Dataset Search Results

This dataset consists of various input data that are used in the GAMS model. All the data are in the format of .inc which can be read withi... n GAMS or Notepad. Main data sources include: acreage data (acre), crop budget data ($/acre), crop yield data (e.g. bushel/acre), Soil carbon sequestration data (KgCO2/ha/yr). Model details can be found in the "Assessing the Additional Carbon Savings with Biofuel" and GAMS model package. ## File Description (1) GAMS Model.zip: This includes all the input files and scripts for running the model (2) Table*.csv: These files include the data from the tables in the manuscript (3) Figure2_3_4.csv: This contains the data used to create the figures in the manuscript (4) BaselineResults.csv: This includes a summary of the model results. (5) SensitivityResults_*.csv: Model results from the various sensitivity analyses performed (6) LUC_emission.csv: land use change emissions by crop reporting district for changes of pasturelands to annual crops.   more description

Data on permanent plots at Fortuna and the Panama Canal Watershed, Republic of Panama, containing counts and percent of trees with one or m... ore multiple stems >10cm diameter, with and without palms. Accompanying environmental data includes elevation, precipitation, soil type and soil chemical variables (pH, total N, NO3, NO4, resin P, mehlich Ca, K and Mg.   more description

Increasingly pervasive location-aware sensors interconnected with rapidly advancing wireless network services are motivating the developmen... t of near-real-time urban analytics. This development has revealed both tremendous challenges and opportunities for scientific innovation and discovery. However, state-of-the-art urban discovery and innovation are not well equipped to resolve the challenges of such analytics, which in turn limits new research questions from being asked and answered. Specifically, commonly used urban analytics capabilities are typically designed to handle, process, and analyze static datasets that can be treated as map layers and are consequently ill-equipped in (a) resolving the volume and velocity of urban big data; (b) meeting the computing requirements for processing, analyzing, and visualizing these datasets; and (c) providing concurrent online access to such analytics. To tackle these challenges, we have developed a novel cyberGIS framework that includes computationally reproducible approaches to streaming urban analytics. This framework is based on CyberGIS-Jupyter, through integration of cyberGIS and real-time urban sensing, for achieving capabilities that have previously been unavailable toward helping cities solve challenging urban informatics problems. The files included in this dataset functions as follows: 1) Spatial_interpolation.ipynb is a python based Jupyter notebook that enables users to conduct spatial interpolation with AoT data; 2) Urban_Informatics.ipynb is a Jupyter notebook that helps to explore the AoT dataset; 3) chicago-complete.weekly.2019-09-30-to-2019-10-06.tar includes all the high-frequency urban sensing data from AoT sensors from 2019 September 30th to 2019 October 6th collected in Chicago, US; 4) sensors.csv is a processed dataset including information about the temperature in Chicago, and it is used in Spatial_interpolation.ipynb.   more description

Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying Our approach is described i... n our paper titled: Mishra, Sudhanshu, Shivangi Prasad, and Shubhanshu Mishra. 2020. “Multilingual Joint Fine-Tuning of Transformer Models for Identifying Trolling, Aggression and Cyberbullying at TRAC 2020.” In Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying (TRAC-2020). The source code for training this model and more details can be found on our code repository: https://github.com/socialmediaie/TRAC2020 NOTE: These models are retrained for uploading here after our submission so the evaluation measures may be slightly different from the ones reported in the paper.   more description

The data provided herein is accelerometer and strain data taken from free vibration response of pre-tensioned, partially submerged steel be... am specimens (modulus of elasticity assumed = 29,000 ksi). The specimens were subjected to various levels of pre-tension, and various levels of submersion in water. The purpose of the testing was to quantify the effects of partial submersion on the vibrating frequencies of pretensioned beams. Three specimens were tested, each with different cross section (but identical cross-sectional area). The different cross sections allow investigation of the effects of specimen width as the specimen vibrates through water. The testing procedure was as follows: 1) Apply a specified level of tension in the beam. Measure tension via 3 strain gages. 2) Submerge the specimens to a specified depth of water 3) Excite the beams with either a hammer impact or a pull-and-release method (physically pull the middle of the bar and quickly release) 4) Measure the free vibration of the beam with 2 accelerometers. Schematic drawings of the test setup and the test specimens are provided, as is a picture of the test setup.   more description

Original leaf gas exchange and absorptance data used in the Collison et al. (2020) Light, Not Age, Underlies the Q9 Maladaptation of Maize ... and Miscanthus Photosynthesis to Self-Shading - Frontiers in Plant Science doi: 10.3389/fpls.2020.00783   more description

This repository includes scripts and datasets for Chapter 6 of my PhD dissertation, " Supertree-like methods for genome-scale species tree ... estimation," that had not been published previously. This chapter is based on the article: Molloy, E.K. and Warnow, T. "FastMulRFS: Fast and accurate species tree estimation under generic gene duplication and loss models." Bioinformatics, In press. https://doi.org/10.1093/bioinformatics/btaa444. The results presented in my PhD dissertation differ from those in the Bioinformatics article, because I re-estimated species trees using FastMulRF and MulRF on the same datasets in the original repository (https://doi.org/10.13012/B2IDB-5721322_V1). To re-estimate species trees, (1) a seed was specified when running MulRF, and (2) a different script (specifically preprocess_multrees_v3.py from https://github.com/ekmolloy/fastmulrfs/releases/tag/v1.2.0) was used for preprocessing gene trees (which were then given as input to MulRF and FastMulRFS). Note that this preprocessing script is a re-implementation of the original algorithm for improved speed (a bug fix also was implemented). Finally, it was brought to my attention that the simulation in the Bioinformatics article differs from prior studies, because I scaled the species tree by 10 generations per year (instead of 0.9 years per generation, which is ~1.1 generations per year). I re-simulated datasets (true-trees-with-one-gen-per-year-psize-10000000.tar.gz and true-trees-with-one-gen-per-year-psize-50000000.tar.gz) using 0.9 years per generation to quantify the impact of this parameter change (see my PhD dissertation or the supplementary materials of Bioinformatics article for discussion).   more description

This dataset contains the ClonalKinetic dataset that was used in SimiC and its intermediate results for comparison. The Detail description ... can be found in the text file 'clonalKinetics_Example_data_description.txt' and 'ClonalKinetics_filtered.DF_data_description.txt'. The required input data for SimiC contains: 1. ClonalKinetics_filtered.clustAssign.txt => cluster assignment for each cell. 2. ClonalKinetics_filtered.DF.pickle => filtered scRNAseq matrix. 3. ClonalKinetics_filtered.TFs.pickle => list of driver genes. The results after running SimiC contains: 1. ClonalKinetics_filtered_L10.01_L20.01_Ws.pickle => inferred GRNs for each cluster 2. ClonalKinetics_filtered_L10.01_L20.01_AUCs.pickle => regulon activity scores for each cell and each driver gene. <b>NOTE:</b> “ClonalKinetics_filtered.rds” file which is mentioned in “ClonalKinetics_filtered.DF_data_description.txt” is an intermediate file and the authors have put all the processed in the pickle/txt file as described in the filtered data text.   more description

This is a collection of 31 quasi-linear convective system (QLCS) mesovortices (MVs) that were manually identified and analyzed using the lo... west elevation scan of the nearest relevant Weather Surveillance Radar–1988 Doppler (WSR-88D) during the two years (springs of 2022 and 2023) of the Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign. Throughout the two years of PERiLS, a total of nine intensive observing periods (IOPs) occurred (see https://catalog.eol.ucar.edu/perils_2022/missions and https://catalog.eol.ucar.edu/perils_2023/missions for exact IOP dates/times). However, only six of these IOPs (specifically, IOPs 2, 3, and 4 from both years) are included in this dataset. The inclusion criteria were based on the presence of strictly QLCS MVs within the C-band On Wheels (COW) domain, one of the research radars deployed in the field for the PERiLS project. Further details on how MVs were identified are provided below. This analysis was completed using the Gibson Ridge radar-viewing software (GR2Analyst). Each MV had to be produced by a QLCS, defined as a continuous area of 35 dBZ radar reflectivity over at least 100 km when viewed from the lowest elevation scan. The MVs analyzed also had to pass through/near the COW’s domain at some point during their lifetimes to allow for additional analysis using the COW data. Tornadic (TOR), wind-damaging (WD), and non-damaging (ND) MVs were analyzed. ND MVs were ones that usually had a tornado warning placed on them but did not produce any damage and persisted for five or more radar scans; this was done to target the strongest MVs that forecasters thought could be tornadic. The QLCS MVs were identified using objective criteria, which included the existence of a circulation with a maximum differential velocity (dV; i.e., the difference between the maximum outbound and minimum inbound velocities at a constant range) of at least 20 kt over a distance ≤ 7 km. The following radar-based characteristics were catalogued for each QLCS MV at the lowest elevation angle of the nearest WSR-88D: latitude and longitude locations of the MV, the genesis to decay time of the MV, the maximum dV across the MV, the maximum rotational velocity (Vrot; i.e., dV divided by two), diameter of the MV, the range from the radar of the MV center, and the height above radar level of the MV center. In the Excel sheet, there are a total of 37 sheets. 32 of the 37 sheets are for each MV that was examined. One of those MVs (sheet titled 'EFU_tor_iop3') was not included in the final count of MVs (31). This MV produced an EFU tornado and only tornadoes that were given ratings were used to calculate MV statistics. The 31 MV sheets that were used to calculate MV statistics are labeled following the convention 'mv#_iop#_qlcs'. ‘mv#’ is the unique number that was assigned to each MV for clear identification, 'iop#' is the IOP in which the MV occurred, 'qlcs' denotes that the MV was produced by a QLCS, and the 2023 IOPs are denoted by ‘_2023’ after ‘qlcs’ in the sheet name. In these sheets, there are notes on what was visually seen in the radar data, damage associated with each MV (using the National Centers for Environmental Information (NCEI) database), and the characteristics of the MV at each time step of its lifetime. The yellow rows in each of the sheets indicate the last row of data included in the pretornadic, predamaging (wind damage), and pre-nondamaging statistics. The orange boxes in the notes column indicate any reports that were in NCEI but not in GR2Analyst. There are also sheets that examine pretornadic and predamaging diameter trends, box and whisker plot statistics of the overall characteristics of the different types of MVs, and the overall characteristics of each MV, with one Excel sheet (‘combined_qlcs_mvs’) examining the characteristics of each MV over its entire lifetime and one Excel sheet (‘combined_qlcs_mvs_before_report’) examining the characteristics of each MV before it first produced damage or had a tornado warning placed on it.   more description

