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Chen, Bowen; Gramig, Benjamin; Yun, Seong (2021): Data for Conservation Tillage Mitigates Drought Induced Soybean Yield Losses in the US Corn Belt. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9179636_V1
Data files and R code to replicate the econometric analysis in the journal article: B Chen, BM Gramig and SD Yun. “Conservation Tillage Mitigates Drought Induced Soybean Yield Losses in the US Corn Belt.” Q Open. https://doi.org/10.1093/qopen/qoab007
R, Conservation Tillage, Drought, Yield, Corn, Soybeans, Resilience, Climate Change
Kim, Hyunbin; Makhnenko, Roman (2022): Data on "Evaluation of CO2 sealing potential of heterogeneous Eau Claire shale". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5509498_V1
This dataset is provided to support the statements in Kim, H., and R.Y. Makhnenko. 2022. "Evaluation of CO2 sealing potential of heterogeneous Eau Claire shale". Journal of the Geological Society. In geologic carbon dioxide (CO2) storage in deep saline aquifers, buoyant CO2 tends to float upwards in the reservoirs overlaid by low permeable formations called caprocks. Caprocks should serve as barriers to potential CO2 leakage that can happen through a diffusion loss and permeation through faults, fractures, or pore spaces. The leakage through intact caprock would mainly depend on its permeability and CO2 breakthrough pressure, and is affected by the heterogeneities in the material. Here, we study the sealing potential of a caprock from Illinois Basin - Eau Claire shale, with sandy and shaly fractions distinguished via electron microscopy and grain/pore size and surface area characterization. The direct measurements of permeability of sandy shale provides the values ~ 10-15 m2, while clayey specimens are three orders of magnitude less permeable. The CO2 breakthrough pressure under in-situ stress conditions is 0.1 MPa for the sandy shale and 0.4 MPa for the clayey counterpart – these values are higher than those predicted by the porosimetry methods performed on the unconfined specimens. Sandy Eau Claire shale would allow penetration of large CO2 volumes at low overpressures, while the clayey formation can serve as a caprock in the absence of faults and fractures in it.
Geologic carbon storage; Caprock; Shale; CO2 breakthrough pressure; Porosimetry.
Crawford, Reed D.; Dodd, Luke E.; Tillman, Frank E.; O'Keefe, Joy M. (2022): Data for Evaluating bat boxes: Design and placement alter bioenergetic costs and overheating risk. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3592866_V1
This dataset contains our bi-hourly temperature recordings from 40 rocket box style artificial roosts of 5 designs deployed in Indiana and Kentucky, USA from April through September 2019. This dataset also includes our endothermic and faculatively heterothermic daily energy expenditure datasets used in our bioenergetic analysis, which were calculated from the bi-hourly rocket box temperature data. Lastly, we include our overheating counts dataset which summarizes daily overheating events (i.e., temperatures > 40 Celsius) in each rocket box style bat box over the course of the study period, these daily summaries were also calculated from the bi-hourly rocket box temperature recordings.
artificial roost; bat box; microcllimate; temperature
Tiemann, Jeremy S.; Stodola, Alison P.; Douglass, Sarah A.; Vinsel, Rachel M.; Cummings, Kevin S. (2022): Dataset associated with Nonindigenous Aquatic Mollusks in Illinois manuscript. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8947838_V1
This dataset is associated with a larger manuscript published in 2022 in the Illinois Natural History Survey Bulletin to summarize all known records for nonindigenous aquatic mollusks in Illinois, and full sources are referenced within the manuscript. We examined museum holdings, literature accounts, publicly available databases sponsored by the U.S. Geological Survey (USGS) - Nonindigenous Aquatic Species program (http://nas.er.usgs.gov/.) and InvertEBase (invertebase.org). We also included sporadic field survey data of encounters of nonindigenous aquatic species from colleagues within the Illinois Natural History Survey, Illinois Department of Natural Resources, U.S. Fish and Wildlife Service, county forest preserve districts, and other natural resource agencies about their encounters with nonindigenous aquatic mollusk species. Lastly, we examined the role and utility of citizen-science data to document occurrences of nonindigenous aquatic mollusk species. We queried iNaturalist (www.inaturalist.org) for all available nonindigenous freshwater mollusk data for Illinois. Table heading descriptions (if not intuitive) are: “INHS verified” is whether an INHS staff member verified the record by observing vouchered specimen or photograph; “Source” is where a record was accessed or obtained; “individualCount” is number collected or observed in a record; “MuseumCode” is standard museum abbreviation or acronym; “Institution” is source that housed or reported a record, and this also includes the spelled-out museum code; “Collectors” typically indicates who collected the specimen or voucher; “Lat_Long determined by” denotes whether collection coordinates were stated by the collector or by a curator (using inference from data available); “fieldNumber” typically indicates a unique field number that a collector may have used in the field; “identifiedBy” typically explains who identified a specimen or verified a specimen identification.
