Displaying Dataset 51 - 75 of 260 in total

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2019 (80)
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published: 2020-02-12
 
The XSEDE program manages the database of allocation awards for the portfolio of advanced research computing resources funded by the National Science Foundation (NSF). The database holds data for allocation awards dating to the start of the TeraGrid program in 2004 to present, with awards continuing through the end of the second XSEDE award in 2021. The project data include lead researcher and affiliation, title and abstract, field of science, and the start and end dates. Along with the project information, the data set includes resource allocation and usage data for each award associated with the project. The data show the transition of resources over a fifteen year span along with the evolution of researchers, fields of science, and institutional representation.
keywords: allocations; cyberinfrastructure; XSEDE
published: 2019-12-03
 
These are the alignments of transcriptome data used for the analysis of members of Heteroptera. This dataset is analyzed in "Deep instability in the phylogenetic backbone of Heteroptera is only partly overcome by transcriptome-based phylogenomics" published in Insect Systematics and Diversity.
keywords: Heteroptera; Hemiptera; Phylogenomics; transcriptome
published: 2020-01-20
 
This datasets provide basis of our analysis in the paper - Revising the Ozone Depletion Potentials for Short-Lived Chemicals such as CF3I and CH3I. All datasets here are from the model output (CAM4-chem). All the simulations (background and perturbation) were run to steady-state and only the last year outputs used in analysis are archived here.
keywords: Illinois Data Bank; NetCDF; Ozone Depletion Potential; CF3I and CH3I
published: 2020-02-05
 
The Delt_Comb.NEX text file contains the original data used in the phylogenetic analyses of Zahniser & Dietrich, 2013 (European Journal of Taxonomy, 45: 1-211). The text file is marked up according to the standard NEXUS format commonly used by various phylogenetic analysis software packages. The file will be parsed automatically by a variety of programs that recognize NEXUS as a standard bioinformatics file format. The first nine lines of the file indicate the file type (Nexus), that 152 taxa were analyzed, that a total of 3971 characters were analyzed, the format of the data, and specification for two symbols used in the dataset. There are four datasets separated into blocks, one each for: 28S rDNA gene, Histone H3 gene, morphology, and insertion/deletion characters scored based on the alignment of the 28S rDNA dataset. Descriptions of the morphological characters and more details on the species and specimens included in the dataset are provided in the publication using this dataset. A text file, Delt_morph_char.txt, is available here that states the morphological characters and characters states that were scored in the Delt_Comb.NEX dataset. The original DNA sequence data are available from NCBI GenBank under the accession numbers indicated in publication. Chromatogram files for each sequencing read are available from the first author upon request.
keywords: phylogeny; DNA sequence; morphology; parsimony analysis; Insecta; Hemiptera; Cicadellidae; leafhopper; evolution; 28S rDNA; histone H3; bayesian analysis
planned publication date: 2020-12-01
 
This is the data set from the published manuscript 'Vertebrate scavenger guild composition and utilization of carrion in an East Asian temperate forest' by Inagaki et al.
keywords: Japan;Sika Deer
published: 2020-02-01
 
This data describes habitat use, availability, landscape level influences, and daily movement of dabbling ducks in the Wabash River Valley of southeastern Illinois and southwestern Indiana. It contains triangulated locations of individual ducks, associated habitat assignments of those locations, flood survey data to determine water availability, and randomly generated points to assess landscape level questions.
keywords: waterfowl; ducks; dabbling; mallard; teal; habitat
published: 2020-01-28
 
This dataset includes two data files that provide the time series (Jul. - Sep. 2017) data of sun-induced chlorophyll fluorescence (SIF_760) collected under sunny conditions at two maize sites (one rainfed and the other irrigated) in Nebraska in 2017. Data contain 392 SIF_760 records at the rainfed site and 707 records at the irrigated site. The timestamp uses local standard time. Data are available for the sunny conditions from 8 am to 5 pm (corresponding to 9 am to 6 pm local time) throughout the study period.
keywords: sun-induced chlorophyll fluorescence (SIF); maize; gross primary production(GPP); light use efficiency(LUE); SIF yield
published: 2020-01-27
 
