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Illinois Data Bank Dataset Search Results
Dataset Search Results
published: 2016-06-06
Fegley, Brent D. (2016): Datasets for modeling collaborative formation and collaborative "success". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/J81Z429G
These datasets represent first-time collaborations between first and last authors (with mutually exclusive publication histories) on papers with 2 to 5 authors in years [1988,2009] in PubMed. Each record of each dataset captures aspects of the similarity, nearness, and complementarity between two authors about the paper marking the formation of their collaboration.
published: 2018-05-06
Sukenik, Shahar; Salam, Mohammed; Wang, Yuhan; Gruebele, Martin (2018): Dataset for: In-cell titration of small solutes controls protein stability and aggregation. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4308433_V1
This deposit contains all raw data and analysis from the paper "In-cell titration of small solutes controls protein stability and aggregation". Data is collected into several types: 1) analysis*.tar.gz are the analysis scripts and the resulting data for each cell. The numbers correspond to the numbers shown in Fig.S1. (in publication) 2) scripts.tar.gz contains helper scripts to create the dataset in bash format. 3) input.tar.gz contains headers and other information that is fed into bash scripts to create the dataset. 4) All rawData*.tar.gz are tarballs of the data of cells in different solutes in .mat files readable by matlab, as follows: - Each experiment included in the publication is represented by two matlab files: (1) a calibration jump under amber illumination (_calib.mat suffix) (2) a full jump under blue illumination (FRET data) - Each file contains the following fields: coordleft - coordinates of cropped and aligned acceptor channel on the original image coordright - coordinates of cropped and aligned donor channel on the original image] dataleft - a 3d 12-bit integer matrix containing acceptor channel flourescence for each pixel and time step. Not available in _calib files dataright - a 3d 12-bit integer matrix containing donor channel flourescence for each pixel and time step. This will be mCherry in _calib files and AcGFP in data files. frame1 - original image size imgstd - cropped dimensions numFrames - number of frames in dataleft and dataright videos - a structure file containing camera data. Specifically, videos.TimeStamp includes the time from each frame.
keywords:
Live cell; FRET microscopy; osmotic challenge; intracellular titrations; protein dynamics
published: 2022-08-08
Shen, Chengze; Liu, Baqiao; Williams, Kelly P.; Warnow, Tandy (2022): Datasets for EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2567453_V1
This upload contains all datasets used in Experiment 2 of the EMMA paper (appeared in WABI 2023): Shen, Chengze, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. "EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment". The zip file has the following structure (presented as an example): salma_paper_datasets/ |_README.md |_10aa/ |_crw/ |_homfam/ |_aat/ | |_... |_... |_het/ |_5000M2-het/ | |_... |_5000M3-het/ ... |_rec_res/ Generally, the structure can be viewed as: [category]/[dataset]/[replicate]/[alignment files] # Categories: 1. 10aa: There are 10 small biological protein datasets within the `10aa` directory, each with just one replicate. 2. crw: There are 5 selected CRW datasets, namely 5S.3, 5S.E, 5S.T, 16S.3, and 16S.T, each with one replicate. These are the cleaned version from Shen et. al. 2022 (MAGUS+eHMM). 3. homfam: There are the 10 largest Homfam datasets, each with one replicate. 4. het: There are three newly simulated nucleotide datasets from this study, 5000M2-het, 5000M3-het, and 5000M4-het, each with 10 replicates. 5. rec\_res: It contains the Rec and Res datasets. Detailed dataset generation can be found in the supplementary materials of the paper. # Alignment files There are at most 6 `.fasta` files in each sub-directory: 1. `all.unaln.fasta`: All unaligned sequences. 2. `all.aln.fasta`: Reference alignments of all sequences. If not all sequences have reference alignments, only the sequences that have will be included. 3. `all-queries.unaln.fasta`: All unaligned query sequences. Query sequences are sequences that do not have lengths within 25% of the median length (i.e., not full-length sequences). 4. `all-queries.aln.fasta`: Reference alignments of query sequences. If not all queries have reference alignments, only the sequences that have will be included. 5. `backbone.unaln.fasta`: All unaligned backbone sequences. Backbone sequences are sequences that have lengths within 25% of the median length (i.e., full-length sequences). 6. `backbone.aln.fasta`: Reference alignments of backbone sequences. If not all backbone sequences have reference alignments, only the sequences that have will be included. >If all sequences are full-length sequences, then `all-queries.unaln.fasta` will be missing. >If fewer than two query sequences have reference alignments, then `all-queries.aln.fasta` will be missing. >If fewer than two backbone sequences have reference alignments, then `backbone.aln.fasta` will be missing. # Additional file(s) 1. `350378genomes.txt`: the file contains all 350,378 bacterial and archaeal genome names that were used by Prodigal (Hyatt et. al. 2010) to search for protein sequences.
