Displaying datasets 176 - 200 of 478 in total

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published: 2021-02-10
 
This dataset consists of microclimatic temperature and vegetation structure maps at a 3-meter spatial resolution across the Great Smoky Mountains National Park. Included are raster models for sub-canopy, near-surface, minimum and maximum temperature averaged across the study period, season, and month during the growing season months of March through November from 2006-2010. Also available are the topographic and vegetation inputs developed for the microclimate models, including LiDAR-derived vegetation height, LiDAR-derived vegetation structure within four height strata, solar insolation, distance-to-stream, and topographic convergence index (TCI).
keywords: microclimate buffering; forest vegetation structure; temperature; Appalachian Mountains; climate downscaling; understory; LiDAR
published: 2021-08-28
 
Metabolite identifications and profiles of liver samples from 22 day old male and female pigs from gilt that exposed to porcine reproductive and respiratory syndrome virus (P) or not (C) that were weaned at 21 days of age (W) or not (N). Profiles were obtained by University of Illinois Carver Metabolomics Center. Spectrum for each sample was acquired using a gas chromatography mass spectrometry system consisting of an Agilent 7890 gas chromatograph, an Agilent 5975 MSD, and an HP 7683B auto sampler.
keywords: gas chromatography; mass spectrometry; maternal immune activation; weaning; liver
published: 2021-03-15
 
Dataset associated with "Hiding in plain sight: genetic confirmation of putative Louisiana Fatmucket Lampsilis hydiana in Illinois" as submitted to Freshwater Mollusk Biology and Conservation by Stodola et al. Images are from cataloged specimens from the Illinois Natural History Survey (INHS) Mollusk Collection in Champaign, Illinois that were used for genetic research. File names indicate the species as confirmed in Stodola et al. (i.e., Lampsilis siliquoidea or Lampsilis hydiana) followed by the INHS Mollusk Collection catalog number, followed by the individual specimen number, followed by shell view (interior or exterior). If no specimen number is noted in the file name, there is only one specimen for that catalog number. For example: Lsiliquoidea_46515_1_2_3_exterior. Images were created by photographing specimens on a metric grid in an OrTech Photo-e-Box Plus with a Nikon D610 single lens reflex camera using a 60mm lens. Post-processing of images (cropping, image rotation, and auto contrast) occurred in Adobe Photoshop and saved as TIFF files using no image compression, interleaved pixel order, and IBM PC Byte Order. One additional partial lot, INHS Mollusk Catalog No. 37059 (shown with both interior and exterior view in one image), is included for reference but was not genetically sequenced. A .csv file contains an index of all specimens photographed. SPECIES: species confirmed using genetic analyses GENE: cox1 or nad1 mitochondrial gene ACCESSION: GenBank accession number INHS CATALOG NO: Illinois Natural History Survey Mollusk Collection Catalog number WATERBODY: waterbody where specimen was collected PUTATIVE SPECIES: species determination based on morphological characters prior to genetic analysis Phylogenetic sequence data (.nex files) were aligned using BioEdit (Hall, T.A. 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series 41:95-98.). Pertinent methodology for the analysis are contained within the manuscript submittal for Stodola et al. to Freshwater Mollusk Biology and Conservation. In these files, "N" is a standard symbol for an unknown base.
keywords: Lampsilis hydiana; Lampsilis siliquoidea; unionid; Louisiana Fatmucket; Fatmucket; genetic confirmation
published: 2021-02-01
 
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.
keywords: clean energy; ozone; particulates
published: 2021-01-27
 