Morphologic data of dunes in the World's big rivers. Morphologic descriptors for large dunes include: dune height, dune mean leeside angle, dune maximum leeside angle, dune wavelength, dune flow depth (at the crest), and the fractional height of the maximum slope on the leeside for each dune. Morphologic descriptors for small dunes include: dune height, dune mean leeside angle, dune maximum leeside angle, dune wavelength, and dune flow depth (at the crest).
keywords: dune; bedform; rivers; morphology;
planned publication date: 2020-12-12
 
Dataset associated with Jones et al FE-2019-01175 submission: Does the size and developmental stage of traits at fledging reflect juvenile flight ability among songbirds? Excel CSV files with all of the data used in analyses and file with descriptions of each column. The flight ability variable in this dataset was derived from fledgling drop tests, examples of which can be found in the related dataset: Jones, Todd M.; Benson, Thomas J.; Ward, Michael P. (2019): Flight Ability of Juvenile Songbirds at Fledgling: Examples of Fledgling Drop Tests. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2044905_V1.
keywords: body condition; fledgling; flight ability; locomotor ability; post-fledging; songbirds; wing development; wing emergence
published: 2020-01-08
 
These are abundance dynamics data and simulations for the paper "Higher-order interaction between species inhibits bacterial invasion of a phototroph-predator microbial community" .
keywords: Microbial community; Higher order interaction; Invasion; Algae; Bacteria; Ciliate
published: 2019-12-22
 
Dataset providing calculation of a Competition Index (CI) for Late Pleistocene carnivore guilds in Laos and Vietnam and their relationship to humans. Prey mass spectra, Prey focus masses, and prey class raw data can be used to calculate the CI following Hemmer (2004). Mass estimates were calculated for each species following Van Valkenburgh (1990). Full citations to methodological papers are included as relationships with other resources
keywords: competition; Southeast Asia; carnivores; humans
published: 2019-12-20
 
This dynamic photosynthesis model of soybean canopy is developed by Yu Wang (yuwangcn@illinois.edu), IGB, University of Illinois. If you want to know more details, please check the following publication Yu Wang, Steven J. Burgess, Elsa de Becker, Stephen P. Long. Photosynthesis in the fleeting shadows: An overlooked opportunity for increasing crop productivity? The Plant Journal.
keywords: Matlab; Soybean canopy; photosynthesis model
published: 2019-12-17
 
This dataset provides the raw data, code and related figures for the paper, "Channel Activation of CHSH Nonlocality"
keywords: Super-activation; Non-locality breaking channel
published: 2019-12-12
 
This dataset contains gamma-ray spectra templates for a source interdiction and uranium enrichment measurement task. This dataset also contains Keras machine learning models trained using datasets created using these templates.
keywords: gamma-ray spectroscopy; neural networks; machine learning; isotope identification; uranium enrichment; sodium iodide; NaI(Tl)
published: 2019-12-10
 
The dataset consists of two types of data: the estimate of land productivity (the maximum productivity, MP) and the estimate of land that has low productivity for any major crops planted in the Contiguous United States and then may be available for growing bioenergy crops (the marginal land, ML). All data items are in GeoTiff format, under the World Geodetic System (WGS) 84 project, and with a resolution of 0.0020810045 degree (~250 m). The MP values are calculated based on machine learning model estimated yields of major crops in the CONUS, and its expected value (MP_mean.tif), and associated uncertainty (MP_IDP.tif). The ML availability data have two versions: a deterministic version and a version with uncertainty. The deterministic MLs are determined as the land pixels with expected MP values falling in the range defined in the following criteria, and the MLs with uncertainty are determined as the probability that the MP value of a land pixel falls in the range defined in the following criteria: Criteria_____Description S1________ Current crop and pasture land with MP <= P50 S2________ Current crop and pasture land with MP <= P25 S3________ S1 + current grass and shrub land with P25 < MP < P50 S4________ S2 + current grass and shrub land with P10 < MP < P25 Economic__ Current crop and pasture land with potential profitability < 0 Here P10, P25 and P50 are the 10th, 25th and 50th percentile of crop MP values
keywords: Land productivity;marginal land;land use
published: 2019-12-03
 
