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Chiyoko Uchida, Mai Uchida
Objective: To examine the prevalence of and the factors contributing to leaves of absence and school discontinuation in Japanese college students over a 27-year period. Trends in these academic events over time were assessed, and students at elevated risk and psychosocial difficulties in need of supportive intervention were identified. Methods: Surveys were collected from the majority of Japanese national universities between 1985 and 2012, yielding data on a total of 9...
August 10, 2017: Primary Care Companion to CNS Disorders
Shuang-Bo Sun, Zhi-Heng Zhang, Xin-Ling Dong, Heng-Ru Zhang, Tong-Jun Li, Lin Zhang, Fan Min
This paper proposes a new measure for recommendation through integrating Triangle and Jaccard similarities. The Triangle similarity considers both the length and the angle of rating vectors between them, while the Jaccard similarity considers non co-rating users. We compare the new similarity measure with eight state-of-the-art ones on four popular datasets under the leave-one-out scenario. Results show that the new measure outperforms all the counterparts in terms of the mean absolute error and the root mean square error...
2017: PloS One
Peter Pipelers, Lieven Clement, Matthijs Vynck, Jan Hellemans, Jo Vandesompele, Olivier Thas
Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is considered as the gold standard for accurate, sensitive, and fast measurement of gene expression. Prior to downstream statistical analysis, RT-qPCR fluorescence amplification curves are summarized into one single value, the quantification cycle (Cq). When RT-qPCR does not reach the limit of detection, the Cq is labeled as "undetermined". Current state of the art qPCR data analysis pipelines acknowledge the importance of normalization for removing non-biological sample to sample variation in the Cq values...
2017: PloS One
LiMin Wang, FangYuan Cao, ShuangCheng Wang, MingHui Sun, LiYan Dong
Numerous data mining models have been proposed to construct computer-aided medical expert systems. Bayesian network classifiers (BNCs) are more distinct and understandable than other models. To graphically describe the dependency relationships among clinical variables for thyroid disease diagnosis and ensure the rationality of the diagnosis results, the proposed k-dependence causal forest (KCF) model generates a series of submodels in the framework of maximum spanning tree (MST) and demonstrates stronger dependence representation...
2017: PloS One
John T Brooks, Jennifer F Kawwass, Dawn K Smith, Dmitry M Kissin, Margaret Lampe, Lisa B Haddad, Sheree L Boulet, Denise J Jamieson
Existing U.S. guidelines recommend that men with human immunodeficiency virus (HIV) infection should achieve virologic suppression* with effective antiretroviral therapy (ART) before attempting conception (1). Clinical studies have demonstrated that effective ART profoundly reduces the risk for HIV transmission (2-4). This information might be useful for counseling couples planning a pregnancy in which the man has HIV infection and the woman does not (i.e., a mixed HIV-status couple, often referred to as a serodiscordant couple)...
August 18, 2017: MMWR. Morbidity and Mortality Weekly Report
Samuel L Bartlett, Jeffrey S Johnson
The unique role that stereochemistry plays in molecular recognition events continues to provide a driving force for synthesizing organic compounds in enantioenriched form. The tendency of enantioenriched organic compounds to revert to an entropically favored racemic state in the presence of viable racemization pathways (e.g., the enolization of stereogenic carbonyl derivatives) can sometimes interfere with this objective; however, beginning with Noyori's foundational disclosure of a dynamic kinetic transfer hydrogenation, the ability to channel racemic, configurationally labile starting materials through stereoconvergent reaction pathways has been recognized as a powerful strategy in asymmetric synthesis...
August 17, 2017: Accounts of Chemical Research
Kun Song, Feiping Nie, Junwei Han, Xuelong Li
The amount of matrix data has increased rapidly nowadays. How to classify matrix data efficiently is an important issue. In this paper, by discovering the shortages of 2-D linear discriminant analysis and 2-D logistic regression, a novel 2-D framework named rank-k 2-D multinomial logistic regression (2DMLR-RK) is proposed. The 2DMLR-RK is designed for a multiclass matrix classification problem. In the proposed framework, each category is modeled by a left projection matrix and a right projection matrix with rank k...
