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Reservoir computing

Seiyed Mossa Hosseini, Behzad Ataie-Ashtiani
In this study, two conceptual models, the classic reservoir (CR) model and exchange reservoirs model embedded by dual porosity approach (DPR) are developed for simulation of karst aquifer functioning drained by multiple outlets. The performances of two developed models are demonstrated at a less developed karstic aquifer with three spring outlets located in Zagros Mountain in the south-west of Iran using 22-years of daily data. During the surface recharge, a production function based on water mass balance is implemented for computing the time series of surface recharge to the karst formations...
February 16, 2017: Ground Water
Ingrid Keupers, Patrick Willems
Modern, model based river quality management strongly relies on river water quality models to simulate the temporal and spatial evolution of pollutant concentrations in the water body. Such models are typically constructed by extending detailed hydrodynamic models with a component describing the advection-diffusion and water quality transformation processes in a detailed, physically based way. This approach is too computational time demanding, especially when simulating long time periods that are needed for statistical analysis of the results or when model sensitivity analysis, calibration and validation require a large number of model runs...
February 1, 2017: Water Research
Romain Modeste Nguimdo, Eric Lacot, Olivier Jacquin, Olivier Hugon, Guy Van der Sande, Hugues Guillet de Chatellus
Reservoir computing (RC) systems are computational tools for information processing that can be fully implemented in optics. Here, we experimentally and numerically show that an optically pumped laser subject to optical delayed feedback can yield similar results to those obtained for electrically pumped lasers. Unlike with previous implementations, the input data are injected at a time interval that is much larger than the time-delay feedback. These data are directly coupled to the feedback light beam. Our results illustrate possible new avenues for RC implementations for prediction tasks...
February 1, 2017: Optics Letters
Francesco Asnicar, Serena Manara, Moreno Zolfo, Duy Tin Truong, Matthias Scholz, Federica Armanini, Pamela Ferretti, Valentina Gorfer, Anna Pedrotti, Adrian Tett, Nicola Segata
The gut microbiome becomes shaped in the first days of life and continues to increase its diversity during the first months. Links between the configuration of the infant gut microbiome and infant health are being shown, but a comprehensive strain-level assessment of microbes vertically transmitted from mother to infant is still missing. We collected fecal and breast milk samples from multiple mother-infant pairs during the first year of life and applied shotgun metagenomic sequencing followed by computational strain-level profiling...
January 2017: MSystems
Vincent C Müller, Matej Hoffmann
The contribution of the body to cognition and control in natural and artificial agents is increasingly described as "offloading computation from the brain to the body," where the body is said to perform "morphological computation." Our investigation of four characteristic cases of morphological computation in animals and robots shows that the "offloading" perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word...
January 31, 2017: Artificial Life
Osman Yeşilbaş, Esra Şevketoğlu, Hasan Serdar Kıhtır, Mey Talip Petmezci, Elif Bato, Seda Balkaya, Nevin Hatipoğlu, Mert Ahmet Kuşkucu, Figen Palabıyık, Erkan Çakır
Human metapneumovirus (hMPV), formerly classified in Paramyxoviridae family is now moved into Pneumoviridae, which was described as a novel family. It causes upper and lower respiratory tract infections (LRTIs) usually in children younger than five years old. The recent epidemiological studies indicated that hMPV is the second most frequently detected virus in LRTIs of young children, following the respiratory syncytial virus (RSV). Bronchiolitis obliterans (BO) is a chronic obstructive lung disease characterized by fibrosis of the distal respiratory airways...
October 2016: Mikrobiyoloji Bülteni
Shu-Jing Gao, Hua-Hua Cao, Yu-Ying He, Yu-Jiang Liu, Xiang-Yu Zhang, Guo-Jing Yang, Xiao-Nong Zhou
BACKGROUND: Motivated by the first mathematical model for schistosomiasis proposed by Macdonald and Barbour's classical schistosomiasis model tracking the dynamics of infected human population and infected snail hosts in a community, in our previous study, we incorporated seasonal fluctuations into Barbour's model, but ignored the effect of bovine reservoir host in the transmission of schistosomiasis. Inspired by the findings from our previous work, the model was further improved by integrating two definitive hosts (human and bovine) and seasonal fluctuations, so as to understand the transmission dynamics of schistosomiasis japonica and evaluate the ongoing control measures in Liaonan village, Xingzi County, Jiangxi Province...
January 25, 2017: Parasites & Vectors
Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi
In this paper, we elaborate over the well-known interpretability issue in echo-state networks (ESNs). The idea is to investigate the dynamics of reservoir neurons with time-series analysis techniques developed in complex systems research. Notably, we analyze time series of neuron activations with recurrence plots (RPs) and recurrence quantification analysis (RQA), which permit to visualize and characterize high-dimensional dynamical systems. We show that this approach is useful in a number of ways. First, the 2-D representation offered by RPs provides a visualization of the high-dimensional reservoir dynamics...
December 2, 2016: IEEE Transactions on Neural Networks and Learning Systems
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
Thomas Plehn, Volkhard May
The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented...