This is the data set associated with the manuscript titled "Extensive host-switching of avian feather lice following the Cretaceous-Paleogene mass extinction event." Included are the gene alignments used for phylogenetic analyses and the cophylogenetic input files.
keywords: phylogenomics, cophylogenetics, feather lice, birds
published: 2019-11-18
 
VCF files used to analyze a novel filtering tool VEF, presented in the article "VEF: a Variant Filtering tool based on Ensemble methods".
keywords: VCF files; filtering; VEF
published: 2019-10-27
 
This dataset accompanies the paper "STREETS: A Novel Camera Network Dataset for Traffic Flow" at Neural Information Processing Systems (NeurIPS) 2019. Included are: *Over four million still images form publicly accessible cameras in Lake County, IL. The images were collected across 2.5 months in 2018 and 2019. *Directed graphs describing the camera network structure in two communities in Lake County. *Documented non-recurring traffic incidents in Lake County coinciding with the 2018 data. *Traffic counts for each day of images in the dataset. These counts track the volume of traffic in each community. *Other annotations and files useful for computer vision systems. Refer to the accompanying "readme.txt" or "readme.pdf" for further details.
keywords: camera network; suburban vehicular traffic; roadways; computer vision
published: 2019-10-16
 
Human annotations of randomly selected judged documents from the AP 88-89, Robust 2004, WT10g, and GOV2 TREC collections. Seven annotators were asked to read documents in their entirety and then select up to ten terms they felt best represented the main topic(s) of the document. Terms were chosen from among a set sampled from the document in question and from related documents.
keywords: TREC; information retrieval; document topicality; document description
published: 2019-10-05
 
This dataset contains collected and aggregated network information from NCSA’s Blue Waters system, which is comprised of 27,648 nodes connected via Cray Gemini* 3D torus (dimension 24x24x24) interconnect, from Jan/01/2017 to May/31/2017. Network performance counters for links are exposed via Cray's gpcdr (<a href="https://github.com/ovis-hpc/ovis/wiki/gpcdr-kernel-module">https://github.com/ovis-hpc/ovis/wiki/gpcdr-kernel-module</a>) kernel module. Lightweight Distributed Metric Service ([LDMS](<a href="https://github.com/ovis-hpc/ovis">https://github.com/ovis-hpc/ovis</a>)) is used to sampled the performance counters at 60 second intervals. Please read "README.md" file. <b>Acknowledgement:</b> This dataset is collected as a part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications.
keywords: HPC; Interconnect; Network; Congestion; Blue Waters; Dataset
published: 2019-11-12
 
We are sharing the tweet IDs of four social movements: #BlackLivesMatter, #WhiteLivesMatter, #AllLivesMatter, and #BlueLivesMatter movements. The tweets are collected between May 1st, 2015 and May 30, 2017. We eliminated the location to the United States and focused on extracting the original tweets, excluding the retweets. Recommended citations for the data: Rezapour, R. (2019). Data for: How do Moral Values Differ in Tweets on Social Movements?. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9614170_V1 and Rezapour, R., Ferronato, P., and Diesner, J. (2019). How do moral values differ in tweets on social movements?. In 2019 Computer Supported Cooperative Work and Social Computing Companion Publication (CSCW’19 Companion), Austin, TX.
keywords: Twitter; social movements; black lives matter; blue lives matter; all lives matter; white lives matter
published: 2019-10-23
 
