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Illinois Data Bank Dataset Search Results
Dataset Search Results
published: 2024-09-24
Sawyer, Elle; Kreps, Timothy; Lodge, David; Larson, Eric (2024): Rusty crayfish body size in Vilas County, Wisconsin lakes 1980-2020. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1143617_V1
Data at the lake summary and individual crayfish level that supports the manuscript Sawyer, E.K., Kreps, T. A., Lodge, D. M. and E.R. Larson. “Long-term declines in body size of the invasive rusty crayfish (Faxonius rusticus) in temperate lakes." Includes size measurements of 69,303 individual rusty crayfish (Faxonius rusticus) for 17 lakes of Vilas County, Wisconsin, United States collected between 1980 and 2020.
keywords:
body size; Faxonius rusticus; invasive species; non-native species; rusty crayfish; Wisconsin; Vilas County
published: 2024-09-19
Klimasmith, Isaac; Kent, Angela (2024): Propagule Pressure in Microbial Introductions. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0907683_V1
The use of potentially beneficial microorganisms in agriculture (microbial inoculants) has rapidly accelerated in recent years. For microbial inoculants to be effective as agricultural tools, these organisms must be able to survive and persist in novel environments while not destabilizing the resident community or spilling over into adjacent natural ecosystems. Here, we adapt a macroecological propagule pressure model to a microbial scale and present an experimental approach for testing the role of propagule pressure in microbial inoculant introductions. We experimentally determined the risk-release relationship for an IAA-expressing Pseudomonas simiae inoculant in a model monocot system. We then used this relationship to simulate establishment outcomes under a range of application frequencies (propagule number) and inoculant concentrations (propagule size). Our simulations show that repeated inoculant applications may increase establishment, even when increased inoculant concentration does not alter establishment probabilities. The dataset filed here includes the experimemtal datafile, and a RMarkdown file that includes all the code used in in both the modeling and anaylsis.
keywords:
microbial inoculants; invasion ecology; propagule pressure; agriculture; modeling
published: 2024-09-03
Bishop, Rebecca; Jonk, Kaitlyn M; Migliorisi, Alessandro; Austin, Scott M; Mullins, Emma C; Wilkins, Pamela (2024): Effect of phenylepherine-induced increased PCV on viscoelastic coagulation testing in horses. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0295993_V1
Healthy mares were administered phenylephrine to induce transient polycythemia secondary to splenic contraction. Data was collected at baseline (T0), 5 minutes (T1) and 2 hours (T2) post-phenylephrine infusion. Collected data included baseline CBC, chemistry, fibrinogen, and serum amyloid A; at each time point viscoelastic coagulation profiles (VCM Vet), traditional in-vitro coagulation profiles, and ultrasonographic measurements of the spleen were obtained.
keywords:
horse; coagulation; polycythemia; blood clotting; viscoelastic testing
published: 2024-08-29
Li, Shuai; Montes, Christopher; Aspray, Elise; Ainsworth, Elizabeth (2024): How do drought and heat affect the response of soybean seed yield to elevated O3? An analysis of 15 seasons of free-air O3 concentration enrichment (O3-FACE) studies. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9394312_V1
Over the past 15 years, soybean seed yield response to season-long elevated O3 concentrations [O3] and to year-to-year weather conditions was studied using free-air O3 concentration enrichment (O3-FACE) in the field at the SoyFACE facility in Central Illinois. Elevated [O3] significantly reduced seed yield across cultivars and years. However, our results quantitatively demonstrate that weather conditions, including soil water availability and air temperature, did not alter yield sensitivity to elevated [O3] in soybean.