Illinois; Exotic species; Non-native aquatic species; NAS; Aquatic Invasive Species; AIS; Mollusk
Cao, Yanghui; Dietrich, Christopher H.; Kits, Joel; Dmitriev, Dmitry A.; Xu, Ye; Huang, Min (2023): Datasets for Phylogenomics of microleafhoppers (Hemiptera: Cicadellidae: Typhlocybinae): morphological evolution, divergence times and biogeography. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8636195_V1
The following files were used to reconstruct the phylogeny of the leafhopper subfamily Typhlocybinae, using IQ-TREE v1.6.12 and ASTRAL v 4.10.5. <b>1) Taxon_sampling.csv:</b> contains the sample IDs (1st column) and the taxonomic information (2nd column). Sample IDs were used in the alignment files and partition files. <b>2) concatenated_nt_complete.phy:</b> a complete concatenated nucleotide dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12. The file lists the sequences of 248 samples with 154,992 nucleotide positions (intron included) from 665 loci. Hyphens are used to represent gaps. <b>3) concatenated_nt_complete_partition.nex:</b> the partitioning schemes for concatenated_nt_complete.phy. The file partitions the 154,992 nucleotide characters into 426 character sets, and defines the best substitution model for each character set. <b>4) concatenated_cds_complete.phy:</b> a complete concatenated coding DNA sequence dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12. The file lists the sequences of 248 samples with 153,525 nucleotide positions (intron excluded) from 665 loci. Hyphens are used to represent gaps. <b>5) concatenated_cds_complete_partition.nex:</b> the partitioning schemes for concatenated_cds_complete.phy. The file partitions the 153,525 nucleotide characters into 426 character sets, and defines the best substitution model for each character set. <b>6) concatenated_nt_reduced.phy:</b> a reduced concatenated nucleotide dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12. The file lists the sequences of 248 samples with 95,076 nucleotide positions (intron included) from 374 loci. Hyphens are used to represent gaps. <b>7) concatenated_nt_reduced_partition.nex:</b> the partitioning schemes for concatenated_nt_reduced.phy. The file partitions the 95,076 nucleotide characters into 312 character sets, and defines the best substitution model for each character set. <b>8) concatenated_aa_complete.phy:</b> a complete concatenated amino acid dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12, corresponding to concatenated_cds_complete.phy. The file lists the sequences of 248 samples with 51,175 amino acid positions from 665 loci. Hyphens are used to represent gaps. <b>9) concatenated_aa_complete_partition.nex:</b> the partitioning schemes for concatenated_aa_complete.phy. The file partitions the 51,175 amino acid characters into 426 character sets, and defines the best substitution model for each character set. <b>10) concatenated_aa_reduced.phy:</b> a reduced concatenated amino acid dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12, corresponding to concatenated_nt_reduced.phy. The file lists the sequences of 248 samples with 31,384 amino acid positions from 374 loci. Hyphens are used to represent gaps. <b>11) concatenated_aa_reduced_partition.nex:</b> the partitioning schemes for concatenated_aa_reduced.phy. The file partitions the 31,384 amino acid characters into 312 character sets, and defines the best substitution model for each character set. <b>12) Individual_gene_alignment.zip:</b> contains 426 FASTA files, each one is an alignment for a gene. Hyphens are used to represent gaps. These files were used to construct gene trees using IQ-TREE v1.6.12, followed by multispecies coalescent analysis using ASTRAL v 4.10.5 based the consensus trees with a minimum average bootstrap value of 70.