*This is the third version of the dataset*. New changes in this 3rd version: <i>1.replaces simulations where the initial condition consists of a sinusoidal channel with topographic perturbations with simulations where the initial condition consists of a sinusoidal channel without topographic perturbations. These simulations better illustrate the transformation of a nondendritic network into a dendritic one. 2. contains two additional simulations showing how total domain size affects the landscape's dynamism. 3. changes dataset title to reflect the publication's title</i> This dataset contains data from 18 simulations using a landscape evolution model. A landscape evolution model simulates how uplift and rock incision shape the Earth's (or other planets) surface. To date, most landscape evolution models exhibit "extreme memory" (paper: https://doi.org/10.1029/2019GL083305 and dataset: https://doi.org/10.13012/B2IDB-4484338_V1). Extreme memory in landscape evolution models causes initial conditions to be unrealistically preserved. This dataset contains simulations from a new landscape evolution model that incorporates a sub-model that allows bedrock channels to erode laterally. With this addition, the landscapes no longer exhibit extreme memory. Initial conditions are erased over time, and the landscapes tend towards a dynamic steady state instead of a static one. The model with lateral erosion is named LEM-wLE (Landscape Evolution Model with Lateral Erosion) and the model without lateral erosion is named LEM-woLE (Landscape Evolution Model without Lateral Erosion). There are 16 folders in total. Here are the descriptions: <i>>LEM-woLE_simulations:</i> This folder contains simulations using LEM-woLE. Inside the folder are 5 subfolders containing 100 elevation rasters, 100 drainage area rasters, and 100 plots showing the slope-area relationship. Elevation depicts the height of the landscape, and drainage area represents a contributing area that is upslope. Each folder corresponds to a different initial condition. Driver files and code for these simulations can be found at https://github.com/jeffskwang/LEM-wLE. <i>>MOVIE_S#_data:</i> There are 13 data folders that contain raster data for 13 simulations using LEM-wLE. Inside each folder are 1000 elevation rasters, 1000 drainage area rasters, and 1000 plots showing the slope-area relationship. Driver files and code for these simulations can be found at https://github.com/jeffskwang/LEM-wLE. <i>>movies_mp4_format:</i> For each data folder there are 3 movies generated that show elevation (a), drainage area (b), and erosion rates (c). These files are formatted in the mp4 format and are best viewed using VLC media player (https://www.videolan.org/vlc/index.html). <i>>movies_wmv_format:</i> This folder contains the same movies as the "movies_mp4_format" folder, but they are in a wmv format. These movies can be viewed using Windows media player or other Windows platform movie software. Here are the captions for the 13 movies: Movie S1. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Sinusoidal channel without randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 1. Movie S2. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Inclined with small, randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 1. Movie S3. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Inclined with large, randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 1. Movie S4. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: V-shaped valley with randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 1. Movie S5. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Sinusoidal channel with randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 1. Movie S6. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Sinusoidal channel without randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 0.25. Movie S7. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Sinusoidal channel without randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 0.5. Movie S8. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Sinusoidal channel without randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 0.75. Movie S9. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Flat with randomized perturbations. Boundary Condition: 1 open boundary at the bottom of the domain, and 3 closed boundaries elsewhere. KL/KV = 1. Movie S10. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Flat with randomized perturbations. Boundary Condition: 2 open boundaries at the top and bottom of the domain, and 2 closed boundaries on the left and right sides. KL/KV = 1. Movie S11. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Flat with randomized perturbations. Boundary Condition: 4 open boundaries. KL/KV = 1. Movie S12. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Flat with randomized perturbations. Boundary Condition: 4 open boundaries. KL/KV = 1. Compared to Movie S11, the length of the domain is 50% shorter, decreasing the total domain area. Movie S13. 200 MYR (1,000 RUs eroded) simulation showing elevation (a), logarithm of drainage area (b), and change in elevation (c). Initial Condition: Flat with randomized perturbations. Boundary Condition: 4 open boundaries. KL/KV = 1. Compared to Movie S11, the length of the domain is 50% longer, increasing the total domain area. The associated publication for this dataset has not yet been published, and we will update this description with a link when it is.
keywords: landscape evolution; drainage networks; lateral migration; geomorphology
published: 2021-01-25
 
