost (SIB) technique could selectively deliver a boost dose of radiation to the GTV in patients with esophageal cancer. Methods and Materials Treatment plans were generated using four different approaches (two-dimensional conformal RT [2D-CRT] to 50.4 Gy or 64.8 Gy, intensity-modulated RT [IMRT] to 50.4 Gy, and SIB-IMRT to 64.8 Gy) and optimized for 10 patients with distal esophageal cancer. All plans were constructed to deliver the target dose in 28 fractions using heterogeneity corrections. Isodose distributions were evaluated for target coverage and normal tissue exposure. Results The 50.4-Gy IMRT plan was associated with significant reductions in mean cardiac, pulmonary, and hepatic doses relative to the 50.4-Gy 2D-CRT plan. The 64.8-Gy SIB-IMRT plan produced a 28% increase in GTV dose and the same normal tissue doses as the 50.4-Gy IMRT plan; compared with the 50.4-Gy 2D-CRT plan, the 64.8-Gy SIB-IMRT produced significant dose reductions to all critical structures (heart, lung, liver, and spinal cord). Conclusions The use of SIB-IMRT allowed us to selectively increase the dose to the GTV, the area at highest risk of failure, while simultaneously reducing the dose to the normal heart, lung, and liver. Clinical implications warrant systematic evaluation. PMID:21123005

Combined prime-boost vaccination against tick-borne encephalitis (TBE) using a recombinant vaccinia virus and a bacterial plasmid both expressing TBE virus non-structural NS1 protein

PubMed Central

Aleshin, SE; Timofeev, AV; Khoretonenko, MV; Zakharova, LG; Pashvykina, GV; Stephenson, JR; Shneider, AM; Altstein, AD

2005-01-01

Background Heterologous prime-boost immunization protocols using different gene expression systems have proven to be successful tools in protecting against various diseases in experimental animal models. The main reason for using this approach is to exploit the ability of expression cassettes to prime or boost the immune system in different ways during vaccination procedures. The purpose of the project was to study the ability of recombinant vaccinia virus (VV) and bacterial plasmid, both carrying the NS1 gene from tick-borne encephalitis (TBE) virus under the control of different promoters, to protect mice against lethal challenge using a heterologous prime-boost vaccination protocol. Results The heterologous prime-boost vaccination protocol, using a VV recombinant and bacterial plasmid, both containing the NS1 TBE virus protein gene under the control of different promoters, achieved a high level of protection in mice against lethal challenge with a highly pathogenic TBE virus strain. No signs of pronounced TBE infection were detected in the surviving animals. Conclusion Heterologous prime-boost vaccination protocols using recombinant VV and bacterial plasmids could be used for the development of flavivirus vaccines. PMID:16076390

Dark Matter "Collider" from Inelastic Boosted Dark Matter.

PubMed

Kim, Doojin; Park, Jong-Chul; Shin, Seodong

2017-10-20

We propose a novel dark matter (DM) detection strategy for models with a nonminimal dark sector. The main ingredients in the underlying DM scenario are a boosted DM particle and a heavier dark sector state. The relativistic DM impinged on target material scatters off inelastically to the heavier state, which subsequently decays into DM along with lighter states including visible (standard model) particles. The expected signal event, therefore, accompanies a visible signature by the secondary cascade process associated with a recoiling of the target particle, differing from the typical neutrino signal not involving the secondary signature. We then discuss various kinematic features followed by DM detection prospects at large-volume neutrino detectors with a model framework where a dark gauge boson is the mediator between the standard model particles and DM.

Effectiveness of the BOOST-A™ online transition planning program for adolescents on the autism spectrum: a quasi-randomized controlled trial.

PubMed

Hatfield, Megan; Falkmer, Marita; Falkmer, Torbjorn; Ciccarelli, Marina

2017-01-01

The majority of existing transition planning programs are focused on people with a disability in general and may not meet the specific need of adolescents on the autism spectrum. In addition, these interventions focus on specific skills (e.g. job readiness or self-determination) rather than the overall transition planning process and there are methodological limitations to many of the studies determining their effectiveness. The Better OutcOmes & Successful Transitions for Autism (BOOST-A™) is an online program that supports adolescents on the autism spectrum to prepare for leaving school. This study aimed to determine the effectiveness of the BOOST-A™ in enhancing self-determination. A quasi-randomized controlled trial was conducted with adolescents on the autism spectrum enrolled in years 8 to 11 in Australian schools (N = 94). Participants had to have basic computer skills and the ability to write at a year 5 reading level. Participants were allocated to a control (n = 45) or intervention (n = 49) group and participants were blinded to the trial hypothesis. The intervention group used the BOOST-A™ for 12 months, while the control group participated in regular practice. Outcomes included self-determination, career planning and exploration, quality of life, environmental support and domain specific self-determination. Data were collected from parents and adolescents. There were no significant differences in overall self-determination between groups. Results indicated significant differences in favor of the intervention group in three areas: opportunity for self-determination at home as reported by parents; career exploration as reported by parents and adolescents; and transition-specific self-determination as reported by parents. Results provide preliminary evidence that the BOOST-A™ can enhance some career-readiness outcomes. Lack of significant outcomes related to self-determination at school and career planning may be due to the lack of face

Helical Tomotherapy With Simultaneous Integrated Boost After Laparoscopic Staging in Patients With Cervical Cancer: Analysis of Feasibility and Early Toxicity

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

Marnitz, Simone, E-mail: simone.marnitz@charite.de; Koehler, Christhardt; Burova, Elena

