Dataset Search

This dataset consists of the secondary ion mass spectrometry (SIMS) depth profiling data that was collected with a Cameca NanoSIMS 50 instrument from a 10 micron by 10 micron region on a Madin-Darby canine kidney (MDCK) cell that had been metabolically labeled so most of its sphingolipids and cholesterol contained the rare nitrogen-15 oxygen-18 isotopes, respectively.

Simulation trajectory data and scripts for Nature Nanotechnology manuscript "A DNA turbine powered by a transmembrane potential across a nanopore" that demonstrates a rationally designed nanoscale DNA-origami turbine with three chiral blades that uses a transmembrane electrochemical potential across a nanopore to drive a DNA bundle into sustained unidirectional rotations of up to 10 revolutions/s. Driven by the asymmetric mobility of a DNA duplex, the rotation direction of the turbine is set by its designed chirality and the salinity of the solvent.

This dataset is associated with the manuscript "Transcriptional responses of detoxification genes to coumaphos in a nontarget species, Galleria mellonella (greater wax moth) (Lepidoptera: Pyralidae), in the beehive environment" This dataset includes 2 Excel files: 1) raw_data_bioassay.xlsx: this file contains the raw data for waxworm bioassay. There are 2 worksheets within this file: - LC50: raw data for measuring LC50 in the laboratory and field strain of Galleria mellonella. - RGR: Relative Growth Rate, raw data for measuring body weight of field strain of Galleria mellonella . 2) raw-data_RT-qPCR.xlsx: this file contains raw data (Ct value) of RT-qPCR.

Data sets from "Inferring Species Trees from Gene-Family with Duplication and Loss using Multi-Copy Gene-Family Tree Decomposition." It contains trees and sequences simulated with gene duplication and loss under a variety of different conditions. <b>Note:</b> - trees.tar.gz contains the simulated gene-family trees used in our experiments (both true trees from SimPhy as well as trees estimated from alignements). - sequences.tar.gz contains simulated sequence data used for estimating the gene-family trees as well as the concatenation analysis. - biological.tar.gz contains the gene trees used as inputs for the experiments we ran on empirical data sets as well as species trees outputted by the methods we tested on those data sets. - stats.txt list statistics (such as AD, MGTE, and average size) for our simulated model conditions.

This study evaluates the bioethanol potential in response to irrigation (IR) and non-irrigation (NIR) of oilcane (OC) during a seasonal drought prior harvest. The juice was extracted through mechanical pressing of stems and fermented by Ethanol Red® yeast to produce first-generation bioethanol. Hydrothermal pretreatment followed by enzymatic hydrolysis of bagasse was performed to produce monomeric sugars from structural carbohydrates. The hydrolysates were fermented with engineered yeast for second-generation bioethanol production. The irrigated oilcane juice (276.3 ± 8.9 g/L) constitutes higher sugar concentrations than non-irrigated oilcane juice (236.5 ± 2.2 g/L). The enzymatic hydrolysis of IR-OC and NIR-OC pretreated bagasse yielded similar concentrations of 247.5 ± 2.22 and 249.7 ± 4.98 g/L fermentable sugars. Industry-relevant bioethanol titers of ≥99 g/L and ≥75 g/L were achieved from juice and hydrolysates, respectively. Therefore, the non-irrigation regime did not impact the 1G and 2G bioethanol titers. However, the overall bioethanol yield can be lower due to the reduction of stem yield (8 %) per hectare.

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

In a set of field studies across four years, the effect of self-shading on photosynthetic performance in lower canopy sorghum leaves was studied at sites in Champaign County, IL. Photosynthetic parameters in upper and lower canopy leaves, carbon assimilation, electron transport, stomatal conductance, and activity of three C4-specific photosynthetic enzymes, were compared within a genetically diverse range of accessions varying widely in canopy architecture and thereby in the degree of self-shading. Accessions with erect leaves and high light transmission through the canopy are henceforth referred to as ‘erectophile’ and those with low leaf erectness, ‘planophile’. In the final year of the study, bundle sheath leakiness in erectophile and planophile accessions was also compared.

