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These datasets contain the complete output from a Monte Carlo simulation of the number of wild cervids to test for chronic wasting disease (CWD) depending on true prevalence. Five CSVs of the simulation results are provided, split due to limitations in file size. The R code used to run the simulation and process the data is included. The data to replicated Table 1 and the data used to compare the simulation results to the CWD surveillance efforts of the Illinois Department of Natural Resources (IDNR) are also provided.

Raw data associated with pre- and post-removal surveys in the Fox River near the Carpentersville dam. Data include survey details (date, location, method), freshwater mussel data (species, age, growth, tag numbers), and habitat (substrate, notes).

Lignocellulolytic enzymes remain one of the primary cost constraints in second-generation (2G) ethanol biorefineries. Achieving efficient hydrolysis of structural carbohydrates with minimal enzyme dosage, maintaining slurry fermentability for industrially relevant ethanol titers, and maximizing ethanol yield per ton of biomass are among the major challenges in 2G processes. In this study, we optimized the dosages of pre-commercial cellulase (NS22257) and hemicellulase (NS22244) on pilot-scale, hydrothermally pretreated lignocellulosic substrates. Enzyme dosages were evaluated at three levels: 20 mg of cellulase with 7.25 mg of hemicellulase (ED-1), 40 mg with 14.5 mg (ED-2), and 60 mg with 21.75 mg (ED-3). As expected, the highest sugar yields were obtained with ED-3; however, for sweet sorghum, oilcane, and miscanthus, sugar yields from ED-2 and ED-3 were not significantly different (p < 0.05). For example, sweet sorghum produced 123.78 ± 1.54 g L−1 and 125.76 ± 0.46 g L−1 of total sugars (glucose and xylose) with ED-2 and ED-3, respectively. Although energycane exhibited a statistically significant difference between ED-2 and ED-3, the incremental gain with ED-3 was modest, increasing sugar release by only 9.02 g L−1 relative to ED-2. Importantly, ED-1 resulted in sugar yields of 88.88 ± 3.64 to 106.86 ± 1.21 g L−1, sufficient to achieve ethanol titers ≥40 g L−1, the threshold required for industrial relevance. A semi-integrated bioprocess validated this outcome, producing 42.09 ± 2.38 g L−1 ethanol and an estimated yield of 213.38 L of ethanol per dry ton of pretreated biomass, requiring only 20.83 L of cellulase and 6.25 L of hemicellulase per ton. Remarkably, these enzyme dosages were approximately tenfold lower than those reported in prior studies.

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

This dataset corresponds to the project "Enhancement of Hole Mobility in Monolayer WSe2 via Process-Induced Strain". Included are: Photoluminescence measurements, transport measurements, atomc force microscope images of strained p-doped WSe2 monolayer FETs, Finite-element analysis of strained AlOx-on-WSe2, Wafer bending topography data of AlOx-on-silica, Full-band simulation scripts and data of strained WSe2. Author contacts by dataset: Primary corresponding author and PI for experimentation: A.M.v.d. Zande PI for simulation: S. Rakheja PI for STEM: P.Y. Huang General fabrication and characterization: H.L. Zhao General simulation: S.M.T.S. Afrid FEA analysis: Z. Islam Wafer bending tests: D.Y. Yoon STEM images: Z. Martin Tungsten oxy-selenide formation: S. Chen

This dataset contains simulation results and scrips from PartMC-MOSAIC and WRF-PartMC that used in the journal article: "Compensating biases in CCN predictions from composition averaging and neglected surfactant effects. Two compressed folder are uploaded here, one is for the data that used in this article, the other folder is the python scripts to process the data. For more details of the uploaded files, please check the README file.