Purpose: To demonstrate the feasibility and safety of the simultaneous integrated boost technique for dose escalation in combination with helical tomotherapy in patients with cervical cancer. Methods and Materials: Forty patients (International Federation of Gynecology and Obstetrics Stage IB1 pN1-IVA) underwent primary chemoradiation with helical tomotherapy. Before therapy, 29/40 patients underwent laparoscopic pelvic and para-aortic lymphadenectomy. In 21%, 31%, and 3% of the patients, pelvic, pelvic and para-aortic, and skip metastases in the para-aortic region could be confirmed. All patients underwent radiation with 1.8-50.4 Gy to the tumor region and the pelvic (para-aortic) lymph node region (planning target volume-A), andmore » a simultaneous boost with 2.12-59.36 Gy to the boost region (planning target volume-B). The boost region was defined using titan clips during laparoscopic staging. In all other patients, standardized borders for the planning target volume-B were defined. High-dose-rate brachytherapy was performed in 39/40 patients. The mean biologic effective dose to the macroscopic tumor ranged from 87.5 to 97.5 Gy. Chemotherapy consisted of weekly cisplatin 40 mg/m{sup 2}. Dose-volume histograms and acute gastrointestinal, genitourinary, and hematologic toxicity were evaluated. Results: The mean treatment time was 45 days. The mean doses to the small bowel, rectum, and bladder were 28.5 {+-} 6.1 Gy, 47.9 {+-} 3.8 Gy, and 48 {+-} 3 Gy, respectively. Hematologic toxicity Grade 3 occurred in 20% of patients, diarrhea Grade 2 in 5%, and diarrhea Grade 3 in 2.5%. There was no Grade 3 genitourinary toxicity. All patients underwent curettage 3 months after chemoradiation, which confirmed complete pathologic response in 38/40 patients. Conclusions: The concept of simultaneous integrated boost for dose escalation in patients with cervical cancer is feasible, with a low rate of acute gastrointestinal and genitourinary toxicity. Whether dose escalation can

A prime-boost vaccination strategy using attenuated Salmonella typhimurium and a replication-deficient recombinant adenovirus vector elicits protective immunity against human respiratory syncytial virus.

PubMed

Fu, Yuan-Hui; He, Jin-Sheng; Wang, Xiao-Bo; Zheng, Xian-Xian; Wu, Qiang; Xie, Can; Zhang, Mei; Wei, Wei; Tang, Qian; Song, Jing-Dong; Qu, Jian-Guo; Hong, Tao

2010-04-23

Human respiratory syncytial virus (RSV), for which no clinically approved vaccine is available yet, is globally a serious pediatric pathogen of the lower respiratory tract. Several approaches have been used to develop vaccines against RSV, but none of these have been approved for use in humans. An efficient vaccine-enhancing strategy for RSV is still urgently needed. We found previously that oral SL7207/pcDNA3.1/F and intranasal FGAd/F were able to induce an effective protective immune response against RSV. The heterologous prime-boost immunization regime has been reported recently to be an efficient vaccine-enhancing strategy. Therefore, we investigated the ability of an oral SL7207/pcDNA3.1/F prime and intranasal (i.n.) FGAd/F boost regimen to generate immune responses to RSV. The SL7207/pcDNA3.1/F prime-FGAd/F boost regimen generated stronger RSV-specific humoral and mucosal immune responses in BALB/c mice than the oral SL7207/pcDNA3.1/F regimen alone, and stronger specific cellular immune responses than the i.n. FGAd/F regimen alone. Histopathological analysis showed an increased efficacy against RSV challenge by the heterologous prime-boost regimen. These results suggest that such a heterologous prime-boost strategy can enhance the efficacy of either the SL7207 or the FGAd vector regimen in generating immune responses in BALB/c mice. 2010 Elsevier Inc. All rights reserved.

Clinical results of conformal versus intensity-modulated radiotherapy using a focal simultaneous boost for muscle-invasive bladder cancer in elderly or medically unfit patients.

PubMed

Lutkenhaus, Lotte J; van Os, Rob M; Bel, Arjan; Hulshof, Maarten C C M

2016-03-18

For elderly or medically unfit patients with muscle-invasive bladder cancer, cystectomy or chemotherapy are contraindicated. This leaves radical radiotherapy as the only treatment option. It was the aim of this study to retrospectively analyze the treatment outcome and associated toxicity of conformal versus intensity-modulated radiotherapy (IMRT) using a focal simultaneous tumor boost for muscle-invasive bladder cancer in patients not suitable for cystectomy. One hundred eighteen patients with T2-4 N0-1 M0 bladder cancer were analyzed retrospectively. Median age was 80 years. Treatment consisted of either a conformal box technique or IMRT and included a simultaneous boost to the tumor. To enable an accurate boost delivery, fiducial markers were placed around the tumor. Patients were treated with 40 Gy in 20 fractions to the elective treatment volumes, and a daily tumor boost up to 55-60 Gy. Clinical complete response was seen in 87 % of patients. Three-year overall survival was 44 %, with a locoregional control rate of 73 % at 3 years. Toxicity was low, with late urinary and intestinal toxicity rates grade ≥ 2 of 14 and 5 %, respectively. The use of IMRT reduced late intestinal toxicity, whereas fiducial markers reduced acute urinary toxicity. Radical radiotherapy using a focal boost is feasible and effective for elderly or unfit patients, with a 3-year locoregional control of 73 %. Toxicity rates were low, and were reduced by the use of IMRT and fiducial markers.

Safety and Survival With GVAX Pancreas Prime and Listeria Monocytogenes–Expressing Mesothelin (CRS-207) Boost Vaccines for Metastatic Pancreatic Cancer

PubMed Central

Le, Dung T.; Wang-Gillam, Andrea; Picozzi, Vincent; Greten, Tim F.; Crocenzi, Todd; Springett, Gregory; Morse, Michael; Zeh, Herbert; Cohen, Deirdre; Fine, Robert L.; Onners, Beth; Uram, Jennifer N.; Laheru, Daniel A.; Lutz, Eric R.; Solt, Sara; Murphy, Aimee Luck; Skoble, Justin; Lemmens, Ed; Grous, John; Dubensky, Thomas; Brockstedt, Dirk G.; Jaffee, Elizabeth M.

