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This dataset contains the data related to Chapter 2 of Iacaruso, N. (2026) "EVALUATING ENVIRONMENTAL DNA AS AN EARLY DETECTION METHOD FOR AQUATIC INVASIVE SPECIES". Doctoral Dissertation. University of Illinois Urbana-Champaign. This chapter will also be represented in Iacaruso et al. (2025) "Environmental DNA metabarcoding for monitoring fish biodiversity in remote lakes". North American Journal of Fisheries Management. (Forthcoming). The files contain the eDNA metabarcoding sequences from sampling Isle Royale lakes in 2021 and 2022, species read counts for each eDNA sample, and other information collected at each site.

Steady-state and dynamic gas exchange data for maize (B73), sugarcane (CP88-1762) and sorghum (Tx430)

This repository includes scripts and datasets for the paper, "Accurate Large-scale Phylogeny-Aware Alignment using BAli-Phy" submitted to Bioinformatics.

Dataset includes temperature data (local average April daily temperatures), first egg dates and reproductive output of Prothonotary Warblers breeding in southernmost Illinois, USA. Also included are arrival dates for warblers returning to breeding grounds from wintering grounds, and global temperature anomaly data for comparison with local temperatures. These data were used in the manuscript entitled "Warmer April Temperatures on Breeding Grounds Promote Earlier Nesting in a Long-Distance Migratory Bird, the Prothonotary Warbler" published in Frontiers in Ecology and Evolution. A rich text file is included with explanations of each variable in the dataset.

This dataset includes supporting data for our article 'Assessing long-term impacts of cover crops on soil organic carbon in the central U.S. Midwestern agroecosystems'. The dataset contains carbon fluxes and SOC benefits from cover crops at six cover crop experiment sites in Illinois with three rotation systems: (1) without-cover-crop (maize-soybean rotations), (2) non-legume-preceding-maize (maize-annual ryegrass-soybean-annual ryegrass rotations), and (3) legume-preceding-maize (maize-cereal rye-soybean-hairy vetch rotations). <b>*NOTE:</b> there should be 13 files + 1 readme file, instead of 15 files as mentioned in readme.

Terrorism is among the most pressing challenges to democratic governance around the world. The Responsible Terrorism Coverage (or ResTeCo) project aims to address a fundamental dilemma facing 21st century societies: how to give citizens the information they need without giving terrorists the kind of attention they want. The ResTeCo hopes to inform best practices by using extreme-scale text analytic methods to extract information from more than 70 years of terrorism-related media coverage from around the world and across 5 languages. Our goal is to expand the available data on media responses to terrorism and enable the development of empirically-validated models for socially responsible, effective news organizations. This particular dataset contains information extracted from terrorism-related stories in the Foreign Broadcast Information Service (FBIS) published between 1995 and 2013. It includes variables that measure the relative share of terrorism-related topics, the valence and intensity of emotional language, as well as the people, places, and organizations mentioned. This dataset contains 3 files: 1. "ResTeCo Project FBIS Dataset Variable Descriptions.pdf" A detailed codebook containing a summary of the Responsible Terrorism Coverage (ResTeCo) Project Foreign Broadcast Information Service (FBIS) Dataset and descriptions of all variables. 2. "resteco-fbis.csv" This file contains the data extracted from terrorism-related media coverage in the Foreign Broadcast Information Service (FBIS) between 1995 and 2013. It includes variables that measure the relative share of topics, sentiment, and emotion present in this coverage. There are also variables that contain metadata and list the people, places, and organizations mentioned in these articles. There are 53 variables and 750,971 observations. The variable "id" uniquely identifies each observation. Each observation represents a single news article. Please note that care should be taken when using "resteco-fbis.csv". The file may not be suitable to use in a spreadsheet program like Excel as some of the values get to be quite large. Excel cannot handle some of these large values, which may cause the data to appear corrupted within the software. It is encouraged that a user of this data use a statistical package such as Stata, R, or Python to ensure the structure and quality of the data remains preserved. 3. "README.md" This file contains useful information for the user about the dataset. It is a text file written in mark down language Citation Guidelines 1) To cite this codebook please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project Foreign Broadcast Information Service (FBIS) Dataset Variable Descriptions. Responsible Terrorism Coverage (ResTeCo) Project Foreign Broadcast Information Service (FBIS) Dataset. Cline Center for Advanced Social Research. December 16. University of Illinois Urbana-Champaign. doi: https://doi.org/10.13012/B2IDB-6360821_V1 2) To cite the data please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project Foreign Broadcast Information Service (FBIS) Dataset. Cline Center for Advanced Social Research. December 16. University of Illinois Urbana-Champaign. doi: https://doi.org/10.13012/B2IDB-6360821_V1