Raw MD simulation trajectory, input and configuration files, SEM current data, and experimental raw data accompanying the publication, "Electrical recognition of the twenty proteinogenic amino acids using an aerolysin nanopore". README.md contains a description of all associated files.
keywords: molecular dynamics; protein sequencing; aerolysin; nanopore sequencing
published: 2019-10-22
 
We summarize peer reviewed literature reporting associations between for three soil quality indicators (SQIs) (β-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) and crop yield and greenhouse gas emissions. Peer-reviewed articles published between January of 1990 and May 2018 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: “β-glucosidase”, “permanganate oxidizable carbon”, “active carbon”, “readily oxidizable carbon”, or “fluorescein diacetate hydrolysis”, together with one or more of the following: “crop yield”, “productivity”, “greenhouse gas’, “CO2”, “CH4”, or “N2O”. Meta-data for records include the following descriptor variables and covariates useful for scoring function development: 1) identifying factors for the study site (location, duration of the experiment), 2) soil textural class, pH, and SOC, 3) depth of soil sampling, 4) units used in published works (i.e.: equivalent mass, concentration), 5) SQI abundances and measured ecosystem functions, and 6) summary statistics for correlation between SQIs and functions (yield and greenhouse gas emissions). *Note: Blank values in tables are considered unreported data.
keywords: Soil health promoting practices; Soil quality indicators; β-glucosidase; fluorescein diacetate hydrolysis; Permanganate oxidizable carbon; Greenhouse gas emissions; Scoring curves; Soil Management Assessment Framework
published: 2019-10-22
 
Dataset compiled by Yushu Xia and Michelle Wander for the Soil Health Institute. Data were recovered from peer reviewed literature reporting results for three soil quality indicators (SQIs) (β-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) in terms of their relative response to management where soils under grassland cover, no-tillage, cover crops, residue return and organic amendments were compared to conventionally managed controls. Peer-reviewed articles published between January of 1990 and May 2018 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: “β-glucosidase”, “permanganate oxidizable carbon”, “active carbon”, “readily oxidizable carbon”, and “fluorescein diacetate hydrolysis”, together with one or more of the following: “management practice”, “tillage”, “cover crop”, “residue”, “organic fertilizer”, or “manure”. Records were tabulated to compare SQI abundance in soil maintained under a control and soil aggrading practice with the intent to contribute to SQI databases that will support development of interpretive frameworks and/or algorithms including pedo-transfer functions relating indicator abundance to management practices and site specific factors. Meta-data include the following key descriptor variables and covariates useful for development of scoring functions: 1) identifying factors for the study site (location, year of initiation of study and year in which data was reported), 2) soil textural class, pH, and SOC, 3) depth and timing of soil sampling, 4) analytical methods for SQI quantification, 5) units used in published works (i.e. equivalent mass, concentration), 6) SQI abundances, and 7) statistical significance of difference comparisons. *Note: Blank values in tables are considered unreported data.
keywords: Soil health promoting practices; Soil quality indicators; β-glucosidase; fluorescein diacetate hydrolysis; Permanganate oxidizable carbon; Greenhouse gas emissions; Scoring curves; Soil Management Assessment Framework
published: 2019-10-19
 
Large, distributed microphone arrays could offer dramatic advantages for audio source separation, spatial audio capture, and human and machine listening applications. This dataset contains acoustic measurements and speech recordings from 10 loudspeakers and 160 microphones spread throughout a large, reverberant conference room. The distributed microphone system contains two types of array: four wearable microphone arrays of 16 sensors each placed near the ears and across the upper body, and twelve tabletop arrays of 8 microphones each in enclosures designed to resemble voice-assistant speakers. The dataset includes recordings of chirps that can be used to measure impulse responses and of speech clips derived from the CSTR VCTK corpus. The speech clips are recorded both individually and as a mixture to support source separation experiments. The uncompressed files are about 13.4 GB.
keywords: microphone arrays; audio source separation; augmented listening; wireless sensor networks