This dataset consists of all the figure files that are part of the main text and supplementary of the manuscript titled "Optical manipulati... on of the charge density wave state in RbV3Sb5". For detailed information on the individual files refer to the readme file.   more description

This is the raw topographies (without linear background subtraction) related to the publication: https://www.nature.com/articles/s41586-024... -07519-5   more description

This repository includes scripts and datasets for the paper, "FastMulRFS: Fast and accurate species tree estimation under generic gene dupl... ication and loss models." Note: The results from estimating species trees with ASTRID-multi (included in this repository) are *not* included in the FastMulRFS paper. We estimated species trees with ASTRID-multi in the fall of 2019, but ASTRID-multi had an important bug fix in January 2020. Therefore, the ASTRID-multi species trees in this repository should be ignored.   more description

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.   more description

Dataset associated with Jones et al FE-2019-01175 submission: Does the size and developmental stage of traits at fledging reflect juvenile ... flight ability among songbirds? Excel CSV files with all of the 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.   more description

This dataset provides files for use in analysis of human land preference across Australasia, and in a localized analysis of land preference...  in Laos and Vietnam. All files can be imported into ArcGIS for visualization, and re-analyzed using the open source Maxent species distribution modeling program. CSV files contain known human presence sites for model validation. ASC files contain geographically coded environmental data for mean annual temperature and mean annual precipitation during the Last Glacial Maximum, as well as downward slope data. All ASC files are in the WGS 1984 Mercator map projection for visualization in ArcGIS and can be opened as text files in text editors supporting large file sizes.   more description

The Delt_Comb.NEX text file contains the original data used in the phylogenetic analyses of Zahniser & Dietrich, 2013 (European Journal...  of Taxonomy, 45: 1-211). The text file is marked up according to the standard NEXUS format commonly used by various phylogenetic analysis software packages. The file will be parsed automatically by a variety of programs that recognize NEXUS as a standard bioinformatics file format. The first nine lines of the file indicate the file type (Nexus), that 152 taxa were analyzed, that a total of 3971 characters were analyzed, the format of the data, and specification for two symbols used in the dataset. There are four datasets separated into blocks, one each for: 28S rDNA gene, Histone H3 gene, morphology, and insertion/deletion characters scored based on the alignment of the 28S rDNA dataset. Descriptions of the morphological characters and more details on the species and specimens included in the dataset are provided in the publication using this dataset. A text file, Delt_morph_char.txt, is available here that states the morphological characters and characters states that were scored in the Delt_Comb.NEX dataset. The original DNA sequence data are available from NCBI GenBank under the accession numbers indicated in publication. Chromatogram files for each sequencing read are available from the first author upon request.   more description

This is the dataset used in the Landscape Ecology publication of the same name. This dataset consists of the following files: NWCA_Int_Veg... .txt NWCA_Reg_Veg.txt NWCA_Site_Attributes.txt NWCA_Int_Veg.txt is a site and plot by species matrix. Column labeled SITES consists of site IDs. Column labeled Plots consist of Plot ID numbers. All other columns represent species abundances (estimates of percent cover, summed across five plots). NWCA_Reg_Veg.txt is a site by species matrix of species abundances. Column labeled SITES consist of site IDs. All other columns represent species abundances (estimates of percent cover within individual plots). NWCA_Site_Attributes.txt is a matrix of site attributes. Column labeled SITES consist of site IDs. Column labeled AA_CENTER_LAT consist of latitudinal coordinates for the Assessment Area center point in decimal degrees. Column labeled AA_CENTER_LONG consist of longitudinal coordinates for the Assessment Area center point in decimal degrees. Column REFPLUS_NWCA represents disturbance gradient classes including MIN (minimally disturbed), L (least disturbed), I (intermediate), M (most disturbed). Column REFPLUS_NWCA2 represents revised disturbance gradient classes based on protocols described in the article. These revised classes were used for analysis. Column labeled STRESS_HEAVYMETAL represents heavy metal stressor classes, used to ascertain which wetlands were missing soil data. Classes in the STRESS_HEAVYMETAL column include Low, Moderate, High, and Missing. Sites with Missing STRESS_HEAVYMETAL classes were removed from analysis. More information about this dataset: All of the data used in this analysis was gathered from the National Wetlands Condition Assessment. Wetland surveys were conducted from 4/4/2011 to 11/2/2011. The entire National Wetlands Condition Assessment Dataset, which includes 3640 unique taxonomic identities of plants, can be found at: https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys   more description

The XSEDE program manages the database of allocation awards for the portfolio of advanced research computing resources funded by the Nation... al Science Foundation (NSF). The database holds data for allocation awards dating to the start of the TeraGrid program in 2004 to present, with awards continuing through the end of the second XSEDE award in 2021. The project data include lead researcher and affiliation, title and abstract, field of science, and the start and end dates. Along with the project information, the data set includes resource allocation and usage data for each award associated with the project. The data show the transition of resources over a fifteen year span along with the evolution of researchers, fields of science, and institutional representation.   more description

These data were collected for an experiment examining effects of neonicotinoid (clothianidin) presence on hover fly (Diptera: Syrphidae) be... havior. Hover flies of two species (Eristalis arbustorum and Toxomerus marginatus) were offered a choice to feed on artificial flowers laced with sucrose solution that was either contaminated (CLO) or not contaminated (CON) with clothianidin. Two different concentrations of clothianidin in 0.5 M sucrose solution were tested: 2.5 ppb and 150 ppb. We conducted four sets of 10 trials, each trial set examining a different combination of species and clothianidin dose. Across 6 hours of video for each trial we recorded 1) number of visits to each flower that resulted in feeding, and 2) amount of time spent feeding during each visit. We found that while neither species fed significantly longer on either of the solutions, E. arbustorum appeared to avoid flowers with clothianidin particularly at high rates. In the paper, we attribute this avoidance response, partially, to hover fly-visible spectral differences between the two flower choices and discuss potential implications for field and lab-based studies. In the enclosed zip file we have included all data for this project and code scripts from R. * Note: Data folder contains 4 files (instead of 6 as mentioned in Readme): e.tenax_photoreceptors.csv; hoverfly_data_UPDATE.csv; number_visits_UPDATE.csv; and Original 2018 hover fly choice test data_Clem2020.xlsx   more description

This data set shows how density effects have an important influence on mixing at a small river confluence. The data consist of results of ... simulations using a detached eddy simulation model.   more description

This second version (V2) provides additional data cleaning compared to V1, additional data collection (mainly to include data from 2019), a... nd more metadata for nodes. Please see NETWORKv2README.txt for more detail.   more description

Baseline data from a multi-modal intervention study conducted at the University of Illinois at Urbana-Champaign. Data include results from...  a cardiorespiratory fitness assessment (maximal oxygen consumption, VO2max), a body composition assessment (Dual-Energy X-ray Absorptiometry, DXA), and Magnetic Resonance Spectroscopy Imaging. Data set includes data from 435 participants, ages 18-44 years.   more description

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/   more description

This data has tweets collected in paper Shubhanshu Mishra, Sneha Agarwal, Jinlong Guo, Kirstin Phelps, Johna Picco, and Jana Diesner. 2014....  Enthusiasm and support: alternative sentiment classification for social movements on social media. In Proceedings of the 2014 ACM conference on Web science (WebSci '14). ACM, New York, NY, USA, 261-262. DOI: https://doi.org/10.1145/2615569.2615667 The data only contains tweet IDs and the corresponding enthusiasm and support labels by two different annotators.   more description