Terrorism is among the most pressing challenges to democratic governance around the world. The Responsible Terrorism Coverage (or ResTeCo) project aims to address a fundamental dilemma facing 21st century societies: how to give citizens the information they need without giving terrorists the kind of attention they want. The ResTeCo hopes to inform best practices by using extreme-scale text analytic methods to extract information from more than 70 years of terrorism-related media coverage from around the world and across 5 languages. Our goal is to expand the available data on media responses to terrorism and enable the development of empirically-validated models for socially responsible, effective news organizations. This particular dataset contains information extracted from terrorism-related stories in the Summary of World Broadcasts published between 1979 and 2019. It includes variables that measure the relative share of terrorism-related topics, the valence and intensity of emotional language, as well as the people, places, and organizations mentioned. This dataset contains 3 files: 1. "ResTeCo Project SWB Dataset Variable Descriptions.pdf" A detailed codebook containing a summary of the Responsible Terrorism Coverage (ResTeCo) Project BBC Summary of World Broadcasts (SWB) Dataset and descriptions of all variables. 2. "resteco-swb.csv" This file contains the data extracted from terrorism-related media coverage in the BBC Summary of World Broadcasts (SWB) between 1979 and 2019. It includes variables that measure the relative share of topics, sentiment, and emotion present in this coverage. There are also variables that contain metadata and list the people, places, and organizations mentioned in these articles. There are 53 variables and 438,373 observations. The variable "id" uniquely identifies each observation. Each observation represents a single news article. Please note that care should be taken when using "resteco-swb.csv". The file may not be suitable to use in a spreadsheet program like Excel as some of the values get to be quite large. Excel cannot handle some of these large values, which may cause the data to appear corrupted within the software. It is encouraged that a user of this data use a statistical package such as Stata, R, or Python to ensure the structure and quality of the data remains preserved. 3. "README.md" This file contains useful information for the user about the dataset. It is a text file written in markdown language Citation Guidelines 1) To cite this codebook please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project BBC Summary of World Broadcasts (SWB) Dataset Variable Descriptions. Responsible Terrorism Coverage (ResTeCo) Project BBC Summary of World Broadcasts (SWB) Dataset. Cline Center for Advanced Social Research. December 16. University of Illinois Urbana-Champaign. doi: https://doi.org/10.13012/B2IDB-2128492_V1 2) To cite the data please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project Summary of World Broadcasts (SWB) Dataset. Cline Center for Advanced Social Research. December 16. University of Illinois Urbana-Champaign. doi: https://doi.org/10.13012/B2IDB-2128492_V1

Femoral skeletal traits (cross-sectional properties, maximum distal metaphyseal breadth of the femur, and maximum superior/inferior femoral head diameter) of 219 Taiwanese subadult individuals (aged 0 to 17) as used in the manuscript "Allometric scaling and growth: evaluation and applications in subadult body mass estimation."

This data set documents bat activity (counts per detector-night per phonic group) and bat diversity (number of bat species per detector-night) in relation to distance to the nearest forested corridor in a row crop agriculture dominated landscape and in relation to relative crop pest abundance. This data set was used to assess if bats were homogeneously distributed over a near-uninterrupted agricultural landscape and to assess the importance of forested corridors and the presence of pest species on their distribution across the landscape. Data was collected with 50 AudioMoth bat detectors along 10 transects, with each transect having 5 detectors. The transects started at a forest corridor and extended out for 4 km into uninterrupted row crop agriculture. Pest abundance was extrapolated from data collected in the same county during the same time as the study. Potentially important weather covariates were extracted from the nearest operational weather station.

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.

This dataset contains the .npy and .pkl files required to reproduce the plots in the study.

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.

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".