This dataset includes data on soil properties, soil N pools, and soil N fluxes presented in the manuscript, "Refining the role of nitrogen mineralization in mycorrhizal nutrient syndromes". Please refer to that publication for details about methodologies used to generate these data and for the experimental design. For this verison 2, we added specific gross nitrogen mineralization rates (ugN/gOM/d), microbial biomass carbon (ugC/gdw), microbial biomass nitrogen (ugN/gdw) and microbial biomass C:N ratios to the newest version of the data set. Additionally, we updated values for gross nitrogen mineralization, microbial NO3 assimilation and microbial NH4 assimilation to reflect slight changes in data processing. Those changes are reflected in "220829_All data_repository.csv". "220829_nitrogen_mineralization_readme.txt " is updated readme for the new file. The other 2 files begin with “220426_” are older version and same as in V1.

These data were used to make a predictive model of when ornate box turtles (Terrapene ornata) are likely to be above ground and at risk from fire. The data were generated using shell temperatures, soil temperatures at 0.35 m deep from known overwintering sites, and the spring and fall soil temperature inversion dates during 2019–2022 to infer if 26 individual radio-tracked turtles were above or below ground at three sites in Illinois.

This dataset containes the images of B73xMS71 RIL population used in QTL linkage mapping for maize epidermal traits in year 2016 and 2017. 2016RIL_all_mns.rar and 2017RIL_all_mns.rar: contain raw images produced by Nanofocus lsurf Explorer Optical Topometer (Oberhausen, Germany) at 20X magnification with 0.6 numerical aperture. Files were processed in Nanofocus μsurf analysis extended software (Oberhausen,Germany). 2016RIL_all_TIF.rar and 2017RIL_all_TIF.rar: contain images processed from the Topology layer in each nms file to strengthen the edges of cell outlines, and used in downstream cell detection. 2016RIL_all_detection_result.rar and 2017RIL_all_detection_result.rar: contain images with epidermal cells predicted using the Mask R-CNN model. training data.rar: contain images used for Mask R-CNN model training and validation.

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.

References - Li, Fu, Umberto Villa, Seonyeong Park, and Mark A. Anastasio. "3-D stochastic numerical breast phantoms for enabling virtual imaging trials of ultrasound computed tomography." IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 69, no. 1 (2021): 135-146. DOI: 10.1109/TUFFC.2021.3112544 - Li, Fu; Villa, Umberto; Park, Seonyeong; Anastasio, Mark, 2021, "2D Acoustic Numerical Breast Phantoms and USCT Measurement Data", https://doi.org/10.7910/DVN/CUFVKE, Harvard Dataverse, V1 Overview - This dataset includes 1,089 two-dimensional slices extracted from 3D numerical breast phantoms (NBPs) for ultrasound computed tomography (USCT) studies. The anatomical structures of these NBPs were obtained using tools from the Virtual Imaging Clinical Trial for Regulatory Evaluation (VICTRE) project. The methods used to modify and extend the VICTRE NBPs for use in USCT studies are described in the publication cited above. - The NBPs in this dataset represent the following four ACR BI-RADS breast composition categories: > Type A - The breast is almost entirely fatty > Type B - There are scattered areas of fibroglandular density in the breast > Type C - The breast is heterogeneously dense > Type D - The breast is extremely dense - Each 2D slice is taken from a different 3D NBP, ensuring that no more than one slice comes from any single phantom. File Name Format - Each data file is stored as an HDF5 .mat file. The filenames follow this format: {type}{subject_id}.mat where{type} indicates the breast type (A, B, C, or D), and {subject_id} is a unique identifier assigned to each sample. For example, in the filename D510022534.mat, "D" represents the breast type, and "510022534" is the sample ID. File Contents - Each file contains the following variables: > "type": Breast type > "sos": Speed-of-sound map [mm/μs] > "den": Ambient density map [kg/mm³] > "att": Acoustic attenuation (power-law prefactor) map [dB/ MHzʸ mm] > "y": power-law exponent > "label": Tissue label map. Tissue types are denoted using the following labels: water (0), fat (1), skin (2), glandular tissue (29), ligament (88), lesion (200). - All spatial maps ("sos", "den", "att", and "label") have the same spatial dimensions of 2560 x 2560 pixels, with a pixel size of 0.1 mm x 0.1 mm. - "sos", "den", and "att" are float32 arrays, and "label" is an 8-bit unsigned integer array.