This network is a curated version of a network created by harvesting citing and cited articles around Whitman et al. (1988) Nature, 332(6165):644–646. For further details refer to <a href="https://databank.illinois.edu/datasets/IDB-4897629">https://databank.illinois.edu/datasets/IDB-4897629</a>. Curation was performed by removing nodes (articles identified by Dimensions publication ids) whose year or DOI record was missing from the Dimensions database and retaining the largest connected component of the resulting network. This curated network represents the largest connected component. Integer ids were generated by the authors to replace the Dimensions ids. Access to the raw data requires a license from Digital Science. The original pi3k network contains 17,970,340 nodes of which only 17,508,111 (97.42%) them have both year and DOI information. In this curated version, 127,255,020 edges were reduced to 125,118,817 edges (98.32%). The edges are represented with two columns in the file where the "source_iid" column represents the citing node and "target_iid" column represents the cited node. Restricting the original pi3k network to only those nodes with both year and DOI information results in a graph that has 21,469 connected components where the largest connected component has 17,486,619 nodes (97.31%) . Thus, this network represents 97.31% of the nodes and 98.32% of the edges in the original network. The authors thank Digital Science for supporting this project through access to the Dimensions database.

Sugarcane plant engineered to accumulate lipids in its vegetative tissue is being developed as a new bioenergy crop. The new crop would be a source of juice, oil, and cellulosic sugars. However, limited tolerance of industrially recognized yeasts towards inhibitors generated during the processing of lignocellulosic biomass to produce fermentable sugars is a major challenge in developing scalable processes for second-generation drop-in fuel production. To this end, hydrolysates generated from engineered sugarcane—‘oilcane’ bagasse contain added phenolics and fatty acids that further restrict the growth of fermenting microorganisms and necessitate nutrient supplementation and/or detoxification of hydrolysate which makes the fermentation process expensive. Herein, we propose a resourceful and economical approach for growing lab and commercial strains of S. cerevisiae on unrefined cellulosic sugars aerobically and fermentatively. An equal ratio of hydrolysate and juice was found optimum for growth and fermentation by lab and commercial strains of Saccharomyces cerevisiae engineered for xylose fermentation. The industrial strain grew and fermented efficiently under low aeration conditions having an ethanol titer, yield, specific and volumetric productivities of 46.96 ± 0.19 g/l, 0.51 ± 0.00 g/g, 0.27 ± 0.02 g/g.h and 1.95 ± 0.01 g/l.h, respectively, while the lab strain grew better under higher aeration conditions having the ethanol titer, yield, specific and volumetric productivities of 24.93 ± 0.09, 0.27 ± 0.00 g/g, 0.17 ± 0.00 g/g.h and 1.04 ± 0.00 g/l.h, respectively. Acclimation of cultures in a blended medium significantly improved the performance of the yeast strains. The addition of transgenic oilcane juice, which is inedible and rich in amino acids, to the hydrolysate averted the need for expensive nutrient supplementation and detoxification steps of hydrolysate. The approach provides an economical solution to reduce the cost of fermentation at an industrial scale for second-generation drop-in fuel production.

Data on the chemistry, phosphatase enzyme activity and fungal taxa associated with (i) roots of the tree Podocarpus oleifolius collected from three habitats (soil, litter layer, and aerial microsites), and (ii) roots collected from soil from the trees Weinmannia pinnata and Graffenrieda bella. Samples were collected in the Chorro watershed in the Fortuna Forest Reserve, Panama. Fungal data are from Illumina sequencing and include read number and taxon assignment for Podocarpus oleifolius based on the ITS region, and read number and taxon assignment from NCBI based on the LSU region.

This dataset contains ecological and demographic data for William’s bright‑eyed frog (Boophis williamsi), a critically endangered amphibian restricted to the Ankaratra Massif in Madagascar’s central highlands. Field surveys were conducted between September 2018 – March 2019 and July 2021 across ten 100‑m stream transects to estimate abundance and identify habitat associations for both tadpoles and adult frogs. Data include repeated counts of individuals and associated habitat variables (e.g., canopy cover, substrate type, stream depth, discharge, and temperature). Abundance was estimated using N‑mixture models implemented in R (version 4.3.1) with the ubms package, with separate models for tadpoles and frogs to account for differences in detection probability. The dataset consists of multiple CSV files capturing microhabitat, environmental variables, and raw survey count data (y_frogs.csv and y_tadpoles.csv) and an R script (boophis_abundance.R) used for model fitting. The dataset was compiled for an article accepted in the Herpetological Journal by the British Herpetological Society and is intended to support long‑term monitoring and conservation planning for B. williamsi and other threatened amphibians in Madagascar available at https://doi.org/10.33256/36.2.8797