Dataset associated with Zenzal et al. Oikos submission: Retreat, detour, or advance? Understanding the movements of birds confronting the Gulf of Mexico. https://doi.org/10.1111/oik.07834 Four CSV files were used for analysis and are related to the following subsections under the “Statistics” heading in the “Materials and Methods” section of the journal article: 1. Departing the Edge = “AIC Analysis.csv” 2. Comparing Retreating to Advancing = “Advance and Retreat Analysis.csv” and “Wind Data at Departure.csv” 3. Food Abundance = “Fruit Data.csv” and “Arthropod Data.csv” <b>Description of variables:</b> Year: the year in which data were collected. Departure: the direction in which an individual departed the Bon Secour National Wildlife Refuge. “North” indicates an individual that departed ≥315° or <45°; “Circum” indicates an individual that departed east (45 – 134°) or west ( 225 – 314°); “Trans” indicates an individual that departed south (135 – 224°). Age: the age of an individual at capture. Individuals were aged as hatch year (HY) or after hatch year (AHY) according to Pyle (1997; see related article for full citation). Fat: the fat score of an individual at capture. Individuals were scored on a 6-point scale ranging from 0-5 following Helms and Drury (1960; see related article for full citation). Species: the standardized four letter alphabetic code used as an abbreviation for English common names of North American Birds. SWTH: Catharus ustulatus; REVI: Vireo olivaceus; INBU: Passerina cyanea; WOTH: Hylocichla mustelina; RTHU: Archilochus colubris. FTM_SD: stopover duration or number of days between first capture and departure from automated radio telemetry system coverage at the Bon Secour National Wildlife Refuge. TMB_SD: stopover duration or number of days between first and last detection from automated radio telemetry systems north of Mobile Bay, AL, USA. Mean speed north (km/hr): the northbound travel speed of individuals retreating from the Bon Secour National Wildlife Refuge by determining the time when the signal strength indicated the bird was directly east or west of the automated telemetry system and dividing the amount of time it took for an individual to move in an assumed straight path between the Refuge systems and those north of Mobile Bay, AL, USA. Mean speed south (km/hr): the southbound travel speed of individuals advancing from north of Mobile Bay, AL, USA by determining the time when the signal strength indicated the bird was directly east or west of the automated telemetry system and dividing the amount of time it took for an individual to move in an assumed straight path between the Refuge systems and those north of Mobile Bay, AL, USA. LN_FTM_DEP_TIME: the natural log of departure time from the Bon Secour National Wildlife Refuge. Departure time is defined as the number of hours before or after civil twilight. LN_TMB_DEP_TIME: the natural log of departure time from north of Mobile Bay, AL, USA. Departure time is defined as the number of hours before or after civil twilight. Paired_FTM_DEP_TIME: the departure time or number of hours before or after civil twilight from Bon Secour National Wildlife Refuge. Paired_TMB_DEP_TIME: the departure time or number of hours before or after civil twilight from north of Mobile Bay, AL, USA. Wind Direction: the direction from which the wind originated at the Bon Secour National Wildlife Refuge on nights when individuals were departing. “N” indicates winds from the north (≥315° or <45°); “E” indicates winds from the east (45 – 134°); “W” indicates winds from the west ( 225 – 314°); “S” indicates winds from the south (135 – 224°). Wind Speed (m/s): the wind speed on nights when individuals were departing the Bon Secour National Wildlife Refuge. Group: the direction the bird was traveling under specific wind conditions. Northbound individuals traveled north from Bon Secour National Wildlife Refuge. Southbound individuals traveled south from habitats north of Mobile Bay, AL, USA. Fruit: weekly mean number of ripe fruit per meter. Site: the site from which the data were collected. FTM is located within the Bon Secour National Wildlife Refuge. TMB is located within the Jacinto Port Wildlife Management Area. DOY: number indicating day of year (i.e., 1 January = 001….31 December = 365). Arthropod Biomass: estimated mean arthropod biomass from each sampling period. <b>Note:</b> Empty cells indicate unavailable data where applicable.
keywords: migratory birds; migration; automated telemetry; Gulf of Mexico
published: 2021-01-23
 
Data sets from "Comparing Methods for Species Tree Estimation With Gene Duplication and Loss." It contains data simulated with gene duplication and loss under a variety of different conditions.
keywords: gene duplication and loss; species-tree inference;
published: 2021-09-06
 