2015-01-01

Purpose GVAX pancreas, granulocyte-macrophage colony-stimulating factor–secreting allogeneic pancreatic tumor cells, induces T-cell immunity to cancer antigens, including mesothelin. GVAX is administered with low-dose cyclophosphamide (Cy) to inhibit regulatory T cells. CRS-207, live-attenuated Listeria monocytogenes–expressing mesothelin, induces innate and adaptive immunity. On the basis of preclinical synergy, we tested prime/boost vaccination with GVAX and CRS-207 in pancreatic adenocarcinoma. Patients and Methods Previously treated patients with metastatic pancreatic adenocarcinoma were randomly assigned at a ratio of 2:1 to two doses of Cy/GVAX followed by four doses of CRS-207 (arm A) or six doses of Cy/GVAX (arm B) every 3 weeks. Stable patients were offered additional courses. The primary end point was overall survival (OS) between arms. Secondary end points were safety and clinical response. Results A total of 90 patients were treated (arm A, n = 61; arm B, n = 29); 97% had received prior chemotherapy; 51% had received ≥ two regimens for metastatic disease. Mean number of doses (± standard deviation) administered in arms A and B were 5.5 ± 4.5 and 3.7 ± 2.2, respectively. The most frequent grade 3 to 4 related toxicities were transient fevers, lymphopenia, elevated liver enzymes, and fatigue. OS was 6.1 months in arm A versus 3.9 months in arm B (hazard ratio [HR], 0.59; P = .02). In a prespecified per-protocol analysis of patients who received at least three doses (two doses of Cy/GVAX plus one of CRS-207 or three of Cy/GVAX), OS was 9.7 versus 4.6 months (arm A v B; HR, 0.53; P = .02). Enhanced mesothelin-specific CD8 T-cell responses were associated with longer OS, regardless of treatment arm. Conclusion Heterologous prime/boost with Cy/GVAX and CRS-207 extended survival for patients with pancreatic cancer, with minimal toxicity. PMID:25584002

Safety and survival with GVAX pancreas prime and Listeria Monocytogenes-expressing mesothelin (CRS-207) boost vaccines for metastatic pancreatic cancer.

PubMed

Le, Dung T; Wang-Gillam, Andrea; Picozzi, Vincent; Greten, Tim F; Crocenzi, Todd; Springett, Gregory; Morse, Michael; Zeh, Herbert; Cohen, Deirdre; Fine, Robert L; Onners, Beth; Uram, Jennifer N; Laheru, Daniel A; Lutz, Eric R; Solt, Sara; Murphy, Aimee Luck; Skoble, Justin; Lemmens, Ed; Grous, John; Dubensky, Thomas; Brockstedt, Dirk G; Jaffee, Elizabeth M

2015-04-20

GVAX pancreas, granulocyte-macrophage colony-stimulating factor-secreting allogeneic pancreatic tumor cells, induces T-cell immunity to cancer antigens, including mesothelin. GVAX is administered with low-dose cyclophosphamide (Cy) to inhibit regulatory T cells. CRS-207, live-attenuated Listeria monocytogenes-expressing mesothelin, induces innate and adaptive immunity. On the basis of preclinical synergy, we tested prime/boost vaccination with GVAX and CRS-207 in pancreatic adenocarcinoma. Previously treated patients with metastatic pancreatic adenocarcinoma were randomly assigned at a ratio of 2:1 to two doses of Cy/GVAX followed by four doses of CRS-207 (arm A) or six doses of Cy/GVAX (arm B) every 3 weeks. Stable patients were offered additional courses. The primary end point was overall survival (OS) between arms. Secondary end points were safety and clinical response. A total of 90 patients were treated (arm A, n = 61; arm B, n = 29); 97% had received prior chemotherapy; 51% had received ≥ two regimens for metastatic disease. Mean number of doses (± standard deviation) administered in arms A and B were 5.5 ± 4.5 and 3.7 ± 2.2, respectively. The most frequent grade 3 to 4 related toxicities were transient fevers, lymphopenia, elevated liver enzymes, and fatigue. OS was 6.1 months in arm A versus 3.9 months in arm B (hazard ratio [HR], 0.59; P = .02). In a prespecified per-protocol analysis of patients who received at least three doses (two doses of Cy/GVAX plus one of CRS-207 or three of Cy/GVAX), OS was 9.7 versus 4.6 months (arm A v B; HR, 0.53; P = .02). Enhanced mesothelin-specific CD8 T-cell responses were associated with longer OS, regardless of treatment arm. Heterologous prime/boost with Cy/GVAX and CRS-207 extended survival for patients with pancreatic cancer, with minimal toxicity. © 2015 by American Society of Clinical Oncology.

Query-Adaptive Reciprocal Hash Tables for Nearest Neighbor Search.

PubMed

Liu, Xianglong; Deng, Cheng; Lang, Bo; Tao, Dacheng; Li, Xuelong

2016-02-01

Recent years have witnessed the success of binary hashing techniques in approximate nearest neighbor search. In practice, multiple hash tables are usually built using hashing to cover more desired results in the hit buckets of each table. However, rare work studies the unified approach to constructing multiple informative hash tables using any type of hashing algorithms. Meanwhile, for multiple table search, it also lacks of a generic query-adaptive and fine-grained ranking scheme that can alleviate the binary quantization loss suffered in the standard hashing techniques. To solve the above problems, in this paper, we first regard the table construction as a selection problem over a set of candidate hash functions. With the graph representation of the function set, we propose an efficient solution that sequentially applies normalized dominant set to finding the most informative and independent hash functions for each table. To further reduce the redundancy between tables, we explore the reciprocal hash tables in a boosting manner, where the hash function graph is updated with high weights emphasized on the misclassified neighbor pairs of previous hash tables. To refine the ranking of the retrieved buckets within a certain Hamming radius from the query, we propose a query-adaptive bitwise weighting scheme to enable fine-grained bucket ranking in each hash table, exploiting the discriminative power of its hash functions and their complement for nearest neighbor search. Moreover, we integrate such scheme into the multiple table search using a fast, yet reciprocal table lookup algorithm within the adaptive weighted Hamming radius. In this paper, both the construction method and the query-adaptive search method are general and compatible with different types of hashing algorithms using different feature spaces and/or parameter settings. Our extensive experiments on several large-scale benchmarks demonstrate that the proposed techniques can significantly outperform both

UCLA at TREC 2014 Clinical Decision Support Track: Exploring Language Models, Query Expansion, and Boosting

DTIC Science & Technology

2014-11-01

for 6 months. Median performance for this topic was relatively low, despite being an easy diagnosis of hypothyroidism for a medical expert. However... hypothyroidism was ranked 3rd in the retrieval results. Without boosting, the highest-ranked article on hypothyroidism was ranked 16th. In contrast, this

Do Acting out Verbs with Dolls and Comparison Learning between Scenes Boost Toddlers' Verb Comprehension?

