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planned publication date: 2024-10-16
 
School testing data were provided by Shield Illinois (ShieldIL), which conducted weekly in-school testing on behalf of the Illinois Department of Public Health (IDPH) for all participating schools in the state excluding Chicago Public Schools. The populations and proportions of students and employees in the studied school districts are reported by Elementary/Secondary Information System (ElSi) database.
keywords: COVID-19; school testing
planned publication date: 2024-08-24
 
Dataset associated with Jones et al. GCB-23-1273.R1 submission: Phenotypic signatures of urbanization? Resident, but not migratory, songbird eye size varies with urban-associated light pollution levels. Excel CSV file with all of the data used in analyses and file with descriptions of each column.
keywords: body size; demographics; eye size; phenotypic divergence; songbirds; sensory pollution; urbanization
published: 2024-01-31
 
The included files were used to reconstruct the phylogeny of Coelidiinae using combined morphological and molecular data, estimate divergence times and reconstruct ancestral biogeographic areas as described in the manuscript submitted for publication. The file “Coelidiinae_dna_morph_combined.nex” is a text file in standard NEXUS format used by various phylogenetic analysis programs. This file includes the aligned and concatenated nucleotide sequences or five gene regions (mitochondrial COI and 16S, and nuclear 28S D-2, histone H3, histone H2A and wingless) indicated by standard “ACGT” nucleotide symbols with missing data indicated by “?”, and morphological character data as defined in Table S3 used in the analyses. The data partitions are indicated toward the end of the file by ranges of numbers (“charset Subset 1 – 4” for the DNA data and “charset morph” for the morphological characters) followed by commands for the phylogenetic analysis program MrBayes that specify the model settings for each data partition. Detailed data on species included (as rows) in the dataset, including collection localities and GenBank accession numbers are provided in the Table_S1_Specimen_information.csv file. The file "TablesS2-S4.pdf" lists the primers used for polymerase chain reaction amplification, the list of morphological character definitions, and the morphological character matrix. The file “RASP_Distribution.csv” contains a list of the species included in the phylogenetic dataset (first column) and a code (second column) indicating their distributions as follows: (A) Oriental, (B) Palaearctic, (C) Australian, (D) Afrotropical, (E) Neotropical, and (F) Nearctic. More than one letter indicates that the species occurs in more than one region. The file "infile_for_BEAST.txt" is the input file in XML format used for the molecular divergence time analysis using the program BEAST (Bayesian Evolutionary Analysis by Sampling Trees) as described in the Methods section of the manuscript. This file includes comments that document the steps of the analysis.
keywords: leafhopper; phylogeny; DNA sequence; insect; timetree; biogeography
published: 2024-02-25
 
Simulation trajectory data and scripts for Nature manuscript "The structure and physical properties of a packaged bacteriophage particle" that reports the all-atom structure of a complete HK97 virion, including its entire 39,732 base pair genome, obtained through multi-resolution simulations.
keywords: Virus capsid; Bacteriophage packaging; Multiresolution simulations; all-atom MD simulation
published: 2023-02-23
 
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 current version, Version 2.1.2, adds 6 additional coup events that occurred in 2022 and updates the coding of an attempted coup event in Kazakhstan in January 2022. Version 2.1.1 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. Version 2.1.0 added 36 cases to the data set and removes two cases from the v2.0.0 data. This update also added actor coding for 46 coup events and adds executive outcomes to 18 events from version 2.0.0. A few other changes were made to correct inconsistencies in the coup ID variable and the date of the event. 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.2.1.2 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 a 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 February 2023</i> 2. <i>Coup Data v2.1.2.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 981 observations. <i>Revised February 2023</i> 3. <i>Source Document v2.1.2.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>Revised February 2023</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>Revised February 2023</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. 2023. “Cline Center Coup d’État Project Dataset Codebook”. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.2. February 23. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V6 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. 2023. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.2. February 23. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V6
published: 2016-05-19
 
This dataset contains records of four years of taxi operations in New York City and includes 697,622,444 trips. Each trip records the pickup and drop-off dates, times, and coordinates, as well as the metered distance reported by the taximeter. The trip data also includes fields such as the taxi medallion number, fare amount, and tip amount. The dataset was obtained through a Freedom of Information Law request from the New York City Taxi and Limousine Commission. The files in this dataset are optimized for use with the ‘decompress.py’ script included in this dataset. This file has additional documentation and contact information that may be of help if you run into trouble accessing the content of the zip files.
keywords: taxi;transportation;New York City;GPS
published: 2024-03-09
 
Hype - PubMed dataset Prepared by Apratim Mishra This dataset captures ‘Hype’ within biomedical abstracts sourced from PubMed. The selection chosen is ‘journal articles’ written in English, published between 1975 and 2019, totaling ~5.2 million. The classification relies on the presence of specific candidate ‘hype words’ and their abstract location. Therefore, each article might have multiple instances in the dataset due to the presence of multiple hype words in different abstract sentences. The candidate hype words are 36 in count: 'major', 'novel', 'central', 'critical', 'essential', 'strongly', 'unique', 'promising', 'markedly', 'excellent', 'crucial', 'robust', 'importantly', 'prominent', 'dramatically', 'favorable', 'vital', 'surprisingly', 'remarkably', 'remarkable', 'definitive', 'pivotal', 'innovative', 'supportive', 'encouraging', 'unprecedented', 'bright', 'enormous', 'exceptional', 'outstanding', 'noteworthy', 'creative', 'assuring', 'reassuring', 'spectacular', and 'hopeful'. File 1: hype_dataset.csv Primary dataset. It has the following columns: 1. PMID: represents unique article ID in PubMed 2. Hype_word: Candidate hype word, such as ‘novel.’ 3. Sentence: Sentence in abstract containing the hype word. 4. Abstract_length: Length of article abstract. 5. Hype_percentile: Abstract relative position of hype word. 6. Hype_value: Propensity of hype based on the hype word, the sentence, and the abstract location. 7. Introduction: The ‘I’ component of the hype word based on IMRaD 8. Methods: The ‘M’ component of the hype word based on IMRaD 9. Results: The ‘R’ component of the hype word based on IMRaD 10. Discussion: The ‘D’ component of the hype word based on IMRaD File 2: hype_removed_phrases.csv Secondary dataset with same columns as File 1. Hype in the primary dataset is based on excluding certain phrases that are rarely hype. The phrases that were removed are included in File 2 and modeled separately. Removed phrases: 1. Major: histocompatibility, component, protein, metabolite, complex, surgery 2. Novel: assay, mutation, antagonist, inhibitor, algorithm, technique, series, method, hybrid 3. Central: catheters, system, design, composite, catheter, pressure, thickness, compartment 4. Critical: compartment, micelle, temperature, incident, solution, ischemia, concentration 5. Essential: medium, features, properties, opportunities 6. Unique: model, amino 7. Robust: regression 8. Vital: capacity, signs, organs, status, structures, staining, rates, cells, information 9. Outstanding: questions, issues, question, challenge, problems, problem, remains 10. Remarkable: properties 11. Definite: radiotherapy, surgery 12. Bright: field
keywords: Hype; PubMed; Abstracts; Biomedicine
published: 2024-03-06
 
These data are the result of analyses of the metagenome of North American bats, including 18s and 16s barcode genes designed to target microorganisms of the gut. These files are Phyloseq import files created by the DADA2 program. Each barcode gene is uploaded separately as the four files required to build a phyloseq object. For each barcode gene, the files include amplicon sequence variant (ASV) sequences, sequence tables (seqtab) which connect individual samples to the ASVs, tax tables (taxtab) which identify the taxa present as determined by a Bayesian RDP classifier, and rooted phylogenetic trees for the ASVs. Additionally, we have included a "sample_data" file which is necessary for sorting of samples across all four sequence analysis data sets by study and species. Some sample information which could identify the location of endangered species has been restricted. Multiple studies are represented in the data which can be accessed using standard methods in the Phyloseq program (e.g. For a study of bats, parasites, and gut microbiome dysregulation by Bennett, Suski, and OKeefe 2024 [in prep March 2024], study specific data can be accessed using the Study variable "DYSBIOMICS." File names include reference to the primer set used to generate them (18s primer sets: G3, G4, G6; 16s primer set: 341F3_806R5).
keywords: metagenomics
published: 2024-03-01
 
This dataset contains model output from the Community Earth System Model, Version 1 (CESM1; Hurrell et al., 2013) and variables from the European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis v5 (ERA5; Hersbach et al., 2020). These data were used for analysis in “The location of large-scale soil moisture anomalies affects moisture transport and precipitation over southeastern South America”, published in Geophysical Research Letters. Acknowledgments: This work was supported by NSF Award AGS-1852709. We acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the NSF. We thank Dr. Haiyan Teng for providing guidance on setting up the CESM experiments and offering valuable advice. References: Hersbach H, Bell B, Berrisford P, et al. The ERA5 global reanalysis. Q J R Meteorol Soc. 2020; 146: 1999–2049. https://doi.org/10.1002/qj.3803 Hurrell, J. W., and Coauthors, 2013: The Community Earth System Model: A Framework for Collaborative Research. Bull. Amer. Meteor. Soc., 94, 1339–1360, https://doi.org/10.1175/BAMS-D-12-00121.1
keywords: atmospheric sciences; climate modeling; land-atmosphere interactions; soil moisture; regional atmospheric circulation; southeastern South America
published: 2015-12-16
 
This dataset contains the data for PASTA and UPP. PASTA data was used in the following articles: Mirarab, Siavash, Nam Nguyen, Sheng Guo, Li-San Wang, Junhyong Kim, and Tandy Warnow. “PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences.” Journal of Computational Biology 22, no. 5 (2015): 377–86. doi:10.1089/cmb.2014.0156. Mirarab, Siavash, Nam Nguyen, and Tandy Warnow. “PASTA: Ultra-Large Multiple Sequence Alignment.” Edited by Roded Sharan. Research in Computational Molecular Biology, 2014, 177–91. UPP data was used in: Nguyen, Nam-phuong D., Siavash Mirarab, Keerthana Kumar, and Tandy Warnow. “Ultra-Large Alignments Using Phylogeny-Aware Profiles.” Genome Biology 16, no. 1 (December 16, 2015): 124. doi:10.1186/s13059-015-0688-z.
published: 2017-09-16
 
This dataset contains the data for 16S and 23S rRNA alignments including their reference trees. The original alignments are from the Gutell Lab CRW, currently located at https://crw-site.chemistry.gatech.edu/DAT/3C/Alignment/.
published: 2009-06-19
 
This dataset contains the data for SATe-I. SATe-I data was used in the following article: K. Liu, S. Raghavan, S. Nelesen, C. R. Linder, T. Warnow, "Rapid and Accurate Large-Scale Coestimation of Sequence Alignments and Phylogenetic Trees," Science, vol. 324, no. 5934, pp. 1561-1564, 19 June 2009.
published: 2024-02-29
 
This dataset consists the 286 publications retrieved from Web of Science and Scopus on July 6, 2023 as citations for (Willoughby et al., 2014): Willoughby, Patrick H., Jansma, Matthew J., & Hoye, Thomas R. (2014). A guide to small-molecule structure assignment through computation of (¹H and ¹³C) NMR chemical shifts. Nature Protocols, 9(3), Article 3. https://doi.org/10.1038/nprot.2014.042 We added the DOIs of the citing publications into a Zotero collection, which we exported into a .csv file and an .rtf file. Willoughby2014_286citing_publications.csv is a Zotero data export of the citing publications. Willoughby2014_286citing_publications.rtf is a bibliography of the citing publications, using a variation of American Psychological Association style (7th edition) with full names instead of initials.
keywords: scientific publications; arguments; citation contexts; defeasible reasoning; Zotero; Web of Science; Scopus;
published: 2024-02-27
 
Coups d'Ètat 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, unrealized, or conspiracy) the type of actor(s) who initiated the coup (i.e., military, rebels, etc.), as well as the fate of the deposed leader. Version 2.1.3 adds 19 additional coup events to the data set, corrects the date of a coup in Tunisia, and reclassifies an attempted coup in Brazil in December 2022 to a conspiracy. Version 2.1.2 added 6 additional coup events that occurred in 2022 and updated the coding of an attempted coup event in Kazakhstan in January 2022. Version 2.1.1 corrected 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 fixed this omission by marking the case as both a dissident coup and an auto-coup. Version 2.1.0 added 36 cases to the data set and removed two cases from the v2.0.0 data. This update also added actor coding for 46 coup events and added executive outcomes to 18 events from version 2.0.0. A few other changes were made to correct inconsistencies in the coup ID variable and the date of the event. Version 2.0.0 improved several aspects of the previous version (v1.0.0) and incorporated additional source material to include: • Reconciling missing event data • Removing events with irreconcilable event dates • Removing events with insufficient sourcing (each event needs at least two sources) • Removing events that were inaccurately coded as coup events • Removing variables that fell below the threshold of inter-coder reliability required by the project • Removing the spreadsheet ‘CoupInventory.xls’ because of inadequate attribution and citations in the event summaries • Extending the period covered from 1945-2005 to 1945-2019 • Adding events from Powell and Thyne’s Coup Data (Powell and Thyne, 2011) <br> <b>Items in this Dataset</b> 1. <i>Cline Center Coup d'État Codebook v.2.1.3 Codebook.pdf</i> - This 15-page document describes 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 a 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 February 2024</i> 2. <i>Coup Data v2.1.3.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 1000 observations. <i>Revised February 2024</i> 3. <i>Source Document v2.1.3.pdf</i> - This 325-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>Revised February 2024</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>Revised February 2024</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. 2024. “Cline Center Coup d’État Project Dataset Codebook”. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.3. February 27. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V7 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. 2024. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.3. February 27. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V7
published: 2024-02-26
 
Traces created using DeathStarBench (https://github.com/delimitrou/DeathStarBench) benchmark of microservice applications with injected failures on containers. Failures consist of disk/CPU/memory failures.
keywords: Murphy;Performance Diagnosis;Microservice;Failures
published: 2023-12-20
 
Important Note: the raw transient files need to be downloaded through this separate link: https://uofi.box.com/s/oagdxhea1wi8tvfij4robj0z0w8wq7j4. Once downloaded, place the file within the within the .d folder in the unzipped 20210930_ShortTransient_S3_5 folder to perform reconstruction step. The minimal datasets to run the computational pipeline MEISTER introduced in the manuscript titled "Integrative Multiscale Biochemical Mapping of the Brain via Deep-Learning-Enhanced High-Throughput Mass Spectrometry". The key steps of our computational pipeline include (1) tissue mass spectrometry imaging (MSI) reconstruction; (2) multimodal image registration and 3D reconstruction; (3) regional analysis; and (4) single-cell and tissue data integration. Detailed protocols to reproduce our results in the manuscript are provided with an example data set shared for learning the protocols. Our computational processing codes are implemented mostly in Python as well as MATLAB (for image registration).
keywords: deep learning;mass spectrometry;single cells
published: 2023-12-19
 
Data for the Appendices of Bush et al. article published in Ecology and Evolution. Contains genomic analysis information for a strain of Aspergillus flavus isolated from bee bread in East Central Illinois.
keywords: Excel; UIUC; Evolution and Ecology; Aspergillus flavus; genome
published: 2024-02-15
 
Dataset includes the dataset for estimating bat density from acoustic data and the R code. The data support a publication by Meredith L. Hoggatt, Clarissa A. Starbuck, and Joy M. O'Keefe entitled Acoustic monitoring yields informative bat population density estimates.
keywords: acoustics; bats; monitoring; population density; random encounter model
published: 2024-02-21
 
Data associated with the manuscript "Niche conservatism and spread explain hybridization and introgression between native and invasive fish" by Jordan H. Hartman, Joel B. Corush, Eric R. Larson, Jeremy S. Tiemann, Philip Willink, and Mark A. Davis. For this project, we combined results of ecological niche models (ENMs) and next-generation restriction site-associated DNA sequencing (RADseq) to test theories of niche conservatism and biotic resistance on the success of invasion, hybridization, and extent of introgression between native Western Banded Killifish and non-native Eastern Banded Killifish. This dataset provides the sampling locations and number of Banded Killifish in each population, accession numbers for RADseq from the National Center for Biotechnology Information Sequence Read Archive and the assignment of each Banded Killifish, the habitat associations of each population from the ENMs, and the occurrence points used to build the ENMs.
keywords: Banded Killifish; ecological niche model; Fundulus diaphanus; hybrid swarm; invasive species; Laurentian Great Lakes
published: 2024-02-16
 
This dataset contains five files. (i) open_citations_jan2024_pub_ids.csv.gz, open_citations_jan2024_iid_el.csv.gz, open_citations_jan2024_el.csv.gz, and open_citation_jan2024_pubs.csv.gz represent a conversion of Open Citations to an edge list using integer ids assigned by us. The integer ids can be mapped to omids, pmids, and dois using the open_citation_jan2024_pubs.csv and open_citations_jan2024_pub_ids.scv files. The network consists of 121,052,490 nodes and 1,962,840,983 edges. Code for generating these data can be found https://github.com/chackoge/ERNIE_Plus/tree/master/OpenCitations. (ii) The fifth file, baseline2024.csv.gz, provides information about the metadata of PubMed papers. A 2024 version of PubMed was downloaded using Entrez and parsed into a table restricted to records that contain a pmid, a doi, and has a title and an abstract. A value of 1 in columns indicates that the information exists in metadata and a zero indicates otherwise. Code for generating this data: https://github.com/illinois-or-research-analytics/pubmed_etl
keywords: PubMed
published: 2024-02-16
 
