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Jin Woo Huh, Dong Kyu Lee, Hwan-Jin Jeon, Chi Won Ahn
In this study, hybrid-structured metal mesh (HMM) films as potential flexible transparent electrodes, composed of aligned micro-sized metal fibers integrated into random network of metal nanofibers, were fabricated by the combination of electrospinning and metal deposition. These naturally fiber-bridged HMMs, with a gold layer thickness of 85 nm, exhibited a high transmittance of around 90% and a sheet resistance of approximately 10 Ω sq(-1), as well as favorable mechanical stability under bending stress. These results demonstrate that the approach employed herein is a simple, highly efficient, and facile process for fabricating, uniform, interconnected fiber networks with potential for producing high-performance flexible transparent electrodes...
November 25, 2016: Nanotechnology
Fuming Fang, Takahiro Shinozaki, Yasuo Horiuchi, Shingo Kuroiwa, Sadaoki Furui, Toshimitsu Musha
Eye motion-based human-machine interfaces are used to provide a means of communication for those who can move nothing but their eyes because of injury or disease. To detect eye motions, electrooculography (EOG) is used. For efficient communication, the input speed is critical. However, it is difficult for conventional EOG recognition methods to accurately recognize fast, sequentially input eye motions because adjacent eye motions influence each other. In this paper, we propose a context-dependent hidden Markov model- (HMM-) based EOG modeling approach that uses separate models for identical eye motions with different contexts...
2016: Computational Intelligence and Neuroscience
Antonio López-Orenes, María C Bueso, Héctor M Conesa, Antonio A Calderón, María A Ferrer
Soil pollution by heavy metals/metalloids (HMMs) is a problem worldwide. To prevent dispersion of contaminated particles by erosion, the maintenance of a vegetative cover is needed. Successful plant establishment in multi-polluted soils can be hampered not only by HMM toxicities, but also by soil nutrient deficiencies and the co-occurrence of abiotic stresses. Some plant species are able to thrive under these multi-stress scenarios often linked to marked fluctuations in environmental factors. This study aimed to investigate the metabolic adjustments involved in Zygophyllum fabago acclimative responses to conditions prevailing in HMM-enriched mine-tailings piles, during Mediterranean spring and summer...
October 14, 2016: Science of the Total Environment
Mahsa Akhbari, Mohammad B Shamsollahi, Omid Sayadi, Antonis A Armoundas, Christian Jutten
In this paper, we propose a novel method for extracting fiducial points (FPs) of electrocardiogram (ECG) signals. We propose the use of multi hidden Markov model (MultiHMM) as opposed to the traditional use of Classic HMM. In the MultiHMM method, each segment of an ECG beat is represented by a separate ergodic continuous density HMM. Each HMM has different state number and is trained separately. In the test step, the log-likelihood of two consecutive HMMs is compared and a path is estimated, which shows the correspondence of each part of the ECG signal to the HMM with the maximum log-likelihood...
September 28, 2016: Computers in Biology and Medicine
Pritha Ghosh, Oommen K Mathew, Ramanathan Sowdhamini
BACKGROUND: RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information...
October 7, 2016: BMC Bioinformatics
Weijie Kong, Wenjuan Du, Kaipeng Liu, Changtao Wang, Ling Liu, Zeyu Zhao, Xiangang Luo
Hyperbolic metamaterials (HMMs) composed of multiple nanometal-dielectric films are proposed for launching deep subwavelength bulk plasmon polaritons (BPPs) as uniform, large area surface imaging illumination sources with a skin depth even beyond 10 nm. Benefiting from the coupled plasmon modes over a wide wavevector range in HMMs, the illumination depth could be continually tuned, simply by adjusting the incidence angle of light impinged on a grating structure for BPP excitation. As an example, the illumination depths of 19-63 nm at a light wavelength of 532 nm are demonstrated with SiO2-Ag multifilms...