keywords:
drought, elevated O3, heat, O3-FACE, soybean, yield
published: 2022-10-10
Varela, Sebastian; Leakey, Andrew; Sacks, Erik (2022): UAV remote sensing imagery - Miscanthus trials 2020 - Energy Farm - UIUC . University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5689586_V1
Aerial imagery utilized as input in the manuscript "Deep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus" . Data was collected over M. Sacchariflorus and Sinensis breeding trials at the Energy Farm, UIUC in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into an unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. 'MMDDYYYY' is the date of data collection, 'MSA' is M. Sacchariflorus trial, 'MSI' is Miscanthus Sinensis trial, 'CSM' is crop surface model layer, and 'MULTSP' are the five multispectral bands.
keywords:
convolutional neural networks; miscanthus; perennial grasses; bioenergy; field phenotyping; remote sensing; UAV
published: 2024-08-13
Maffeo, Christopher; Chhabra, Hemani; Aksimentiev, Aleksei (2024): Scripts for computationally estimating the current in "A lumen-tunable triangular DNA nanopore for molecular sensing and cross-membrane transport". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6464580_V1
Scripts used to computationally estimate the current through a DNA nanopore, starting from an equilibrated oxDNA configuration, in association with the manuscript "A lumen-tunable triangular DNA nanopore for molecular sensing and cross-membrane transport".
keywords:
DNA origami nanopore; Steric exclusion model; Ionic current
published: 2024-08-24
Jones, Todd; Llamas, Alfredo; Phillips, Jennifer (2024): Data for Jones et al. GCB-23-1273.R1. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6010827_V1
Dataset associated with Jones et al. GCB-23-1273.R1 submission: Phenotypic signatures of urbanization? Resident, but not migratory, songbird eye size varies with urban-associated light pollution levels. Excel CSV file with all of the data used in analyses and file with descriptions of each column.
keywords:
body size; demographics; eye size; phenotypic divergence; songbirds; sensory pollution; urbanization
published: 2024-08-15
Gounder, Babu; Kadiyan, Lakshya; Sarker, Zafar Waziha (2024): Oil Spill Shell Data Set. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9244463_V1
This study acquired publicly available Shell annual reports. Reports were selected for the years since the UN investigation in 2011, resulting in documents from 2012 to 2023.
keywords:
environmental justice; ethics of care; indigenous communities; Niger River Delta; oil spills
published: 2024-08-19
Ward, Michael; Stewart, Sarah; Benson, Thomas (2024): Whip-poor-will nesting success. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7835826_V1
Data on the nesting success and post-fledgling survival of Eastern Whip-poor-wills in central Illinois. Data was part of Sarah Stewart's MS project at the University of Illinois.
keywords:
bird nesting success; post-fledgling survival; eastern whip-poor-will
published: 2024-08-17
Storms, Suzanna; Leonardi-Cattolica, Antonio; Prezioso, Tara; Varga, Csaba; Wang, Leyi; Lowe, James (2024): Data for Influenza A virus shedding and reinfection during the post-weaning period in swine: longitudinal study of two nurseries. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0440849_V1
This dataset includes the RT-PCR shedding data and primers used for whole genome sequencing of Influenza A virus in swine. It also includes the GenBank accession numbers for all segments generated by Influenza A virus sequencing from nasal swab samples. Additionally, all nucleotide changes are listed by sample.
published: 2024-08-11
Curtis, Jeffrey H.; Riemer, Nicole; West, Matthew (2024): Data for Explicit stochastic advection algorithms for the regional scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0). University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3847217_V2
This dataset contains all material required to produce the figures found within the manuscript submitted to Geoscientific Model Development entitled “Explicit stochastic advection algorithms for the regional scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)”. The dataset consists of Python Jupyter notebooks and any applicable WRF-PartMC output. This dataset covers the three numerical examples of the manuscript, 1D advection by a uniform constant wind, a 2D rotational flow and a 3D time-evolving WRF simulated flow.