August 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
Zifa Han, Chi Sing Leung, Hing Cheung So, Anthony George Constantinides
A commonly used measurement model for locating a mobile source is time-difference-of-arrival (TDOA). As each TDOA measurement defines a hyperbola, it is not straightforward to compute the mobile source position due to the nonlinear relationship in the measurements. This brief exploits the Lagrange programming neural network (LPNN), which provides a general framework to solve nonlinear constrained optimization problems, for the TDOA-based localization. The local stability of the proposed LPNN solution is also analyzed...
August 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu
Random forests (RFs) are recognized as one type of ensemble learning method and are effective for the most classification and regression tasks. Despite their impressive empirical performance, the theory of RFs has yet been fully proved. Several theoretically guaranteed RF variants have been presented, but their poor practical performance has been criticized. In this paper, a novel RF framework is proposed, named Bernoulli RFs (BRFs), with the aim of solving the RF dilemma between theoretical consistency and empirical performance...
August 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
Kangkan Wang, Guofeng Zhang, Shihong Xia
We present a novel templateless approach for nonrigid reconstruction and motion tracking using a single RGB-D camera. Without any template prior, our system achieves accurate reconstruction and tracking for considerably deformable objects. To robustly register the input sequence of partial depth scans with dynamic motion, we propose an efficient local-toglobal hierarchical optimization framework inspired by the idea of traditional structure-from-motion. Our proposed framework mainly consists of two stages, local nonrigid bundle adjustment and global optimization...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Zezhou Cheng, Qingxiong Yang, Bin Sheng
This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a careful selection of colorful reference images. The recent learning-based colorization techniques automatically colorize a grayscale image using a single neural network. Since different scenes usually have distinct color styles, it is difficult to accurately capture the color characteristics using a single neural network...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Jiao Wu, Feilong Cao, Juncheng Yin
A novel multi-morphological representation model for solving the nonlocal similarity-based image reconstruction from compressed measurements is introduced in this paper. Under the probabilistic framework, the proposed approach provides the nonlocal similarity clustering for image patches by using the Gaussian mixture models, and endows a multimorphological representation for image patches in each cluster by using the Gaussians that represent the different features to model the morphological components. Using the simple alternating iteration, the developed piecewise morphological diversity estimation (PMDE) algorithm can effectively estimate the MAP of morphological components, thus resulting in the nonlinear estimation for image patches...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Xiatian Zhu, Botong Wu, Dongcheng Huang, Wei-Shi Zheng
Existing person re-identification (re-id) methods typically assume that (1) any probe person is guaranteed to appear in the gallery target population during deployment (i.e. closed-world), and (2) the probe set contains only a limited number of people (i.e. small search scale). Both assumptions are artificial and breached in real-world applications, since the probe population in target people search can be extremely vast in practice due to the ambiguity of probe search space boundary. Therefore, it is unrealistic that any probe person is assumed as one target people, and a large-scale search in person images is inherently demanded...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Siyu Huang, Xi Li, Zhongfei Zhang, Fei Wu, Shenghua Gao, Rongrong Ji, Junwei Han
Crowd counting is a challenging task, mainly due to the severe occlusions among dense crowds. This work aims to take a broader view to address crowd counting from the perspective of semantic modelling. In essence, crowd counting is a task of pedestrian semantic analysis involving three key factors: pedestrians, heads, and their context structure. The information of different body parts is an important cue to help us judge whether there exists a person at a certain position. Existing methods usually perform crowd counting from the perspective of directly modelling the visual properties of either the whole body or the heads only, without explicitly capturing the composite body-part semantic structure information that is crucial for crowd counting...