keywords:
SALMA;MAFFT;alignment;eHMM;sequence length heterogeneity
published: 2022-02-14
Yao, Yu; Curtis, Jeffrey; Ching, Joseph; Zheng, Zhonghua; Riemer, Nicole (2022): Data for: Quantifying the effects of mixing state on aerosol optical properties. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8157303_V1
This dataset contains simulation results from numerical model PartMC-MOSAIC used in the article "Quantifying the effects of mixing state on aerosol optical properties". This article is submitted to the journal Atmospheric Physics and Chemistry. There are total 100 scenario directories in this dataset, denoted from 00-99. Each scenario contains 25 NetCDF files hourly output from PartMC-MOSAIC simulations containing the simulated gas and particle information. The data was produced using version 2.5.0 of PartMC-MOSAIC. Instructions to compile and run PartMC-MOSAIC are available at https://github.com/compdyn/partmc. The chemistry code MOSAIC is available by request from Rahul.Zaveri@pnl.gov. For more details of reproducing the cases, please contact nriemer@illinois.edu and yuyao3@illinois.edu.
keywords:
Aerosol mixing state; Aerosol optical properties; Mie calculation; Black Carbon
published: 2015-12-16
Nguyen, Nam-phuong; Mirarab, Siavash; Kumar, Keerthana; Warnow, Tandy (2015): Data for Ultra-Large Alignments Using Phylogeny-Aware Profiles. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3174395_V1
This dataset contains the data for PASTA and UPP. PASTA data was used in the following articles: Mirarab, Siavash, Nam Nguyen, Sheng Guo, Li-San Wang, Junhyong Kim, and Tandy Warnow. “PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences.” Journal of Computational Biology 22, no. 5 (2015): 377–86. doi:10.1089/cmb.2014.0156. Mirarab, Siavash, Nam Nguyen, and Tandy Warnow. “PASTA: Ultra-Large Multiple Sequence Alignment.” Edited by Roded Sharan. Research in Computational Molecular Biology, 2014, 177–91. UPP data was used in: Nguyen, Nam-phuong D., Siavash Mirarab, Keerthana Kumar, and Tandy Warnow. “Ultra-Large Alignments Using Phylogeny-Aware Profiles.” Genome Biology 16, no. 1 (December 16, 2015): 124. doi:10.1186/s13059-015-0688-z.
published: 2019-08-13
Nowak, Jennifer E.; Sweet, Andrew D.; Weckstein, Jason D.; Johnson, Kevin P. (2019): Data for: A molecular phylogenetic analysis of the genera of fruit doves and their allies using dense taxonomic sampling. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9797270_V1
Multiple sequence alignments from concatenated nuclear and mitochondrial genes and resulting phylogenetic tree files of fruit doves and their close relatives. Files include: BEAST input XML file (fruit_dove_beast_input.xml); a maximum clade credibility tree from a BEAST analysis (fruit_dove_beast_mcc.tre); concatenated multiple sequence alignment NEXUS files for the novel dataset (fruit_dove_concatenated_alignment.nex, 76 taxa, 4,277 characters) and the dataset with additional sequences (fruit_dove_plus_cibois_data_concatenated_alignment.nex, 204 taxa, 4,277 characters), both of which contain a MrBayes block including partition information; and 50% majority-rule consensus trees generated from MrBayes analyses, using the NEXUS alignment files as inputs (fruit_dove_mrbayes_consensus.tre, fruit_dove_plus_cibois_data_mrbayes_consensus.tre).
