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Reservoir computing

Pallavi Surase, Gita Nataraj, Sunil Kuyare, Preeti Mehta
OBJECTIVES: The study was carried out to determine the extent and type of contamination of the hands and accessories of staff from different settings and also to determine the phenotypic similarity between the isolates recovered from the same staff. DESIGN: Prospective cross-sectional study. SETTING: Tertiary care center. PARTICIPANTS: Health care workers (HCWs') and administrative staff. METHODS: Samples were collected and processed for bacteriology from the dominant hand, mobiles, aprons, stethoscopes and computer keyboards of 280 staff working in different settings after consent...
August 2016: Journal of the Association of Physicians of India
Pedro H Guimarães, Gabriel T Landi, Mario J de Oliveira
We study a quantum XX chain coupled to two heat reservoirs that act on multiple sites and are kept at different temperatures and chemical potentials. The baths are described by Lindblad dissipators, which are constructed by direct coupling to the fermionic normal modes of the chain. Using a perturbative method, we are able to find analytical formulas for all steady-state properties of the system. We compute both the particle or magnetization current and the energy current, both of which are found to have the structure of Landauer's formula...
September 2016: Physical Review. E
N Crampe, E Ragoucy, V Rittenberg, M Vanicat
We study a one-parameter generalization of the symmetric simple exclusion process on a one-dimensional lattice. In addition to the usual dynamics (where particles can hop with equal rates to the left or to the right with an exclusion constraint), annihilation and creation of pairs can occur. The system is driven out of equilibrium by two reservoirs at the boundaries. In this setting the model is still integrable: it is related to the open XXZ spin chain through a gauge transformation. This allows us to compute the full spectrum of the Markov matrix using Bethe equations...
September 2016: Physical Review. E
Sebastian Haefner, Philipp Frank, Martin Elstner, Johannes Nowak, Stefan Odenbach, Andreas Richter
Smart hydrogels are useful elements in microfluidic systems because they respond to environmental stimuli and are capable of storing reagents. We present here a concept of using hydrogels (poly(N-isopropylacrylamide)) as an interface between continuous and discontinuous microfluidics. Their swelling and shrinking capabilities allow them to act as storage elements for reagents absorbed in the swelling process. When the swollen hydrogel collapses in an oil-filled channel, the incorporated water and molecules are expelled from the hydrogel and form a water reservoir...
October 5, 2016: Lab on a Chip
Michiel Hermans, Piotr Antonik, Marc Haelterman, Serge Massar
Delay-coupled electro-optical systems have received much attention for their dynamical properties and their potential use in signal processing. In particular, it has recently been demonstrated, using the artificial intelligence algorithm known as reservoir computing, that photonic implementations of such systems solve complex tasks such as speech recognition. Here, we show how the backpropagation algorithm can be physically implemented on the same electro-optical delay-coupled architecture used for computation with only minor changes to the original design...
September 16, 2016: Physical Review Letters
Michał Baciak, Łukasz Sikorski, Agnieszka I Piotrowicz-Cieślak, Barbara Adomas
Aquatic plants are continuously exposed to a variety of stress factors. No data on the impact of antibiotics on the biogenic amines in duckweed (Lemna minor) have been available so far, and such data could be significant, considering the ecological role of this plant in animal food chains. In the tissues of control (non-stressed) nine-day-old duckweed, the following biogenic amines were identified: tyramine, putrescine, cadaverine, spermidine and spermine. Based on the tetracycline contents and the computed EC values, the predicted toxicity units have been calculated...
September 9, 2016: Aquatic Toxicology
Pavel Zuloaga-Molero, Wei Yu, Yifei Xu, Kamy Sepehrnoori, Baozhen Li
The recent development of tight oil reservoirs has led to an increase in oil production in the past several years due to the progress in horizontal drilling and hydraulic fracturing. However, the expected oil recovery factor from these reservoirs is still very low. CO2-based enhanced oil recovery is a suitable solution to improve the recovery. One challenge of the estimation of the recovery is to properly model complex hydraulic fracture geometries which are often assumed to be planar due to the limitation of local grid refinement approach...