Airglow images and Meteor radar data used in the paper "Mesospheric gravity wave activity estimated via airglow imagery, multistatic meteor radar, and SABER data taken during the SIMONe–2018 campaign".
keywords: airglow; meteor radar; gravity waves; momentum flux;
published: 2016-05-16
 
This dataset contains the protein sequences and trees used to compare Non-Ribosomal Peptide Synthetase (NRPS) condensation domains in the AMB gene cluster and was used to create figure S1 in Rojas et al. 2015. Instead of having to collect representative sequences independently, this set of condensation domain sequences may serve as a quick reference set for coarse classification of condensation domains.
keywords: NRPS; biosynthetic gene cluster; antimetabolite; Pseudomonas; oxyvinylglycine; secondary metabolite; thiotemplate; toxin
published: 2020-05-04
 
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/
keywords: OEDA; Open Event Data Alliance (OEDA); Cline Center; Cline Center for Advanced Social Research; civil unrest; petrarch; phoenix event data; violence; protest; political; conflict; political science
published: 2019-08-29
 
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.
keywords: Cline Center for Advanced Social Research; civil unrest; Social Political Economic Event Dataset (SPEED); political; event data; war; conflict; protest; violence; social; SPEED; Cline Center; Political Science
published: 2020-12-16
 
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
keywords: Terrorism, Text Analytics, News Coverage, Topic Modeling, Sentiment Analysis
published: 2021-02-28
 