This dataset contains Northern Sunfish (Lepomis peltastes) catch record data from Multi-Agency Monitoring dataset from the Illinois Waterway (Lockport Pool-Alton Pool) Illinois, USA from 2019-2024. These data are associated with a paper accepted for publication in Northeastern Naturalist in May 2026 entitled "Distribution, abundance, and detection frequency of Lepomis peltastes Cope (Northern Sunfish) in the Illinois Waterway, Illinois USA." These data are in a CSV format. There are seven data columns: year, pool (LP: Lockport Pool, BN: Brandon Road Pool, DR: Dresden Island Pool, MA: Marseilles Pool, ST: Starved Rock Pool, PE: Peoria Pool, LG: La Grange Pool, and AL: Alton Pool), gear (D: daytime boat electrofishing, F: regular fyke net, HS: small hoop net, and M: mini fyke net), coordinate_north_south (latitude), coordinate_east_west (longitude), habitat (MCB: main-channel boarder, SCB: side-channel boarder, and BWC: fully connected backwater), and catch (number of Norther Sunfish caught at that location). These data were analyzed using R Statistical Software (version 4.4.2; R Core Team 2024). See Readme file for a more detailed description of dataset and dataset variables.

Hype - PubMed dataset Prepared by Apratim Mishra This dataset captures ‘Hype’ within biomedical abstracts sourced from PubMed. The selection chosen is ‘journal articles’ written in English, published between 1975 and 2019, totaling ~5.2 million. The classification relies on the presence of specific candidate ‘hype words’ and their abstract location. Therefore, each article (PMID) might have multiple instances in the dataset due to the presence of multiple hype words in different abstract sentences. The candidate hype words are 35 in count: 'major', 'novel', 'central', 'critical', 'essential', 'strongly', 'unique', 'promising', 'markedly', 'excellent', 'crucial', 'robust', 'importantly', 'prominent', 'dramatically', 'favorable', 'vital', 'surprisingly', 'remarkably', 'remarkable', 'definitive', 'pivotal', 'innovative', 'supportive', 'encouraging', 'unprecedented', 'enormous', 'exceptional', 'outstanding', 'noteworthy', 'creative', 'assuring', 'reassuring', 'spectacular', and 'hopeful’. This is version 3 of the dataset. Added new file - WSD_hype.tsv File 1: hype_dataset_final.tsv Primary dataset. It has the following columns: 1. PMID: represents unique article ID in PubMed 2. Year: Year of publication 3. Hype_word: Candidate hype word, such as ‘novel.’ 4. Sentence: Sentence in abstract containing the hype word. 5. Hype_percentile: Abstract relative position of hype word. 6. Hype_value: Propensity of hype based on the hype word, the sentence, and the abstract location. 7. Introduction: The ‘I’ component of the hype word based on IMRaD 8. Methods: The ‘M’ component of the hype word based on IMRaD 9. Results: The ‘R’ component of the hype word based on IMRaD 10. Discussion: The ‘D’ component of the hype word based on IMRaD File 2: hype_removed_phrases_final.tsv Secondary dataset with same columns as File 1. Hype in the primary dataset is based on excluding certain phrases that are rarely hype. The phrases that were removed are included in File 2 and modeled separately. Removed phrases: 1. Major: histocompatibility, component, protein, metabolite, complex, surgery 2. Novel: assay, mutation, antagonist, inhibitor, algorithm, technique, series, method, hybrid 3. Central: catheters, system, design, composite, catheter, pressure, thickness, compartment 4. Critical: compartment, micelle, temperature, incident, solution, ischemia, concentration, thinking, nurses, skills, analysis, review, appraisal, evaluation, values 5. Essential: medium, features, properties, opportunities, oil 6. Unique: model, amino 7. Robust: regression 8. Vital: capacity, signs, organs, status, structures, staining, rates, cells, information 9. Outstanding: questions, issues, question, questions, challenge, problems, problem, remains 10. Remarkable: properties 11. Definite: radiotherapy, surgery File 3: WSD_hype.tsv Includes hype-based disambiguation for candidate words targeted for WSD (Word sense disambiguation)

