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https://www.readbyqxmd.com/read/28727547/designing-and-implementation-of-stable-sinusoidal-rough-neural-identifier
#1
Ghasem Ahmadi, Mohammad Teshnehlab
A rough neuron is defined as a pair of conventional neurons that are called the upper and lower bound neurons. In this paper, the sinusoidal rough-neural networks (SR-NNs) are used to identify the discrete dynamic nonlinear systems (DDNSs) with or without noise in series-parallel configuration. In the identification of periodic nonlinear systems, sinusoidal activation functions provide more efficient neural networks than the sigmoidal activation functions. Based on the Lyapunov stability theory, an online learning algorithm is developed to train the SR-NNs...
August 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28726745/dual-source-linear-energy-prediction-line-p-model-in-the-context-of-wsns
#2
Faisal Ahmed, Gert Tamberg, Yannick Le Moullec, Paul Annus
Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source...
July 20, 2017: Sensors
https://www.readbyqxmd.com/read/28726544/evaluating-wais-iv-structure-through-a-different-psychometric-lens-structural-causal-model-discovery-as-an-alternative-to-confirmatory-factor-analysis
#3
Marjolein J A M van Dijk, Tom Claassen, Christiany Suwartono, William M van der Veld, Paul T van der Heijden, Marc P H Hendriks
OBJECTIVE: Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV (WAIS-IV-NL) by applying an alternative analysis based on causal modeling in addition to confirmatory factor analysis (CFA). The Bayesian Constraint-based Causal Discovery (BCCD) algorithm learns underlying network structures directly from data and assesses more complex structures than is possible with factor analysis...
July 20, 2017: Clinical Neuropsychologist
https://www.readbyqxmd.com/read/28724399/health-needs-access-to-healthcare-and-perceptions-of-ageing-in-an-urbanizing-community-in-india-a-qualitative-study
#4
Nandita Bhan, Pavitra Madhira, Arundati Muralidharan, Bharati Kulkarni, Gvs Murthy, Sanjay Basu, Sanjay Kinra
BACKGROUND: India's elderly population is rising at an unprecedented rate, with a majority living in rural areas. Health challenges associated with ageing, changing social networks and limited public health infrastructure are issues faced by the elderly and caregivers. We examined perceptions of health needs of the elderly across local stakeholders in an urbanizing rural area. METHODS: The qualitative study was conducted among participants in the Andhra Pradesh Children and Parents Study (APCAPS) site in Rangareddy district, Telangana...
July 19, 2017: BMC Geriatrics
https://www.readbyqxmd.com/read/28723311/visual-perceptual-learning-and-models
#5
Barbara Dosher, Zhong-Lin Lu
Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision...
July 19, 2017: Annual Review of Vision Science
https://www.readbyqxmd.com/read/28718193/metacommunity-theory-meets-restoration-isolation-may-mediate-how-ecological-communities-respond-to-stream-restoration
#6
Christopher M Swan, Bryan L Brown
An often-cited benefit of river restoration is an increase in biodiversity or shift in composition to more desirable taxa. Yet, hard manipulations of habitat structure often fail to elicit a significant response in terms of biodiversity patterns. In contrast to conventional wisdom, the dispersal of organisms may have as large an influence on biodiversity patterns as environmental conditions. This influence of dispersal may be particularly influential in river networks which are linear branching, or dendritic, and thus constrain most dispersal to the river corridor...
July 17, 2017: Ecological Applications: a Publication of the Ecological Society of America
https://www.readbyqxmd.com/read/28717517/knowledge-mapping-visualization-analysis-of-the-military-health-and-medicine-papers-published-in-the-web-of-science-over-the-past-10%C3%A2-years
#7
Xuan-Ming Zhang, Xuan Zhang, Xu Luo, Hai-Tao Guo, Li-Qun Zhang, Ji-Wei Guo
BACKGROUND: Military medicine is a research field that seeks to solve the medical problems that occur in modern war conditions based on public medicine theory. METHODS: We explore the main research topics of military health and medical research in the web of science™ core collection (WoSCC) from 2007 to 2016, and the goal of this work is to serve as a reference for orientation and development in military health and medicine. Based on CiteSpace III, a reference co-citation analysis is performed for 7921 papers published in the WoSCC from 2007 to 2016...
2017: Military Medical Research
https://www.readbyqxmd.com/read/28714325/actor-network-theory-and-micro-learning-networks
#8
Alex Harding
No abstract text is available yet for this article.
July 16, 2017: Education for Primary Care
https://www.readbyqxmd.com/read/28713345/experimental-study-and-ann-dual-time-scale-perturbation-model-of-electrokinetic-properties-of-microbiota
#9
Yong Liu, Cristian R Munteanu, Carlos Fernandez-Lozano, Alejandro Pazos, Tao Ran, Zhiliang Tan, Yizun Yu, Chuanshe Zhou, Shaoxun Tang, Humberto González-Díaz
The electrokinetic properties of the rumen microbiota are involved in cell surface adhesion and microbial metabolism. An in vitro study was carried out in batch culture to determine the effects of three levels of special surface area (SSA) of biomaterials and four levels of surface tension (ST) of culture medium on electrokinetic properties (Zeta potential, ξ; electrokinetic mobility, μe), fermentation parameters (volatile fatty acids, VFAs), and ST over fermentation processes (ST-a, γ). The obtained results were combined with previously published data (digestibility, D; pH; concentration of ammonia nitrogen, c(NH3-N)) to establish a predictive artificial neural network (ANN) model...
2017: Frontiers in Microbiology
https://www.readbyqxmd.com/read/28711053/representations-in-neural-network-based-empirical-potentials
#10
Ekin D Cubuk, Brad D Malone, Berk Onat, Amos Waterland, Efthimios Kaxiras
Many structural and mechanical properties of crystals, glasses, and biological macromolecules can be modeled from the local interactions between atoms. These interactions ultimately derive from the quantum nature of electrons, which can be prohibitively expensive to simulate. Machine learning has the potential to revolutionize materials modeling due to its ability to efficiently approximate complex functions. For example, neural networks can be trained to reproduce results of density functional theory calculations at a much lower cost...
July 14, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/28709656/analyses-of-integrated-aircraft-cabin-contaminant-monitoring-network-based-on-kalman-consensus-filter
#11
Rui Wang, Yanxiao Li, Hui Sun, Zengqiang Chen
The modern civil aircrafts use air ventilation pressurized cabins subject to the limited space. In order to monitor multiple contaminants and overcome the hypersensitivity of the single sensor, the paper constructs an output correction integrated sensor configuration using sensors with different measurement theories after comparing to other two different configurations. This proposed configuration works as a node in the contaminant distributed wireless sensor monitoring network. The corresponding measurement error models of integrated sensors are also proposed by using the Kalman consensus filter to estimate states and conduct data fusion in order to regulate the single sensor measurement results...
July 11, 2017: ISA Transactions
https://www.readbyqxmd.com/read/28709280/collapse-of-resilience-patterns-in-generalized-lotka-volterra-dynamics-and-beyond
#12
Chengyi Tu, Jacopo Grilli, Friedrich Schuessler, Samir Suweis
Recently, a theoretical framework aimed at separating the roles of dynamics and topology in multidimensional systems has been developed [Gao et al., Nature (London) 530, 307 (2016)10.1038/nature16948]. The validity of their method is assumed to hold depending on two main hypotheses: (i) The network determined by the the interaction between pairs of nodes has negligible degree correlations; (ii) the node activities are uniform across nodes on both the drift and the pairwise interaction functions. Moreover, the authors consider only positive (mutualistic) interactions...
June 2017: Physical Review. E
https://www.readbyqxmd.com/read/28709222/population-density-equations-for-stochastic-processes-with-memory-kernels
#13
Yi Ming Lai, Marc de Kamps
We present a method for solving population density equations (PDEs)--a mean-field technique describing homogeneous populations of uncoupled neurons-where the populations can be subject to non-Markov noise for arbitrary distributions of jump sizes. The method combines recent developments in two different disciplines that traditionally have had limited interaction: computational neuroscience and the theory of random networks. The method uses a geometric binning scheme, based on the method of characteristics, to capture the deterministic neurodynamics of the population, separating the deterministic and stochastic process cleanly...
June 2017: Physical Review. E
https://www.readbyqxmd.com/read/28709195/finite-size-analysis-of-the-detectability-limit-of-the-stochastic-block-model
#14
Jean-Gabriel Young, Patrick Desrosiers, Laurent Hébert-Dufresne, Edward Laurence, Louis J Dubé
It has been shown in recent years that the stochastic block model is sometimes undetectable in the sparse limit, i.e., that no algorithm can identify a partition correlated with the partition used to generate an instance, if the instance is sparse enough and infinitely large. In this contribution, we treat the finite case explicitly, using arguments drawn from information theory and statistics. We give a necessary condition for finite-size detectability in the general SBM. We then distinguish the concept of average detectability from the concept of instance-by-instance detectability and give explicit formulas for both definitions...
