University Library, University of Illinois at Urbana-Champaign

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.

The data file contains a list of articles and their RCT Tagger prediction scores, which were used in a project associated with the manuscript "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

The data file contains a list of articles that have PubMed identifiers, which were used in a project associated with the manuscript "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

The data file contains a list of articles given low score by the RCT Tagger and an error analysis of them, which were used in a project associated with the manuscript "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

The data file contains a list of included studies with their detailed metadata, taken from Cochrane reviews which were used in a project associated with the manuscript "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

The data file contains detailed information of the Cochrane reviews that were used in a project associated with the manuscript (working title) "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

This dataset 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].

A 30 year record of the vegetation in sample plots in a woodland in the Chicago area. The changes in these plots over time show how ecological restoration can yield dramatic results.

The data are original electron micrographs from the lab of the late Dr. Burt Endo of the USDA. These data were digitized from photographic prints and glass plate negatives at 600 DPI as 16 bit TIFF files.

This is the second version of the dataset. The major changes are the following: 1. Reuploaded the movie files, there were .wmv playback issues for the original files because the resolution had an odd number. 2. Added data files for LEM-woLE (Landscape Evolution Model without Lateral Erosion) in addition to LEM-wLE (Landscape Evolution Model with Lateral Erosion) 3. Added 5 LEM-woLEM simulations and an additional LEM-wLEM simulation 4. Added new animations that show rates of elevation change. 5. Added plots that show the slope-area relationships. 6. Reorganized the folder structure so that elevation and drainage area rasters are located in the same folder. This dataset contains data from 16 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 14 folders in total. Here are the descriptions: >LEM-woLE_simulations: 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. >MOVIE_S#_data: There are 11 data folders that contain raster data for 11 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. >movies_mp4_format: 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). >movies_wmv_format: 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. The associated publication for this dataset has not yet been published, and we will update this description with a link when it is.

We are releasing the tracing dataset of four microservice benchmarks deployed on our dedicated Kubernetes cluster consisting of 15 heterogeneous nodes. The dataset is not sampled and is from selected types of requests in each benchmark, i.e., compose-posts in the social network application, compose-reviews in the media service application, book-rooms in the hotel reservation application, and reserve-tickets in the train ticket booking application. The four microservice applications come from [DeathStarBench](https://github.com/delimitrou/DeathStarBench) and [Train-Ticket](https://github.com/FudanSELab/train-ticket). The performance anomaly injector is from [FIRM](https://gitlab.engr.illinois.edu/DEPEND/firm.git). The dataset was preprocessed from the raw data generated in FIRM's tracing system. The dataset is separated by on which microservice component is the performance anomaly located (as the file name suggests). Each dataset is in CSV format and fields are separated by commas. Each line consists of the tracing ID and the duration (in 10^(-3) ms) of each component. Execution paths are specified in `execution_paths.txt` in each directory.

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

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

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 within 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.

Data on permanent plots at Fortuna and the Panama Canal Watershed, Republic of Panama, containing counts and percent of trees with one or more 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.

Data in this spreadsheet presents basic information on Cahokia, Mound 72 shell artifacts. This includes taxonomic identifications, provenience, and bead measurements. There are five tabs: 1. Raw data; 2. Disk bead measurements; 3. Columella bead measurements; 4. Data on cups and pendants; and, 5. Information on whole shell beads.

Raw gas exchange data for photosynthetic induction in 6 rice accession flag leaves. Photosynthetic induction and point measurements were made at ambient [CO2]. Two accessions (AUS 278 and IR64) were selected to screen in greater detail in which photosynthetic induction was measured at six [CO2].

This repository contains the datasets and corresponding results for the paper "MAGUS: Multiple Sequence Alignment using Graph Clustering". The Datasets.zip archive contains the ROSE, balibase, Gutell, and RNASim datasets used in our experiments. The Results.zip archive contains the outputs of running our methods against these datasets. Datasets used: ROSE: 10 simulated nucleotide model conditions from the SATe paper, each with 20 replicates, and with 1000 sequences per replicate. The ROSE datasets were originally taken from <a href="https://sites.google.com/eng.ucsd.edu/datasets/alignment/sate-i">https://sites.google.com/eng.ucsd.edu/datasets/alignment/sate-i</a> RNASim: This is a collection of simulated nucleotide datasets that were generated under a model of evolution that reflects selection due to RNA structural constraints. We sampled 20 subsets of 1000 sequences each, as well as 10 subsets of 10000 each, by randomly sampling from the original million-sequence RNASim dataset. Gutell: 16S.M, 16S.3, 16S.T, 16S.B.ALL: Four biological nucleotide datasets from the Comparative Ribosomal Website (CRW) with cleaned reference alignments from SATe. Since PASTA is restricted to datasets without sequence length heterogeneity, these were modified to remove sequences that deviate by more than 20% from the median length. The scrubbed datasets range from 740 to 24,246 sequences. The pre-screened 16S datasets were taken from <a href="https://sites.google.com/eng.ucsd.edu/datasets/alignment/16s23s">https://sites.google.com/eng.ucsd.edu/datasets/alignment/16s23s</a> BAliBASE: We use eight BAliBASE amino acid datasets used in the PASTA paper. As above, we remove outlier sequences, which leaves us with sizes ranging from 195 to 732 sequences. The pre-screened Balibase datasets were taken from <a href="https://sites.google.com/eng.ucsd.edu/datasets/alignment/pastaupp">https://sites.google.com/eng.ucsd.edu/datasets/alignment/pastaupp</a>