MapAffil 2016 dataset -- PubMed author affiliations mapped to cities and their geocodes worldwide. Prepared by Vetle Torvik 2018-04-05 The dataset comes as a single tab-delimited Latin-1 encoded file (only the City column uses non-ASCII characters), and should be about 3.5GB uncompressed. &bull; How was the dataset created? The dataset is based on a snapshot of PubMed (which includes Medline and PubMed-not-Medline records) taken in the first week of October, 2016. Check here for information to get PubMed/MEDLINE, and NLMs data <a href ="https://www.nlm.nih.gov/databases/download/pubmed_medline.html">Terms and Conditions</a> &bull; Affiliations are linked to a particular author on a particular article. Prior to 2014, NLM recorded the affiliation of the first author only. However, MapAffil 2016 covers some PubMed records lacking affiliations that were harvested elsewhere, from PMC (e.g., PMID 22427989), NIH grants (e.g., 1838378), and Microsoft Academic Graph and ADS (e.g. 5833220). &bull; Affiliations are pre-processed (e.g., transliterated into ASCII from UTF-8 and html) so they may differ (sometimes a lot; see PMID 27487542) from PubMed records. &bull; All affiliation strings where processed using the MapAffil procedure, to identify and disambiguate the most specific place-name, as described in: <i>Torvik VI. MapAffil: A bibliographic tool for mapping author affiliation strings to cities and their geocodes worldwide. D-Lib Magazine 2015; 21 (11/12). 10p</i> &bull; Look for <a href="https://doi.org/10.1186/s41182-017-0073-6">Fig. 4</a> in the following article for coverage statistics over time: <i>Palmblad M, Torvik VI. Spatiotemporal analysis of tropical disease research combining Europe PMC and affiliation mapping web services. Tropical medicine and health. 2017 Dec;45(1):33.</i> Expect to see big upticks in coverage of PMIDs around 1988 and for non-first authors in 2014. &bull; The code and back-end data is periodically updated and made available for query by PMID at <a href="http://abel.ischool.illinois.edu/">Torvik Research Group</a> &bull; What is the format of the dataset? The dataset contains 37,406,692 rows. Each row (line) in the file has a unique PMID and author postition (e.g., 10786286_3 is the third author name on PMID 10786286), and the following thirteen columns, tab-delimited. All columns are ASCII, except city which contains Latin-1. 1. PMID: positive non-zero integer; int(10) unsigned 2. au_order: positive non-zero integer; smallint(4) 3. lastname: varchar(80) 4. firstname: varchar(80); NLM started including these in 2002 but many have been harvested from outside PubMed 5. year of publication: 6. type: EDU, HOS, EDU-HOS, ORG, COM, GOV, MIL, UNK 7. city: varchar(200); typically 'city, state, country' but could inlude further subvisions; unresolved ambiguities are concatenated by '|' 8. state: Australia, Canada and USA (which includes territories like PR, GU, AS, and post-codes like AE and AA) 9. country 10. journal 11. lat: at most 3 decimals (only available when city is not a country or state) 12. lon: at most 3 decimals (only available when city is not a country or state) 13. fips: varchar(5); for USA only retrieved by lat-lon query to https://geo.fcc.gov/api/census/block/find