ERIC Educational Resources Information Center

Schwarz, Amy Louise; Van Kleeck, Anne; Maguire, Mandy J.; Abdi, Herve

2017-01-01

To better understand how toddlers integrate multiple learning strategies to acquire verbs, we compared sensorimotor recruitment and comparison learning because both strategies are thought to boost children's access to scene-level information. For sensorimotor recruitment, we tested having toddlers use dolls as agents and compared this strategy…

Research on the Boost of Development on Young Children's Fine Motor by Folk Games

ERIC Educational Resources Information Center

Wei, Xia

2016-01-01

As Chinese traditional folk culture, folk games have unique educational value which can boost the development of young children's fine motor. Based on previous investigation of fine motor skill of children in Nanchong, Sichuan Province, the researcher chose a middle class in public city kindergarten A with lower survey score as the study object.…

A new method to distinguish hadronically decaying boosted Z bosons from W bosons using the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansil, H. S.; Barak, L.; Barberio, E. 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B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopczak, A.; Sopko, B.; Sopko, V.; Sorin, V.; Sosa, D.; Sosebee, M.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Spearman, W. R.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Spreitzer, T.; St. Denis, R. D.; Stabile, A.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, F. E.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thun, R. P.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Velz, T.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Wasicki, C.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Wharton, A. M.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamada, M.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yurkewicz, A.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zwalinski, L.

2016-05-01

The distribution of particles inside hadronic jets produced in the decay of boosted W and Z bosons can be used to discriminate such jets from the continuum background. Given that a jet has been identified as likely resulting from the hadronic decay of a boosted W or Z boson, this paper presents a technique for further differentiating Z bosons from W bosons. The variables used are jet mass, jet charge, and a b-tagging discriminant. A likelihood tagger is constructed from these variables and tested in the simulation of W'→ WZ for bosons in the transverse momentum range 200 GeV boosted W bosons is studied in data using a tbar{t}-enriched sample of events in 20.3 fb{}^{-1} of data at √{s}=8 TeV. The inputs are well modelled within uncertainties, which builds confidence in the expected tagger performance.

Boosted Higgs bosons from chromomagnetic b 's: b b ¯h at high luminosity

NASA Astrophysics Data System (ADS)

Bramante, Joseph; Delgado, Antonio; Lehman, Landon; Martin, Adam

2016-03-01

This paper examines detection prospects and constraints on the chromomagnetic dipole operator for the bottom quark. This operator has a flavor, chirality and Lorentz structure that is distinct from other dimension-6 operators considered in Higgs coupling studies. Its nonstandard Lorentz structure results in boosted b b ¯h events, providing a rate-independent signal of new physics. To date, we find this operator is unconstrained by p p →h +jets and p p →b ¯b searches: for order-1 couplings the permitted cutoff Λ for this operator can be as low as Λ ˜1 TeV . We show how to improve this bound with collider cuts that allow a b -tagged Higgs-plus-dijet search in the Higgs-to-diphoton decay channel to exclude cutoffs as high as ˜6 TeV at 2 σ with 3 ab-1 of luminosity at the 14 TeV LHC. Cuts on the pT of the Higgs are key to this search, because the chromomagnetic dipole yields a nonstandard fraction of boosted Higgses.

Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier.

PubMed

Zhang, Baochang; Yang, Yun; Chen, Chen; Yang, Linlin; Han, Jungong; Shao, Ling

2017-10-01

Human action recognition is an important yet challenging task. This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three orthogonal Cartesian planes, i.e., the frontal, side, and top planes, and thus compactly characterize the salient information of a specific action, on which texture features are calculated to represent the action. Besides this fast feature descriptor, a new multi-class boosting classifier (MBC) is also proposed to efficiently exploit different kinds of features in a unified framework for action classification. Compared with the existing boosting frameworks, we add a new multi-class constraint into the objective function, which helps to maintain a better margin distribution by maximizing the mean of margin, whereas still minimizing the variance of margin. Experiments on the MSRAction3D, MSRGesture3D, MSRActivity3D, and UTD-MHAD data sets demonstrate that the proposed system combining 3DHoTs and MBC is superior to the state of the art.

A resistive magnetohydrodynamics solver using modern C++ and the Boost library

NASA Astrophysics Data System (ADS)

Einkemmer, Lukas

2016-09-01

In this paper we describe the implementation of our C++ resistive magnetohydrodynamics solver. The framework developed facilitates the separation of the code implementing the specific numerical method and the physical model from the handling of boundary conditions and the management of the computational domain. In particular, this will allow us to use finite difference stencils which are only defined in the interior of the domain (the boundary conditions are handled automatically). We will discuss this and other design considerations and their impact on performance in some detail. In addition, we provide a documentation of the code developed and demonstrate that a performance comparable to Fortran can be achieved, while still maintaining a maximum of code readability and extensibility. Catalogue identifier: AFAH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFAH_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 592774 No. of bytes in distributed program, including test data, etc.: 43771395 Distribution format: tar.gz Programming language: C++03. Computer: PC, HPC systems. Operating system: POSIX compatible (extensively tested on various Linux systems). In fact only the timing class requires POSIX routines; all other parts of the program can be run on any system where a C++ compiler, Boost, CVODE, and an implementation of BLAS are available. RAM: Hundredths of Kilobytes to Gigabytes (depending on the problem size) Classification: 19.10, 4.3. External routines: Boost, CVODE, either a BLAS library or Intel MKL Nature of problem: An approximate solution to the equations of resistive magnetohydrodynamics for a given initial value and given boundary conditions is computed. Solution method: The discretization is performed using a finite difference approximation in

Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

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

Schmidt, Matthew, E-mail: matthew.schmidt@varian.com; Grzetic, Shelby; Lo, Joseph Y.

Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinicalmore » database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human

SU-F-T-328: Real-Time in Vivo Dosimetry of Prostate SBRT Boost Treatments Using MOSkin Detectors

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

Legge, K; O’Connor, D J; Cutajar, D

Purpose: To provide in vivo measurements of dose to the anterior rectal wall during prostate SBRT boost treatments using MOSFET detectors. Methods: Dual MOSkin detectors were attached to a Rectafix rectal sparing device and inserted into patients during SBRT boost treatments. Patients received two boost fractions, each of 9.5–10 Gy and delivered using 2 VMAT arcs. Measurements were acquired for 12 patients. MOSFET voltages were read out at 1 Hz during delivery and converted to dose. MV images were acquired at known frequency during treatment so that the position of the gantry at each point in time was known. Themore » cumulative dose at the MOSFET location was extracted from the treatment planning system at in 5.2° increments (FF beams) or at 5 points during each delivered arc (FFF beams). The MOSFET dose and planning system dose throughout the entirety of each arc were then compared using root mean square error normalised to the final planned dose for each arc. Results: The average difference between MOSFET measured and planning system doses determined over the entire course of treatment was 9.7% with a standard deviation of 3.6%. MOSFETs measured below the planned dose in 66% of arcs measured. Uncertainty in the position of the MOSFET detector and verification point are major sources of discrepancy, as the detector is placed in a high dose gradient region during treatment. Conclusion: MOSkin detectors were able to provide real time in vivo measurements of anterior rectal wall dose during prostate SBRT boost treatments. This method could be used to verify Rectafix positioning and treatment delivery. Further developments could enable this method to be used during high dose treatments to monitor dose to the rectal wall to ensure it remains at safe levels. Funding has been provided by the University of Newcastle. Kimberley Legge is the recipient of an Australian Postgraduate Award.« less

Uncover compressed supersymmetry via boosted bosons from the heavier stop/sbottom

NASA Astrophysics Data System (ADS)

Kang, Zhaofeng; Li, Jinmian; Zhang, Mengchao

2017-06-01

A light stop around the weak scale is a hopeful messenger of natural supersymmetry (SUSY), but it has not shown up at the current stage of LHC. Such a situation raises the question of the fate of natural SUSY. Actually, a relatively light stop can easily be hidden in a compressed spectra such as mild mass degeneracy between stop and neutralino plus top quark. Searching for such a stop at the LHC is a challenge. On the other hand, in terms of the argument of natural SUSY, other members in the stop sector, including a heavier stop \\tilde{t}_2 and lighter sbottom \\tilde{b}_1 (both assumed to be left-handed-like), are also supposed to be relatively light and therefore searching for them would provide an alternative method to probe natural SUSY with a compressed spectra. In this paper we consider quasi-natural SUSY which tolerates relatively heavy colored partners near the TeV scale, with a moderately large mass gap between the heavier members and the lightest stop. Then W / Z / h as companions of \\tilde{t}_2 and \\tilde{b}_1 decaying into \\tilde{t}_1 generically are well boosted, and they, along with other visible particles from \\tilde{t}_1 decay, are a good probe to study compressed SUSY. We find that the resulting search strategy with boosted bosons can have better sensitivity than those utilizing multi-leptons.

Boosted structured additive regression for Escherichia coli fed-batch fermentation modeling.

PubMed

Melcher, Michael; Scharl, Theresa; Luchner, Markus; Striedner, Gerald; Leisch, Friedrich

2017-02-01

The quality of biopharmaceuticals and patients' safety are of highest priority and there are tremendous efforts to replace empirical production process designs by knowledge-based approaches. Main challenge in this context is that real-time access to process variables related to product quality and quantity is severely limited. To date comprehensive on- and offline monitoring platforms are used to generate process data sets that allow for development of mechanistic and/or data driven models for real-time prediction of these important quantities. Ultimate goal is to implement model based feed-back control loops that facilitate online control of product quality. In this contribution, we explore structured additive regression (STAR) models in combination with boosting as a variable selection tool for modeling the cell dry mass, product concentration, and optical density on the basis of online available process variables and two-dimensional fluorescence spectroscopic data. STAR models are powerful extensions of linear models allowing for inclusion of smooth effects or interactions between predictors. Boosting constructs the final model in a stepwise manner and provides a variable importance measure via predictor selection frequencies. Our results show that the cell dry mass can be modeled with a relative error of about ±3%, the optical density with ±6%, the soluble protein with ±16%, and the insoluble product with an accuracy of ±12%. Biotechnol. Bioeng. 2017;114: 321-334. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search.

PubMed

Liu, Xianglong; Huang, Lei; Deng, Cheng; Lang, Bo; Tao, Dacheng

2016-10-01

Hash-based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the literature has shown that adaptively incorporating complementary information from diverse sources or views can significantly boost the search performance. To address the problems, this paper proposes a novel and generic approach to building multiple hash tables with multiple views and generating fine-grained ranking results at bitwise and tablewise levels. For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor search. From the tablewise aspect, multiple hash tables are built for different data views as a joint index, over which a query-specific rank fusion is proposed to rerank all results from the bitwise ranking by diffusing in a graph. Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over the state-of-the-art methods.