Auchenorrhyncha, Cicadomorpha, Membracoidea, anchored hybrid enrichment
Vargas, Fabio (2021): Mesospheric gravity wave activity estimated via airglow imagery, multistatic meteor radar, and SABER data taken during the SIMONe–2018 campaign. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8585682_V1
Airglow images and Meteor radar data used in the paper "Mesospheric gravity wave activity estimated via airglow imagery, multistatic meteor radar, and SABER data taken during the SIMONe–2018 campaign".
airglow; meteor radar; gravity waves; momentum flux;
Barker, Louise; Gaulke, Sarah M.; Chace, Jordyn Z.; Davis, Mark A.; Niemiller, Matthew L.; Taylor, Steven J.; Schuett, Gordon W. (2020): Video: Agkistrodon contortrix combat behavior. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9209722_V1
Video recorded by Louise Barker using a Cannon Powershot camera documents late-season combat behavior in Agkistrodon contortrix. Recorded in Beaufort County, North Carolina, 11.1 km SE of downtown Washington on 21 October 2020.
Agkistrodon contortrix; combat; mating; reproduction; copperhead; pit viper; Viperidae;
Sashittal, Palash; Zhang, Chuanyi; El-Kebir, Mohammed (2020): Simulation Data for JUMPER: Discontinuous Transcript Assembly in SARS-CoV-2. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6667667_V1
This data contains bam files and transcripts in the simulated instances generated for the paper 'JUMPER: Discontinuous Transcript Assembly in SARS-CoV-2' submitted for RECOMB 2021. The folder 'bam' contained the simulated bam files aligned using STAR wile the reads were generated using the method polyester Note: in the readme file, close to the end of the document, please ignore this sentence: 'Those files can be opened by using [name of software].'
transcript assembly; SARS-CoV-2; discontinuous transcription; coronaviruses
Warner, Genoa R; Pacyga, Diana; Strakovsky, Rita; Smith, Rebecca; James-Todd, Tamarra; Williams, Paige; Hauser, Russ; Meling, Daryl; Li, Lucas; Flaws, Jodi (2020): Phthalates and Hot Flashes SI. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9238850_V1
Supporting information for "Urinary Phthalate Metabolite Concentrations and Hot Flashes in Pre- and Perimenopausal Women from the Midlife Women’s Health Study." This file contains tables of the results of stratified analyses of the associations of hot flash outcomes with urinary phthalates metabolites by menopause status, race/ethnicity, body mass index, and depressive status. This file also contains supplementary HPLC methods for the analysis of phthalate metabolites.
Hot flashes; menopause; phthalates; women
Miller, Andrew; Raudabaugh, Daniel (2020): Data from Species Distribution, Phylogenetic Structure, and Functional Roles of Detritius Inhabiting Fungi Across Contrasting Aquatic Environments.. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6862941_V2
This version 2 dataset contains 34 files in total with one (1) additional file, called "Culture-dependent Isolate table with taxonomic determination and sequence data.csv". The remaining files (33) are identical to version 1. The following is the information about the new file and its variables: <b>Culture-dependent Isolate table with taxonomic determination and sequence data.csv</b>: Culture table with assigned taxonomy from NCBI. Single direction sequence for each isolate is include if one could be obtained. Sequence is derived from ITS1F-ITS4 PCR amplicons, with Sanger sequencing in one direction using ITS5. The files contains 20 variables with explanation as below: IsolateNumber : unique number identify each isolate cultured Time: season in which the sample was collected Location: the specific name of the location Habitat: type of habitat : either stream or peatland State: state in the USA in which the specific location is located Incubation_pH ID: pH of the medium during isolation of fungal cultures Genus: phylogenetic genus of the fungal isolates (determined by sequence similarity) Sequence_quality: base call quality of the entire sequence used for blast analysis, if known %_coverage: sequence coverage reported from GenBank %_ID: sequence similarity reported from GenBank Life_style : ecological life style if known Phylum: phylogenetic phylum as indicated by Index Fungorum Subphylum: phylogenetic subphylum as indicated by Index Fungorum Class: phylogenetic class as indicated by Index Fungorum Subclass: phylogenetic subclass as indicated by Index Fungorum Order: phylogenetic order as indicated by Index Fungorum Family: phylogenetic Family as indicated by Index Fungorum ITS5_Sequence: single direction sequence used for sequence similarity match using blastn. Primer ITS5 Fasta: sequence with nomenclature in a fasta format for easy cut and paste into phylogenetic software Note: blank cells mean no data is available or unknown.
