Dataset Search Results

This dataset provides a 50-state (and DC) survey of state-level tax credits modeled after the federal New Markets Tax Credit program, including summaries of the tax credit amount and credit periods, key definitions, eligibility criteria, application process, and degree of conformity to federal law.

This dataset provides a 50-state (and DC) survey of state-level enterprise zone laws, including summaries and analyses of zone eligibility criteria, eligible investments, incentives to invest in human capital and affordable housing, and taxpayer eligibility.

This is part of the Cline Center’s ongoing Social, Political and Economic Event Database Project (SPEED) project. Each observation represents an event involving civil unrest, repression, or political violence in Sierra Leone, Liberia, and the Philippines (1979-2009). These data were produced in an effort to describe the relationship between exploitation of natural resources and civil conflict, and to identify policy interventions that might address resource-related grievances and mitigate civil strife. This work is the result of a collaboration between the US Army Corps of Engineers’ Construction Engineer Research Laboratory (ERDC-CERL), the Swedish Defence Research Agency (FOI) and the Cline Center for Advanced Social Research (CCASR). The project team selected case studies focused on nations with a long history of civil conflict, as well as lucrative natural resources. The Cline Center extracted these events from country-specific articles published in English by the British Broadcasting Corporation (BBC) Summary of World Broadcasts (SWB) from 1979-2008 and the CIA’s Foreign Broadcast Information Service (FBIS) 1999-2004. Articles were selected if they mentioned a country of interest, and were tagged as relevant by a Cline Center-built machine learning-based classification algorithm. Trained analysts extracted nearly 10,000 events from nearly 5,000 documents. The codebook—available in PDF form below—describes the data and production process in greater detail.

All code in Matlab .m scripts or functions (version R2019b) Affiliated with article “Temperate and chronic virus competition leads to low lysogen frequency” published in the Journal of Theoretical Biology (2021) Codes simulate and plot the solutions of an Ordinary Differential Equations model and generate bifurcation diagrams.

These are the data sets associated with our publication "Field borders provide winter refuge for beneficial predators and parasitoids: a case study on organic farms." For this project, we compared the communities of overwintering arthropod natural enemies in organic cultivated fields and wildflower-strip field borders at five different sites in central Illinois. Abstract: Semi-natural field borders are frequently used in midwestern U.S. sustainable agriculture. These habitats are meant to help diversify otherwise monocultural landscapes and provision them with ecosystem services, including biological control. Predatory and parasitic arthropods (i.e., potential natural enemies) often flourish in these habitats and may move into crops to help control pests. However, detailed information on the capacity of semi-natural field borders for providing overwintering refuge for these arthropods is poorly understood. In this study, we used soil emergence tents to characterize potential natural enemy communities (i.e., predacious beetles, wasps, spiders, and other arthropods) overwintering in cultivated organic crop fields and adjacent field borders. We found a greater abundance, species richness, and unique community composition of predatory and parasitic arthropods in field borders compared to arable crop fields, which were generally poorly suited as overwintering habitat. Furthermore, potential natural enemies tended to be positively associated with forb cover and negatively associated with grass cover, suggesting that grassy field borders with less forb cover are less well-suited as winter refugia. These results demonstrate that semi-natural habitats like field borders may act as a source for many natural enemies on a year-to-year basis and are important for conserving arthropod diversity in agricultural landscapes.

This dataset contains the files used to perform the work savings and recall evaluation in the study titled "Data from Testing a filtering strategy for systematic reviews: Evaluating work savings and recall."

This dataset provides a 50-state (and DC) survey of state-level Opportunity Zones laws, including summaries of states' Opportunity Zone tax preferences, supplemental tax preferences, and approach to Opportunity Zones conformity. Data was last updated on January 14, 2022.

