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https://www.readbyqxmd.com/read/28453724/a-generative-angular-model-of-protein-structure-evolution
#1
Michael Golden, Eduardo Garcia-Portugues, Michael Sørensen, Kanti V Mardia, Thomas Hamelryck, Jotun Hein
Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modeled using a novel angular diffusion process on the two-dimensional torus...
April 27, 2017: Molecular Biology and Evolution
https://www.readbyqxmd.com/read/28445404/support-vector-data-description-model-to-map-specific-land-cover-with-optimal-parameters-determined-from-a-window-based-validation-set
#2
Jinshui Zhang, Zhoumiqi Yuan, Guanyuan Shuai, Yaozhong Pan, Xiufang Zhu
This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space...
April 26, 2017: Sensors
https://www.readbyqxmd.com/read/28437797/central-and-peripheral-vision-for-scene-recognition-a-neurocomputational-modeling-exploration
#3
Panqu Wang, Garrison W Cottrell
What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy. However, central vision is more efficient for scene recognition than peripheral, based on the amount of visual area needed for accurate recognition. In this study, we model and explain the results of Larson and Loschky (2009) using a neurocomputational modeling approach. We show that the advantage of peripheral vision in scene recognition, as well as the efficiency advantage for central vision, can be replicated using state-of-the-art deep neural network models...
April 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28437634/convolutional-neural-network-regression-for-short-axis-left-ventricle-segmentation-in-cardiac-cine-mr-sequences
#4
Li Kuo Tan, Yih Miin Liew, Einly Lim, Robert A McLaughlin
Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints...
April 12, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28437615/experimental-demonstration-of-feature-extraction-and-dimensionality-reduction-using-memristor-networks
#5
Shinhyun Choi, Jong Hoon Shin, Jihang Lee, Patrick Sheridan, Wei D Lu
Memristors have been considered as a leading candidate for a number of critical applications ranging from non-volatile memory to non-Von Neumann computing systems. Feature extraction, which aims to transform input data from a high dimensional space to a space with fewer dimensions, is an important technique widely used in machine learning and pattern recognition applications. Here, we experimentally demonstrate that memristor arrays can be used to perform principal component analysis (PCA), one of the most commonly-used feature extraction techniques, through online, unsupervised learning...
April 24, 2017: Nano Letters
https://www.readbyqxmd.com/read/28436896/online-hashing
#6
Long-Kai Huang, Qiang Yang, Wei-Shi Zheng
Although hash function learning algorithms have achieved great success in recent years, most existing hash models are off-line, which are not suitable for processing sequential or online data. To address this problem, this paper proposes an online hash model to accommodate data coming in stream for online learning. Specifically, a new loss function is proposed to measure the similarity loss between a pair of data samples in hamming space. Then, a structured hash model is derived and optimized in a passive-aggressive way...
April 24, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28436875/zero-shot-learning-with-transferred-samples
#7
Yuchen Guo, Guiguang Ding, Jungong Han, Yue Gao
By transferring knowledge from the abundant labeled samples of known source classes, zero-shot learning (ZSL) makes it possible to train recognition models for novel target classes that have no labeled samples. Conventional ZSL approaches usually adopt a two-step recognition strategy, in which the test sample is projected into an intermediary space in the first step, and then the recognition is carried out by considering the similarity between the sample and target classes in the intermediary space. Due to this redundant intermediate transformation, information loss is unavoidable, thus degrading the performance of overall system...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28436847/learning-trans-dimensional-random-fields-with-applications-to-language-modeling
#8
Bin Wang, Zhijian Ou, Zhiqiang Tan
To describe trans-dimensional observations in sample spaces of different dimensions, we propose a probabilistic model, called the trans-dimensional random field (TRF) by explicitly mixing a collection of random fields. In the framework of stochastic approximation (SA), we develop an effective training algorithm, called augmented SA, which jointly estimates the model parameters and normalizing constants while using trans-dimensional mixture sampling to generate observations of different dimensions. Furthermore, we introduce several statistical and computational techniques to improve the convergence of the training algorithm and reduce computational cost, which together enable us to successfully train TRF models on large datasets...