2016: Scientific Reports
Atsushi Arai, Hirohito Miyamoto, Ryoji Shiomi, Shotaro Tatsumi, Eiji Kohmura
Spontaneous cerebrospinal fluid leak and intracranial hypotension associated with cervical spondylosis have rarely been observed, and only a few cases are reported. A 69-year-old woman, previously treated for rectal and thyroid cancer, complained of a non-postural persistent headache. The patient regularly practiced aerobic exercise, but a month earlier she had started experiencing headache and neck pain while exercising. Computed tomography(CT)showed bilateral chronic subdural hematomas, and magnetic resonance imaging(MRI)revealed diffuse dural enhancement and tonsillar herniation...
September 2016: No Shinkei Geka. Neurological Surgery
Xiao-Dong Tan, Cornelie Koop, Xiao-Ping Liao, Litao Sun
We compute the entanglement and the quantum discord (QD) between two edge spins in chiral graphene nanoribbons (CGNRs) thermalized with a reservoir at temperature T (canonical ensemble). We show that the entanglement only exists in inter-edge coupled spin pairs, and there is no entanglement between any two spins at the same ribbon edge. By contrast, almost all edge spin pairs can hold non-zero QD, which strongly depends on the ribbon width and the Coulomb repulsion among electrons. More intriguingly, the dominant entanglement always occurs in the pair of nearest abreast spins across the ribbon, and even at room temperature this type of entanglement is still very robust, especially for narrow CGNRs with the weak Coulomb repulsion...
November 2, 2016: Journal of Physics. Condensed Matter: An Institute of Physics Journal
Igor Farkaš, Radomír Bosák, Peter Gergeľ
Reservoir computing became very popular due to its potential for efficient design of recurrent neural networks, exploiting the computational properties of the reservoir structure. Various approaches, ranging from appropriate reservoir initialization to its optimization by training have been proposed. In this paper, we extend our previous work and focus on short-term memory capacity, introduced by Jaeger in case of echo state networks. Memory capacity has been previously shown to peak at criticality, when the network switches from a stable regime to an unstable dynamic regime...
November 2016: Neural Networks: the Official Journal of the International Neural Network Society
J D Hyman, J Jiménez-Martínez, H S Viswanathan, J W Carey, M L Porter, E Rougier, S Karra, Q Kang, L Frash, L Chen, Z Lei, D O'Malley, N Makedonska
Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nanometres to kilometres. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical and experimental efforts/methods. At the field scale, we use discrete fracture network modelling to simulate production of a hydraulically fractured well from a fracture network that is based on the site characterization of a shale gas reservoir...
October 13, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
Thomas C Halsey
The predominant technical challenge of the upstream oil and gas industry has always been the fundamental uncertainty of the subsurface from which it produces hydrocarbon fluids. The subsurface can be detected remotely by, for example, seismic waves, or it can be penetrated and studied in the extremely limited vicinity of wells. Inevitably, a great deal of uncertainty remains. Computational sciences have been a key avenue to reduce and manage this uncertainty. In this review, we discuss at a relatively non-technical level the current state of three applications of computational sciences in the industry...
October 13, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
Solomon Kibret, Jonathan Lautze, Matthew McCartney, Luxon Nhamo, G Glenn Wilson
BACKGROUND: Sub-Saharan Africa (SSA) has embarked on a new era of dam building to improve food security and promote economic development. Nonetheless, the future impacts of dams on malaria transmission are poorly understood and seldom investigated in the context of climate and demographic change. METHODS: The distribution of malaria in the vicinity of 1268 existing dams in SSA was mapped under the Intergovernmental Panel on Climate Change (IPCC) representative concentration pathways (RCP) 2...