keywords:
fruit doves; multiple sequence alignment; phylogeny; Aves: Columbidae
published: 2020-06-02
Xue, Qingquan; Dietrich, Christopher; Zhang, Yalin (2020): NEXUS file for phylogenetic analysis of Eurymelinae (Hemiptera: Cicadellidae). University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3573054_V1
The text file contains the original data used in the phylogenetic analyses of Xue et al. (2020: Systematic Entomology, in press). 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 six lines of the file identify the file as NEXUS, indicate that the file contains data for 89 taxa (species) and 2676 characters, indicate that the first 2590 characters are DNA sequence and the last 86 are morphological, that gaps inserted into the DNA sequence alignment and inapplicable morphological characters are indicated by a dash, and that missing data are indicated by a question mark. The file contains aligned nucleotide sequence data for 5 gene regions and 86 morphological characters. The positions of data partitions are indicated in the mrbayes block of commands for the phylogenetic program MrBayes at the end of the file (Subset1 = 16S gene; Subset2 = 28S gene; Subset3 = COI gene; Subset 4 = Histone H3 and H2A genes). The mrbayes block also contains instructions for MrBayes on various non-default settings for that program. These are explained in the original publication. Descriptions of the morphological characters and more details on the species and specimens included in the dataset are provided in the supplementary document included as a separate pdf, also available from the journal website. The original raw DNA sequence data are available from NCBI GenBank under the accession numbers indicated in the supplementary file.
keywords:
phylogeny; DNA sequence; morphology; Insecta; Hemiptera; Cicadellidae; leafhopper; evolution; 28S rDNA; 16S rDNA; histone H3; histone H2A; cytochrome oxidase I; Bayesian analysis
published: 2020-02-12
Asplund, Joshua; Karahalios, Karrie (2020): Data for: Auditing Race and Gender Discrimination in Online Housing Markets. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1408573_V1
This dataset contains the results of a three month audit of housing advertisements. It accompanies the 2020 ICWSM paper "Auditing Race and Gender Discrimination in Online Housing Markets". It covers data collected between Dec 7, 2018 and March 19, 2019. There are two json files in the dataset: The first contains a list of json objects representing advertisements separated by newlines. Each object includes the date and time it was collected, the image and title (if collected) of the ad, the page on which it was displayed, and the training treatment it received. The second file is a list of json objects representing a visit to a housing lister separated by newlines. Each object contains the url, training treatment applied, the location searched, and the metadata of the top sites scraped. This metadata includes location, price, and number of rooms. The dataset also includes the raw images of ads collected in order to code them by interest and targeting. These were captured by selenium and named using a perceptive hash to de-duplicate images.
keywords:
algorithmic audit; advertisement audit;
published: 2021-10-27
de Jesús Astacio, Luis Miguel ; Prabhakara, Kaumudi Hassan; Li, Zeqian; Mickalide, Harry; Kuehn , Seppe (2021): Closed microbial communities self-organize to persistently cycle carbon -- 16S Sequencing data. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8967648_V1
Shared dataset consists of 16S sequencing data of microbial communities. Each community is composed of heterotrophic bacteria derived from one of two soil samples and the model algae Chlamydomonas reinhardtii. Each comunity was placed in a materially closed environment with an initial supply of carbon in the media and subjected to light-dark cycles. The closed microbial ecosystems (CES) survived via carbon cycling. Each CES was subjected to rounds of dilution, after which the community was sequenced (data provided here). The shared dataset allowed us to conclude that CES consistently self-assembled to cycle carbon (data not provided) via conserved metabolic capabilites (data not provided) dispite differences in taxonomic composition (data provided). --------------------------- Naming convention: [soil sample = A or B][CES replicate = 1,2,3, or 4]_[round number = 1,2,3,or 4]_[reverse read = R or forward read = F]_filt.fastq Example -- A1_r1_F_filt.fastq means soil sample A, CES replicate 1, end of round1, forward read
keywords:
16S seq; .fastq; closed microbial ecosystems; carbon cycling
published: 2018-07-29
Molloy, Erin K.; Warnow, Tandy (2018): NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1424746_V1
This repository includes scripts, datasets, and supplementary materials for the study, "NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees", presented at RECOMB-CG 2018. The supplementary figures and tables referenced in the main paper can be found in njmerge-supplementary-materials.pdf. The latest version of NJMerge can be downloaded from Github: https://github.com/ekmolloy/njmerge. ***When downloading datasets, please note that the following errors.*** In README.txt, lines 37 and 38 should read: + fasttree-exon.tre contains lines 1-25, 1-100, or 1-1000 of fasttree-total.tre + fasttree-intron.tre contains lines 26-50, 101-200, or 1001-2000 of fasttree-total.tre Note that the file names (fasttree-exon.tre and fasttree-intron.tre) are swapped. In tools.zip, the compare_trees.py and the compare_tree_lists.py scripts incorrectly refer to the "symmetric difference error rate" as the "Robinson-Foulds error rate". Because the normalized symmetric difference and the normalized Robinson-Foulds distance are equal for binary trees, this does not impact the species tree error rates reported in the study. This could impact the gene tree error rates reported in the study (see data-gene-trees.csv in data.zip), as FastTree-2 returns trees with polytomies whenever 3 or more sequences in the input alignment are identical. Note that the normalized symmetric difference is always greater than or equal to the normalized Robinson-Foulds distance, so the gene tree error rates reported in the study are more conservative. In njmerge-supplementary-materials.pdf, the alpha parameter shown in Supplementary Table S2 is actually the divisor D, which is used to compute alpha for each gene as follows. 1. For each gene, a random value X between 0 and 1 is drawn from a uniform distribution. 2. Alpha is computed as -log(X) / D, where D is 4.2 for exons, 1.0 for UCEs, and 0.4 for introns (as stated in Table S2). Note that because the mean of the uniform distribution (between 0 and 1) is 0.5, the mean alpha value is -log(0.5) / 4.2 = 0.16 for exons, -log(0.5) / 1.0 = 0.69 for UCEs, and -log(0.5) / 0.4 = 1.73 for introns.