Large, distributed microphone arrays could offer dramatic advantages for audio source separation, spatial audio capture, and human and machine listening applications. This dataset contains acoustic measurements and speech recordings from 10 loudspeakers and 160 microphones spread throughout a large, reverberant conference room. The distributed microphone system contains two types of array: four wearable microphone arrays of 16 sensors each placed near the ears and across the upper body, and twelve tabletop arrays of 8 microphones each in enclosures designed to resemble voice-assistant speakers. The dataset includes recordings of chirps that can be used to measure impulse responses and of speech clips derived from the CSTR VCTK corpus. The speech clips are recorded both individually and as a mixture to support source separation experiments. The uncompressed files are about 13.4 GB.

Plant species and floral traits shape arthropod communities in restored prairies more than neonicotinoid contamination. Using a manipulated field experiment in an established prairie in Champaign Co., IL, we compared the importance of clothianidin contamination and floral traits on arthropod feeding guild abundances and community structure. These datasets contain observations of insects and plants collected during all sampling periods throughout the experiment (JT-HT_Insect_Sampling_2022.csv) and combined feeding guild abundances and floral variables by sample (JT-HT_SEM_Data.csv). The columns in the individual observation dataset include: sampling date, plot number, treatment (1 = CLO for Clothianidin; 0 = CONT for Control), flower abundance, order, superfamily, family, genus, species, and assigned feeding guild. There were inconsistencies in insect determinations and taxonomic resolution among the observations. Cells left empty due to undetermined taxonomic resolution are filled with a period. Additional supporting information—such as seed set, aboveground plant biomass, clothianidin tissue levels, sample design, and proposed structural models—can be found through the publisher. The columns for the combined variables by sample include: Plot #, Plant (USDA plant code), Treatment, Treat (binary variable of treatment required by the R package), Average Seed Set, Plant Dry Weight (in grams), Heads (number of individual flower units), Inflorescences (number of grouped flowering units), Herbivore, Ants, Omnivore, Pollinator, Predator, and Omni. R code for running analyses (SEMs, PERMANOVA) and plot visualization are also provided.

This is species specific scavenger data documented at puma kills in the Santa Cruz Mountains, relating to the manuscript: Allen, M.L., A.T.L. Allan, R.M. King, B.H. Warner, J.J. Morgan, and C.C. Wilmers. 2026. Scavenger assemblage behavior at puma kills in the Santa Cruz Mountains, California. Ecology and Evolution.

We apply prospect theory to examining farmers’ economic incentives to divert a share of their land to bioenergy crops (miscanthus and switchgrass in this study). Numerical simulation is conducted for 1,919 rain‐fed U.S. counties to identify the impact of loss aversion on bioenergy crop adoption, and how this impact is influenced by biomass price, discount rate, credit constraint status, and policy instruments. Results show that ignoring farmer’s loss aversion causes overestimation of miscanthus production but underestimation of switchgrass production, particularly when farmers are credit constrained and have a high discount rate. We find that establishment cost subsidy induces more miscanthus production whereas subsidized energy crop insurance induces more switchgrass production. The efficacy of these two policy instruments, measured by biomass production increased by per dollar of government outlay, depends on the magnitude of farmers’ loss aversion and discount rate.