Data extracted from Text, Tables and Figures of publications in summarizing crop responses to Free-Air CO2 Elevation (FACE)

This dataset contains R codes used to produce the figures submitted in the manuscript titled "Understanding the multifaceted geospatial software ecosystem: a survey approach". The raw survey data used to populate these charts cannot be shared due to the survey consent agreement.

This dataset includes neuronal development of the Caenorhabditis elegans dauer and adult.

Restriction site-associated DNA sequencing (RAD-seq) data from 643 Miscanthus accessions from a diversity panel, including 613 Miscanthus sacchariflorus, three M. sinensis, and 27 M. xgiganteus. DNA was digested with PstI and MspI, and single-end Illumina sequencing was performed adjacent to the PstI site. Variant and genotype calling was performed with TASSEL-GBSv2, using the Miscanthus sinensis v7.1 reference genome from Phytozome 12 (https://phytozome.jgi.doe.gov). Additional ploidy-aware genotype calling was performed by polyRAD v1.1.

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.

Data are from a long-term fire manipulation experiment in the Missouri Ozarks, USA. Data include the raw, annual ring-width increment (rwl), basal area increment (BAI), population-level annual growth resistance (Drs) and resilience (Drl) to drought, intrinsic water use efficiency values (WUEi) and oxygen isotopic composition of individual radial growth rings (δ18O) from southern red oak (Quercus falcata) and post oak (Q. stellata) trees. ---------------------- TITLE: Data for "Sixty-five years of fire manipulation reveals climate and fire interact to determine growth rates of Quercus spp." ---------------------- FILE OVERVIEW: This dataset contains four (4) CSV files as described below: Refsland_et_al_ECS20-0465_BAI.csv: annual basal area increment between 1948-2015 for trees across the fire manipulation experiment Refsland_et_al_ECS20-0465_DroughtIndices.csv: population-level drought resistance and resilience of trees during each target drought period Refsland_et_al_ECS20-0465_WUEi.csv: carbon isotope indicators of drought stress for trees across the fire manipulation experiment Refsland_et_al_ECS20-0465_d18Or.csv: oxygen isotope indicators of drought stress for trees across the fire manipulation experiment ---------------------- VARIABLE EXPLANATION: All the variables in those four files are explained as below: treeID: unique character string that identifies subject tree block: integer (1, 2) that identifies the study block plot: integer (1-12) that identifies the plot nested within each study block trt: character string (Annual, Control, Periodic) that identifies the fire treatment of a given plot species: character string (Quercus falcata, Quercus stellata) that identifies species of subject tree year: integer (1948-2015) that identifies the dated year of each tree ring rwl_mm: numerical value representing the annual tree ring-width, in mm bai_cm2: numerical value representing the annual basal area increment, in cm2 timeperiod: integer value (1953, 1964, 2007, 2012) representing the periods encompassing target dry and wet years Drs_2yr: numerical value representing the drought resistance, defined as the population-level annual growth of trees during drought years relative to pre-drought years for a given time period Drl_2yr: numerical value representing the drought resilience, defined as the population-level annual growth of trees following drought years relative to pre-drought years for a given time period stand_ba_m2ha: numerical value representing the total basal area of a given plot, in m2 per ha stand_density_stems_ha: numerical value representing the total stem density of a given plot, in stems per ha pool: numerical value (1-40) identifying the set of tree ring samples pooled for analysis. Samples were pooled by block, plot, year and species period: integer value (1953, 1964, 1980, 2007, 2012) representing the periods encompassing target dry and wet years type: character string (Dry, Wet) indicating the water availability of a given year d13C: numerical value representing the carbon isotopic composition of radial growth rings within a given sample pool, in per mil WUEi: numerical value representing the annual intrinsic water use efficiency of radial growth rings within a given sample pool d18O: numerical value representing the oxygen isotopic composition of radial growth rings within a given sample pool, in per mil