The file “Fla.fasta”, comprising 10526 positions, is the concatenated amino acid alignments of 51 orthologues of 182 bacterial strains. It was used for the maximum likelihood and maximum parsimony analyses of Flavobacteriales. Bacterial species names and strains were used as the sequence names, host names of insect endosymbionts were shown in brackets. The file “16S.fasta” is the alignment of 233 bacterial 16S rRNA sequences. It contains 1455 positions and was used for the maximum likelihood analysis of flavobacterial insect endosymbionts. The names of endosymbiont strains were replaced by the name of their hosts. In addition to the species names, National Center for Biotechnology Information (NCBI) accession numbers were also indicated in the sequence names (e.g., sequence “Cicadellidae_Deltocephalinae_Macrostelini_Macrosteles_striifrons_AB795320” is the 16S rRNA of Macrosteles striifrons (Cicadellidae: Deltocephalinae: Macrostelini) with a NCBI accession number AB795320). The file “Sulcia_pep.fasta” is the concatenated amino acid alignments of 131 orthologues of “Candidatus Sulcia muelleri” (Sulcia). It contains 41970 positions and presents 101 Sulcia strains and 3 Blattabacterium strains. This file was used for the maximum likelihood analysis of Sulcia. The file “Sulcia_nucleotide.fasta” is the concatenated nucleotide alignment corresponding to the sequences in “Sulcia_pep.fasta” but also comprises the alignment of 16S rRNA. It has 127339 positions and was used for the maximum likelihood and maximum parsimony analyses of Sulcia. Individual gene alignments (16S rRNA and 131 orthologues of Sulcia and Blattabacterium) are deposited in the compressed file “individual_gene_alignments.zip”, which were used to construct gene trees for multispecies coalescent analysis. The names of Sulcia strains were replaced by the name of their hosts in “Sulcia_pep.fasta”, “Sulcia_nucleotide.fasta” and the files in “individual_gene_alignments.zip”. In all the alignment files, gaps are indicated by “-”.

The data file contains a list of articles and their RCT Tagger prediction scores, which were used in a project associated with the manuscript "Evaluation of publication type tagging as a strategy to screen randomized controlled trial articles in preparing systematic reviews".

The data file contains a list of articles with PMIDs information, which were used in a project associated with the manuscript "Evaluation of publication type tagging as a strategy to screen randomized controlled trial articles in preparing systematic reviews".

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.

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.

Dataset associated with Jones and Ward BEAS-D-21-00106R2 submission: Parasitic cowbird development up to fledging and subsequent post-fledging survival reflect life history variation found across host species. Excel CSV files and .inp file with data used in nest survival and Brown-headed Cowbird post-fledging analyses and file with descriptions of each column. The CSV file is setup for logistic exposure models in SAS or R and the .inp file is setup to be uploaded into program MARK for multi-state recaptures only analysis. Species included in the analyses: American Robin, Blue Grosbeak, Brown Thrasher, Blue-winged Warbler, Carolina Chickadee, Chipping Sparrow, Common Yellowthroat, Dickcissel, Eastern Bluebird, Eastern Phoebe, Eastern Towhee, Field Sparrow, Gray Catbird, House Wren, Indigo Bunting, Northern Cardinal, Red-winged Blackbird, Tree Swallow, Yellow-breasted Chat, and Yellow Warbler.

This dataset contain information for the paper "Changes in neuropeptide prohormone genes among Cetartio-dactyla livestock and wild species associated with evolution and domestication" Veterinary Sciences, MDPI. Protein sequences were predicted using GeneWise for 98 neuropeptide prohormone genes from publicly available genomes of 118 Cetartiodactyla species. All predictions (CetartiodactylaSequences2022.zip) were manually verified. Sequences were aligned within each prohormone using MAFFT (MDPImultalign2022.zip includes multiple sequence alignment of all species available for each prohormone). Phylogenetic gene trees were constructed using PhyML and the species tree was constructed using ASTRAL (MDPItree2022.zip). The data is released under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).