Nitrogenous fertilizers provide a short-lived benefit to crops in agroecosystems, but stimulate nitrification and denitrification, processes that result in nitrate pollution, N2O production, and reduced soil fertility. Recent advances in plant microbiome science suggest that genetic variation in plants can modulate the composition and activity of rhizosphere N-cycling microorganisms. Here we attempted to determine whether genetic variation exists in Zea mays for the ability to influence the rhizosphere nitrifier and denitrifier microbiome under “real-world” conventional agricultural conditions. To capture an extensive amount of genetic diversity within maize we grew and sampled the rhizosphere microbiome of a diversity panel of germplasm that included ex-PVP inbreds (Z. mays ssp. mays), ex-PVP hybrids (Z. mays ssp. mays), and teosinte (Z. mays ssp. mexicana and Z. mays ssp. parviglumis). From these samples, we characterized the microbiome, a suite of microbial genes involved in nitrification and denitrification and carried out N-cycling potential assays. Here we are showing that populations/genotypes of a single species can vary in their ecological interaction with denitrifers and nitrifers. Some hybrid and teosinte genotypes supported microbial communities with lower potential nitrification and potential denitrification activity in the rhizosphere, while inbred genotypes stimulated/did not inhibit these N-cycling activities. These potential differences translated to functional differences in N2O fluxes, with teosinte plots producing less GHG than maize plots. Taken together, these results suggest that Zea genetic variation can lead to changes in N-cycling processes that result in N leaching and N2O production, and thereby are selectable targets for crop improvement. Understanding the underlying genetic variation contributing to belowground microbiome N-cycling into our conventional agricultural system could be useful for sustainability.

This file contains the delta 15N values for leaf material collected from Cyathea rojasiana tree ferns before and after fertilization using ammonium -15N chloride solution to determine whether 15N update is possible from senescent leaves. Details of the experiment are provided in the online supplement to the published paper. Briefly, In February 2022 we selected three mature C. rojasiana individuals 1-1.5m in height that had leaves rooted in the soil and one new developing (but unexpanded) leaf. For each fern, two plastic pots (10 x 10 x 12 cm) were filled with a 50:50 mixture of washed river sand and soil from the Chorro watershed. For each pot, one senescent leaf that was rooted in the soil was carefully excavated and its roots transplanted into the pot. Pots were then fertilized by adding 30 ml of a 0.02 M 15N solution of ammonium-15N chloride (98% 15N; Sigma-Aldrich 299251; St Louis, MO) to yield a target concentration of 2 µg15N cm-3 of soil. After fertilization pots were carefully enclosed within thick plastic bags, and sealed around the senescent leaf rachis to prevent leaching any of 15N from the pot to the surrounding soil. At the time of N fertilization, pinnae of the youngest fully expanded leaf were collected from each fern. One pinna was collected from the base of the leaf and one from the distal end of the leaf. In March 2022, after 28 days the roots were removed from pots and two additional leaf pinnae sampled from each fern: one from the base and one from the distal end of the youngest (now fully expanded) leaf. Leaf samples were dried for 72 hours at 60 C and then leaf lamina tissue finely ground with a bead beater. The delta 15N for each leaf sample determined at the University of Illinois, Urbana-Champaign using a Thermo Delta V Advantage IRMS run in combination with a Costech 4010 Elemental Analyzer. Samples were run in continuous flow relative to laboratory standards that were calibrated with USGS 40, 41, and NBS 19 reference materials.

Producing enantioenriched molecules from racemic mixtures is essential for manufacturing. Traditional methods such as resolution, deracemization and enantioconvergent catalysis primarily involve separating or converting enantiomers without altering their structures, or functionalization of stereocentres at or proximal to functional groups. However, there are challenges in enantioselectively forging C–H bonds that are remote from functional groups via hydrogen atom transfer (HAT) with these methods. Here we introduce a strategy for the photoenzymatic stereoablative enantioconvergence of γ-chiral oximes using repurposed flavin-dependent ene-reductases. A photoinduced single-electron reduction of the γ-chiral oxime by an ene-reductase generates an iminyl radical, which then undergoes stereoablative 1,5-HAT at the γ-stereocentre. Subsequent chiral reconstruction through enzymatic HAT and spontaneous imine hydrolysis yields the γ-chiral ketone with high enantioselectivity. This work provides a robust method for remote stereoablative enantioconvergent HAT and broadens the synthetic utility of photobiocatalysis.