This dataset contains raw data of plasma glucose, insulin, c-peptide, GLP-1, and FGF21 collected as part of a study aimed to study alcohol pharmacokinetics in women who underwent metabolic surgery.

High-speed X-ray videos of four E. abruptus specimens recorded at the Advanced Photron Source (Argonne National lab) in the Summer of 2018 and corresponding position data of landmarks tracked during the motion. See readme file for more details.

This dataset contains the publication record of 6429 computer science researchers collected from the Microsoft Academic dataset provided through their Knowledge Service API (http://bit.ly/microsoft-data).

This is the dataset used in the BioScience publication of the same name. More information about this dataset: Interested parties can request data from the Critical Trends Assessment Program, which was the source for the data on natural areas in this study. More information on the program and data requests can be obtained by visiting the program webpage. Critical Trends Assessment Program, Illinois Natural History Survey. http://wwx.inhs.illinois.edu/research/ctap/ These spatial datasets were used for analyses: Illinois Natural History Survey. 2003. Illinois GAP analysis land cover classification 1999-2000, 1:100 000 Scale, Raster Digital Data, Version 2.0. Champaign, IL, USA. Illinois State Geological Survey. 1995. Illinois Landcover Thematic Map Coverage Map 1991-1995. Champaign, IL, USA. Illinois State Geological Survey. 2001. Illinois Landcover Thematic Map Coverage Map 1999-2000. Champaign, IL, USA. USDA National Agricultural Statistics Service Cropland Data Layer. 1999-2015. Published crop-specific data layer [Online]. Available at https://nassgeodata.gmu.edu/CropScape/. USDA-NASS, Washington, DC. Information on agricultural practices and landcover changes were derived from the following U.S. Department of Agriculture (USDA) resources: USDA Economic Research Service. 2016. Adoption of Genetically Engineered Crops in the U.S. Available at http://www.ers.usda.gov/data-products/. USDA-ERS, Washington, DC. USDA Natural Resources Conservation Service. 2015. Summary Report: 2012 National Resources Inventory. https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcseprd396218.pdf. USDA-NRCS, Washington, DC, and Center for Survey Statistics and Methodology, Iowa State University, Ames, Iowa.

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".

Data from census of peer-reviewed papers discussing nosZ and published from 2013 to 2019. These data were reported in the manuscript titled, "Beyond denitrification: the role of microbial diversity in controlling nitrous oxide reduction and soil nitrous oxide emissions" published in Global Change Biology as an Invited Report.

Exploiting nature’s catalysts for non-natural transformations that are inaccessible to chemocatalysis is highly desirable but challenging. On the one hand, the widespread nicotinamide-dependent oxidoreductases have not been utilized for single-electron-transfer-induced bimolecular cross-couplings; on the other, the addition of catalytic asymmetric radical conjugate to terminal alkenes remains a challenge owing to strong racemic background reaction and unselective termination of prochiral radical species. Here we report a chemomimetic biocatalysitic approach for construction of alpha-carbonyl stereocentres via an unnatural intermolecular conjugate addition of N-(acyloxy)phthalimides-derived radicals with acceptor-substituted terminal alkenes, by combination of visible-light excitation and nicotinamide-dependent ketoreductases (KREDs). Based on protein crystal structure, we engineered KREDs via a semi-rational mutagenesis strategy to improve reaction outcomes with a small and high-quality variants library. Mechanistic investigations combining wet experiments, crystallographic studies and computational simulations demonstrate that the repurposed biocatalyst can suppress racemic background reaction and unselected side reactions, yielding enantioselectivity that is challenging to achieve by chemocatalysis.

Video footage of an Eastern Box Turtle (Terrapene carolina carolina) partially predating a Field Sparrow nest (Spizella pusilla) at 0845 h on the 31 of May 2020. Please note that the date on the video footage is incorrect due to user error, but the time is correct.