keywords:
Atmospheric chemistry; Atmospheric Science; Particle-resolved modeling; Numerical modeling; Advection;
published: 2024-07-31
LaBonte, Nicholas R.; Zerpa-Catanho, Dessiree P.; Liu, Siyao; Xiao, Liang; Dong, Hongxu; Clark, Lindsay V.; Sacks, Erik J. (2024): Improving precision and accuracy of genetic mapping with genotyping-by-sequencing data in outcrossing species. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1435220_V1
This dataset contains all data and supplementary materials from "Improving precision and accuracy of genetic mapping with genotyping-by-sequencing data in outcrossing species". An Excel file a list of all QTLs and linkage group length (in cM) obtained with two different SNP-calling methods (Tassel-Uneak and Tassel-GBS), genetic map-construction method (linkage-only and reference order-corrected) and depth filters (12x, 20x, 30x and 40x) for genetic mapping of 18 biomass yield traits in a biparental Miscanthus sinensis population using RAD-Seq SNPs is provided as "Supplementary file 1". A Perl script with the code for filtering VCF and HapMap-formatted data files is provided as “Supplementary file 2”. Phenotype data used for QTL mapping is provided as “Supplementary File 3”. A Perl script with the code for the simulation study is provided as “Supplementary file 4”.
keywords:
HapMapParser; GenotypingSimulator
published: 2024-07-22
Ferguson, John; Schumuker, Peter; Dmitrieva, Anna; Quach, Truyen; Zhang, Tieling; Ge, Zhengxiang; Nersesian, Natalya; Sato, Shirley; Clemente, Thomas; Leakey, Andrew (2024): Data for Reducing stomatal density by expression of a synthetic EPF increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4017279_V1
Raw data for the results presented in Ferguson et al 2024.
keywords:
Sorghum bicolor; stomata; stomatal conductance; C4 photosynthesis; water-use efficiency; drought
published: 2024-07-12
Tejeda-Lunn, Daniel; Kannan, Baskaran; Germon, Amandine; Leverett, Alistair; Clemente, Tom; Altpeter, Fredy; Leakey, Andrew (2024): Dataset for Greater aperture counteracts effects of reduced stomatal density on WUE: a case study on sugarcane and meta-analysis. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9701546_V1
Data for each figure of the article "Greater aperture counteracts effects of reduced stomatal density on WUE: a case study on sugarcane and meta-analysis" published in J. Ex. Bot.
keywords:
stomatal density; water use efficiency; stomatal conductance; epidermal patterning factor; epidermal patterning
published: 2018-12-20
Sun, Tianye; Liu, Liang; Flanner, Mark; Kirchstetter, Thomas; Jiao, Chaoyi; Preble, Chelsea; Chang, Wayne; Bond, Tami (2018): Constraining a Historical Black Carbon Emission Inventory of U.S. for 1960 to 2000 data. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9686195_V2
This dataset contains data used to generate figures and tables in the corresponding paper.
keywords:
Black carbon; Emission Inventory; Observations; Climate change, Diesel engine, Coal burning
published: 2020-11-18
Chase, Randy (2020): Dataset for: "A Dual-Frequency Radar Retrieval of Snowfall Properties Using a Neural Network". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0791318_V2