September 29, 2016: Nanoscale
Wonbae Lee, John P Gillies, Davis Jose, Brett A Israels, Peter H von Hippel, Andrew H Marcus
Gene 32 protein (gp32) is the single-stranded (ss) DNA binding protein of the bacteriophage T4. It binds transiently and cooperatively to ssDNA sequences exposed during the DNA replication process and regulates the interactions of the other sub-assemblies of the replication complex during the replication cycle. We here use single-molecule FRET techniques to build on previous thermodynamic studies of gp32 binding to initiate studies of the dynamics of the isolated and cooperative binding of gp32 molecules within the replication complex...
September 30, 2016: Nucleic Acids Research
Marwa Al Arab, Christian Höner Zu Siederdissen, Kifah Tout, Abdullah H Sahyoun, Peter F Stadler, Matthias Bernt
Mitochondrial genome sequences are available in large number and new sequences become published nowadays with increasing pace. Fast, automatic, consistent, and high quality annotations are a prerequisite for downstream analyses. Therefore, we present an automated pipeline for fast de novo annotation of mitochondrial protein-coding genes. The annotation is based on enhanced phylogeny-aware hidden Markov models (HMMs). The pipeline builds taxon-specific enhanced multiple sequence alignments (MSA) of already annotated sequences and corresponding HMMs using an approximation of the phylogeny...
September 28, 2016: Molecular Phylogenetics and Evolution
Kiyoshi Ezawa
BACKGROUND: Insertions and deletions (indels) account for more nucleotide differences between two related DNA sequences than substitutions do, and thus it is imperative to develop a stochastic evolutionary model that enables us to reliably calculate the probability of the sequence evolution through indel processes. Recently, indel probabilistic models are mostly based on either hidden Markov models (HMMs) or transducer theories, both of which give the indel component of the probability of a given sequence alignment as a product of either probabilities of column-to-column transitions or block-wise contributions along the alignment...
August 11, 2016: BMC Bioinformatics
Haitao Guo, Hongwei Huo, Qiang Yu
The discovery of cis-regulatory modules (CRMs) is a challenging problem in computational biology. Limited by the difficulty of using an HMM to model dependent features in transcriptional regulatory sequences (TRSs), the probabilistic modeling methods based on HMMs cannot accurately represent the distance between regulatory elements in TRSs and are cumbersome to model the prevailing dependencies between motifs within CRMs. We propose a probabilistic modeling algorithm called SMCis, which builds a more powerful CRM discovery model based on a hidden semi-Markov model...
2016: PloS One
Y Tang, Z Xi, M Xu, S Bäumer, A J L Adam, H P Urbach
Hyperbolic metamaterials (HMMs) are anisotropic materials with a permittivity tensor that has both positive and negative eigenvalues. Here we report that by using a type II HMM as a cladding material, a waveguide that only supports higher-order modes can be achieved, while the lower-order modes become leaky and are absorbed in the HMM cladding. This counter-intuitive property can lead to novel application in optical communications and photonic integrated circuits. The loss in our HMM insulator-HMM (HIH) waveguide is smaller than that of similar guided modes in a metal-insulator-metal (MIM) waveguide...
September 15, 2016: Optics Letters
I Gregor, A Schönhuth, A C McHardy
MOTIVATION: Gene assembly is an important step in functional analysis of shotgun metagenomic data. Nonetheless, strain aware assembly remains a challenging task, as current assembly tools often fail to distinguish among strain variants or require closely related reference genomes of the studied species to be available. RESULTS: We have developed Snowball, a novel strain aware gene assembler for shotgun metagenomic data that does not require closely related reference genomes to be available...
September 1, 2016: Bioinformatics
Siddhartha Kundu, Rita Sharma
The glycoside hydrolase 9 superfamily, mainly comprising the endoglucanases, is represented in all three domains of life. The current division of GH9 enzymes, into three subclasses, namely A, B, and C, is centered on parameters derived from sequence information alone. However, this classification is ambiguous, and is limited by the paralogous ancestry of classes B and C endoglucanases, and paucity of biochemical and structural data. Here, we extend this classification schema to putative GH9 endoglucanases present in green plants, with an emphasis on identifying novel members of the class C subset...