This repository contains the training dataset associated with the 2023 Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics (DGM-Image Challenge), hosted by the American Association of Physicists in Medicine. This dataset contains more than 100,000 8-bit images of size 512x512. These images emulate coronal slices from anthropomorphic breast phantoms adapted from the VICTRE toolchain [1], with assigned X-ray attenuation coefficients relevant for breast computed tomography. Also included are the labels indicating the breast type. The challenge has now concluded. More information about the challenge can be found here: <a href="https://www.aapm.org/GrandChallenge/DGM-Image/">https://www.aapm.org/GrandChallenge/DGM-Image/</a>. * New in V3: we added a CSV file containing the image breast type labels and example images (PNG).

___________________________________SUMMARY This dataset contains derivative data from concurrent fMRI and scalp EEG recordings used in: Mostame Parham, Wirsich Jonathan, Alderson Thomas H, Ridley Ben, Giraud Anne-Lise, Carmichael David W, Vulliemoz Serge, Guye Maxime, Lemieux Louis, Sadaghiani Sepideh (2024) A multiplex of connectome trajectories enables several connectivity patterns in parallel eLife 13:RP98777. doi: https://doi.org/10.7554/eLife.98777.3 ___________________________________RAW DATA The data has been originally published and described as part of other studies (Morillon et al., 2010; Sadaghiani et al., 2012). Briefly, 10 minutes of eyes-closed resting state were analyzed from 26 healthy subjects (average age = 24.39 years; range: 18-31 years; 8 females) with no history of psychiatric or neurological disorders. Informed consent was given by each participant and the study was approved by the local Research Ethics Committee (CPP Ile de France III). FMRI was acquired using a 3T Siemens Tim Trio scanner with a GE-EPI pulse sequence (TR = 2 s; TE = 50 ms; 40 slices; 300 volumes; field of view: 192×192; voxel size: 3×3×3 mm3). Structural T1-weighted scan were acquired using the MPRAGE pulse sequence (176 slices; field of view: 256×256; voxel size: 1×1×1 mm3). 62-channel scalp EEG (Easycap, with an additional EOG and an ECG channel) was recorded using an MR-compatible amplifier (BrainAmp MR, Brain Products) at 5Hz sampling rate. ___________________________________PREPROCESSING fMRI and EEG data were preprocessed with standard preprocessing steps as explained in detail elsewhere (Wirsich et al., 2020). In brief, fMRI underwent standard slice-time correction, spatial realignment (SPM12, http://www.fil.ion.ucl.ac.uk/spm/software/spm12). Structural T1-weighted images were processed using Freesurfer (recon-all, v6.0.0, https://surfer.nmr.mgh.harvard.edu/) in order to perform non-uniformity and intensity correction, skull stripping and gray/white matter segmentation. The cortex was parcellated into 68 regions of the Desikan-Kiliany atlas (Desikan et al., 2006). This atlas was chosen because —as an anatomical parcellation— avoids biases towards one or the other functional data modality. The T1 images of each subject and the Desikan-Killiany were co-registered to the fMRI images (FSL-FLIRT 6.0.2, https://fsl.fmrib.ox.ac.uk/fsl/fslwiki). We extracted signals of no interest such as the average signals of cerebrospinal fluid (CSF) and white matter from manually defined regions of interest (ROI, 5 mm sphere, Marsbar Toolbox 0.44, http://marsbar.sourceforge.net) and regressed out of the BOLD timeseries along with 6 rotation, translation motion parameters and global gray matter signal (Wirsich et al., 2017a). Then we bandpass-filtered the timeseries at 0.009–0.08 Hz. Average timeseries of each region was then used to calculate connectivity. EEG underwent gradient and cardio-ballistic artifact removal using Brain Vision Analyzer software (Allen et al., 1998, 2000) and was down-sampled to 250 Hz. EEG was projected into source space using the Tikhonov-regularized minimum norm in Brainstorm software (Baillet et al., 2001; Tadel et al., 2011). Source activity was then averaged to the 68 regions of the Desikan-Killiany atlas. Band-limited EEG signals in each canonical frequency band and every atlas region were then used to calculate frequency-specific connectome dynamics. Note that the MEG-ROI-nets toolbox in the OHBA Software Library (OSL; https://ohba-analysis.github.io/osl-docs/) was used to minimize source leakage in the band-limited source-localized EEG data (Colclough et al., 2015). ___________________________________FOLDER STRUCTURE The dataset includes five separate folders as described below: 1) EEGfMRI_dFC folder: connectome dynamics of scalp data This folder contains 26 single MATLAB (.mat) files for each subject. Inside each `.mat` is a structure with fields `A`, `B`, and `C`, corresponding to fMRI, amplitude-coupling, and phase-coupling connectome dynamics, respectively. The fMRI data are 3-dimensional (ROI × ROI × timepoints). The EEG data are stored in a 1×5 cell array (Delta, Theta, Alpha, Beta, Gamma), each cell containing a 3-D ROI × ROI × timepoints matrix. 2) EEGfMRI_dFC_SourceOrtho foldeR: connectome dynamics of source-orthogonalized scalp data Same format as above, except that EEG connectome dynamics are derived from source-orthogonalized signals. The MEG-ROI-nets toolbox in the OHBA Software Library (OSL; https://ohba-analysis.github.io/osl-docs/) was used to minimize source leakage in the band-limited, source-localized EEG data (Colclough et al., 2015). 3-5) Cross-modal Recurrence Plot (CRP) data Each subject has an Excel file with five sheets (Delta through Gamma), corresponding to the five frequency bands. Each sheet contains a 2-D CRP matrix (rows = fMRI timepoints, columns = band-limited EEG timepoints). - Scalp EEG–fMRI CRPs (CRP_EEGfMRI and CRP_EEGfMRI_SourceOrtho folder): two versions (with and without source-orthogonalization), each has 52 Excel files, including amplitude- and phase-coupling CRPs. - Intracranial EEG–fMRI CRPs (CRP_iEEGfMRI folder): one version, 27 Excel files, containing three cases: amplitude coupling, HRF-convolved amplitude coupling, and phase coupling.