This dataset contains the RegCM4 simulations used in the article " Implementation of dynamic ageing of carbonaceous aerosols in regional climate model RegCM". This dataset was used to investigate the impact of a new aging parameterisation scheme implemented in a regional climate model RegCM4. The dataset contains two sets of simulations: Expt_fix and Expt_dyn. It consists of the seasonal mean and daily mean values of the variables that were used to create the visualizations of this study. The Expt_fix and Expt_dyn dataset contain 34 and 38 NetCDF files, respectively. The CERES_vs_2expts_new.mat file is the comparison between CERES shortwave downward flux at the surface and same model outputs from two experiments for clear sky and all sky conditions. -------------------------------------------------- The following information about the dataset was generated on 2021-01-08 by SUDIPTA GHOSH <b>GENERAL INFORMATION</b> <i>1. Date of data collection (single date, range, approximate date):</i> 2019-01-01 to 2019-12-31 <i>2. Geographic location of data collection:</i> Urbana-Champaign,Illinois, USA <i>3. Information about funding sources that supported the collection of the data:</i> This work is supported by the MoEFCC under the NCAP-COALESCE project [Grant No. 14/10/2014-CC]. The first author acknowledges DST-INSPIRE fellowship [IF150055] and Fulbright-Kalam Climate Doctoral fellowship. N. R. acknowledges funding from NSF AGS-1254428 and DOE grant DE-SC0019192. Department of Science and Technology, Funds for Improvement of Science and Technology infrastructure in universities and higher educational institutions (DST-FIST) grant (SR/FST/ESII-016/2014) are acknowledged for the computing support. <b>DATA & FILE OVERVIEW</b> <i>1. File List:</i> Expt_fix and Expt_dyn datasets contain the analysed seasonal means and daily means of the variables that have been used to create the visualizations of this study. Each of the Expt_fix and Expt_dyn datasets contains 34 and 38 NetCDF files, respectively. <i>2. Relationship between files, if important:</i> NA <i>3. Additional related data collected that was not included in the current data package:</i> No <b>METHODOLOGICAL INFORMATION</b> <i>1. Description of methods used for collection/generation of data: </i> The model RegCM4 code is freely available online from <a href="http://gforge.ictp.it/gf/project/regcm/">http://gforge.ictp.it/gf/project/regcm/</a>. The anthropogenic aerosol emissions considered for the simulations are taken from IIASA inventory. The data used can be easily accessed online <a href="http://clima-dods.ictp.it/regcm4/">http://clima-dods.ictp.it/regcm4/</a> website. TRMM observed precipitation data can be assessed from <a href="https://giovanni.gsfc.nasa.gov/giovanni/">https://giovanni.gsfc.nasa.gov/giovanni/</a> website. CRU temperature data is available at <a href="https://crudata.uea.ac.uk/cru/data/hrg/">https://crudata.uea.ac.uk/cru/data/hrg/</a>. CERES satellite surface shortwave downward fluxes are available at <a href="https://ceres.larc.nasa.gov/data/">https://ceres.larc.nasa.gov/data/</a> website. Input files for the RegCM4 model are archived in <a href="http://clima-dods.ictp.it/regcm4/">http://clima-dods.ictp.it/regcm4/</a> website. This dataset contains the RegCM4 simulations used in the article " Implementation of dynamic ageing of carbonaceous aerosols in regional climate model RegCM ". Two sets of simulations: Expt_fix and Expt_dyn consists of the output data . This dataset only contains the analysed seasonal mean and daily mean of the variables that have been used to create the visualizations of this study. Each of Expt_fix and Expt_dyn contains 34 and 38 NetCDF files respectively. This dataset was used to investigate the impact of a new aging parameterisation scheme implemented in a regional climate model RegCM4. <i>2. Methods for processing the data:</i> Seasonal Mean and daily average values were extracted from 6-hourly model output. <i>3. Instrument- or software-specific information needed to interpret the data:</i> CDO-1.7.1, Grads-2.0.a9, Matlab2016b <i>4. Standards and calibration information, if appropriate:</i> NA <i>5. Environmental/experimental conditions:</i> NA <i>6. Describe any quality-assurance procedures performed on the data:</i> NA <i>7. People involved with sample collection, processing, analysis and/or submission:</i> Sudipta Ghosh, Nicole Riemer, Graziano Giuliani, Filippo Giorgi, Dilip Ganguly, Sagnik Dey <b>DATA-SPECIFIC INFORMATION FOR: Expt_fix_data.tar.gz</b> <i>1. Number of variables:</i> 29 <i>2. Number of cases/rows:</i> NA <i>3. Variable List:</i> Mass concentration (Kg m-3) of BC, BC_HB, BC_HL, OC, OC_HB, OC_HL; Columnar burden (mg m-2)] of BC, BC_HL, BC_HB, OC; Dry deposition flux (mg m-2 day-1) of BC_HB, BC_HL, OC_HB, OC_HL; Wet deposition flux due washout (mg m-2 day-1) of BC_HB, BC_HL, OC_HB, OC_HL; Wet deposition flux due to rainout (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; AOD (unit less), precipitation (Kg m-2 s-1), temperature (K) , v-wind (m s-1), u-wind (m s-1), Surface shortwave downward flux (W m-2), Shortwave radiative forcing at the surface and top of atmosphere (W m-2) <b>DATA-SPECIFIC INFORMATION FOR: Expt_dyn_data.tar.gz</b> <i>1. Number of variables:</i> 30 <i>2. Number of cases/rows:</i> NA <i>3. Variable List:</i> Mass concentration (Kg m-3) of BC, BC_HB, BC_HL, OC, OC_HB, OC_HL; Columnar burden (mg m-2)] of BC, BC_HL, BC_HB, OC; Dry deposition flux (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; Wet deposition flux due washout (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; Wet deposition flux due to rainout (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; AOD (unit less); precipitation (Kg m-2 s-1); temperature (K); v-wind (m s-1); u-wind (m s-1); Surface shortwave downward flux (W m-2); Shortwave radiative forcing at the surface and top of atmosphere (W m-2); ageingscale (s-1) <b>DATA-SPECIFIC INFORMATION FOR: CERES_vs_2expts_new.mat</b> <i>1. Number of variables:</i> 12 <i>2. Number of cases/rows:</i> NA <i>3. Variable List:</i> Surface shortwave downward flux for clear sky (W/m-2) for CERES, Expt_fix, Expt_dyn (for winter JF and monsoon JJAS seasons); Surface shortwave downward flux for all sky conditions (W/m-2) for CERES, Expt_fix, Expt_dyn (for winter JF and monsoon JJAS seasons). <b>NOTE:</b> The following information applies for all three (3) files: <i> Missing data codes:</i> NA <i>Specialized formats or other abbreviations used:</i> NA
keywords: Carbonaceous aerosols; ageing parameterisation scheme; regional climate model; NetCDF
published: 2021-06-08
 
