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JerrySiRi

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SWN_Bert_based_2014_2018_100

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[ { "contexts": [ "Twenty-three patients with FGDS and 22 healthy controls (HC) were examined with a Logiq E9 scanner in a fasting state. " ], "name": "Logiq E9 scanner" } ]

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[ { "contexts": [ "Using near-infrared spectroscopy (NIRS), we measured the hemodynamic responses in the prefrontal and superior temporal cortical surface areas during a working memory task. " ], "name": "NIRS" } ]

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[ { "contexts": [ "The first approach is based on the finite volume compositional (i.e., water, radon, air) transport model TOUGH2/EOS7Rn (Transport Of Unsaturated Groundwater and Heat version 2/Equation Of State 7 for Radon; Saâdi et al., 2014), while the second one is based on the finite difference one-component (i.e., radon) transport model TRACI (Transport de RAdon dans la Couche Insaturée; Ferry et al., 2001). " ], "name": "TOUGH2/EOS7Rn" }, { "contexts": [ "The first approach is based on the finite volume compositional (i.e., water, radon, air) transport model TOUGH2/EOS7Rn (Transport Of Unsaturated Groundwater and Heat version 2/Equation Of State 7 for Radon; Saâdi et al., 2014), while the second one is based on the finite difference one-component (i.e., radon) transport model TRACI (Transport de RAdon dans la Couche Insaturée; Ferry et al., 2001). ", "Transient simulations during six months of variable rainfall and atmospheric air pressure showed that the model TRACI usually overestimates both measured radon exhalation rate and concentration. ", "However, on average, the radon exhalation rate calculated by EOS7Rn was 34% less than that was calculated by TRACI, and much closer to the measured one for physically-based soil radon diffusion models. ", "Unlike TRACI, EOS7Rn was able to simulate qualitatively seasonal variations of both radon exhalation and concentration. ", "These results show that EOS7Rn produces less numerical errors than TRACI, and can be considered as a promising model for predicting radon transport in the landfill, if soil evaporation is modelled and its numerical inversion for parameter estimation is realized." ], "name": "TRACI" } ]

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[ { "contexts": [ "In this study, the known peptidoglycan hydrolases were divided into multiple classes based on their site of action and were used for the development of a computational tool 'HyPe' for identification and classification of novel peptidoglycan hydrolases from genomic and metagenomic data. ", "Random Forest multiclass model was selected for the development of HyPe tool as it showed up to 71.12 % sensitivity, 99.98 % specificity, 99.55 % accuracy and 0.80 MCC in four different classes of peptidoglycan hydrolases. ", "The ability of HyPe to identify novel peptidoglycan hydrolases was also demonstrated on 24 metagenomic datasets.\n\n\n", "http://metagenomics.iiserb.ac.in/hype/ and http://metabiosys.iiserb.ac.in/hype/ ." ], "name": "HyPe" }, { "contexts": [ "Various classification models were developed using amino acid and dipeptide composition features by training and optimization of Random Forest and Support Vector Machines. ", "Random Forest multiclass model was selected for the development of HyPe tool as it showed up to 71.12 % sensitivity, 99.98 % specificity, 99.55 % accuracy and 0.80 MCC in four different classes of peptidoglycan hydrolases. " ], "name": "Random Forest" }, { "contexts": [ "Various classification models were developed using amino acid and dipeptide composition features by training and optimization of Random Forest and Support Vector Machines. " ], "name": "Support Vector Machines" } ]

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[ { "contexts": [ "The DNAm profile (Illumina 450K array) of cord blood (n = 7) derived nRBCs was compared with B cells, CD4 and CD8 T cells, natural killer cells, granulocytes, monocytes and placenta (n = 5).\n\n\n" ], "name": "Illumina 450K array" } ]

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[ { "contexts": [ "Exploratory Analysis of Biological Networks through Visualization, Clustering, and Functional Annotation in Cytoscape. ", "The visualization procedure described here relies on the open-source network visualization software Cytoscape and includes detailed instructions on formatting and loading the data, clustering networks, and overlaying functional annotations." ], "name": "Cytoscape" } ]

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[ { "contexts": [ "[Structural Analysis and Optimization Performance Forecast of SiO2-Based Phase Change and Humidity Storage Composite Materials with Fourier Transform Infrared Spectrum]. ", "Composition structure of SiO2-based phase change and humidity storage composite materials were tested by Fourier transform infrared spectrum to analyze chimeric mechanism of SiO2 and fatty acid. " ], "name": "Fourier transform infrared spectrum" }, { "contexts": [ "Characteristic FTIR absorption peaks of SiO2-based phase change and humidity storage composite materials were considered as input layer; different fatty acid content of SiO2-based phase change and humidity storage composite materials, average values of absorption equilibrium moisture content and desorption equilibrium moisture content of SiO2-based phase change and humidity storage composite materials with relative humidity as 52.89%, and cooling time from 30 to 15 ℃ of SiO2-based phase change and humidity storage composite materials were seen as output layer respectively; S activation function was treated as hidden layer; then, optimization performance forecast model of SiO2-based phase change and humidity storage composite materials with structural parameters and phase change and humidity storage comprehensive performance was established by back-propagation neural network. " ], "name": "back-propagation neural network" } ]

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