January 21, 2017: Journal of Chemical Physics
Daniel A McCurry, Ryan C Bailey
Nanopores, and nanoporous materials in general, are interesting for applications in chemical and biomolecular transport as pore sizes are on the same scale as the dimension of many (bio)chemical species. Many studies have focused on either single pores or small arrays of cylindrical pores, which are convenient in terms of their amenability toward computational modeling of transport phenomenon. However, the limited overall porosity may inhibit transport flux as well as the eventual implementation of these materials as active separation elements...
February 3, 2017: Langmuir: the ACS Journal of Surfaces and Colloids
Ryan Pyle, Robert Rosenbaum
Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework...
January 6, 2017: Physical Review Letters
Yomna E Saleh, Mohamed A Gepreel, Nageh K Allam
Different strategies have been investigated to allow for optimum duration and conditions for endothelium healing through the enhancement of coronary stents. In this study, a nanoarchitectured system is proposed as a surface modification for drug eluting stents. Highly oriented nanotubes were vertically grown on the surface of a new Ni-free biocompatible Ti-based alloy, as a potential material for self-expandable stents. The fabricated nanotubes were self-grown from the potential stent substrate, which are also proposed to enhance endothelial proliferation while acting as drug reservoir to hinder Vascular Smooth Muscle Cells (VSMC) proliferation...
January 12, 2017: Scientific Reports
Anna V Abramova, Vladimir O Abramov, Vadim M Bayazitov, Roman V Nikonov
The regeneration of water wells is an urgent problem nowadays, when drilling of new wells becomes more and more expensive. Formation damage leads to a reduction of the formation's permeability and/or pore volume which in turn inhibits the ability of the water to flow from the reservoir formation into the wellbore. A new technology that uses high-power ultrasound to remove formation damage of water wells has been developed. The effectiveness of regeneration of wells can be enhanced if ultrasound and shockwaves are used during the same treatment...
May 2017: Ultrasonics Sonochemistry
S Graves, B Cox, M Farhoud, H Valdovinos, J Jeffery, K Eliceiri, T Barnhart, R Nickles
PURPOSE: To design a linearly-filled Derenzo positron emission tomography (PET) phantom, eliminating the extraneous radioisotope volumes in a conventional reservoir-type design. This activity reduction combined with the elimination of bubbles in smaller phantom channels would significantly reduce personnel dose, radioisotope cost, and would improve image quality by reducing out-of-slice activity scatter. METHODS: A computer-aided design (CAD) was created of a modular Derenzo phantom consisting of three phantom layers with gaskets between the layers...
June 2016: Medical Physics
James M Salter, Daniel Williamson
Expensive computer codes, particularly those used for simulating environmental or geological processes, such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power...
December 2016: Environmetrics
Mojtaba G Mahmoodlu, Elizabeth M Pontedeiro, Jesús S Pérez Guerrero, Amir Raoof, S Majid Hassanizadeh, Martinus Th van Genuchten
In this study we performed batch experiments to investigate the dissolution kinetics of trichloroethylene (TCE) and toluene vapors in water at room temperature and atmospheric pressure. The batch systems consisted of a water reservoir and a connected headspace, the latter containing a small glass cylinder filled with pure volatile organic compound (VOC). Results showed that air phase concentrations of both TCE and toluene increased relatively quickly to their maximum values and then became constant. We considered subsequent dissolution into both stirred and unstirred water reservoirs...
January 2017: Journal of Contaminant Hydrology
Carlo Cafaro, Sean Alan Ali
We investigate the maximum caliber variational principle as an inference algorithm used to predict dynamical properties of complex nonequilibrium, stationary, statistical systems in the presence of incomplete information. Specifically, we maximize the path entropy over discrete time step trajectories subject to normalization, stationarity, and detailed balance constraints together with a path-dependent dynamical information constraint reflecting a given average global behavior of the complex system. A general expression for the transition probability values associated with the stationary random Markov processes describing the nonequilibrium stationary system is computed...
November 2016: Physical Review. E
Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi
In this paper, we elaborate over the well-known interpretability issue in echo-state networks (ESNs). The idea is to investigate the dynamics of reservoir neurons with time-series analysis techniques developed in complex systems research. Notably, we analyze time series of neuron activations with recurrence plots (RPs) and recurrence quantification analysis (RQA), which permit to visualize and characterize high-dimensional dynamical systems. We show that this approach is useful in a number of ways. First, the 2-D representation offered by RPs provides a visualization of the high-dimensional reservoir dynamics...
December 2, 2016: IEEE Transactions on Neural Networks and Learning Systems
Clemens Schäfermeier, Hugo Kerdoncuff, Ulrich B Hoff, Hao Fu, Alexander Huck, Jan Bilek, Glen I Harris, Warwick P Bowen, Tobias Gehring, Ulrik L Andersen
Laser cooling is a fundamental technique used in primary atomic frequency standards, quantum computers, quantum condensed matter physics and tests of fundamental physics, among other areas. It has been known since the early 1990s that laser cooling can, in principle, be improved by using squeezed light as an electromagnetic reservoir; while quantum feedback control using a squeezed light probe is also predicted to allow improved cooling. Here we show the implementation of quantum feedback control of a micro-mechanical oscillator using squeezed probe light...
November 29, 2016: Nature Communications
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