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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.

Biomass crops engineered to accumulate energy-dense triacylglycerols (TAG or ‘vegetable oils’) in their vegetative tissues have emerged as potential feedstocks to meet the growing demand for renewable diesel and sustainable aviation fuel (SAF). Unlike oil palm and oilseed crops, the current commercial sources of TAG, vegetative tissues, such as leaves and stems, only transiently accumulate TAG. In this report, we used grain (Texas430 or TX430) and sugar-accumulating ‘sweet’ (Ramada) genotypes of sorghum, a high-yielding, environmentally resilient biomass crop, to accumulate TAG in leaves and stems. We initially tested several gene combinations for a ‘push-pull-protect’ strategy. The top TAG-yielding constructs contained five oil transgenes for a sorghum WRINKLED1 transcription factor (‘push’), a Cuphea viscosissima diacylglycerol acyltransferase (DGAT; ‘pull’), a modified sesame oleosin (‘protect’) and two combinations of specialized Cuphea lysophosphatidic acid acyltransferases and medium-chain acyl-acyl carrier protein thioesterases. Though intended to generate oils with medium-chain fatty acids, engineered lines accumulated oleic acid-rich oil to amounts of up to 2.5% DW in leaves and 2.0% DW in stems in the greenhouse, 36-fold and 49-fold increases relative to wild-type (WT) plants, respectively. Under field conditions, the top-performing event accumulated TAG to amount to 5.5% DW in leaves and 3.5% DW in stems, 78-fold and 58-fold increases, respectively, relative to WT TX430. Transcriptomic and fluxomic analyses revealed potential bottlenecks for increased TAG accumulation. Overall, our studies highlight the utility of a lab-to-field pipeline coupled with systems biology studies to deliver high vegetative oil sorghum for SAF and renewable diesel production.

Environmental DNA (eDNA) data for mudpuppy (Necturus maculosus) and salamander mussels (Simpsonaias ambigua) collected at stream sites in the Sangamon River watershed of central Illinois, United States from 2024 to 2025, used to optimize environmental DNA sampling for these species over time and space.

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.

This page contains the data for the publication "Regulation of growth and cell fate during tissue regeneration by the two SWI/SNF chromatin-remodeling complexes of Drosophila" published in Genetics, 2020

These are images and associated statistics of A549 cells treated with pIC. They are stained with DAPI for nucleus detection and IRF3.

95, 150, and 220 GHz light curves and thumbnails of 828 symbiotic star candidates from the New Online Database of Symbiotic Variables that are within the SPT-3G and ACT DR6 footprints.

Yarrowia lipolytica, an oleaginous yeast, shows promise for industrial fermentation due to its robust acetyl-CoA flux and well-developed genetic engineering tools. However, its lack of an active xylose metabolism restricts the conversion of cellulosic sugars to valuable products. To address this, metabolic engineering, and adaptive laboratory evolution (ALE) were applied to the Y. lipolytica PO1f strain, resulting in an efficient xylose-assimilating strain (XEV). Whole-genome sequencing (WGS) of the XEV followed by reverse engineering revealed that the amplification of the heterologous oxidoreductase pathway and a mutation in the GTPase-activating protein gene (YALI0B12100g) might be the primary reasons for improved xylose assimilation in the XEV strain. When a sorghum hydrolysate was used, the XEV strain showed superior xylose consumption and lipid production compared to its parental strain (X123). This study advances our understanding of xylose metabolism in Y. lipolytica and proposes effective metabolic engineering strategies for optimizing lignocellulosic hydrolysates.

This dataset compiles records of 60 of the largest documented crayfish specimens from multiple institutional collections across North America. It includes standardized measurements of body size (carapace length in millimeters), collection year, and generalized geographic locality, along with institutional identifiers and catalog numbers that enable traceability to physical specimens. By aggregating extreme size records across taxa and regions, the dataset is designed to support analyses of maximum body size limits, geographic patterns in size distribution, and historical collection trends. It may also serve as a reference for comparative morphological studies, validation of specimen records, and future investigations into ecological or physiological constraints on crayfish growth.

This dataset is a subset of a companion dataset to the manuscript: Seonyeong Park, Gangwon Jeong, Umberto Villa, Mark A. Anastasio, "A Virtual Imaging Framework for Three-Dimensional Quantitative Optoacoustic Tomography Using Stochastic Numerical Breast Phantoms," arXiv preprint arXiv:2510.00189 (2025) <a href="https://doi.org/10.48550/arXiv.2510.00189">https://doi.org/10.48550/arXiv.2510.00189</a> This subset was specifically used in the following publication: Refik Mert Cam, Seonyeong Park, Umberto Villa, Mark A. Anastasio, "Application of a Virtual Imaging Framework for Investigating a Deep Learning-based Reconstruction Method for 3D Quantitative Photoacoustic Computed Tomography," Photoacoustics 100792 (2025) <a href="https://doi.org/10.1016/j.pacs.2025.100792">https://doi.org/10.1016/j.pacs.2025.100792</a> The dataset contains 64 sets of three-dimensional (3D) numerical breast phantoms (NBPs) for use in virtual imaging studies of optoacoustic tomography (OAT), along with the corresponding simulated multi-wavelength optical fluence distributions, induced initial pressure distributions, and OAT measurement data. Each set corresponds to a distinct breast anatomy and includes four anatomy-matched variants: (i) a healthy breast with Fitzpatrick skin tone 1, and (ii-iv) lesion-inserted breasts with Fitzpatrick skin tones 1, 3, and 5. More detailed information is provided in the accompanying README.txt file.

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. This work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

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.

Scripts for the manuscript "A fluorescence-based transient expression assay for the analysis of upstream open reading frames in plant" by Haas et al. Upstream open reading frames (uORFs) are regulatory elements present in the 5′ leaders of mRNA that can significantly impact downstream gene expression in eukaryotes. In crop engineering, editing of uORFs can provide an avenue to upregulate expression of native genes without the need to add persistent transgenic copies. Even with genome- wide methods to identify translated uORFs such as ribosome profiling, their functional characterization depends on validation through reporter gene assays and mutagenesis studies. Current screening methods for plants use luciferases or protoplasts to measure differential gene expression between wild- type and mutated transcript leaders, which requires tissue processing and/or substrate addition. Here, we present a time- and cost- efficient alternative to investigate transcript leaders by co- expression of two fluorescent proteins in Nicotiana benthamiana leaf tissue and test our assay on genes involved in photoprotection, editing of which could provide a pathway to increase CO2 assimilation during sun–shade transitions.

The dataset contains sample data from those generated for the manuscript "Modeling citations and cartels" by Park et al. (2026), who describe the use of the SASCA-ReSA agent-based model to simulate the growth of citation networks and mimic citation cartels through simulations. The manuscript is presently under review. SASCA-ReSA s the latest stage in a series of progressively complex models of citation dynamics (Chacko et al. 2026 Applied Network Science, Park et al 2025 Proceedings of the XIV International Conference on Complex Networks and their Applications , Park et al 2025 MetaRoR). The model is implemented for high performance computing environments and all the results were generated on the Illinois Campus Cluster. The standard simulation reported in this manuscript results in roughly 1.2M nodes. The input to a simulation is a seed network, a configuration file, and real-world distributions for number of references made per article, and the count of authors per article. The output of a simulation is a larger citation network that includes the input network. Details of the model are described in the manuscript and instructions on how to use the software are available on the SASCA-ReSA GIthub site. We have included annotated nodelists from three different simulations. <b>a) bsl1 (bsl1.csv.tar.xz):</b> has 1,193,102 rows, output of a standard simulation. <b>b) p5_1 (p5_1.csv.tar.xz):</b> has 1,193,102 rows, output of a standard simulation with 5 agents "planted" in year 1 of the simulation. <b>c) ps5_1 (ps5_1.csv.tar.xz):</b> has 1,193,102 rows, output of a standard simulation with one agent planted in each of the first five years of a simulation. <b>d) sample_config.ini:</b> contains configuration parameters for a simulation <b>e) louvain.parquet.gz:</b> has 160,714,032 rows, with two columns: node_id, and cluster_id with header row data representing a louvain clustering of the ABM161 network (<a href "https://doi.org/10.13012/B2IDB-9265079_V1">https://doi.org/10.13012/B2IDB-9265079_V1</a>). