University Library, University of Illinois at Urbana-Champaign

This dataset contains gamma-ray spectra templates for a source interdiction and uranium enrichment measurement task. This dataset also contains Keras machine learning models trained using datasets created using these templates.

Dataset associated with Hoover et al AUK-19-093 submission: Local conspecific density does not influence reproductive output in a secondary cavity-nesting songbird. Excel CSV with all of the data used in analyses. Description of variables YEARS: year ORDINAL_DATE: number for what day of the year it is with 1 January = 1,……30 December = 365 SITE: acronym for each study site BOX: unique nest box identifier on each study site TREAT: designates whether nest box was in a high- or low- nest box density area within each study site ACTUAL_NO_NEIGHBORS: number of pairs of warblers using a nest box within 200 m of a given pair’s nest box CLUTCH_SIZE: number of warbler eggs in nest at the onset of incubation PROWN: number of warbler nestlings once eggs have hatched PROWF: number of warbler nestlings that fledged out of the nest box HATCH_SUCCESS: proportion of eggs in the nest that hatched FLEDG_SUCCESS: proportion of the nestlings that fledged from the nest box HATCH_SUCCESS2: binary category where “0” indicates there was some, and “1” indicates there was no hatching failure FLEDG_SUCCESS2: binary category where “0” indicates there was some, and “1” indicates there was no nestling failure (i.e. nestling death) BHCO_PARASIT2: binary category where “0” indicates no cowbird parasitism, and “1” indicates there was cowbird parasitism BHCOE: number of cowbird eggs in clutch BHCOF: number of cowbird nestlings that fledged from the nest PAIRID: unique number that identifies a male and female warbler that are together at a nest box and this number is the same in a subsequent nesting attempt or year if the same male and female are together again FEMALE_ID: unique identifier for each female which represents her leg band combination. Each letter represents a band with letters preceding the hyphen being on the right leg and after the hyphen the left leg FEM_AGE: binary category where “0” indicates a 1-year-old bird and “1” indicates a >1-year-old bird FEMALE_BREEDING_ATTEMPT: “1” indicates first, “2” indicates second,……..breeding attempt within a given year SECOND_ATTEMPT: for any female that fledged a brood in a given year, binary category where “0” represents that they did not, and “1” indicates that they did attempt a second brood that year F_TOT_PROWF: total reproductive output (number of warbler fledglings produced) for a given female in a given year MALE_ID: unique identifier for each male which represents his leg band combination. Each letter represents a band with letters preceding the hyphen being on the right leg and after the hyphen the left leg MALE_AGE2: binary category where “0” indicates a 1-year-old bird and “1” indicates a >1-year-old bird Provisioning_rate: total number of food provisions per nestling per hour by male and female warbler combined BROOD_MASS: average nestling mass (g) for the brood BROOD_TARSUS: average nestling tarsus length (mm) for the brood Brood_condition: unit-less index of nestling condition that uses the residuals of the BROOD_MASS/BROOD_TARSUS relationship A period (“.”) represents where data were not collected, not available, or because individual nest or female did not qualify for consideration of a category assignment.

This is the data set from the published manuscript 'Vertebrate scavenger guild composition and utilization of carrion in an East Asian temperate forest' by Inagaki et al.

The dataset consists of two types of data: the estimate of land productivity (the maximum productivity, MP) and the estimate of land that has low productivity for any major crops planted in the Contiguous United States and then may be available for growing bioenergy crops (the marginal land, ML). All data items are in GeoTiff format, under the World Geodetic System (WGS) 84 project, and with a resolution of 0.0020810045 degree (~250 m). The MP values are calculated based on machine learning model estimated yields of major crops in the CONUS, and its expected value (MP_mean.tif), and associated uncertainty (MP_IDP.tif). The ML availability data have two versions: a deterministic version and a version with uncertainty. The deterministic MLs are determined as the land pixels with expected MP values falling in the range defined in the following criteria, and the MLs with uncertainty are determined as the probability that the MP value of a land pixel falls in the range defined in the following criteria: Criteria_____Description S1________ Current crop and pasture land with MP <= P50 S2________ Current crop and pasture land with MP <= P25 S3________ S1 + current grass and shrub land with P25 < MP < P50 S4________ S2 + current grass and shrub land with P10 < MP < P25 Economic__ Current crop and pasture land with potential profitability < 0 Here P10, P25 and P50 are the 10th, 25th and 50th percentile of crop MP values

The Cline Center Historical Phoenix Event Data covers the period 1945-2019 and includes several million events extracted from 18.9 million news stories. This data was produced using the state-of-the-art PETRARCH-2 software to analyze content from the New York Times (1945-2018), the BBC Monitoring's Summary of World Broadcasts (1979-2019) and the Central Intelligence Agency’s Foreign Broadcast Information Service (1995-2004). It documents the agents, locations, and issues at stake in a wide variety of conflict, cooperation and communicative events in the CAMEO ontology. The Cline Center produced this data with the generous support of Linowes Fellow and Faculty Affiliate Prof. Dov Cohen and help from our academic and private sector collaborators in the Open Event Data Alliance (OEDA).

Data files associated with the assembly of mitochondrial minicircles from five species of parasitic lice. This includes data from four species in the genus Columbicola and from the human louse (Pediculus humanus). The files include FASTA sequences for all five species, reference sequences for read mapping approaches, resulting contigs produced by various assembly approaches, and alignments of human louse minicircles mapped to published sequences of the same species.

This is the data set associated with the manuscript titled "Extensive host-switching of avian feather lice following the Cretaceous-Paleogene mass extinction event." Included are the gene alignments used for phylogenetic analyses and the cophylogenetic input files.

These are the alignments of transcriptome data used for the analysis of members of Heteroptera. This dataset is analyzed in "Deep instability in the phylogenetic backbone of Heteroptera is only partly overcome by transcriptome-based phylogenomics" published in Insect Systematics and Diversity.

Dataset providing calculation of a Competition Index (CI) for Late Pleistocene carnivore guilds in Laos and Vietnam and their relationship to humans. Prey mass spectra, Prey focus masses, and prey class raw data can be used to calculate the CI following Hemmer (2004). Mass estimates were calculated for each species following Van Valkenburgh (1990). Full citations to methodological papers are included as relationships with other resources

Nest survival and Fledgling production data for Bell's Vireo and Willow Flycatcher nests.

This data describes habitat use, availability, landscape level influences, and daily movement of dabbling ducks in the Wabash River Valley of southeastern Illinois and southwestern Indiana. It contains triangulated locations of individual ducks, associated habitat assignments of those locations, flood survey data to determine water availability, and randomly generated points to assess landscape level questions.

VCF files used to analyze a novel filtering tool VEF, presented in the article "VEF: a Variant Filtering tool based on Ensemble methods".

This repository includes scripts and datasets for the paper, "Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss."

This repository includes scripts and datasets for the paper, "FastMulRFS: Statistically consistent polynomial time species tree estimation under gene duplication."

This dataset accompanies the paper "STREETS: A Novel Camera Network Dataset for Traffic Flow" at Neural Information Processing Systems (NeurIPS) 2019. Included are: *Over four million still images form publicly accessible cameras in Lake County, IL. The images were collected across 2.5 months in 2018 and 2019. *Directed graphs describing the camera network structure in two communities in Lake County. *Documented non-recurring traffic incidents in Lake County coinciding with the 2018 data. *Traffic counts for each day of images in the dataset. These counts track the volume of traffic in each community. *Other annotations and files useful for computer vision systems. Refer to the accompanying "readme.txt" or "readme.pdf" for further details.

Human annotations of randomly selected judged documents from the AP 88-89, Robust 2004, WT10g, and GOV2 TREC collections. Seven annotators were asked to read documents in their entirety and then select up to ten terms they felt best represented the main topic(s) of the document. Terms were chosen from among a set sampled from the document in question and from related documents.

This dataset contains collected and aggregated network information from NCSA’s Blue Waters system, which is comprised of 27,648 nodes connected via Cray Gemini* 3D torus (dimension 24x24x24) interconnect, from Jan/01/2017 to May/31/2017. Network performance counters for links are exposed via Cray's gpcdr (<a href="https://github.com/ovis-hpc/ovis/wiki/gpcdr-kernel-module">https://github.com/ovis-hpc/ovis/wiki/gpcdr-kernel-module</a>) kernel module. Lightweight Distributed Metric Service ([LDMS](<a href="https://github.com/ovis-hpc/ovis">https://github.com/ovis-hpc/ovis</a>)) is used to sampled the performance counters at 60 second intervals. Please read "README.md" file. <b>Acknowledgement:</b> This dataset is collected as a part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications.

Data used for network analyses. deduplicated nodes.csv - List of all nodes in the network. Each node represents a paper. Column headings: ID, Authors, Title, Year Descriptions of column headings: ID - ID for the paper/node. IDs follow the following conventions: - A00 represents the retracted Matsuyama paper. - F### represents a first-generation citation that directly cites the retracted Matsuyama paper. - F###S### represents a second-generation citation that does not cite the retracted Matsuyama paper but that cites some first-generation citation (where F### is one of the first-generation articles it cites). Authors - Authors of the paper Title - Title of the paper (some in Unicode) Year - Year of publication of the paper; Either a 4-digit year or NA (which indicates that the first data source we got it from either did not provide a year, or provided a year that we deemed unreliable) NOTE: Authors/Title/Year were taken primarily from Google Scholar (since it had the larger number of items) with unique items from Web of Science added. ------- deduplicated edges.csv - List of all edges in the network. Each edge represents a citation between two papers. Column headings: from, to Descriptions of column headings: from - ID for the cited paper. This is what the citation goes FROM. to - ID for the citing paper. This is what the citation goes TO. NOTE: All IDs are from deduplicated nodes.csv and follow the conventions above. ------- nodesFG.txt - List of the IDs for the 135 first-generation citations, from 2005 (when Matsuyama was published) through 2018. ------- nodesSGnotFG.txt - List of the IDs for the 2559 second-generation citations that are not first-generation citations from 2005 (when Matsuyama was published), through 2018 -------

We are sharing the tweet IDs of four social movements: #BlackLivesMatter, #WhiteLivesMatter, #AllLivesMatter, and #BlueLivesMatter movements. The tweets are collected between May 1st, 2015 and May 30, 2017. We eliminated the location to the United States and focused on extracting the original tweets, excluding the retweets. Recommended citations for the data: Rezapour, R. (2019). Data for: How do Moral Values Differ in Tweets on Social Movements?. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9614170_V1 and Rezapour, R., Ferronato, P., and Diesner, J. (2019). How do moral values differ in tweets on social movements?. In 2019 Computer Supported Cooperative Work and Social Computing Companion Publication (CSCW’19 Companion), Austin, TX.

Raw MD simulation trajectory, input and configuration files, SEM current data, and experimental raw data accompanying the publication, "Electrical recognition of the twenty proteinogenic amino acids using an aerolysin nanopore". README.md contains a description of all associated files.

We summarize peer reviewed literature reporting associations between for three soil quality indicators (SQIs) (β-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) and crop yield and greenhouse gas emissions. Peer-reviewed articles published between January of 1990 and May 2018 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: “β-glucosidase”, “permanganate oxidizable carbon”, “active carbon”, “readily oxidizable carbon”, or “fluorescein diacetate hydrolysis”, together with one or more of the following: “crop yield”, “productivity”, “greenhouse gas’, “CO2”, “CH4”, or “N2O”. Meta-data for records include the following descriptor variables and covariates useful for scoring function development: 1) identifying factors for the study site (location, duration of the experiment), 2) soil textural class, pH, and SOC, 3) depth of soil sampling, 4) units used in published works (i.e.: equivalent mass, concentration), 5) SQI abundances and measured ecosystem functions, and 6) summary statistics for correlation between SQIs and functions (yield and greenhouse gas emissions). *Note: Blank values in tables are considered unreported data.

Dataset compiled by Yushu Xia and Michelle Wander for the Soil Health Institute. Data were recovered from peer reviewed literature reporting results for three soil quality indicators (SQIs) (β-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) in terms of their relative response to management where soils under grassland cover, no-tillage, cover crops, residue return and organic amendments were compared to conventionally managed controls. Peer-reviewed articles published between January of 1990 and May 2018 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: “β-glucosidase”, “permanganate oxidizable carbon”, “active carbon”, “readily oxidizable carbon”, and “fluorescein diacetate hydrolysis”, together with one or more of the following: “management practice”, “tillage”, “cover crop”, “residue”, “organic fertilizer”, or “manure”. Records were tabulated to compare SQI abundance in soil maintained under a control and soil aggrading practice with the intent to contribute to SQI databases that will support development of interpretive frameworks and/or algorithms including pedo-transfer functions relating indicator abundance to management practices and site specific factors. Meta-data include the following key descriptor variables and covariates useful for development of scoring functions: 1) identifying factors for the study site (location, year of initiation of study and year in which data was reported), 2) soil textural class, pH, and SOC, 3) depth and timing of soil sampling, 4) analytical methods for SQI quantification, 5) units used in published works (i.e. equivalent mass, concentration), 6) SQI abundances, and 7) statistical significance of difference comparisons. *Note: Blank values in tables are considered unreported data.

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.

Supporting secondary data used in a manuscript currently in submission regarding the invasion dynamics of the asian tiger mosquito, Aedes albopictus, in the state of Illinois

Filtered trophallaxis interactions for two honeybee colonies, each containing 800 worker bees and one queen. Each colony consists of bees that were administered a juvenile hormone analogy, a vehicle treatment, or a sham treatment to determine the effect of colony perturbation on the duration of trophallaxis interactions. Columns one and two display the unique identifiers for each bee involved in a particular trophallaxis exchange, and columns three and four display the Unix timestamp of the beginning/end of the interaction (in milliseconds), respectively.<br /><b>Note</b>: the queen interactions were omitted from the uploaded dataset for reasons that are described in submitted manuscript. Those bees that performed poorly are also omitted from the final dataset.