Dataset associated with Jones and Ward JAE-2020-0031.R1 submission: Pre-to post-fledging carryover effects and the adaptive significance of variation in wing development for juvenile songbirds. Excel CSV files with data used in analyses and file with descriptions of each column. The flight ability variable in this dataset was derived from fledgling drop tests, examples of which can be found in the related dataset: Jones, Todd M.; Benson, Thomas J.; Ward, Michael P. (2019): Flight Ability of Juvenile Songbirds at Fledgling: Examples of Fledgling Drop Tests. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2044905_V1.
keywords: fledgling; wing development; life history; adaptive significance; post-fledging; songbirds
published: 2021-05-13
 
Data files and R code to replicate the econometric analysis in the journal article: B Chen, BM Gramig and SD Yun. “Conservation Tillage Mitigates Drought Induced Soybean Yield Losses in the US Corn Belt.” Q Open. https://doi.org/10.1093/qopen/qoab007
keywords: R, Conservation Tillage, Drought, Yield, Corn, Soybeans, Resilience, Climate Change
published: 2020-10-28
 
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.
keywords: Corbicula; detection probability; eDNA; invasive species; lotic; occupancy modeling
published: 2020-11-25
 
Video recorded by Louise Barker using a Cannon Powershot camera documents late-season combat behavior in Agkistrodon contortrix. Recorded in Beaufort County, North Carolina, 11.1 km SE of downtown Washington on 21 October 2020.
keywords: Agkistrodon contortrix; combat; mating; reproduction; copperhead; pit viper; Viperidae;
published: 2020-12-14
 
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."
keywords: femur; cross-sectional geometry; osteometrics; subadult
published: 2020-12-16
 
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
keywords: Terrorism, Text Analytics, News Coverage, Topic Modeling, Sentiment Analysis
published: 2020-12-29
 
Three datasets: species_abundance_data, species_traits, and environmental_data. The three datasets were collected in the Fortuna Forest Reserve (8°45′ N, 82°15′ W) and Palo Seco Protected Forest (8°45′ N, 82°13′ W) located in western Panama. The two reserves support humid to super-humid rainforests, according to Holdridge (1947). The species_abundance_data and species_traits datasets were collected across 15 subplots of 25 m2 in 12 one-hectare permanent plots distributed across the two reserves. The subplots were spaced 20 m apart along three 5 m wide transects, each 30 m apart. Please read Prada et al. (2017) for details on the environmental characteristics of the study area. Prada CM, Morris A, Andersen KM, et al (2017) Soils and rainfall drive landscape-scale changes in the diversity and functional composition of tree communities in a premontane tropical forest. J Veg Sci 28:859–870. https://doi.org/10.1111/jvs.12540
keywords: functional traits; plants; ferns; environmental data; Fortuna; species data; community ecology
published: 2020-10-20
 
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].
keywords: Striatopollis catatumbus; superresolution microscopy; Cenozoic; tropics; Zeiss; CZI; striate pollen.
published: 2020-12-30
 
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.
published: 2020-10-01
 
We measured the effects of fire or drought treatment on plant, microbial and biogeochemical responses in temperate deciduous forests invaded by the annual grass Microstegium vimineum with a history of either frequent fire or fire exclusion. Please note, on Documentation tab / Experimental or Sampling Design, “15 (XVI)” should be “16 (XVI)”.
keywords: plant-soil interaction; grass-fire cycle; Microstegium; carbon and nitrogen cycling; microbial decomposers
published: 2020-12-31
 
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.
keywords: Plecoptera; stoneflies; phylogeny; insects
published: 2020-10-01
 
These datasets were performed to assess whether color pattern phenotypes of the polymorphic tortoise beetle, Chelymorpha alternans, mate randomly with one another, and whether there are any reproductive differences between assortative and disassortative pairings.
keywords: mate choice, color polymorphisms, random mating