ITS1 forward reads; Illumina; peatlands; streams; bogs; fens
South, Eric J.; Skinner, Rachel; DeWalt, R. Edward; Kondratieff, Boris; Johnson, Kevin P.; Davis, Mark; Lee, Jonathan; Durfee, Richard (2020): Phylogenomics of the North American Plecoptera. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6081616_V1
This dataset contains the amino acid and nucleotide alignments corresponding to the phylogenetic analyses of South et al. 2020 in Systematic Entomology. This dataset also includes the gene trees that were used as input for coalescent analysis in ASTRAL.
Plecoptera; stoneflies; phylogeny; insects
Kansara, Yogeshwar; Hoang, Linh; Dong, Xiaoru; Xie, Jingyi; Schneider, Jodi (2020): Sampled Cochrane Reviews Included RCTs Only. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3285089_V2
The data file contains detailed information of the Cochrane reviews that were used in a project associated with the manuscript (working title) "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".
Cochrane reviews; systematic reviews; randomized control trial; RCT; automation
Curtis, Amanda; Tiemann, Jeremy; Douglass, Sarah; Davis, Mark; Larson, Eric (2020): Data for: High stream flows dilute environmental DNA (eDNA) concentrations and reduce detectability. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1591542_V1
We studied we examined the role of stream flow on environmental DNA (eDNA) concentrations and detectability of an invasive clam (Corbicula fluminea), while also accounting for other abiotic and biotic variables. This data includes the eDNA concentrations, quadrat estimates of clam density, and abiotic variables.
Corbicula; detection probability; eDNA; invasive species; lotic; occupancy modeling
Kansara, Yogeshwar; Hoang, Linh (2020): Included Articles from Cochrane Reviews. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8212056_V2
The data file contains a list of included studies with their detailed metadata, taken from Cochrane reviews which were used in a project associated with the manuscript "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".