Skin dose differences between intensity-modulated radiation therapy and volumetric-modulated arc therapy and between boost and integrated treatment regimens for treating head and neck and other cancer sites in patients

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

Penoncello, Gregory P.; Ding, George X., E-mail: george.ding@vanderbilt.edu

The purpose of this study was (1) to evaluate dose to skin between volumetric-modulated arc therapy (VMAT) and intensity-modulated radiation therapy (IMRT) treatment techniques for target sites in the head and neck, pelvis, and brain and (2) to determine if the treatment dose and fractionation regimen affect the skin dose between traditional sequential boost and integrated boost regimens for patients with head and neck cancer. A total of 19 patients and 48 plans were evaluated. The Eclipse (v11) treatment planning system was used to plan therapy in 9 patients with head and neck cancer, 5 patients with prostate cancer, andmore » 5 patients with brain cancer with VMAT and static-field IMRT. The mean skin dose and the maximum dose to a contiguous volume of 2 cm{sup 3} for head and neck plans and brain plans and a contiguous volume of 5 cm{sup 3} for pelvis plans were compared for each treatment technique. Of the 9 patients with head and neck cancer, 3 underwent an integrated boost regimen. One integrated boost plan was replanned with IMRT and VMAT using a traditional boost regimen. For target sites located in the head and neck, VMAT reduced the mean dose and contiguous hot spot most noticeably in the shoulder region by 5.6% and 5.4%, respectively. When using an integrated boost regimen, the contiguous hot spot skin dose in the shoulder was larger on average than a traditional boost pattern by 26.5% and the mean skin dose was larger by 1.7%. VMAT techniques largely decrease the contiguous hot spot in the skin in the pelvis by an average of 36% compared with IMRT. For the same target coverage, VMAT can reduce the skin dose in all the regions of the body, but more noticeably in the shoulders in patients with head and neck and pelvis cancer. We also found that using integrated boost regimens in patients with head and neck cancer leads to higher shoulder skin doses compared with traditional boost regimens.« less

A heterologous prime-boosting strategy with replicating Vaccinia virus vectors and plant-produced HIV-1 Gag/dgp41 virus-like particles

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

Meador, Lydia R.

Showing modest efficacy, the RV144 HIV-1 vaccine clinical trial utilized a non-replicating canarypox viral vector and a soluble gp120 protein boost. Here we built upon the RV144 strategy by developing a novel combination of a replicating, but highly-attenuated Vaccinia virus vector, NYVAC-KC, and plant-produced HIV-1 virus-like particles (VLPs). Both components contained the full-length Gag and a membrane anchored truncated gp41 presenting the membrane proximal external region with its conserved broadly neutralizing epitopes in the pre-fusion conformation. We tested different prime/boost combinations of these components in mice and showed that the group primed with NYVAC-KC and boosted with both the viralmore » vectors and plant-produced VLPs have the most robust Gag-specific CD8 T cell responses, at 12.7% of CD8 T cells expressing IFN-γ in response to stimulation with five Gag epitopes. The same immunization group elicited the best systemic and mucosal antibody responses to Gag and dgp41 with a bias towards IgG1. - Highlights: • We devised a prime/boost anti HIV-1 vaccination strategy modeled after RV144. • We used plant-derived virus-like particles (VLPs) consisting of Gag and dgp41. • We used attenuated, replicating vaccinia virus vectors expressing the same antigens. • The immunogens elicited strong cellular and humoral immune responses.« less

Antibody response and maternal immunity upon boosting PRRSV-immune sows with experimental farm-specific and commercial PRRSV vaccines.

PubMed

Geldhof, Marc F; Van Breedam, Wander; De Jong, Ellen; Lopez Rodriguez, Alfonso; Karniychuk, Uladzimir U; Vanhee, Merijn; Van Doorsselaere, Jan; Maes, Dominiek; Nauwynck, Hans J

2013-12-27

The porcine reproductive and respiratory syndrome virus (PRRSV) causes reproductive failure in sows and respiratory disease in pigs of all ages. Despite the frequent use of vaccines to maintain PRRSV immunity in sows, little is known on how the currently used vaccines affect the immunity against currently circulating and genetically divergent PRRSV variants in PRRSV-immune sows, i.e. sows that have a pre-existing PRRSV-specific immunity due to previous infection with or vaccination against the virus. Therefore, this study aimed to assess the capacity of commercially available attenuated/inactivated PRRSV vaccines and autogenous inactivated PRRSV vaccines - prepared according to a previously optimized in-house protocol - to boost the antibody immunity against currently circulating PRRSV variants in PRRSV-immune sows. PRRSV isolates were obtained from 3 different swine herds experiencing PRRSV-related problems, despite regular vaccination of gilts and sows against the virus. In a first part of the study, the PRRSV-specific antibody response upon booster vaccination with commercial PRRSV vaccines and inactivated farm-specific PRRSV vaccines was evaluated in PRRSV-immune, non-pregnant replacement sows from the 3 herds. A boost in virus-neutralizing antibodies against the farm-specific isolate was observed in all sow groups vaccinated with the corresponding farm-specific inactivated vaccines. Use of the commercial attenuated EU type vaccine boosted neutralizing antibodies against the farm-specific isolate in sows derived from 2 farms, while use of the commercial attenuated NA type vaccine did not boost farm-specific virus-neutralizing antibodies in any of the sow groups. Interestingly, the commercial inactivated EU type vaccine boosted farm-specific virus-neutralizing antibodies in sows from 1 farm. In the second part of the study, a field trial was performed at one of the farms to evaluate the booster effect of an inactivated farm-specific vaccine and a commercial

Defined three-dimensional microenvironments boost induction of pluripotency

NASA Astrophysics Data System (ADS)

Caiazzo, Massimiliano; Okawa, Yuya; Ranga, Adrian; Piersigilli, Alessandra; Tabata, Yoji; Lutolf, Matthias P.

2016-03-01

Since the discovery of induced pluripotent stem cells (iPSCs), numerous approaches have been explored to improve the original protocol, which is based on a two-dimensional (2D) cell-culture system. Surprisingly, nothing is known about the effect of a more biologically faithful 3D environment on somatic-cell reprogramming. Here, we report a systematic analysis of how reprogramming of somatic cells occurs within engineered 3D extracellular matrices. By modulating microenvironmental stiffness, degradability and biochemical composition, we have identified a previously unknown role for biophysical effectors in the promotion of iPSC generation. We find that the physical cell confinement imposed by the 3D microenvironment boosts reprogramming through an accelerated mesenchymal-to-epithelial transition and increased epigenetic remodelling. We conclude that 3D microenvironmental signals act synergistically with reprogramming transcription factors to increase somatic plasticity.