April 24, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28435239/pulmonary-rehabilitation-for-copd-improves-exercise-time-rather-than-exercise-tolerance-effects-and-mechanisms
#9
Keisuke Miki, Ryoji Maekura, Seigo Kitada, Mari Miki, Kenji Yoshimura, Hiroshi Yamamoto, Toshiko Kawabe, Hiroyuki Kagawa, Yohei Oshitani, Akitoshi Satomi, Kohei Nishida, Nobuhiko Sawa, Kimiko Inoue
BACKGROUND: COPD patients undergoing pulmonary rehabilitation (PR) show various responses. The purpose of this study was to investigate the possible mechanisms and predictors of the response to PR in COPD patients. METHODS: Thirty-six stable COPD patients underwent PR including a 4-week high-intensity exercise training program, and they were evaluated by cardiopulmonary exercise testing. All patients (mean age 69 years, severe and very severe COPD 94%) were classified into four groups by whether the exercise time (Tex) or the peak oxygen uptake [Formula: see text] increased after PR: two factors increased (both the Tex and the peak [Formula: see text] increased); two factors decreased; time only increased (the Tex increased, but the peak [Formula: see text] economized); and [Formula: see text] only increased (the Tex decreased, but the peak [Formula: see text] increased)...
2017: International Journal of Chronic Obstructive Pulmonary Disease
https://www.readbyqxmd.com/read/28432316/how-visual-experience-impacts-the-internal-and-external-spatial-mapping-of-sensorimotor-functions
#10
Virginie Crollen, Geneviève Albouy, Franco Lepore, Olivier Collignon
Tactile perception and motor production share the use of internally- and externally-defined coordinates. In order to examine how visual experience affects the internal/external coding of space for touch and movement, early blind (EB) and sighted controls (SC) took part in two experiments. In experiment 1, participants were required to perform a Temporal Order Judgment task (TOJ), either with their hands in parallel or crossed over the body midline. Confirming previous demonstration, crossing the hands led to a significant decrement in performance in SC but did not affect EB...
April 21, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28432141/the-spacing-effect-for-structural-synaptic-plasticity-provides-specificity-and-precision-in-plastic-changes
#11
Martin A San, L Rela, B D Gelb, M R Pagani
In contrast to trials of training without intervals (massed training), training trials spaced over time (spaced training) induce a more persistent memory identified as long-term memory (LTM). This phenomenon known as "the spacing effect for memory" is poorly understood. LTM is supported by structural synaptic plasticity; however, how synapses integrate spaced stimuli remains elusive. Here, we analyzed events of structural synaptic plasticity at the single synapse level after distinct patterns of stimulation in motoneurons of Drosophila We found that the spacing effect is a phenomenon detected at synaptic level, which determine the specificity and the precision in structural synaptic plasticity...
April 21, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28430266/machine-learning-approach-to-oam-beam-demultiplexing-via-convolutional-neural-networks
#12
Timothy Doster, Abbie T Watnik
Orbital angular momentum (OAM) beams allow for increased channel capacity in free-space optical communication. Conventionally, these OAM beams are multiplexed together at a transmitter and then propagated through the atmosphere to a receiver where, due to their orthogonality properties, they are demultiplexed. We propose a technique to demultiplex these OAM-carrying beams by capturing an image of the unique multiplexing intensity pattern and training a convolutional neural network (CNN) as a classifier. This CNN-based demultiplexing method allows for simplicity of operation as alignment is unnecessary, orthogonality constraints are loosened, and costly optical hardware is not required...
April 20, 2017: Applied Optics
https://www.readbyqxmd.com/read/28429572/finding-chemical-structures-corresponding-to-a-set-of-coordinates-in-chemical-descriptor-space
#13
Tomoyuki Miyao, Kimito Funatsu
When chemical structures are searched based on descriptor values, or descriptors are interpreted based on values, it is important that corresponding chemical structures actually exist. In order to consider the existence of chemical structures located in a specific region in the chemical space, we propose to search them inside training data domains (TDDs), which are dense areas of a training dataset in the chemical space. We investigated TDDs' features using diverse and local datasets, assuming that GDB11 is the chemical universe...
April 21, 2017: Molecular Informatics
https://www.readbyqxmd.com/read/28422697/manifold-regularized-correlation-object-tracking
#14
Hongwei Hu, Bo Ma, Jianbing Shen, Ling Shao
In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions...