keywords:
phylogenomics; species trees; incomplete lineage sorting; divide-and-conquer
published: 2024-01-04
Kim, Hyunchul; Zhao, Helin; van der Zande, Arend (2024): Stretchable thin-film transistors based on wrinkled graphene and MoS2 heterostructures. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7325893_V1
This data set includes all of data related to stretchable TFTs based on 2D heterostructures including optical images of TFTs, Raman and Photoluminescence characteristics data, Transport measurement data, and AFM topography data. Abstract Two-dimensional (2D) materials are outstanding candidates for stretchable electronics, but a significant challenge is their heterogeneous integration into stretchable geometries on soft substrates. Here, we demonstrate a strategy for stretchable thin film transistors (2D S-TFT) based on wrinkled heterostructures on elastomer substrates where 2D materials formed the gate, source, drain, and channel, and characterized them with Raman spectroscopy and transport measurements.
keywords:
2D materials; 2D heterstructures; Stretchable electronics; transistors; buckling engineering
published: 2014-10-29
Nguyen, Nam-phuong; Mirarab, Siavash; Bo, Liu; Pop, Mihai; Warnow, Tandy (2014): Data for Taxonomic Identification and Phylogenetic Profiling. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8783447_V1
This dataset provides the data for Nguyen, Nam-phuong, et al. "TIPP: taxonomic identification and phylogenetic profiling." Bioinformatics 30.24 (2014): 3548-3555.
published: 2023-03-08
Majeed, Fahd; Khanna, Madhu (2023): Code and Data for "Carbon Mitigation Payments Can Reduce the Riskiness of Bioenergy Crop Production". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6296964_V1
A stochastic domination analysis model was developed to examine the effect that emerging carbon markets can have on the spatially varying returns and risk profiles of bioenergy crops relative to conventional crops. The code is written in MATLAB, and includes the calculated output. See the README file for instructions to run the code.
keywords:
bioenergy crops; economic modeling; stochastic domination analysis model;
published: 2018-12-20
Dong, Xiaoru; Xie, Jingyi; Linh, Hoang (2018): Inclusion_Criteria_Annotation. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5958960_V1
File Name: Inclusion_Criteria_Annotation.csv Data Preparation: Xiaoru Dong Date of Preparation: 2018-12-14 Data Contributions: Jingyi Xie, Xiaoru Dong, Linh Hoang Data Source: Cochrane systematic reviews published up to January 3, 2018 by 52 different Cochrane groups in 8 Cochrane group networks. Associated Manuscript authors: Xiaoru Dong, Jingyi Xie, Linh Hoang, and Jodi Schneider. Associated Manuscript, Working title: Machine classification of inclusion criteria from Cochrane systematic reviews. Description: The file contains lists of inclusion criteria of Cochrane Systematic Reviews and the manual annotation results. 5420 inclusion criteria were annotated, out of 7158 inclusion criteria available. Annotations are either "Only RCTs" or "Others". There are 2 columns in the file: - "Inclusion Criteria": Content of inclusion criteria of Cochrane Systematic Reviews. - "Only RCTs": Manual Annotation results. In which, "x" means the inclusion criteria is classified as "Only RCTs". Blank means that the inclusion criteria is classified as "Others". Notes: 1. "RCT" stands for Randomized Controlled Trial, which, in definition, is "a work that reports on a clinical trial that involves at least one test treatment and one control treatment, concurrent enrollment and follow-up of the test- and control-treated groups, and in which the treatments to be administered are selected by a random process, such as the use of a random-numbers table." [Randomized Controlled Trial publication type definition from https://www.nlm.nih.gov/mesh/pubtypes.html]. 2. In order to reproduce the relevant data to this, please get the code of the project published on GitHub at: https://github.com/XiaoruDong/InclusionCriteria and run the code following the instruction provided.