Automatic identification of epileptic seizures from EEG signals using linear programming boosting.

PubMed

Hassan, Ahnaf Rashik; Subasi, Abdulhamit

2016-11-01

Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and

Modelling, Simulation and Construction of a DC/DC Boost Power Converter: A School Experimental System

ERIC Educational Resources Information Center

Silva-Ortigoza, R.; Silva-Ortigoza, G.; Hernandez-Guzman, V. M.; Saldana-Gonzalez, G.; Marcelino-Aranda, M.; Marciano-Melchor, M.

2012-01-01

We introduce a dc/dc boost power converter as a didactic prototype intended to support courses on electric circuit analysis experimentally. The corresponding mathematical model is obtained, the converter is designed and an experimental setup is described, constructed and tested. Simplicity of construction as well as low cost of components renders…

Modeling the Swift BAT Trigger Algorithm with Machine Learning

NASA Technical Reports Server (NTRS)

Graff, Philip B.; Lien, Amy Y.; Baker, John G.; Sakamoto, Takanori

2015-01-01

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. (2014) is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of approximately greater than 97% (approximately less than 3% error), which is a significant improvement on a cut in GRB flux which has an accuracy of 89:6% (10:4% error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of eta(sub 0) approximately 0.48(+0.41/-0.23) Gpc(exp -3) yr(exp -1) with power-law indices of eta(sub 1) approximately 1.7(+0.6/-0.5) and eta(sub 2) approximately -5.9(+5.7/-0.1) for GRBs above and below a break point of z(sub 1) approximately 6.8(+2.8/-3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting. The code used in this is analysis is publicly available online.

A primitive study of voxel feature generation by multiple stacked denoising autoencoders for detecting cerebral aneurysms on MRA

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu; Ohtomo, Kuni

2016-03-01

The purpose of this study is to evaluate the feasibility of a novel feature generation, which is based on multiple deep neural networks (DNNs) with boosting, for computer-assisted detection (CADe). It is hard and time-consuming to optimize the hyperparameters for DNNs such as stacked denoising autoencoder (SdA). The proposed method allows using SdA based features without the burden of the hyperparameter setting. The proposed method was evaluated by an application for detecting cerebral aneurysms on magnetic resonance angiogram (MRA). A baseline CADe process included four components; scaling, candidate area limitation, candidate detection, and candidate classification. Proposed feature generation method was applied to extract the optimal features for candidate classification. Proposed method only required setting range of the hyperparameters for SdA. The optimal feature set was selected from a large quantity of SdA based features by multiple SdAs, each of which was trained using different hyperparameter set. The feature selection was operated through ada-boost ensemble learning method. Training of the baseline CADe process and proposed feature generation were operated with 200 MRA cases, and the evaluation was performed with 100 MRA cases. Proposed method successfully provided SdA based features just setting the range of some hyperparameters for SdA. The CADe process by using both previous voxel features and SdA based features had the best performance with 0.838 of an area under ROC curve and 0.312 of ANODE score. The results showed that proposed method was effective in the application for detecting cerebral aneurysms on MRA.

Boosted lopinavir- versus boosted atazanavir-containing regimens and immunologic, virologic, and clinical outcomes: a prospective study of HIV-infected individuals in high-income countries.

PubMed

Cain, Lauren E; Phillips, Andrew; Olson, Ashley; Sabin, Caroline; Jose, Sophie; Justice, Amy; Tate, Janet; Logan, Roger; Robins, James M; Sterne, Jonathan A C; van Sighem, Ard; Reiss, Peter; Young, James; Fehr, Jan; Touloumi, Giota; Paparizos, Vasilis; Esteve, Anna; Casabona, Jordi; Monge, Susana; Moreno, Santiago; Seng, Rémonie; Meyer, Laurence; Pérez-Hoyos, Santiago; Muga, Roberto; Dabis, François; Vandenhende, Marie-Anne; Abgrall, Sophie; Costagliola, Dominique; Hernán, Miguel A

2015-04-15

Current clinical guidelines consider regimens consisting of either ritonavir-boosted atazanavir or ritonavir-boosted lopinavir and a nucleoside reverse transcriptase inhibitor (NRTI) backbone among their recommended and alternative first-line antiretroviral regimens. However, these guidelines are based on limited evidence from randomized clinical trials and clinical experience. We compared these regimens with respect to clinical, immunologic, and virologic outcomes using data from prospective studies of human immunodeficiency virus (HIV)-infected individuals in Europe and the United States in the HIV-CAUSAL Collaboration, 2004-2013. Antiretroviral therapy-naive and AIDS-free individuals were followed from the time they started a lopinavir or an atazanavir regimen. We estimated the 'intention-to-treat' effect for atazanavir vs lopinavir regimens on each of the outcomes. A total of 6668 individuals started a lopinavir regimen (213 deaths, 457 AIDS-defining illnesses or deaths), and 4301 individuals started an atazanavir regimen (83 deaths, 157 AIDS-defining illnesses or deaths). The adjusted intention-to-treat hazard ratios for atazanavir vs lopinavir regimens were 0.70 (95% confidence interval [CI], .53-.91) for death, 0.67 (95% CI, .55-.82) for AIDS-defining illness or death, and 0.91 (95% CI, .84-.99) for virologic failure at 12 months. The mean 12-month increase in CD4 count was 8.15 (95% CI, -.13 to 16.43) cells/µL higher in the atazanavir group. Estimates differed by NRTI backbone. Our estimates are consistent with a lower mortality, a lower incidence of AIDS-defining illness, a greater 12-month increase in CD4 cell count, and a smaller risk of virologic failure at 12 months for atazanavir compared with lopinavir regimens. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Robust immunity to an auxotrophic Mycobacterium bovis BCG-VLP prime-boost HIV vaccine candidate in a nonhuman primate model.