Sample data from one typical phantom test and one deidentified shunt patient test (shown in Fig. 8 of the MRM paper), with the corresponding analysis code for the Shunt-FENSI technique. For the MRM paper “Measuring CSF Shunt Flow with MRI Using Flow Enhancement of Signal Intensity (FENSI)”
keywords: Shunt-FENSI; MRM; Hydrocephalus; VP Shunt; Flow Quantification; Pediatric Neurosurgery; Pulse Sequence; Signal Simulation
published: 2024-01-19
 
This data set is related to a SoyFACE experiment conducted in 2004, 2006, 2007, and 2008 with the soybean cultivars Loda and HS93-4118. The experiment looked at how seed elements were affected by elevated CO2 and yield. In this V2, 2 new files were added per journal requirement. Total there are 5 data files in text format within the digrado_et_al_gcb_data_V2 and 1 readme file. The name of files are listed below. Details about headers are explained in the readme.txt file. <b>1. ionomic_data.txt file</b> contains the ionomic data (mg/kg) for the two cultivars. The file contains all six technical replicates for each plot. The cultivar, year, treatment, and the plot from which the samples were collected are given for each entry. <b>2. yield_data.txt file</b> contains the yield data for the two cultivars (seed yield in kg/ha, seed yield in bu/a, Protein (%), Oil (%)). The file contains yield data for every plot. The cultivar, year, treatment, and the plot from which the samples were collected are given for each entry. <b>3. mineral_pro_oil_yield.txt file</b> contains the yield per hectare for each mineral (g/ha) along with the yield per hectare for protein and oil (t/ha). This was obtained by multiplying the seed content of each element (minerals, protein, and oil) by the total seed yield. The file contains yield data for every plots. The cultivar, year, treatment, and the plot from which the samples were collected are given for each entry. <b>4. economic_assessment.txt file</b> contains data used to assess the financial impact of altered seed oil content on soybean oil production. <b>5. meteorological_data.txt file</b> contains the meteorological data recorded by a weather station located ~ 3km from the experimental site (Willard Airport Champaign). Data covering the period between May 28 and September 24 were used for 2004; between May 25 and September 24 were used in 2006; between May 23 and September 17 in 2007; and between June 16 and October 24 in 2008.
keywords: protein; oil; mineral; SoyFACE; nutrient; Glycine max; soybean; yield; CO2; agriculture; climate change
published: 2023-04-06
 
Example data for https://github.com/chenlabUIUC/UsiNet The data contains computer simulated and experimental tilting series (or sinograms) of gold nanoparticles. Two training data examples are provided: 1. simulated_data.zip 2. experimental_data.zip In each zip folder, we include an image_data.zip and a training_data.zip. The former is for viewing and only the latter is needed for model training. For more details, please refer to our GitHub repository.
keywords: electron tomography; deep learning
published: 2023-12-01
 
Mist netting data for little brown bats (Myotis lucifugus) in McHenry County, Illinois and output of acoustic data processed using Kaleidoscope (Version 5.1.9, Bats of North America 5.1.0; Wildlife Acoustics) auto-identification software. Associated survey metadata and landcover metrics calculated using Fragstats included.
keywords: little brown bats; mist netting; acoustics
published: 2024-02-08
 
This dataset contains transcribed entries from the "Prairie Directory of North America" (Adelman and Schwartz 2013) for the Tallgrass, Mixed Grass, and Shortgrass prairie regions of the united states. We identified the historical spatial extent of the Tallgrass, Mixed Grass, and Shortgrass prairie regions using Ricketts et al. (1999), Olson et al. (2001), and Dixon et al. (2014) and selected the counties entirely or partially within these boundaries from the USDA Forest Service (2022) file. The resulting lists of counties are included as separate files. The dataset contains information on publicly accessible grasslands and prairies in these regions including acreage and amenities like hunting access, restrooms, parking, and trails.
keywords: grasslands; prairies; prairie directory of north america; site amenities; site attributes