This dataset includes a total of 501 images of 42 fossil specimens of Striatopollis and 459 specimens of 45 extant species of the tribe Amherstieae-Fabaceae. These images were taken using Airyscan confocal superresolution microscopy at 630X magnification (63x/NA 1.4 oil DIC). The images are in the CZI file format. They can be opened using Zeiss propriety software (Zen, Zen lite) or in ImageJ. More information on how to open CZI files can be found here: [https://www.zeiss.com/microscopy/us/products/microscope-software/zen/czi.html#microscope---image-data].

DNN weights used in the evaluation of the ApproxTuner system. Link to paper: https://dl.acm.org/doi/10.1145/3437801.3446108

List of differentially expressed genes in human endometrial stromal cells with knockdown of Basigin (BSG) gene expression during decidualization. The BSG siRNA or negative scrambled control siRNA were transfected into human endometrial stromal cells (HESCs) following the protocol of siLentFect™ Lipid (Bio-Rad, Hercules, CA. Following complete knock down of BSG in HESCs (72 hours after adding siRNA), HESCs were treated with medium containing estrogen, progesterone and cAMP to induce decidualization. BSG siRNA and negative control scrambled siRNA were added to the cells every four days (day 0, 4) over the course of the decidualization protocol. Total RNA was harvested at day 6 of the decidualization protocol for microarray analysis. Microarray analysis was performed at the University of Illinois at Urbana-Champaign Roy J. Carver Biotechnology Center. Briefly, 0.2 micrograms of total RNA were labeled using the Agilent two color QuickAmp labeling kit (Agilent Technologies, Santa Clara, CA) according to the manufacturer’s protocol. The optional spike-in controls were not used. Samples were hybridized to Human Gene Expression 4x44K v2 Microarray (Agilent Technologies, Santa Clara, CA) in an Agilent Hybridization Cassette according to standard protocols. The arrays were then scanned on an Axon GenePix 4000B scanner and the images were quantified using Axon GenePix 6.1. Microarray data pre-processing and statistical analyses were done in R (v3.6.2) using the limma package (3.42.0 (Ritchie et al., 2015). Median foreground and median background values from the 4 arrays were read into R and any spots that had been manually flagged (-100 values) were given a weight of zero. The background values were ignored because investigations showed that trying to use them to adjust for background fluorescence added more noise to the data; background was low and even for all arrays, therefore no background correction was done. The individual Cy5 and Cy3 fluorescence for each array were normalized together using the quantile method 3 (Yang and Thorne, 2003). Agilent's Human Gene Expression 4x44K v2 Microarray has a total of 45,220 probes: 1224 probes for positive controls, 153 negative control, 823 labeled “ignore” and 43,118 labeled “cDNA”. The pos+neg+ignore probes were used to ascertain the background level of fluorescence (6, on the log2 scale) then discarded. The cDNA probes comprise 34,127 unique 60mer probes, of which 999 probes are spotted 10 times each and the rest one time each. We averaged the replicate probes for those spotted 10 times and then fit a mixed model that had treatment and dye as fixed effects and array pairing as a random effect (Phipson et al., 2016; Smyth et al., 2005). After fitting the model but before False Discovery Rate (FDR) correction (Benjamini and Hochberg, 1995), probes were filtered out by the following criteria: 1) did not have at least 4/8 samples with expression values > 6 (14,105 probes removed), 2) no longer had an assigned Entrez Gene ID in Bioconductor’s HsAgilentDesign026652.db annotation package (v3.2.3; 2,152 probes removed) (Huber et al., 2015), 3) mapped to the same Entrez Gene ID as another probe but had a larger p-value for treatment effect (4,141 probes removed). This left 13,729 probes representing 13,729 unique genes. <b>*Please note: that there is a discrepancy between the file and the readme as this plain text is the actual data file of this dataset.</b>

This archive contains all the alignments and trees used in the HIPPI paper [1]. The pfam.tar archive contains the PFAM families used to build the HMMs and BLAST databases. The file structure is: ./X/Y/initial.fasttree ./X/Y/initial.fasta where X is a Pfam family, Y is the cross-fold set (0, 1, 2, or 3). Inside the folder are two files, initial.fasta which is the Pfam reference alignment with 1/4 of the seed alignment removed and initial.fasttree, the FastTree-2 ML tree estimated on the initial.fasta. The query.tar archive contains the query sequences for each cross-fold set. The associated query sequences for a cross-fold Y is labeled as query.Y.Z.fas, where Z is the fragment length (1, 0.5, or 0.25). The query files are found in the splits directory. [1] Nguyen, Nam-Phuong D, Mike Nute, Siavash Mirarab, and Tandy Warnow. (2016) HIPPI: Highly Accurate Protein Family Classification with Ensembles of HMMs. To appear in BMC Genomics.

These datasets provide the basis of our analysis in the paper - The Potential Impact of a Clean Energy Society On Air Quality. All datasets here are from the model output (CAM4-chem). All the simulations were run to steady-state and only the outputs used in the analysis are archived here.

To generate the bibliographic and survey data to support a data reuse study conducted by several Library faculty and accepted for publication in the Journal of Academic Librarianship, the project team utilized a series of web-based online scripts that employed several different endpoints from the Scopus API. The related dataset: "Data for: An Examination of Data Reuse Practices within Highly Cited Articles of Faculty at a Research University" contains survey design and results. <br /> 1) <b>getScopus_API_process_dmp_IDB.asp</b>: used the search API query the Scopus database API for papers by UIUC authors published in 2015 -- limited to one of 9 pre-defined Scopus subject areas -- and retrieve metadata results sorted highest to lowest by the number of times the retrieved articles were cited. The URL for the basic searches took the following form: https://api.elsevier.com/content/search/scopus?query=(AFFIL%28(urbana%20OR%20champaign) AND univ*%29) OR (AF-ID(60000745) OR AF-ID(60005290))&apikey=xxxxxx&start=" & nstart & "&count=25&date=2015&view=COMPLETE&sort=citedby-count&subj=PHYS<br /> Here, the variable nstart was incremented by 25 each iteration and 25 records were retrieved in each pass. The subject area was renamed (e.g. from PHYS to COMP for computer science) in each of the 9 runs. This script does not use the Scopus API cursor but downloads 25 records at a time for up to 28 times -- or 675 maximum bibliographic records. The project team felt that looking at the most 675 cited articles from UIUC faculty in each of the 9 subject areas was sufficient to gather a robust, representative sample of articles from 2015. These downloaded records were stored in a temporary table that was renamed for each of the 9 subject areas. <br /> 2) <b>get_citing_from_surveys_IDB.asp</b>: takes a Scopus article ID (eid) from the 49 UIUC author returned surveys and retrieves short citing article references, 200 at a time, into a temporary composite table. These citing records contain only one author, no author affiliations, and no author email addresses. This script uses the Scopus API cursor=* feature and is able to download all the citing references of an article 200 records at a time. <br /> 3) <b>put_in_all_authors_affil_IDB.asp</b>: adds important data to the short citing records. The script adds all co-authors and their affiliations, the corresponding author, and author email addresses. <br /> 4) <b>process_for_final_IDB.asp</b>: creates a relational database table with author, title, and source journal information for each of the citing articles that can be copied as an Excel file for processing by the Qualtrics survey software. This was initially 4,626 citing articles over the 49 UIUC authored articles, but was reduced to 2,041 entries after checking for available email addresses and eliminating duplicates.

Example scripts and configuration files needed to perform select simulations described in the manuscript "Percolation transition prescribes protein size-specific barrier to passive transport through the nuclear pore complex."

Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. This dataset contains all the code, notebooks, datasets used in the study conducted for the research publication titled " A Vector-Based Method for Drainage Network Analysis Based on LiDAR Data ". ## What's Inside A quick explanation of the components * `A Vector Approach to Drainage Network Analysis Based on LiDAR Data.ipynb` is a notebook for finding the drainage network based on LiDAR data *`Picture1.png` is a picture representing the pseudocode of our new algorithm * HPC` folder contains codes for running the algorithm with sbatch in HPC ** `execute.sh` is a bash script file that use sbatch to conduct large scale analysis for the algorithm ** `run.sh` is a bash script file that calls the script file `execute.sh` for large scale calculation for the algorithm ** `run.py` includes the codes implemented for the algorithm * `Rowan Creek Data` includes data that are used in the study ** `3_1.las` and `3_2.las ` are the LiDAR data files that is used in our analysis presented in the paper. Users may use this data file to reproduce our results and may replace it with their own LiDAR file to run this method over different areas ** `reference` folder includes reference data from USGS *** `reference_3_1.tif` and `reference_3_2.tif` are reference data for the drainage system analysis retrieved from USGS.

Ground based radar data sets collected during the 2013 NASA EVEX Campaign conducted in Roi-Namur island of the Kwajalein Atoll in the Republic of Marshall Islands are deposited in this databank. Radar data were collected with IRIS VHF and ALTAIR VHF/UHF systems.

This dataset helps to investigate the Spatial Accessibility to HIV Testing, Treatment, and Prevention Services in Illinois and Chicago, USA. The main components are: population data, healthcare data, GTFS feeds, and road network data. The core components are: 1) `GTFS` which contains GTFS (<a href="https://gtfs.org/">General Transit Feed Specification</a>) data which is provided by Chicago Transit Authority (CTA) from <a href="https://developers.google.com/transit/gtfs">Google's GTFS feeds</a>. Documentation defines the format and structure of the files that comprise a GTFS dataset: <a href="https://developers.google.com/transit/gtfs/reference?csw=1">https://developers.google.com/transit/gtfs/reference?csw=1</a>. 2) `HealthCare` contains shapefiles describing HIV healthcare providers in Chicago and Illinois respectively. The services come from <a href="https://locator.hiv.gov/">Locator.HIV.gov</a>. 3) `PopData` contains population data for Chicago and Illinois respectively. Data come from The American Community Survey and <a href="https://map.aidsvu.org/map">AIDSVu</a>. AIDSVu (https://map.aidsvu.org/map) provides data on PLWH in Chicago at the census tract level for the year 2017 and in the State of Illinois at the county level for the year 2016. The American Community Survey (ACS) provided the number of people aged 15 to 64 at the census tract level for the year 2017 and at the county level for the year 2016. The ACS provides annually updated information on demographic and socio economic characteristics of people and housing in the U.S. 4) `RoadNetwork` contains the road networks for Chicago and Illinois respectively from <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> using the Python <a href="https://osmnx.readthedocs.io/en/stable/">osmnx</a> package. <b>The abstract for our paper is:</b> Accomplishing the goals outlined in “Ending the HIV (Human Immunodeficiency Virus) Epidemic: A Plan for America Initiative” will require properly estimating and increasing access to HIV testing, treatment, and prevention services. In this research, a computational spatial method for estimating access was applied to measure distance to services from all points of a city or state while considering the size of the population in need for services as well as both driving and public transportation. Specifically, this study employed the enhanced two-step floating catchment area (E2SFCA) method to measure spatial accessibility to HIV testing, treatment (i.e., Ryan White HIV/AIDS program), and prevention (i.e., Pre-Exposure Prophylaxis [PrEP]) services. The method considered the spatial location of MSM (Men Who have Sex with Men), PLWH (People Living with HIV), and the general adult population 15-64 depending on what HIV services the U.S. Centers for Disease Control (CDC) recommends for each group. The study delineated service- and population-specific accessibility maps, demonstrating the method’s utility by analyzing data corresponding to the city of Chicago and the state of Illinois. Findings indicated health disparities in the south and the northwest of Chicago and particular areas in Illinois, as well as unique health disparities for public transportation compared to driving. The methodology details and computer code are shared for use in research and public policy.