This repository provides the data and code used to reproduce key plots from the manuscript and to extend discussions that were only briefly covered therein. All MATLAB scripts were developed and tested in MATLAB R2024a. All Python scripts were developed and tested in Python 3.11.2. * <b> NOTE:</b> New in this V3: 1. 2 new MATLAB files (ChiralPointGroups.m and THz_current_estimation.m), ChiralPointGroups.pdf (a compiled version of ChiralPointGroups.m) and theoretical model code (theoretical_model.zip) are added. More information can be found in the readme. 2. Updated and renamed "publication_data.zip" (in V2) to "data_and_analysis.zip" 3. Change License from CC BY to "Other license". Licensing Terms: Data (all .mat files) is under CC BY and Code is released under MIT license. Therefore, V3 is bound to this new license. V2 is still under CC BY. <b>→ Data and analysis code (data_and_analysis.zip):</b> The dataset is organized into five subfolders. Each subfolder corresponds to a unique combination of experimental conditions, including: • Magnetic field orientation (B ∥ c or B ⟂ c) • Scan parameter (magnetic field or temperature) • Pump laser polarization (linear s, linear p, or circular) • Detection polarization (linear s) Each folder contains: • The raw time-domain data files (.mat) • Oscillator parameters extracted via linear prediction algorithm (.mat) • MATLAB scripts (.m) that generate plots of the raw data, processed fits, and amplified modes. Each script should be run within its corresponding folder to ensure proper loading of the associated data files. Folder summary: 1. B_parallel_c_linear_spump_sprobe_field: B ∥ c, s-polarized pump, s-polarized THz detection, magnetic field dependence 2. B_parallel_c_linear_spump_sprobe_temperature: B ∥ c, s-polarized pump, s-polarized THz detection, temperature dependence 3. B_perp_c_linear_spump_sprobe_field: B ⟂ c, s-polarized pump, s-polarized THz detection, magnetic field dependence 4. B_perp_c_linear_spump_sprobe_temperature: B ⟂ c, s-polarized pump, s-polarized THz detection, temperature dependence 5. B_parallel_c_LCPRCP_pump_sprobe_field: B ∥ c, circularly polarized pump (LCP & RCP), s-polarized THz detection, magnetic field dependence <b>→Theoretical model code (theoretical_model.zip):</b> The Python script depends on packages “numpy” and “matplotlib”. The script generates a plot of the dispersion relations of the theoretical model introduced in the Main Text. More precisely, it plots the real (red) and imaginary (blue) parts of the frequency (ω) as a function of wavenumber (k) as obtained by solving the characteristic equation, equation (6) of the Supplemental Information, with σ_E and σ_Μ given respectively by equations (3) and (2) of the Main Text. All branches of the dispersion relations are plotted simultaneously. All model parameters are adjustable. The included Mathematica notebook (printout also provided in .pdf format) was used to obtain symbolic expressions for the coefficients of powers of ω appearing in the characteristic determinant. These coefficients were copied directly into the Python function detCoeffs(). <b>→ Standalone scripts (not in subfolders):</b> • ChiralPointGroups.m Outputs a table summarizing the 2D matrix representation of σ_Μ in the 11 enantiomorphic point groups. ChiralPointGroups.pdf is a compiled version of chiral point groups table, identical to the output of ChiralPointGroups.m. • THz_current_estimation.m Estimates the photoinduced THz current in tellurium under magnetic field. The script evaluates a phenomenological resonant contribution to the magnetoelectric coupling (with negligible dependence on NIR polarization), leading to excitation of s-polarized, B-antisymmetric mode S_odd at ~0.37 THz. These standalone scripts provide additional physical discussion and calculation detail that are intentionally streamlined or omitted from the published manuscript and its supplementary materials for clarity and space.