August 14, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Hanhui Li, Hefeng Wu, Huifang Zhang, Shujin Lin, Xiaonan Luo, Ruomei Wang
Recently, correlation filter (CF) based tracking methods have attracted considerable attention because of their high-speed performance. However, distortion, which refers to the phenomenon that the correlation outputs of CF based trackers are distorted, remains a major obstacle for these methods. In this paper, we propose a Distortion-Aware Correlation Filter (DACF) framework, which can detect distortions and recover from tracking failures. Our framework employs a simple yet effective feature termed normed correlation response to detect distortions...
August 14, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Chun-Hao Huang, Benjamin Allain, Edmond Boyer, Jean-Sebastien Franco, Federico Tombari, Nassir Navab, Slobodan Ilic
3D Human shape tracking consists in fitting a template model to temporal sequences of visual observations. It usually comprises an association step, that finds correspondences between the model and the input data, and a deformation step, that fits the model to the observations given correspondences. Most current approaches follow the Iterative-Closest-Point (ICP) paradigm, where the association step is carried out by searching for the nearest neighbors. It fails when large deformations occur and errors in the association tend to propagate over time...
August 15, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Manus J Donahue, Eric Achten, Petrice M Cogswell, Frank-Erik De Leeuw, Colin P Derdeyn, Rick M Dijkhuizen, Audrey P Fan, Rashid Ghaznawi, Jeremy J Heit, M Arfan Ikram, Peter Jezzard, Lori C Jordan, Eric Jouvent, Linda Knutsson, Richard Leigh, David S Liebeskind, Weili Lin, Thomas W Okell, Adnan I Qureshi, Charlotte J Stagg, Matthias Jp van Osch, Peter Cm van Zijl, Jennifer M Watchmaker, Max Wintermark, Ona Wu, Greg Zaharchuk, Jinyuan Zhou, Jeroen Hendrikse
Cerebrovascular disease (CVD) remains a leading cause of death and the leading cause of adult disability in most developed countries. This work summarizes state-of-the-art, and possible future, diagnostic and evaluation approaches in multiple stages of CVD, including (i) visualization of sub-clinical disease processes, (ii) acute stroke theranostics, and (iii) characterization of post-stroke recovery mechanisms. Underlying pathophysiology as it relates to large vessel steno-occlusive disease and the impact of this macrovascular disease on tissue-level viability, hemodynamics (cerebral blood flow, cerebral blood volume, and mean transit time), and metabolism (cerebral metabolic rate of oxygen consumption and pH) are also discussed in the context of emerging neuroimaging protocols with sensitivity to these factors...
January 1, 2017: Journal of Cerebral Blood Flow and Metabolism
Marcos A Mouriño-García, Roberto Pérez-Rodríguez, Luis E Anido-Rifón
OBJECTIVES: The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space...
August 16, 2017: Methods of Information in Medicine
Haoying Zhai, Taotao Gao, Ting Qi, Yajie Zhang, Guangfeng Zeng, Dan Xiao
Iron-cobalt phosphomolybdate (FeCoPM12) nanoparticles,a high-efficient catalytic material for oxygen evolution reaction (OER), were fabricated via a coprecipitation route. Compared with iron-cobalt hydroxide and state-of-art RuO2 electrocatalysts, the as-prepared FeCoPM12 sample exhibited robust OER catalytic activity with a low overpotential of 258 mV at a current density of 10 mA cm-2 and a small Tafel slope of 33 mV dec-1. Moreover, the as-synthesized sample presented preferable stability, and after 10 h at 1...
August 16, 2017: Chemistry, An Asian Journal
Changyong Lan, Ruoting Dong, Ziyao Zhou, Lei Shu, Dapan Li, SenPo Yip, Johnny C Ho
Recently, due to the possibility of thinning down to the atomic thickness to achieve exotic properties, layered materials have attracted extensive research attention. In particular, PbI2 , a kind of layered material, and its perovskite derivatives, CH3 NH3 PbI3 (i.e., MAPbI3 ), have demonstrated impressive photoresponsivities for efficient photodetection. Herein, the synthesis of large-scale, high-density, and freestanding PbI2 nanosheets is demonstrated by manipulating the microenvironment during physical vapor deposition...
August 17, 2017: Advanced Materials
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