This is the dataset that accompanies the paper titled "A Dual-Frequency Radar Retrieval of Snowfall Properties Using a Neural Network", submitted for peer review in August 2020. Please see the github for the most up-to-date data after the revision process: https://github.com/dopplerchase/Chase_et_al_2021_NN Authors: Randy J. Chase, Stephen W. Nesbitt and Greg M. McFarquhar Corresponding author: Randy J. Chase (randyjc2@illinois.edu) Here we have the data used in the manuscript. Please email me if you have specific questions about units etc. 1) DDA/GMM database of scattering properties: base_df_DDA.csv This is the combined dataset from the following papers: Leinonen & Moisseev, 2015; Leinonen & Szyrmer, 2015; Lu et al., 2016; Kuo et al., 2016; Eriksson et al., 2018. The column names are D: Maximum dimension in meters, M: particle mass in grams kg, sigma_ku: backscatter cross-section at ku in m^2, sigma_ka: backscatter cross-section at ka in m^2, sigma_w: backscatter cross-section at w in m^2. The first column is just an index column. 2) Synthetic Data used to train and test the neural network: Unrimed_simulation_wholespecturm_train_V2.nc, Unrimed_simulation_wholespecturm_test_V2.nc This was the result of combining the PSDs and DDA/GMM particles randomly to build the training and test dataset. 3) Notebook for training the network using the synthetic database and Google Colab (tensorflow): Train_Neural_Network_Chase2020.ipynb This is the notebook used to train the neural network. 4)Trained tensorflow neural network: NN_6by8.h5 This is the hdf5 tensorflow model that resulted from the training. You will need this to run the retrieval. 5) Scalers needed to apply the neural network: scaler_X_V2.pkl, scaler_y_V2.pkl These are the sklearn scalers used in training the neural network. You will need these to scale your data if you wish to run the retrieval. 6) <b>New in this version</b> - Example notebook of how to run the trained neural network on Ku- Ka- band observations. We showed this with the 3rd case in the paper: Run_Chase2021_NN.ipynb 7) <b>New in this version</b> - APR data used to show how to run the neural network retrieval: Chase_2021_NN_APR03Dec2015.nc The data for the analysis on the observations are not provided here because of the size of the radar data. Please see the GHRC website (<a href="https://ghrc.nsstc.nasa.gov/home/">https://ghrc.nsstc.nasa.gov/home/</a>) if you wish to download the radar and in-situ data or contact me. We can coordinate transferring the exact datafiles used. The GPM-DPR data are avail. here: <a href="http://dx.doi.org/10.5067/GPM/DPR/GPM/2A/05">http://dx.doi.org/10.5067/GPM/DPR/GPM/2A/05</a>
published: 2022-07-25
Jett, Jacob (2022): SBKS - Chemical Raw Entity Mentions. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4163883_V1
A set of chemical entity mentions derived from an NERC dataset analyzing 900 synthetic biology articles published by the ACS. This data is associated with the Synthetic Biology Knowledge System repository (https://web.synbioks.org/). The data in this dataset are raw mentions from the NERC data.
keywords:
synthetic biology; NERC data; chemical mentions
published: 2022-07-25
Jett, Jacob (2022): SBKS - Chemical Ambiguous Entity Mentions. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2910468_V1
Related to the raw entity mentions (https://doi.org/10.13012/B2IDB-4163883_V1), this dataset represents the effects of the data cleaning process and collates all of the entity mentions which were too ambiguous to successfully link to the ChEBI ontology.
keywords:
synthetic biology; NERC data; chemical mentions; ambiguous entities
published: 2024-04-15
Lyu, Zhiheng; Lehan, Yao; Zhisheng, Wang; Chang, Qian; Zuochen, Wang; Jiahui, Li; Yufeng, Wang; Qian, Chen (2024): Data for Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0710191_V1
The dataset contains trajectories of Pt nanoparticles in 1.98 mM NaBH4 and NaCl, tracked under liquid-phase TEM. The coordinates (x, y) of nanoparticles are provided, together with the conversion factor that translates pixel size to actual distance. In the file, ∆t denotes the time interval and NaN indicates the absence of a value when the nanoparticle has not emerged or been tracked. The labeling of nanoparticles in the paper is also noted in the second row of the file.