Perennial crops have been the focus of bioenergy research and development for their sustainability benefits associated with high soil carbon (C) and reduced nitrogen (N) requirements. However, perennial crops mature over several years and their sustainability benefits can be negated through land reversion. A photoperiod‐sensitive energy sorghum (Sorghum bicolor) may provide an annual crop alternative more ecologically sustainable than maize (Zea mays) that can more easily integrate into crop rotations than perennials, such as miscanthus (Miscanthus × giganteus). This study presents an ecosystem‐scale comparison of C, N, water and energy fluxes from energy sorghum, maize and miscanthus during a typical growing season in the Midwest United States. Gross primary productivity (GPP) was highest for maize during the peak growing season at 21.83 g C m−2 day−1, followed by energy sorghum (17.04 g C m−2 day−1) and miscanthus (15.57 g C m−2 day−1). Maize also had the highest peak growing season evapotranspiration at 5.39 mm day−1, with energy sorghum and miscanthus at 3.81 and 3.61 mm day−1, respectively. Energy sorghum was the most efficient water user (WUE), while maize and miscanthus were comparatively similar (3.04, 1.75 and 1.89 g C mm−1 H2O, respectively). Maize albedo was lower than energy sorghum and miscanthus (0.19, 0.26 and 0.24, respectively), but energy sorghum had a Bowen ratio closer to maize than miscanthus (0.12, 0.13 and 0.21, respectively). Nitrous oxide (N2O) flux was higher from maize and energy sorghum (8.86 and 12.04 kg N ha−1, respectively) compared with miscanthus (0.51 kg N ha−1), indicative of their different agronomic management. These results are an important first look at how energy sorghum compares to maize and miscanthus grown in the Midwest United States. This quantitative assessment is a critical component for calibrating biogeochemical and ecological models used to forecast bioenergy crop growth, productivity and sustainability.

A mechanistic functional structural plant model. The .gsz file includes a parameterised maize and soybean to be used in GRoIMP software https://grogra.de/. The current model is parameterised to maize cultivar DKC63-21RIB and soybean cultivar AG36X6 for the 2019 growing season in Champaign, IL USA.

The Cline Center Historical Phoenix Event Data covers the period 1945-2019 and includes 8.2 million events extracted from 21.2 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), the Wall Street Journal (1945-2005), 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 Conflict and Mediation Event Observations (CAMEO) ontology. The Cline Center produced these 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). For details on the CAMEO framework, see: Schrodt, Philip A., Omür Yilmaz, Deborah J. Gerner, and Dennis Hermreck. "The CAMEO (conflict and mediation event observations) actor coding framework." In 2008 Annual Meeting of the International Studies Association. 2008. http://eventdata.parusanalytics.com/papers.dir/APSA.2005.pdf Gerner, D.J., Schrodt, P.A. and Yilmaz, O., 2012. Conflict and mediation event observations (CAMEO) Codebook. http://eventdata.parusanalytics.com/cameo.dir/CAMEO.Ethnic.Groups.zip For more information about PETRARCH and OEDA, see: http://openeventdata.org/

Raw data of Auchenorrhyncha (Hemiptera) species presence and abundance from samples collected as part of Morgan Brown's M.S. thesis entitled "Investigating changes in Auchenorrhyncha (Hemiptera) communities in Illinois prairies over 25 years." Collection_Events_MBrown.pdf contains information that corresponds to each collection event code listed in the raw data files, including coordinates, date of collection, collection method, and name of collector. Each CSV file contains Auchenorrhyncha species presence and abundance data from each sampling area in Illinois: Route 45 Railroad Prairie, Richardson Wildlife Foundation, Mason County nature preserves, and Twelve Mile Prairie. Variables included in the CSV files include: Family: Taxonomic family to which each species belongs Subfamily: Taxonomic subfamily to which each species belongs Tribe: Taxonomic tribe to which each species belongs Species: Lowest taxonomic level to which individuals were identified The first row of column 5 to the end are collection event codes which correspond to each code listed in the PDF * New in V2: The CSV files originally uploaded in V1 contained outdated species names. V2 provides updated CSV files with the corrected names. * New in V3: There were some inconsistencies in the collection event codes listed in the PDF and CSV files uploaded in V1 and V2. V3 provides updated PDF and CSV files with the corrected codes. File update status: Collection_Events_MBrown_V2.pdf -> updated in this V3 (in V2 it remained the same as in V1 but now is updated in V3) MasonCounty_RawData_V3.csv -> updated in this V3 RichardsonWildlifeFoundation_RawData_V2.csv -> remains the same as in V2 Route45_RawData_V3.csv -> updated in this V3 TwelveMilePrairie_RawData_V3.csv -> updated in this V3