Sequences from the PRNP coding region of wild white-tailed deer along with chronic wasting disease status. Animals were harvested from 22 Northern Illinois counties between 2002 and 2022.

We present a three-year archival, longitudinal dataset of YouTube Trending videos, collected from July 1, 2022, to June 30, 2025, four retrieval per day. This collection, a unique historical record of digital culture in transition, includes 446,971 snapshots from 104 countries, encompassing 726,627 unique videos and their associated metadata. Each record includes collection timestamp, geographic region, video ranking, core identifiers (video ID, channel ID, category), content metadata (title, description, tags, localization), language information, live status, view and comment counts. Full documentation: https://arxiv.org/abs/2510.23645 Unlike previous datasets with limited geographic scope or short timeframes, our data offers exceptional coverage for cross-national and longitudinal analyses of digital culture. This non-personalized data corpus provides an irreplaceable baseline for understanding crisis communication, platform governance or temporal shifts in content popularity. Publication: Goncalves, A., & Ng, Y. M. M. (2026). Global YouTube Trending Dataset (2022–2025): Three Years of Platform-Curated, Cross-National Trends in Digital Culture. Proceedings of the International AAAI Conference on Web and Social Media, 20(1), 2817–2827. https://doi.org/10.1609/icwsm.v20i1.42784

This dataset is a companion dataset to the manuscript: Hsuan-Kai Huang, Joseph Kuo, Seonyeong Park, Umberto Villa, Lihong V. Wang, Mark A. Anastasio, "Stochastic numerical head phantoms to enable virtual imaging studies of transcranial photoacoustic computed tomography," arXiv: arXiv:2510.09758 (2025) <a href="https://doi.org/10.48550/arXiv.2510.09758">https://doi.org/10.48550/arXiv.2510.09758</a> The dataset contains 50 sets of three-dimensional (3D) numerical head phantoms (NHPs) for use in virtual imaging studies of transcranial photoacoustic computed tomography (t-PACT), along with the corresponding simulated optical fluence distributions, induced initial pressure distributions, and t-PACT measurement data. More detailed information is provided in the accompanying README.txt file.

Visibility Amplitude Pattern Speeds from the v3 Sgr A* Library. Data for "Event Horizon Telescope Pattern Speeds in the Visibility Domain” (Conroy et al.). Data are provided in 2 file formats: a TXT table which is a standard format for the Astrophysical Journal (ApJ) where the paper is submitted and the original NPY format.

Rubisco activase (Rca) facilitates the release of sugar-phosphate inhibitors at Rubisco catalytic sites during CO2 fixation. Most plant species express two Rca isoforms, the larger Rca-α and the shorter Rca-β, either by alternative splicing from a single gene or expression from separate genes. The mechanism of Rubisco activation by Rca isoforms has been intensively studied in C3 plants. However, the functional role of Rca in C4 plants where Rubisco and Rca are located in a much higher [CO2] compartment is less clear. In this study, we selected four C4 bioenergy grasses and the model C4 grass setaria (Setaria viridis) to investigate the role of Rca in C4 photosynthesis. All five C4 grass species contained two Rca genes, one encoding Rca-α and the other Rca-β, which were positioned closely together in the genomes. A variety of abiotic stress-related motifs were identified in the Rca-α promoter of each grass, and while the Rca-β gene was constantly highly expressed at ambient temperature, Rca-α isoforms were expressed only at high temperature but never surpassed 30% of Rca-β content. The pattern of Rca-α induction on transition to high temperature and reduction on return to ambient temperature was the same in all five C4 grasses. In sorghum (Sorghum bicolor), sugarcane (Saccharum officinarum), and setaria, the induction rate of Rca-α was similar to the recovery rate of photosynthesis and Rubisco activation at high temperature. This association between Rca-α isoform expression and maintenance of Rubisco activation at high temperature suggests that Rca-α has a functional thermo-protective role in carbon fixation in C4 grasses by sustaining Rubisco activation at high temperature.