June 2017: Physical Review. E
https://www.readbyqxmd.com/read/28709185/fluctuation-relations-between-hierarchical-kinetically-equivalent-networks-with-arrhenius-type-transitions-and-their-roles-in-systems-and-structural-biology
#15
De-Ming Deng, Yi-Ta Lu, Cheng-Hung Chang
The legality of using simple kinetic schemes to determine the stochastic properties of a complex system depends on whether the fluctuations generated from hierarchical equivalent schemes are consistent with one another. To analyze this consistency, we perform lumping processes on the stochastic differential equations and the generalized fluctuation-dissipation theorem and apply them to networks with the frequently encountered Arrhenius-type transition rates. The explicit Langevin force derived from those networks enables us to calculate the state fluctuations caused by the intrinsic and extrinsic noises on the free energy surface and deduce their relations between kinetically equivalent networks...
June 2017: Physical Review. E
https://www.readbyqxmd.com/read/28708071/evolutionary-origins-of-cancer-driver-genes-and-implications-for-cancer-prognosis
#16
Xin-Yi Chu, Ling-Han Jiang, Xiong-Hui Zhou, Ze-Jia Cui, Hong-Yu Zhang
The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer...
July 14, 2017: Genes
https://www.readbyqxmd.com/read/28708033/neuropsychological-profile-and-social-cognition-in-congenital-central-hypoventilation-syndrome-cchs-correlation-with-neuroimaging-in-a-clinical-case
#17
Borja Esteso Orduña, Raquel Seijas Gómez, Elena García Esparza, Emily M Briceño, Javier Melero Llorente, María de la Concepción Fournier Del Castillo
INTRODUCTION: Congenital central hypoventilation syndrome (CCHS) is a rare genetic disorder due to paired-like homeobox gene (PHOX2B) mutations. CCHS patients suffer from dysregulation of the autonomic nervous system characterized by the absence of or extremely reduced response to hypercapnia and hypoxia, with neuropsychological deficits. The aim of this exploratory study is to describe the longitudinal neuropsychological profile and its correlations with magnetic resonance imaging (MRI) of a child with CCHS with a PHOX2B mutation...
July 14, 2017: Journal of Clinical and Experimental Neuropsychology
https://www.readbyqxmd.com/read/28706740/action-video-game-experience-related-to-altered-large-scale-white-matter-networks
#18
Diankun Gong, Weiyi Ma, Jinnan Gong, Hui He, Li Dong, Dan Zhang, Jianfu Li, Cheng Luo, Dezhong Yao
With action video games (AVGs) becoming increasingly popular worldwide, the cognitive benefits of AVG experience have attracted continuous research attention over the past two decades. Research has repeatedly shown that AVG experience can causally enhance cognitive ability and is related to neural plasticity in gray matter and functional networks in the brain. However, the relation between AVG experience and the plasticity of white matter (WM) network still remains unclear. WM network modulates the distribution of action potentials, coordinating the communication between brain regions and acting as the framework of neural networks...
2017: Neural Plasticity
https://www.readbyqxmd.com/read/28705691/functional-connectivity-within-and-between-intrinsic-networks-correlates-with-trait-mind-wandering
#19
Christine A Godwin, Michael A Hunter, Matthew A Bezdek, Gregory Lieberman, Seth Elkin-Frankston, Victoria L Romero, Katie Witkiewitz, Vincent P Clark, Eric H Schumacher
Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). Furthermore, the extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory...
July 10, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28705239/nap-the-network-analysis-profiler-a-web-tool-for-easier-topological-analysis-and-comparison-of-medium-scale-biological-networks
#20
Theodosios Theodosiou, Georgios Efstathiou, Nikolas Papanikolaou, Nikos C Kyrpides, Pantelis G Bagos, Ioannis Iliopoulos, Georgios A Pavlopoulos
OBJECTIVE: Nowadays, due to the technological advances of high-throughput techniques, Systems Biology has seen a tremendous growth of data generation. With network analysis, looking at biological systems at a higher level in order to better understand a system, its topology and the relationships between its components is of a great importance. Gene expression, signal transduction, protein/chemical interactions, biomedical literature co-occurrences, are few of the examples captured in biological network representations where nodes represent certain bioentities and edges represent the connections between them...
July 14, 2017: BMC Research Notes
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