Cochrane reviews; automation; randomized controlled trial; RCT; systematic review
Lundstrom, Craig (2020): Experimental data from K-Na-Al-Si-H oxides systems. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7110302_V1
Phase equilibria; Granite; Quartz; Feldspar
Xie, Yuxuan Richard; Chari, Varsha.K; Castro, Daniel.C; Grant, Romans; Rubakhin , Stanislav S. ; Sweedler, Jonathan V. (2023): Data-Driven and Machine Learning Based Framework for Image-Guided Single-Cell Mass Spectrometry. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7302959_V1
Data sets to reproduce the results provided by the tutorial in paper "Data-Driven and Machine Learning Based Framework for Image-Guided Single-Cell Mass Spectrometry"
Kole Aspray, Elise; Ainsworth, Elizabeth; McGrath, Jesse; McGrath, Justin; Montes, Christopher; Whetten, Andrew; Ort, Donald; Long, Stephen; Puthuval, Kannan; Mies, Timothy; Bernacchi, Carl; DeLucia, Evan; Dalsing, Bradley; Leakey, Andrew; Li, Shuai; Herriott, Jelena; Miglietta, Franco (2023): SoyFACE Fumigation Data Files. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3496460_V1
This data set is related to the SoyFACE experiments, which are open-air agricultural climate change experiments that have been conducted since 2001. The fumigation experiments take place at the SoyFACE farm and facility in Champaign County, Illinois during the growing season of each year, typically between June and October. - The <i>"SoyFACE Plot Information 2001 to 2021"</i> file contains information about each year of the SoyFACE experiments, including the fumigation treatment type (CO2, O3, or a combination treatment), the crop species, the plots (also referred to as 'rings' and labeled with numbers between 2 and 31) used in each experiment, important experiment dates, and the target concentration levels or 'setpoints' for CO2 and O3 in each experiment. - This data set includes files with minute readings of the fumigation levels (<i>"SoyFACE 1-Minute Fumigation Data Files"</i> folder) from the SoyFACE experiments. The <i>"Soyface 1-Minute Fumigation Data Files"</i> folder contains sub-folders for each year of the experiments, each of which contains sub-folders for each ring used in that year's experiments. This data set also includes hourly data files for the fumigation experiments (<i>"SoyFACE Hourly Fumigation Data Files"</i> folder) created from the 1-minute files, and hourly ambient/weather data files for each year of the experiments (<i>"Hourly Weather and Ambient Data Files"</i> folder). The ambient CO2 and O3 data are collected at SoyFACE, and the weather data are collected from the SURFRAD and WARM weather stations located near the SoyFACE farm. - The <i>"Fumigation Target Percentages"</i> file shows how much of the time the CO2 and O3 fumigation levels are within a 10 or 20 percent margin of the target levels when the fumigation system is turned on. - The <i>"Matlab Files"</i> folder contains custom code (Aspray, E.K.) that was used to clean the <i>"SoyFACE 1-Minute Fumigation Data"</i> files and to generate the <i>"SoyFACE Hourly Fumigation Data"</i> and <i>"Fumigation Target Percentages"</i> files. Code information can be found in <i>"SoyFACE Hourly Fumigation Data Explanation"</i>. - Finally, the <i>" * Explanation"</i> files contain information about the column names, units of measurement, and other pertinent information for each data file.
SoyFACE; agriculture; agricultural; climate; climate change; atmosphere; atmospheric change; CO2; carbon dioxide; O3; ozone; soybean; fumigation; treatment
has sharing link
planned publication date: 2023-07-17
Gotsis, Dimitrios; Kelkar, Varun; Deshpande, Rucha; Brooks, Frank; KC, Prabhat; Myers, Kyle; Zeng, Rongping; Anastasio, Mark (2023): Data for the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2773204_V1
This repository contains the training dataset associated with the 2023 Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics (DGM-Image Challenge), hosted by the American Association of Physicists in Medicine. This dataset contains more than 100,000 8-bit images of size 512x512. These images emulate coronal slices from anthropomorphic breast phantoms adapted from the VICTRE toolchain , with assigned X-ray attenuation coefficients relevant for breast computed tomography. Please follow the instructions given on the following page in order to register for the challenge: <a href="https://www.aapm.org/GrandChallenge/DGM-Image/">https://www.aapm.org/GrandChallenge/DGM-Image/</a>.  Badano, Aldo, et al. <a href="https://doi.org/10.1001/jamanetworkopen.2018.5474">"Evaluation of digital breast tomosynthesis as replacement of full-field digital mammography using an in-silico imaging trial." </a>JAMA network open 1.7 (2018): e185474-e185474
Deep generative models; breast computed tomography
Mischo, William; Schlembach, Mary C. (2023): Processing and Pearson Correlation Scripts for the C&RL Article on the Relationships between Publication, Citation, and Usage Metrics at the University of Illinois at Urbana-Champaign Library . University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0931140_V1
These processing and Pearson correlational scripts were developed to support the study that examined the correlational relationships between local journal authorship, local and external citation counts, full-text downloads, link-resolver clicks, and four global journal impact factor indices within an all-disciplines journal collection of 12,200 titles and six subject subsets at the University of Illinois at Urbana-Champaign (UIUC) Library. This study shows strong correlations in the all-disciplines set and most subject subsets. Special processing scripts and web site dashboards were created, including Pearson correlational analysis scripts for reading values from relational databases and displaying tabular results. The raw data used in this analysis, in the form of relational database tables with multiple columns, is available at <a href="https://doi.org/10.13012/B2IDB-6810203_V1">https://doi.org/10.13012/B2IDB-6810203_V1</a>.