2016: Malaria Journal
Philippe Vincent-Lamarre, Guillaume Lajoie, Jean-Philippe Thivierge
A large body of experimental and theoretical work on neural coding suggests that the information stored in brain circuits is represented by time-varying patterns of neural activity. Reservoir computing, where the activity of a recurrently connected pool of neurons is read by one or more units that provide an output response, successfully exploits this type of neural activity. However, the question of system robustness to small structural perturbations, such as failing neurons and synapses, has been largely overlooked...
September 2, 2016: Journal of Computational Neuroscience
Piotr Antonik, Francois Duport, Michiel Hermans, Anteo Smerieri, Marc Haelterman, Serge Massar
Reservoir computing is a bioinspired computing paradigm for processing time-dependent signals. The performance of its analog implementation is comparable to other state-of-the-art algorithms for tasks such as speech recognition or chaotic time series prediction, but these are often constrained by the offline training methods commonly employed. Here, we investigated the online learning approach by training an optoelectronic reservoir computer using a simple gradient descent algorithm, programmed on a field-programmable gate array chip...
August 26, 2016: IEEE Transactions on Neural Networks and Learning Systems
Vishal V R Nandigana, N R Aluru
In this article, we perform a computational investigation of a nanopore connected to external fluidic reservoirs of asymmetric geometries. The asymmetry between the reservoirs is achieved by changing the cross-sectional areas, and the reservoirs are designated as the micropore reservoir and macropore reservoir. When an electric field is applied, which is directed from the macropore towards the micropore reservoir, we observe local nonequilibrium chaotic current oscillations. The current oscillations originate at the micropore-nanopore interface owing to the local cascade of ions; we refer to this phenomenon as the "avalanche effects...
July 2016: Physical Review. E
Thuy Doan, Michael R Wilson, Emily D Crawford, Eric D Chow, Lillian M Khan, Kristeene A Knopp, Brian D O'Donovan, Dongxiang Xia, Jill K Hacker, Jay M Stewart, John A Gonzales, Nisha R Acharya, Joseph L DeRisi
BACKGROUND: Ocular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~50 % of presumed infectious uveitis cases. The objective of this study is to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis. METHODS: This is a proof-of-concept study, in which intraocular fluid samples were obtained from five subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology...
2016: Genome Medicine
Stefan L Frank, Hartmut Fitz
Prior language input is not lost but integrated with the current input. This principle is demonstrated by "reservoir computing": Untrained recurrent neural networks project input sequences onto a random point in high-dimensional state space. Earlier inputs can be retrieved from this projection, albeit less reliably so as more input is received. The bottleneck is therefore not "Now-or-Never" but "Sooner-is-Better."
January 2016: Behavioral and Brain Sciences
Stefan Widgren, Stefan Engblom, Pavol Bauer, Jenny Frössling, Ulf Emanuelson, Ann Lindberg
European Union legislation requires member states to keep national databases of all bovine animals. This allows for disease spread models that includes the time-varying contact network and population demographic. However, performing data-driven simulations with a high degree of detail are computationally challenging. We have developed an efficient and flexible discrete-event simulator SimInf for stochastic disease spread modelling that divides work among multiple processors to accelerate the computations. The model integrates disease dynamics as continuous-time Markov chains and livestock data as events...
2016: Veterinary Research
Yu-Chih Chiang, Hao-Hueng Chang, Ching-Ching Wong, Yi-Ping Wang, Yin-Lin Wang, Wen-Hsuan Huang, Chun-Pin Lin
OBJECTIVES: Vital pulp therapy aims to treat reversible pulpal injuries via protective dentinogenesis and to preserve more tooth structure. Mineral trioxide aggregate (MTA)-based capping materials demonstrate prolonged setting time increases the risk of pulpal infection during multi-visit treatment. Their non-degradable property occupies pulp space and limits dentin-pulp regeneration. This study reports an inorganic degradable biomaterial that presents a short initial setting time and acts as a growth factor reservoir to promote reparative dentinogenesis...
October 2016: Dental Materials: Official Publication of the Academy of Dental Materials
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