This data and code accompany the manuscript "Small population size and possible extirpation of the threatened Malagasy poison frog Mantella cowanii". The data were collected using photograph capture-recapture at three sites in the central highlands of Madagascar. In Part 1, the script implements robust design capture-mark-recapture models in program MARK through the RMark interface to estimate population sizes and annual survival probabilities. In Part 2, it estimates the number of surveys needed to infer absence at sites where we did not detect the frog.

The Cline Center Global News Index is a searchable database of textual features extracted from millions of news stories, specifically designed to provide comprehensive coverage of events around the world. In addition to searching documents for keywords, users can query metadata and features such as named entities extracted using Natural Language Processing (NLP) methods and variables that measure sentiment and emotional valence. Archer is a web application purpose-built by the Cline Center to enable researchers to access data from the Global News Index. Archer provides a user-friendly interface for querying the Global News Index (with the back-end indexing still handled by Solr). By default, queries are built using icons and drop-down menus. More technically-savvy users can use Lucene/Solr query syntax via a ‘raw query’ option. Archer allows users to save and iterate on their queries, and to visualize faceted query results, which can be helpful for users as they refine their queries. Additional Resources: - Access to Archer and the Global News Index is limited to account-holders. If you are interested in signing up for an account, please fill out the <a href="https://docs.google.com/forms/d/e/1FAIpQLSf-J937V6I4sMSxQt7gR3SIbUASR26KXxqSurrkBvlF-CIQnQ/viewform?usp=pp_url"><b>Archer Access Request Form</b></a> so we can determine if you are eligible for access or not. - Current users who would like to provide feedback, such as reporting a bug or requesting a feature, can fill out the <a href="https://forms.gle/6eA2yJUGFMtj5swY7"><b>Archer User Feedback Form</b></a>. - The Cline Center sends out periodic email newsletters to the Archer Users Group. Please fill out this <a href="https://groups.webservices.illinois.edu/subscribe/154221"><b>form</b></a> to subscribe to it. <b>Citation Guidelines:</b> 1) To cite the GNI codebook (or any other documentation associated with the Global News Index and Archer) please use the following citation: Cline Center for Advanced Social Research. 2025. Global News Index and Extracted Features Repository [codebook], v1.3.0. Champaign, IL: University of Illinois. June. XX. doi:10.13012/B2IDB-5649852_V6 2) To cite data from the Global News Index (accessed via Archer or otherwise) please use the following citation (filling in the correct date of access): Cline Center for Advanced Social Research. 2025. Global News Index and Extracted Features Repository [database], v1.3.0. Champaign, IL: University of Illinois. Jun. XX. Accessed Month, DD, YYYY. doi:10.13012/B2IDB-5649852_V6 *NOTE: V6 is replacing V5 with updated ‘Archer’ documents to reflect changes made to the Archer system.