keywords:
Inclusion criteria, Randomized controlled trials, Machine learning, Systematic reviews
published: 2019-03-25
Clark, Lindsay V.; Dwiyanti, Maria Stefanie; Anzoua, Kossonou G.; Brummer, Joe E.; Ghimire, Bimal Kumar; Głowacka, Katarzyna; Hall, Megan; Heo, Kweon; Jin, Xiaoli; Lipka, Alexander E.; Peng, Junhua; Yamada, Toshihiko; Yoo, Ji Hye; Yu, Chang Yeon; Zhao, Hua; Long, Stephen P.; Sacks, Erik J. (2019): Miscanthus sinensis multi-location trial: phenotypic analysis, genome-wide association, and genomic prediction . University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0790815_V3
This dataset contains genotypic and phenotypic data, R scripts, and the results of analysis pertaining to a multi-location field trial of Miscanthus sinensis. Genome-wide association and genomic prediction were performed for biomass yield and 14 yield-component traits across six field trial locations in Asia and North America, using 46,177 single-nucleotide polymorphism (SNP) markers mined from restriction site-associated DNA sequencing (RAD-seq) and 568 M. sinensis accessions. Genomic regions and candidate genes were identified that can be used for breeding improved varieties of M. sinensis, which in turn will be used to generate new M. xgiganteus clones for biomass.
keywords:
miscanthus; genotyping-by-sequencing (GBS); genome-wide association studies (GWAS); genomic selection
published: 2024-02-15
Hoggatt, Meredith; Starbuck, Clarissa; O'Keefe, Joy (2024): Data for "Acoustic monitoring yields informative bat population density estimates". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7001459_V1
Dataset includes the dataset for estimating bat density from acoustic data and the R code. The data support a publication by Meredith L. Hoggatt, Clarissa A. Starbuck, and Joy M. O'Keefe entitled Acoustic monitoring yields informative bat population density estimates.
keywords:
acoustics; bats; monitoring; population density; random encounter model
published: 2019-02-22
Fernández, Roberto; Parker, Gary; Stark, Colin (2019): Experiments on patterns of alluvial cover and bedrock erosion in a meandering channel. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2-3044828_V1
This dataset includes measurements taken during the experiments on patterns of alluvial cover over bedrock. The dataset includes an hour worth of timelapse images taken every 10s for eight different experimental conditions. It also includes the instantaneous water surface elevations measured with eTapes at a frequency of 10Hz for each experiment. The 'Read me Data.txt' file explains in more detail the contents of the dataset.
keywords:
bedrock; erosion; alluvial; meandering; alluvial cover; sinuosity; flume; experiments; abrasion;
published: 2024-02-16
Zhang, Mingxiao; Sutton, Bradley (2024): Sample Data for “Measuring CSF Shunt Flow with MRI Using Flow Enhancement of Signal Intensity (FENSI)”. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7252521_V1
Sample data from one typical phantom test and one deidentified shunt patient test (shown in Fig. 8 of the MRM paper), with the corresponding analysis code for the Shunt-FENSI technique. For the MRM paper “Measuring CSF Shunt Flow with MRI Using Flow Enhancement of Signal Intensity (FENSI)”
keywords:
Shunt-FENSI; MRM; Hydrocephalus; VP Shunt; Flow Quantification; Pediatric Neurosurgery; Pulse Sequence; Signal Simulation
published: 2016-12-20
Wickes, Elizabeth; Nakamura, Katia (2016): Supporting data processing scripts and example data for Peru AIDData analysis. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7860393_V1
Scripts and example data for AIDData (aiddata.org) processing in support of forthcoming Nakamura dissertation. This dataset includes two sets of scripts and example data files from an aiddata.org data dump. Fuller documentation about the functionality for these scripts is within the readme file. Additional background information and description of usage will be in the forthcoming Nakamura dissertation (link will be added when available). Data originally supplied by Nakamura. Python code and this readme file created by Wickes. Data included within this deposit are examples to demonstrate execution. Roughly, there are two python scripts in here: keyword_search.py, designed to assist in finding records matching specific keywords, and matching_tool.ipynb, designed to assist in detection of which records are and are not contained within a keyword results file and an aiddata project data file.