keywords:
nanomotor; liquid-phase TEM
published: 2024-07-15
Li, Peiyuan; Sharma, Ashish; Wuebbles, Donald (2024): Impact Assessment of Climate Change and Afforestation. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0652675_V1
Rising global temperatures and urban heat island effects challenge environmental health and energy systems at the city level, particularly in summer. Increased heatwaves raise energy demand for cooling, stressing power facilities, increasing costs, and risking blackouts. Heat impacts vary across cities due to differences in urban morphology, geography, land use, and land cover, highlighting vulnerable areas needing targeted heat mitigation. Urban tree canopies, a nature-based solution, effectively mitigate heat. Trees provide shade and cooling through evaporation, improving thermal comfort, reducing air conditioning energy consumption, and enhancing climate resilience. This report focused on the ComEd service area in the Chicago Metropolitan Region and assessed the impacts of population growth, urbanization, climate change, and an ambitious plan to plant 1 million trees. The report evaluated planting 1 million trees to quantify regional cooling effects projected for the 2030s. Afforestation locations were selected to avoid interference with existing infrastructure. Key findings include (i) extreme hot hours (>95°F) will increase from 30 to 200 per year, adding 420 Cooling Degree Days (CCD) by the 2030s, (ii) greener areas can be up to 10°F cooler than less vegetated neighborhoods in summer, (iii) tree canopies can create localized cooling, reducing temperatures by 0.7°F and lowering annual CCD by 60 to 65, and (iv) afforestation can reduce the region’s temperature by 0.7°F, saving 400 to 1100 Megawatt hours of daily power usage during summer. <b>Note: The data is available upon request from <a href="mailto:dpiclimate@uilliois.edu">dpiclimate@uilliois.edu</br>.
keywords:
urban heat; cooling degree days; afforestation; tree canopy; Chicago region
published: 2024-07-11
Pelech, Elena; Long, Steve (2024): Soybean/Soja mesophyll conductance during light induction. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7809185_V2
This dataset includes the gas exchange and TDL (tunable diode laser) files between 4 accessions of Glycine soja and 1 elite accession of Glycine max (soybean) during light induction. In this V2, code files for Matlab and R are also included to calculate mesophyll conductance and calculate the limitation on photosynthesis, respectively.
keywords:
photosynthesis; mesophyll conductance; soybean; light induction
published: 2024-07-11
Schneider, Amy; Suski, Cory (2024): Dataset for Molecular and physical disturbance of silver carp along the Illinois River gradient. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2785696_V1
published: 2024-07-11
Schneider, Amy; Suski, Cory (2024): Dataset for Acute exposure to water from the Chicago Area Waterway System induces molecular indices of stress and disturbance in silver carp: implications for deterrence to range expansion. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0347483_V1
published: 2024-07-11
Gholamalamdari, Omid; Belmont, Andrew (2024): Supporting material for Omid Gholamalamdari et al. 2024. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4383352_V1
This repository contains the data and computational analysis notebooks that were used in the following manuscript. For more information on the methods and contributing authors, please refer to the original manuscript. "Beyond A and B Compartments: how major nuclear locales define nuclear genome organization and function Omid Gholamalamdari et al. 2024"
keywords:
genomic analysis; R markdown; genomic segmentations
published: 2024-07-09
Yan, Bin; Dietrich, Christopher; Yu, Xiaofei; Jiang, Yan; Dai, Renhuai; Du, Shiyu; Cai, Chenyang; Yang, Maofa; Zhang, Feng (2024): Data matrices for "Missing Data and Model Selection in Phylogenomics: A Re-Evaluation of Cicadomorpha (Hemiptera: Auchenorrhyncha) Superfamily Level Relationships Under Site-Heterogeneous Models". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6248629_V1
The included files are the alignments of DNA or amino acid sequences used for phylogenetic analyses of Auchenorrhyncha (Insecta: Hemiptera) in the manuscript by Bin et al. submitted to the journal “Systematic Entomology.” The files are plain text in either FASTA (.fa or .fas suffix) or PHYLIP (.phy suffix) format. Matrix0 is the set of all loci after multiple sequence alignment and trimming (hereafter called). Matrix1 consists of loci having 75% average bootstrap support and 80% taxon completeness (hereafter called Matrix1). Matrix2 consists of loci having 75% average bootstrap support and 95% completeness. Matrix2_nt12 is the same as Matrix2 but with third codon positions excluded. More details on how the datasets were compiled is provided in the Methods section of the manuscript file, also included as a PDF. Supplemental figures for the submitted manuscript are also provided as a PDF for additional information.
keywords:
Insecta; Phylogeny; DNA sequence; Evolution