Pearson Correlation Analysis Scripts; Journal Publication; Citation and Usage Data; University of Illinois at Urbana-Champaign Scholarly Communication
Mischo, William; Schlembach, Mary C.; Cabada, Elisandro (2023): Data for: Relationships between Journal Publication, Citation, and Usage Metrics within a Carnegie R1 University Collection: A Correlation Analysis. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6810203_V1
This dataset was developed as part of a study that examined the correlational relationships between local journal authorship, local and external citation counts, full-text downloads, link-resolver clicks, and four global journal impact factor indices within an all-disciplines journal collection of 12,200 titles and six subject subsets at the University of Illinois at Urbana-Champaign (UIUC) Library. While earlier investigations of the relationships between usage (downloads) and citation metrics have been inconclusive, this study shows strong correlations in the all-disciplines set and most subject subsets. The normalized Eigenfactor was the only global impact factor index that correlated highly with local journal metrics. Some of the identified disciplinary variances among the six subject subsets may be explained by the journal publication aspirations of UIUC researchers. The correlations between authorship and local citations in the six specific subject subsets closely match national department or program rankings. All the raw data used in this analysis, in the form of relational database tables with multiple columns. Can be opned using MS Access. Description for variables can be viewed through "Design View" (by right clik on the selected table, choose "Design View"). The 2 PDF files provide an overview of tables are included in each MDB file. In addition, the processing scripts and Pearson correlation code is available at <a href="https://doi.org/10.13012/B2IDB-0931140_V1">https://doi.org/10.13012/B2IDB-0931140_V1</a>.
Usage and local citation relationships; publication; citation and usage metrics; publication; citation and usage correlation analysis; Pearson correlation analysis
has sharing link
Ruess, Paul ; Konar, Megan ; Wanders, Niko; Bierkens, Marc (2023): Data for Irrigation by crop in the Continental United States from 2008 to 2020. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4607538_V1
Agriculture is the largest user of water in the United States. Yet, we do not understand the spatially resolved sources of irrigation water use by crop. The goal of this study is to estimate crop-specific irrigation water use from surface water withdrawals, total groundwater withdrawals, and nonrenewable groundwater depletion for the Continental United States. Water use by source is provided for 20 crops and crop groups from 2008 to 2020 at the county spatial resolution. These results present the first national-scale assessment of irrigation by crop, county, water source, and year. In total, there are nearly 2.5 million data points in this dataset (3,142 counties; 13 years; 3 water sources; and 20 crops). This dataset supports the paper by Ruess et al (2023) in Water Resources Research, https://doi.org/10.1029/2022WR032804. When using, please cite as: Ruess, P.J., Konar, M., Wanders, N. , & Bierkens, M. (2023). Irrigation by crop in the Continental United States from 2008 to 2020, Water Resources Research, 59, e2022WR032804. https://doi.org/10.1029/2022WR032804
Water use; irrigation; surface water; groundwater; groundwater depletion; counties; crops; time series
Tonks, Adam (2023): Data for the paper "Forecasting West Nile Virus with Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3628170_V1
This is the data used in the paper "Forecasting West Nile Virus with Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data". Code from the Github repository https://github.com/adtonks/mosquito_GNN can be used with the data here to reproduce the paper's results.
