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Stefan Albert, Katharina Schmack, Philipp Sterzer, Gaby Schneider
Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging...
November 20, 2017: PLoS Computational Biology
S François, D Filloux, M Frayssinet, P Roumagnac, D P Martin, M Ogliastro, R Froissart
Metagenomics studies have revolutionized the field of biology by revealing the presence of many previously unisolated and uncultured micro-organisms. However, one of the main problems encountered in metagenomic studies is the high percentage of sequences that cannot be assigned taxonomically using commonly used similarity-based approaches (e.g. BLAST or HMM). These unassigned sequences are allegorically called « dark matter » in the metagenomic literature and are often referred to as being derived from new or unknown organisms...
November 14, 2017: Virus Research
Z Y Shi, C Q Yang, M D Hao, X Y Wang, R D Ward, A B Zhang
Species identification through DNA barcoding or metabarcoding has become a key approach for biodiversity evaluation and ecological studies. However, the rapid accumulation of barcoding data has created some difficulties: for instance, global enquiries to a large reference library can take a very long time. We here devise a two-step searching strategy to speed identification procedures of such queries. This firstly uses a Hidden Markov Model (HMM) algorithm to narrow the searching scope to genus level, and then determines the corresponding species using minimum genetic distance...
November 20, 2017: Molecular Ecology Resources
Mai Desouky, Ahmed M Mahmoud, Mohamed A Swillam
Noble Metals such as Gold and Silver demonstrated for mid IR metamaterials have suffered many obstacles such as: high losses and lack of tunability. The application of doped semiconductors has allowed overcoming the tunability restriction, besides, possessing lower losses as compared to metals. In addition, doped semiconductors have small magnitude of negative real permittivity which is required to realize mid IR Hyperbolic Metamaterials (HMMs). We theoretically demonstrate super focusing based on an all Semiconductor planar HMM using InAs heterostructure...
November 10, 2017: Scientific Reports
Jason Ernst, Manolis Kellis
Noncoding DNA regions have central roles in human biology, evolution, and disease. ChromHMM helps to annotate the noncoding genome using epigenomic information across one or multiple cell types. It combines multiple genome-wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer a complete annotation for each cell type. ChromHMM learns chromatin-state signatures using a multivariate hidden Markov model (HMM) that explicitly models the combinatorial presence or absence of each mark. ChromHMM uses these signatures to generate a genome-wide annotation for each cell type by calculating the most probable state for each genomic segment...
December 2017: Nature Protocols
Jihyun Kim, Thi-Thu-Huong Le, Howon Kim
Monitoring electricity consumption in the home is an important way to help reduce energy usage. Nonintrusive Load Monitoring (NILM) is existing technique which helps us monitor electricity consumption effectively and costly. NILM is a promising approach to obtain estimates of the electrical power consumption of individual appliances from aggregate measurements of voltage and/or current in the distribution system. Among the previous studies, Hidden Markov Model (HMM) based models have been studied very much...
2017: Computational Intelligence and Neuroscience
Joseph W Houpt, Mary E Frame, Leslie M Blaha
The first stage of analyzing eye-tracking data is commonly to code the data into sequences of fixations and saccades. This process is usually automated using simple, predetermined rules for classifying ranges of the time series into events, such as "if the dispersion of gaze samples is lower than a particular threshold, then code as a fixation; otherwise code as a saccade." More recent approaches incorporate additional eye-movement categories in automated parsing algorithms by using time-varying, data-driven thresholds...
October 26, 2017: Behavior Research Methods
Dinghua Li, Yukun Huang, Chi-Ming Leung, Ruibang Luo, Hing-Fung Ting, Tak-Wah Lam
BACKGROUND: The recent release of the gene-targeted metagenomics assembler Xander has demonstrated that using the trained Hidden Markov Model (HMM) to guide the traversal of de Bruijn graph gives obvious advantage over other assembly methods. Xander, as a pilot study, indeed has a lot of room for improvement. Apart from its slow speed, Xander uses only 1 k-mer size for graph construction and whatever choice of k will compromise either sensitivity or accuracy. Xander uses a Bloom-filter representation of de Bruijn graph to achieve a lower memory footprint...