keywords:
aiddata; natural resources
published: 2021-11-05
Keralis, Spencer D. C.; Yakin, Syamil (2021): Becoming A Trans Inclusive Library - Library Employee Survey. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0888551_V1
This data set contains survey results from a 2021 survey of University of Illinois University Library employees conducted as part of the Becoming A Trans Inclusive Library Project to evaluate the awareness of University of Illinois faculty, staff, and student employees regarding transgender identities, and to assess the professional development needs of library employees to better serve trans and gender non-conforming patrons. The survey instrument is available in the IDEALS repository: http://hdl.handle.net/2142/110080.
keywords:
transgender awareness, academic library, gender identity awareness, professional development opportunities
published: 2022-10-27
Holiman, Haley; Kitaif, J. Carson; Fournier, Auriel M.V.; Iglay, Ray; Woodrey, Mark S. (2022): Estimating ability to detect secretive marsh birds over distance using autonomous recording units. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4450613_V1
keywords:
marsh birds; automated recording units
published: 2021-09-17
Stern, Jessica; Herman, Brook D. ; Matthews, Jeffrey (2021): Data from determining vegetation metric robustness to environmental and methodological variables . University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0938556_V1
We studied vegetation metric robustness to environmental (season, interannual, and regional) and methodological (observer) variables, as well as adequate sample size for vegetation metrics across four regions of the United States.
keywords:
coefficients of conservatism; floristic quality assessment; restoration; vegetation metric;
published: 2022-11-11
Hsiao, Haw-Wen; Zuo, Jian-Min (2022): Data for Chemical Short-Range Ordering in a CrCoNi Medium-Entropy Alloy. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4432073_V1
This dataset is for characterizing chemical short-range-ordering in CrCoNi medium entropy alloys. It has three sub-folders: 1. code, 2. sample WQ, 3. sample HT. The software needed to run the files is Gatan Microscopy Suite® (GMS). Please follow the instruction on this page to install the DM3 GMS: <a href="https://www.gatan.com/installation-instructions#Step1">https://www.gatan.com/installation-instructions#Step1</a> 1. Code folder contains three DM scripts to be installed in Gatan DigitalMicrograph software to analyze scanning electron nanobeam diffraction (SEND) dataset: Cepstrum.s: need [EF-SEND_sampleWQ_cropped_aligned.dm3] in Sample WQ and the average image from [EF-SEND_sampleWQ_cropped_aligned.dm3]. Same for Sample HT folder. log_BraggRemoval.s: same as above. Patterson.s: Need refined diffuse patterns in Sample HT folder. 2. Sample WQ and 3. Sample HT folders both contain the SEND data (.ser) and the binned SEND data (.dm3) as well as our calculated strain maps as the strain measurement reference. The Sample WQ folder additionally has atomic resolution STEM images; the Sample HT folder additionally has three refined diffuse patterns as references for diffraction data processing. * Only .ser file is needed to perform the strain measurement using imToolBox as listed in the manuscript. .emi file contains the meta data of the microscope, which can be opened together with .ser file using FEI TIA software.
keywords:
Medium entropy alloy; CrCoNi; chemical short-range-ordering; CSRO; TEM
published: 2022-11-09
Wang, Junren; Konar, Megan; Dalin, Carole; Liu, Yu; Stillwell, Ashlynn S.; Xu, Ming; Zhu, Tingju (2022): Data for: Economic and Virtual Water Multilayer Networks in China. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5215221_V1
This dataset includes the blue water intensity by sector (41 industries and service sectors) for provinces in China, economic and virtual water network flow for China in 2017, and the corresponding network properties for these two networks.
keywords:
Economic network; Virtual water; Supply chains; Network analysis; Multilayer; MRIO
published: 2023-04-02
Lee, Yuanyao; Khanna, Madhu; Chen, Luoye (2023): Code and Data for "Quantifying Uncertainties in Greenhouse Gas Savings and Mitigation Costs with Cellulosic Biofuels". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4326514_V1
Use of cellulosic biofuels from non-feedstocks are modeled using the BEPAM (Biofuel and Environmental Policy Analysis Model) model to quantifying the uncertainties about induced land use change effects, net greenhouse gas saving potential, and economic costs. The code is in GAMS, general algebraic modeling language. NOTE: Column 3 is titled "BAU" in "merged_BAU.gdx", "merged_RFS.gdx", and "merged_CEM.gdx", but contains "RFS" data in "merged_RFS.gdx" and "CEM" data in "merged_CEM.gdx".
keywords:
cellulosic biomass; BEPAM; economic modeling