2016: Frontiers in Plant Science
Francisco J Martinez-Murcia, Juan M Górriz, Javier Ramírez, Andres Ortiz
The usage of biomedical imaging in the diagnosis of dementia is increasingly widespread. A number of works explore the possibilities of computational techniques and algorithms in what is called computed aided diagnosis. Our work presents an automatic parametrization of the brain structure by means of a path generation algorithm based on hidden Markov models (HMMs). The path is traced using information of intensity and spatial orientation in each node, adapting to the structure of the brain. Each path is itself a useful way to characterize the distribution of the tissue inside the magnetic resonance imaging (MRI) image by, for example, extracting the intensity levels at each node or generating statistical information of the tissue distribution...
November 2016: International Journal of Neural Systems
Toshiki Saito, Noriaki Kawakami, Taichi Tsuji, Tetsuya Ohara, Yoshitaka Suzuki, Ayato Nohara, Ryoji Tauchi, Kazuki Kawakami
STUDY DESIGN: This is a retrospective cohort study. BACKGROUND: Hemimetameric segmental shift (HMMS) is defined as a hemivertebral deformation in which 2 or more hemivertebrae exist on both sides of the spine and are separated by at least 1 normal vertebra. Reports of HMMS are rare and based on simple anterior x-ray images. No reports have used 3-dimensional computed tomography (3D-CT) to analyze both the anterior and posterior elements. The objective of this study was to analyze the morphology and clinical features of HMMS 3 dimensionally...
June 8, 2016: Journal of Pediatric Orthopedics
Xiaomu Luo, Huoyuan Tan, Qiuju Guan, Tong Liu, Hankz Hankui Zhuo, Baihua Shen
Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them...
2016: Sensors
Kostas Michalopoulos, Michalis Zervakis, Marie-Pierre Deiber, Nikolaos Bourbakis
We present a novel synergistic methodology for the spatio-temporal analysis of single Electroencephalogram (EEG) trials. This new methodology is based on the novel synergy of Local Global Graph (LG graph) to characterize define the structural features of the EEG topography as a global descriptor for robust comparison of dominant topographies (microstates) and Hidden Markov Models (HMM) to model the topographic sequence in a unique way. In particular, the LG graph descriptor defines similarity and distance measures that can be successfully used for the difficult comparison of the extracted LG graphs in the presence of noise...
September 2016: International Journal of Neural Systems
Michalis K Titsias, Christopher C Holmes, Christopher Yau
Hidden Markov models (HMMs) are one of the most widely used statistical methods for analyzing sequence data. However, the reporting of output from HMMs has largely been restricted to the presentation of the most-probable (MAP) hidden state sequence, found via the Viterbi algorithm, or the sequence of most probable marginals using the forward-backward algorithm. In this article, we expand the amount of information we could obtain from the posterior distribution of an HMM by introducing linear-time dynamic programming recursions that, conditional on a user-specified constraint in the number of segments, allow us to (i) find MAP sequences, (ii) compute posterior probabilities, and (iii) simulate sample paths...
January 2, 2016: Journal of the American Statistical Association
Kandammathe Valiyaveedu Sreekanth, Mohamed ElKabbash, Yunus Alapan, Alireza R Rashed, Umut A Gurkan, Giuseppe Strangi
In recent years, considerable research efforts have been focused on near-perfect and perfect light absorption using metamaterials spanning frequency ranges from microwaves to visible frequencies. This relatively young field is currently facing many challenges that hampers its possible practical applications. In this paper, we present grating coupled-hyperbolic metamaterials (GC-HMM) as multiband perfect absorber that can offer extremely high flexibility in engineering the properties of electromagnetic absorption...
2016: Scientific Reports
Lucas Wafer, Marek Kloczewiak, Yin Luo
Analytical ultracentrifugation-sedimentation velocity (AUC-SV) is often used to quantify high molar mass species (HMMS) present in biopharmaceuticals. Although these species are often present in trace quantities, they have received significant attention due to their potential immunogenicity. Commonly, AUC-SV data is analyzed as a diffusion-corrected, sedimentation coefficient distribution, or c(s), using SEDFIT to numerically solve Lamm-type equations. SEDFIT also utilizes maximum entropy or Tikhonov-Phillips regularization to further allow the user to determine relevant sample information, including the number of species present, their sedimentation coefficients, and their relative abundance...
July 2016: AAPS Journal
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