PubMed

Chege, Gerald K; Burgers, Wendy A; Stutz, Helen; Meyers, Ann E; Chapman, Rosamund; Kiravu, Agano; Bunjun, Rubina; Shephard, Enid G; Jacobs, William R; Rybicki, Edward P; Williamson, Anna-Lise

2013-05-01

We previously reported that a recombinant pantothenate auxotroph of Mycobacterium bovis BCG expressing human immunodeficiency virus type 1 (HIV-1) subtype C Gag (rBCGpan-Gag) efficiently primes the mouse immune system for a boost with a recombinant modified vaccinia virus Ankara (rMVA) vaccine. In this study, we further evaluated the immunogenicity of rBCGpan-Gag in a nonhuman primate model. Two groups of chacma baboons were primed or mock primed twice with either rBCGpan-Gag or a control BCG. Both groups were boosted with HIV-1 Pr55(gag) virus-like particles (Gag VLPs). The magnitude and breadth of HIV-specific cellular responses were measured using a gamma interferon (IFN-γ) enzyme-linked immunosorbent spot (ELISPOT) assay, and the cytokine profiles and memory phenotypes of T cells were evaluated by polychromatic flow cytometry. Gag-specific responses were detected in all animals after the second inoculation with rBCGpan-Gag. Boosting with Gag VLPs significantly increased the magnitude and breadth of the responses in the baboons that were primed with rBCGpan-Gag. These responses targeted an average of 12 Gag peptides per animal, compared to an average of 3 peptides per animal for the mock-primed controls. Robust responses of Gag-specific polyfunctional T cells capable of simultaneously producing IFN-γ, tumor necrosis alpha (TNF-α), and interleukin-2 (IL-2) were detected in the rBCGpan-Gag-primed animals. Gag-specific memory T cells were skewed toward a central memory phenotype in both CD4(+) and CD8(+) T cell populations. These data show that the rBCGpan-Gag prime and Gag VLP boost vaccine regimen is highly immunogenic, inducing a broad and polyfunctional central memory T cell response. This report further indicates the feasibility of developing a BCG-based HIV vaccine that is safe for childhood HIV immunization.

ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches.

PubMed

Lei, Tailong; Sun, Huiyong; Kang, Yu; Zhu, Feng; Liu, Hui; Zhou, Wenfang; Wang, Zhe; Li, Dan; Li, Youyong; Hou, Tingjun

2017-11-06

Xenobiotic chemicals and their metabolites are mainly excreted out of our bodies by the urinary tract through the urine. Chemical-induced urinary tract toxicity is one of the main reasons that cause failure during drug development, and it is a common adverse event for medications, natural supplements, and environmental chemicals. Despite its importance, there are only a few in silico models for assessing urinary tract toxicity for a large number of compounds with diverse chemical structures. Here, we developed a series of qualitative and quantitative structure-activity relationship (QSAR) models for predicting urinary tract toxicity. In our study, the recursive feature elimination method incorporated with random forests (RFE-RF) was used for dimension reduction, and then eight machine learning approaches were used for QSAR modeling, i.e., relevance vector machine (RVM), support vector machine (SVM), regularized random forest (RRF), C5.0 trees, eXtreme gradient boosting (XGBoost), AdaBoost.M1, SVM boosting (SVMBoost), and RVM boosting (RVMBoost). For building classification models, the synthetic minority oversampling technique was used to handle the imbalance data set problem. Among all the machine learning approaches, SVMBoost based on the RBF kernel achieves both the best quantitative (q ext 2 = 0.845) and qualitative predictions for the test set (MCC of 0.787, AUC of 0.893, sensitivity of 89.6%, specificity of 94.1%, and global accuracy of 90.8%). The application domains were then analyzed, and all of the tested chemicals fall within the application domain coverage. We also examined the structure features of the chemicals with large prediction errors. In brief, both the regression and classification models developed by the SVMBoost approach have reliable prediction capability for assessing chemical-induced urinary tract toxicity.

The Adaptive Optics Summer School Laboratory Activities

NASA Astrophysics Data System (ADS)

Ammons, S. M.; Severson, S.; Armstrong, J. D.; Crossfield, I.; Do, T.; Fitzgerald, M.; Harrington, D.; Hickenbotham, A.; Hunter, J.; Johnson, J.; Johnson, L.; Li, K.; Lu, J.; Maness, H.; Morzinski, K.; Norton, A.; Putnam, N.; Roorda, A.; Rossi, E.; Yelda, S.

2010-12-01

Adaptive Optics (AO) is a new and rapidly expanding field of instrumentation, yet astronomers, vision scientists, and general AO practitioners are largely unfamiliar with the root technologies crucial to AO systems. The AO Summer School (AOSS), sponsored by the Center for Adaptive Optics, is a week-long course for training graduate students and postdoctoral researchers in the underlying theory, design, and use of AO systems. AOSS participants include astronomers who expect to utilize AO data, vision scientists who will use AO instruments to conduct research, opticians and engineers who design AO systems, and users of high-bandwidth laser communication systems. In this article we describe new AOSS laboratory sessions implemented in 2006-2009 for nearly 250 students. The activity goals include boosting familiarity with AO technologies, reinforcing knowledge of optical alignment techniques and the design of optical systems, and encouraging inquiry into critical scientific questions in vision science using AO systems as a research tool. The activities are divided into three stations: Vision Science, Fourier Optics, and the AO Demonstrator. We briefly overview these activities, which are described fully in other articles in these conference proceedings (Putnam et al., Do et al., and Harrington et al., respectively). We devote attention to the unique challenges encountered in the design of these activities, including the marriage of inquiry-like investigation techniques with complex content and the need to tune depth to a graduate- and PhD-level audience. According to before-after surveys conducted in 2008, the vast majority of participants found that all activities were valuable to their careers, although direct experience with integrated, functional AO systems was particularly beneficial.