Physiological and yield data from a three year field experiment of soybean exposed to elevated ozone stress and reduced soil moisture at the SoyFACE experiment.

This data set contains data used for “Improved Net Carbon Budgets in the US Midwest through Direct Measured Impacts of Enhanced Weathering.” Data include biomass, soil bulk densities, soil respiration measurements, soil lanthanide element analysis, plant tissue analysis for major cations, and eddy covariance fluxes.

Zika virus (ZIKV) infection has been linked to neurological disorders such as microcephaly in children. Cases of Guillain-Barré Syndrome (GBS), a peripheral nervous system (PNS) disorder, have been reported in adults with ZIKV infection. These ZIKV-related GBS cases often exhibit atypical clinical features compared to classic GBS, including central nervous system (CNS) involvement. This dataset comprises two patient groups and a healthy control group. The first patient group includes adults with confirmed ZIKV infection, presenting both PNS-related GBS symptoms and CNS manifestations. The second group consists of adults with GBS but without ZIKV infection. The final group includes healthy, unaffected individuals.

A novel process applying high solids loading in chemical-free pretreatment and enzymatic hydrolysis was developed to produce sugars from bioenergy sorghum. Hydrothermal pretreatment with 50% solids loading was performed in a pilot scale continuous reactor followed by disc refining. Sugars were extracted from the enzymatic hydrolysis at 10% to 50% solids content using fed-batch operations. Three surfactants (Tween 80, PEG 4000, and PEG 6000) were evaluated to increase sugar yields. Hydrolysis using 2% PEG 4000 had the highest sugar yields. Glucose concentrations of 105, 130, and 147 g/L were obtained from the reaction at 30%, 40%, and 50% solids content, respectively. The maximum sugar concentration of the hydrolysate, including glucose and xylose, obtained was 232 g/L. Additionally, the glucose recovery (73.14%) was increased compared to that of the batch reaction (52.74%) by using two-stage enzymatic hydrolysis combined with fed-batch operation at 50% w/v solids content.

Dataset includes structure and values of a causal model for Training Quality in nuclear power plants. Each entry refers to a piece of evidence supporting causality of the Training Quality causal model. Includes bibliographic information, context-specific text from the reference, and three weighted values; (M1) credibility of reference, (2) causality determined by the author, and (3) analysts confidence level. (M1, M2, and M3) Weight metadata are based on probability language from <a href="https://www.ipcc.ch/ipccreports/tar/vol4/english/index.htm" style="text-decoration: none" >Intergovernmental Panel on Climate Change (IPCC), Climate Change 2001: Synthesis Report</a>. The language can be found in the “Summary for Policymakers” section, in the PDF format. Weight Metadata: LowerBound_Probability, UpperBound_Probability, Qualitative Language 0.99, 1, Virtually Certain 0.9, 0.99, Very Likely 0.66, 0.9, Likely 0.33, 0.66, Medium Likelihood 0.1, 0.33, Unlikely 0.01, 0.1, Very Unlikely 0, 0.01, Extremely Unlikely