April 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28421821/modeling-and-dynamic-simulation-of-astronaut-s-upper-limb-motions-considering-counter-torques-generated-by-the-space-suit
#15
Jingwen Li, Qing Ye, Li Ding, Qianfang Liao
Extravehicular activity (EVA) is an inevitable task for astronauts to maintain proper functions of both the spacecraft and the space station. Both experimental research in a microgravity simulator (e.g. neutral buoyancy tank, zero-g aircraft or a drop tower/tube) and mathematical modeling were used to study EVA to provide guidance for the training on Earth and task design in space. Modeling has become more and more promising because of its efficiency. Based on the task analysis, almost 90% of EVA activity is accomplished through upper limb motions...
April 19, 2017: Computer Methods in Biomechanics and Biomedical Engineering
https://www.readbyqxmd.com/read/28420954/multiple-kernel-based-region-importance-learning-for-neural-classification-of-gait-states-from-eeg-signals
#16
Yuhang Zhang, Saurabh Prasad, Atilla Kilicarslan, Jose L Contreras-Vidal
With the development of Brain Machine Interface (BMI) systems, people with motor disabilities are able to control external devices to help them restore movement abilities. Longitudinal validation of these systems is critical not only to assess long-term performance reliability but also to investigate adaptations in electrocortical patterns due to learning to use the BMI system. In this paper, we decode the patterns of user's intended gait states (e.g., stop, walk, turn left, and turn right) from scalp electroencephalography (EEG) signals and simultaneously learn the relative importance of different brain areas by using the multiple kernel learning (MKL) algorithm...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28420248/creating-an-optimal-3d-printed-model-for-temporal-bone-dissection-training
#17
Kuniyuki Takahashi, Yuka Morita, Shinsuke Ohshima, Shuji Izumi, Yamato Kubota, Yutaka Yamamoto, Sugata Takahashi, Arata Horii
OBJECTIVE: Making a 3-dimensional (3D) temporal bone model is simple using a plaster powder bed and an inkjet printer. However, it is difficult to reproduce air-containing spaces and precise middle ear structures. The objective of this study was to overcome these problems and create a temporal bone model that would be useful both as a training tool and for preoperative simulation. METHODS: Drainage holes were made to remove excess materials from air-containing spaces, ossicle ligaments were manually changed to bony structures, and small and/or soft tissue structures were colored differently while designing the 3D models...
April 1, 2017: Annals of Otology, Rhinology, and Laryngology
https://www.readbyqxmd.com/read/28420142/cross-spectral-local-descriptors-via-quadruplet-network
#18
Cristhian A Aguilera, Angel D Sappa, Cristhian Aguilera, Ricardo Toledo
This paper presents a novel CNN-based architecture, referred to as Q-Net, to learn local feature descriptors that are useful for matching image patches from two different spectral bands. Given correctly matched and non-matching cross-spectral image pairs, a quadruplet network is trained to map input image patches to a common Euclidean space, regardless of the input spectral band. Our approach is inspired by the recent success of triplet networks in the visible spectrum, but adapted for cross-spectral scenarios, where, for each matching pair, there are always two possible non-matching patches: one for each spectrum...
April 15, 2017: Sensors
https://www.readbyqxmd.com/read/28419807/otolaryngology-residency-program-research-resources-and-scholarly-productivity
#19
Jennifer A Villwock, Chelsea S Hamill, Brian D Nicholas, Jesse T Ryan
Objective To delineate research resources available to otolaryngology residents and their impact on scholarly productivity. Study Design Survey of current otolaryngology program directors. Setting Otolaryngology residency programs. Subjects and Methods An anonymous web-based survey was sent to 98 allopathic otolaryngology training program directors. Fisher exact tests and nonparametric correlations were used to determine statistically significant differences among various strata of programs. Results Thirty-nine percent (n = 38) of queried programs responded...
April 1, 2017: Otolaryngology—Head and Neck Surgery
https://www.readbyqxmd.com/read/28419731/a-qualitative-study-of-doctors-and-nurses-barriers-to-communicating-with-seriously-ill-patients-about-their-dependent-children
#20
Annemarie Dencker, Bo Andreassen Rix, Per Bøge, Tine Tjørnhøj-Thomsen
OBJECTIVE: Research indicates that health personnel (HP) caring for seriously ill patients with dependent children aged 0-18 often avoid discussing with them the challenges of being a family with a parent in treatment. Children of seriously ill patients (CSIP) risk serious trauma and emotional difficulty later in life and depend on adult support to minimize these consequences. Patients suffer anxiety about supporting their children during their illness. Due to their potentially pivotal role in supporting patients in enabling parent-child communication, we examined HP's structural and emotional barriers to communicating with patients about their children...
April 18, 2017: Psycho-oncology
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