October 16, 2017: BMC Bioinformatics
Xiao-Hu Zhou, Gui-Bin Bian, Xiao-Liang Xie, Zeng-Guang Hou
Robotic surgical systems are becoming increasingly popular for the treatment of cardiovascular diseases. However, most of them have been designed without considering techniques and skills of natural surgical manipulations, which are key factors to clinical success of percutaneous coronary intervention. This paper proposes an HMM-based framework to recognize six typical endovascular manipulations for surgical skill analysis. A simulative surgical platform is built for endovascular manipulations assessed by five subjects (1 expert and 4 novices)...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Shuang Liu, Di Zhang, Jingjing Tong, Feng He, Hongzhi Qi, Lixin Zhang, Dong Ming
EEG-based emotion recognition has received increasing attention in the past few decades. The frequency components that give effective discrimination between different emotion states are subject specific. Identification of these subject-specific discriminative frequency components (DFCs) is important for the accurate classification of emotional activities. This paper investigated the potential of adaptive tracking of DFCs as an effective method for choosing the discriminative bands of EEG patterns and improving emotion recognition performance...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Raul I Ramos-Garcia, Edward Sazonov, Stephen Tiffany
Previous studies with the Personal Automatic Cigarette Tracker (PACT) wearable system have found that smoking presents a distinct temporal breathing pattern, which might be well-suited for recognition by hidden Markov models (HMMs). In this work, we explored the feasibility of using HMMs to characterize the temporal information of smoking inhalations contained in the respiratory signals such as tidal volume, airflow, and the signal from the hand-to-mouth proximity sensor. Left-to-right HMMs were built to classify smoking and non-smoking inhalations using either only the respiratory signals, or both respiratory and hand proximity signals...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Kairui Guo, Henry Candra, Hairong Yu, Huiqi Li, Hung T Nguyen, Steven W Su
Emotion classification is one of the state-of-the-art topics in biomedical signal research, and yet a significant portion remains unknown. This paper offers a novel approach with a combined classifier to recognise human emotion states based on electroencephalogram (EEG) signal. The objective is to achieve high accuracy using the combined classifier designed, which categorises the extracted features calculated from time domain features and Discrete Wavelet Transform (DWT). Two innovative designs are involved in this project: a novel variable is established as a new feature and a combined SVM and HMM classifier is developed...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Cheol-Hong Min
An infrastructure to record, detect and label the behavioral patterns of children with Autism Spectrum Disorder (ASD) has been developed. The system incorporates 2 different sensor platforms which are wearable and static. The wearable system is based on accelerometer which detects behavioral patterns of a subject, while the static sensors are microphones and cameras which captures the sounds, images and videos of the subjects within a room. The video also provides ground truth for wearable sensor data analysis...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Sabyasachi Mukhopadhyay, Nandan K Das, Indrajit Kurmi, Asima Pradhan, Nirmalya Ghosh, Prasanta K Panigrahi
We report the application of a hidden Markov model (HMM) on multifractal tissue optical properties derived via the Born approximation-based inverse light scattering method for effective discrimination of precancerous human cervical tissue sites from the normal ones. Two global fractal parameters, generalized Hurst exponent and the corresponding singularity spectrum width, computed by multifractal detrended fluctuation analysis (MFDFA), are used here as potential biomarkers. We develop a methodology that makes use of these multifractal parameters by integrating with different statistical classifiers like the HMM and support vector machine (SVM)...
October 2017: Journal of Biomedical Optics
Ronesh Sharma, Maitsetseg Bayarjargal, Tatsuhiko Tsunoda, Ashwini Patil, Alok Sharma
MOTIVATION: Intrinsically Disordered Proteins (IDPs) lack stable tertiary structure and they actively participate in performing various biological functions. These IDPs expose short binding regions called Molecular Recognition Features (MoRFs) that permit interaction with structured protein regions. Upon interaction they undergo a disorder-to-order transition as a result of which their functionality arises. Predicting these MoRFs in disordered protein sequences is a challenging task. METHOD: In this study, we present MoRFpred-plus, an improved predictor over our previous proposed predictor to identify MoRFs in disordered protein sequences...
October 16, 2017: Journal of Theoretical Biology
Wenyang Wu, Lingling Fan, Wenbo Zang, Xin Yang, Peng Zhan, Zhuo Chen, Zhenlin Wang
We theoretically investigate the dipolar whispering-gallery modes (WGMs) with different mode orders supported by spherical hyperbolic metamaterial (HMM) cavities consisting of alternating metal and dielectric layers. Associated with the excitations of the WGMs with the highest and the second highest mode orders, the HMM cavities are capable of creating highly enhanced and uniformly distributed local fields in the entire dielectric core region. Variation on the metal filling ratio allows for easily tuning the resonant wavelengths of WGMs over a wide spectral range...
September 4, 2017: Optics Express
Vikas Bansal
Motivation: The short read lengths of current high-throughput sequencing technologies limit the ability to recover long-range haplotype information. Dilution pool methods for preparing DNA sequencing libraries from high molecular weight DNA fragments enable the recovery of long DNA fragments from short sequence reads. These approaches require computational methods for identifying the DNA fragments using aligned sequence reads and assembling the fragments into long haplotypes. Although a number of computational methods have been developed for haplotype assembly, the problem of identifying DNA fragments from dilution pool sequence data has not received much attention...
July 11, 2017: Bioinformatics
Masanori Tsubosaka, Takafumi Hiranaka, Kenjiro Okimura, Yuta Nakanishi, Yosaku Shibata, Yuichi Hida, Takaaki Fujishiro, Harunobu Uemoto
BACKGROUND: Smart glasses (SG) are a wearable device consisting of a small computer built into a head-mounted monitor (HMM) that can display various kinds of information. Lateral side visualization is displayed on the HMM of SG so the operator may also see it and the anteroposterior (AP) direction simultaneously. The present pilot study aimed to investigate the usefulness of SG in wire insertion for bone fracture. METHODS: We marked both the front and lateral sides of the shaft of an artificial femur bone...
October 1, 2017: Surgical Innovation
Tabinda Zafar, Charly Brouillard, Laurence Lanfumey, Caroline Sévoz-Couche
Recent studies have demonstrated that a mild stimulation of the dorsomedian nucleus of the hypothalamus (DMH), a defense area, induces the inhibition of the carotid chemoreflex tachypnea. DMH activation reduces the cardiac chemoreflex response via the dorsolateral part of the periaqueductal grey matter (dlPAG) and serotonin receptors (5-HT3 subtype) in the nucleus tractus solitarius (NTS). The objectives of this study were to assess whether dlPAG and subsequent NTS 5-HT3 receptors are involved in chemoreflex tachypnea inhibition during mild activation of the DMH...
October 4, 2017: Neuropharmacology
Maria Simak, Chen-Hsiang Yeang, Henry Horng-Shing Lu
The great amount of gene expression data has brought a big challenge for the discovery of Gene Regulatory Network (GRN). For network reconstruction and the investigation of regulatory relations, it is desirable to ensure directness of links between genes on a map, infer their directionality and explore candidate biological functions from high-throughput transcriptomic data. To address these problems, we introduce a Boolean Function Network (BFN) model based on techniques of hidden Markov model (HMM), likelihood ratio test and Boolean logic functions...
2017: PloS One
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