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The dataset contains the Shu-Talas Transboundary Basin shapefiles. The shapefiles are produced using the data from HydroSHEDS project that provides watershed delineations at a global scale. Shu-Talas Basin has two major rivers, Shu and Talas. Their boundary shapefiles are included separately. Very small sub-basins within the Shu-Talas Basin are merged and dissolved.
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Data used in the publication "Evaluating observer performance for dugong aerial surveys in turbid Northern Territory waters"
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We retrospectively investigated the efficacy and toxicity of NCA regimen in unresectable stage IIIC or IV melanoma patients who progressed on previous therapy. The NCA regimen consisted of nab-paclitaxel (260 mg/m2) and carboplatin(AUC=5) on day 1 and bevacizumab, 5 mg/kg IV every 2 weeks or endostatin 7.5mg/m2 days 1-14,Q28.
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The following datasets are the main OpenMC output files converted from dataframe to xlsx files. They are divided in the enrichment folder, where each salt has been parametrized over Li-6 enrichment fraction, and the mesh folder, where mesh results have been used for coming up with the cumulative curves over distance from the neutron source. Each folder contains a Python input as example of the model used.
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Datasets and R code used in the data analysis.
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Techno Stress and Coping Strategies
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The included tests were performed at McMaster University in Hamilton, Ontario, Canada by Dr. Phillip Kollmeyer (phillip.kollmeyer@gmail.com). If this data is utilized for any purpose, it should be appropriately referenced. -A brand new 3Ah LG HG2 cell was tested in an 8 cu.ft. thermal chamber with a 75amp, 5 volt Digatron Firing Circuits Universal Battery Tester channel with a voltage and current accuracy of 0.1% of full scale. these data are used in the design process of an SOC estimator using a deep feedforward neural network (FNN) approach. The data also includes a description of data acquisition, data preparation, development of an FNN example script. -Instructions for Downloading and Running the Script: 1-Select download all files from the Mendeley Data page (https://data.mendeley.com/datasets/cp3473x7xv/2). 2-The files will be downloaded as a zip file. Unzip the file to a folder, do not modify the folder structure. 3-Navigate to the folder with "FNN_xEV_Li_ion_SOC_EstimatorScript_March_2020.mlx" 4-Open and run "FNN_xEV_Li_ion_SOC_EstimatorScript_March_2020.mlx" 5-The matlab script should run without any modification, if there is an issue it's likely due to the testing and training data not being in the expected place. 6-The script is set by default to train for 50 epochs and to repeat the training 3 times. This should take 5-10 minutes to execute. 7-To recreate the results in the paper, set number of epochs to 5500 and number of repetitions to 10. -The test data, or similar data, has been used for some publications, including: [1] C. Vidal, P. Kollmeyer, M. Naguib, P. Malysz, O. Gross, and A. Emadi, “Robust xEV Battery State-of-Charge Estimator Design using Deep Neural Networks,” in Proc WCX SAE World Congress Experience, Detroit, MI, Apr 2020 [2] C. Vidal, P. Kollmeyer, E. Chemali and A. Emadi, "Li-ion Battery State of Charge Estimation Using Long Short-Term Memory Recurrent Neural Network with Transfer Learning," 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, MI, USA, 2019, pp. 1-6.
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Data on which the study is based
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It is the result of the questionnaires at the very beginning. The valid sample size is 200. Reliability: Cronbach α coefficient ranges from 0.7 to 0.9. Validity: KMO= 0.757. Common factor variance [CFA]> 0.7; Cumulative variance contribution [CVC] >80%. The convergent and divergent validity are both achieved. SEM & Hierachical regression 14 hypothesis have been proved to be obviously correlationship.
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In support of the manuscript by Bagley et al. (2020; see below) on quaking aspen phylogeography and ecological niche modeling (ENM), this accession provides 1) the in-house laboratory protocol used to extract DNA from aspen leaf tissues (modified from Strauss Lab); 2) the Supporting Information files for the corresponding manuscript (Bagley et al. 2020); 3) code used to conduct independent runs of the TASSEL-GBSv2 SNP discovery pipeline (Glaubitz et al. 2014) on our final (combined) genotyping-by-sequencing (GBS) dataset; 4) resulting SNP variant files from TASSEL-GBSv2 and final filtered variant call format (VCF) and genotype data files used during our genomic analyses; and 5) unfiltered vs filtered species occurrence data files and computer code used during our ENM analyses of our focal taxon, Populus tremuloides. REFERENCES Bagley, J. C., Heming, N. M., Gutiérrez, E. E., Devisetty, U. K., Mock, K. E., Eckert, A. J., & Strauss, S. H. (2020). Genotyping-by-sequencing and ecological niche modeling illuminate phylogeography, admixture, and Pleistocene range dynamics in quaking aspen (Populus tremuloides). Ecology and Evolution. Glaubitz, J. C., Casstevens, T. M., Lu, F., Harriman, J., Elshire, R. J., Sun, Q., & Buckler, E. S. (2014). TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline. PLoS One, 9(2): e90346
Data Types:
  • Software/Code
  • Geospatial Data
  • Tabular Data
  • Dataset
  • Document
  • Text
  • File Set
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