west nile virus; machine learning; gnn; mosquito; trap; graph neural network; illinois; geospatial
Peyton, Buddy; Bajjalieh, Joseph; Shalmon, Dan; Martin, Michael; Bonaguro, Jonathan; Soto, Emilio (2022): Cline Center Coup d’État Project Dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9651987_V5
Coups d'État are important events in the life of a country. They constitute an important subset of irregular transfers of political power that can have significant and enduring consequences for national well-being. There are only a limited number of datasets available to study these events (Powell and Thyne 2011, Marshall and Marshall 2019). Seeking to facilitate research on post-WWII coups by compiling a more comprehensive list and categorization of these events, the Cline Center for Advanced Social Research (previously the Cline Center for Democracy) initiated the Coup d'État Project as part of its Societal Infrastructures and Development (SID) project. More specifically, this dataset identifies the outcomes of coup events (i.e. realized or successful coups, unrealized coup attempts, or thwarted conspiracies) the type of actor(s) who initiated the coup (i.e. military, rebels, etc.), as well as the fate of the deposed leader. This is version 2.1.1 of this dataset. This version corrects a mistake in version 2.1.0, where the designation of “dissident coup” had been dropped in error for coup_id: 00201062021. Version 2.1.1 fixes this omission by marking the case as both a dissident coup and an auto-coup. Changes from the previously released data (v2.0.0) also include: 1. Adding additional events and expanding the period covered to 1945-2022 2. Filling in missing actor information 3. Filling in missing information on the outcomes for the incumbent executive 4. Dropping events that were incorrectly coded as coup events <br> <b>Items in this Dataset</b> 1. <i>Cline Center Coup d'État Codebook v.2.1.1 Codebook.pdf</i> - This 16-page document provides a description of the Cline Center Coup d’État Project Dataset. The first section of this codebook provides a summary of the different versions of the data. The second section provides succinct definition of a coup d’état used by the Coup d’État Project and an overview of the categories used to differentiate the wide array of events that meet the project's definition. It also defines coup outcomes. The third section describes the methodology used to produce the data. <i>Revised December 2022</i> 2. <i>Coup Data v2.1.1.csv</i> - This CSV (Comma Separated Values) file contains all of the coup event data from the Cline Center Coup d’État Project. It contains 29 variables and 975 observations. <i>Revised December 2022</i> 3. <i>Source Document v2.1.0.pdf</i> - This 315-page document provides the sources used for each of the coup events identified in this dataset. Please use the value in the coup_id variable to identify the sources used to identify that particular event. <i>Created December 2022</i> 4. <i>README.md</i> - This file contains useful information for the user about the dataset. It is a text file written in markdown language. <i>Created December 2022</i> <br> <b> Citation Guidelines</b> 1. To cite the codebook (or any other documentation associated with the Cline Center Coup d’État Project Dataset) please use the following citation: Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Scott Althaus. 2022. “Cline Center Coup d’État Project Dataset Codebook”. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.1. December 22. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V5 2. To cite data from the Cline Center Coup d’État Project Dataset please use the following citation (filling in the correct date of access): Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Emilio Soto. 2022. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.1. December 22. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V5
Clarke, Caitlin; Lischwe Mueller, Natalie; Joshi, Manasi Ballal; Fu, Yuanxi; Schneider, Jodi (2022): The Inclusion Network of 27 Review Articles Published between 2013-2018 Investigating the Relationship Between Physical Activity and Depressive Symptoms. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4614455_V2
The relationship between physical activity and mental health, especially depression, is one of the most studied topics in the field of exercise science and kinesiology. Although there is strong consensus that regular physical activity improves mental health and reduces depressive symptoms, some debate the mechanisms involved in this relationship as well as the limitations and definitions used in such studies. Meta-analyses and systematic reviews continue to examine the strength of the association between physical activity and depressive symptoms for the purpose of improving exercise prescription as treatment or combined treatment for depression. This dataset covers 27 review articles (either systematic review, meta-analysis, or both) and 365 primary study articles addressing the relationship between physical activity and depressive symptoms. Primary study articles are manually extracted from the review articles. We used a custom-made workflow (Fu, Yuanxi. (2022). Scopus author info tool (1.0.1) [Python]. <a href="https://github.com/infoqualitylab/Scopus_author_info_collection">https://github.com/infoqualitylab/Scopus_author_info_collection</a> that uses the Scopus API and manual work to extract and disambiguate authorship information for the 392 reports. The author information file (author_list.csv) is the product of this workflow and can be used to compute the co-author network of the 392 articles. This dataset can be used to construct the inclusion network and the co-author network of the 27 review articles and 365 primary study articles. A primary study article is "included" in a review article if it is considered in the review article's evidence synthesis. Each included primary study article is cited in the review article, but not all references cited in a review article are included in the evidence synthesis or primary study articles. The inclusion network is a bipartite network with two types of nodes: one type represents review articles, and the other represents primary study articles. In an inclusion network, if a review article includes a primary study article, there is a directed edge from the review article node to the primary study article node. The attribute file (article_list.csv) includes attributes of the 392 articles, and the edge list file (inclusion_net_edges.csv) contains the edge list of the inclusion network. Collectively, this dataset reflects the evidence production and use patterns within the exercise science and kinesiology scientific community, investigating the relationship between physical activity and depressive symptoms. FILE FORMATS 1. article_list.csv - Unicode CSV 2. author_list.csv - Unicode CSV 3. Chinese_author_name_reference.csv - Unicode CSV 4. inclusion_net_edges.csv - Unicode CSV 5. review_article_details.csv - Unicode CSV 6. supplementary_reference_list.pdf - PDF 7. README.txt - text file UPDATES IN THIS VERSION COMPARED TO V1(Clarke, Caitlin; Lischwe Mueller, Natalie; Joshi, Manasi Ballal; Fu, Yuanxi; Schneider, Jodi (2022): The Inclusion Network of 27 Review Articles Published between 2013-2018 Investigating the Relationship Between Physical Activity and Depressive Symptoms. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4614455_V1) In V1, we did not upload the file "article_list.csv." We uploaded the missing file in this version, and everything else remains the same.
systematic reviews; meta-analyses; evidence synthesis; network visualization; tertiary studies; physical activity; depressive symptoms; exercise; review articles
Sherwood, Joshua; Tiemann, Jeremy; Stein, Jeffrey (2022): Dataset associated with the "Fishes of Champaign County, Illinois: as affected by 120 years of stream changes" manuscript by Sherwood et al. . University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9011146_V2
This dataset is associated with a larger manuscript published in 2022 in the Illinois Natural History Survey Bulletin that summarized the Fishes of Champaign County project from 2012-1025. With data spanning over 120 years, the Fishes of Champaign County is a comprehensive, long-term investigation into the changing fish communities of east-central Illinois. Surveys first occurred in Champaign County in the late 1880s (40 sites), with subsequent surveys in 1928–1929 (125 sites), 1959–1960 (143 sites), and 1987–1988 (141 sites). Between 2012 and 2015, we resampled 122 sites across Champaign County. The combined data from these five surveys have produced a unique perspective into not only the fish communities of the region, but also insight into in-stream habitat changes during the past 120 years. The dataset is in Microsoft Access format, with five data tables, one for each time period surveyed. Field names are self-explanatory, with some variation in data types collected during different surveys as follows: Forbes & Richardson (1880s) collected presence/absence only. Thompson & Hunt (1928-1929) collected abundance only, Larimore & Smith (1959-1960) collected length and weight for some samples, but only presence/absence at others. In some cases, fish of the same species were weighed in bulk, with the fields “LOW” and “HIGH” indicating the lower and upper limits of total length in the batch, and weight indicating the gross weight of all fish in the batch. Larimore and Bayley (1987-1988) collected length and weight for all surveys, and Sherwood and Stein (2012-2015) collected length and weight for all surveys except for cases where extremely abundant single species where subsampled. Lengths are reported in millimeters, and weight in grams. Two lookup tables provide information about species codes used in the data tables and sample site location and notes.
fishes of Champaign County; streams; anthropogenic disturbances; long-term dataset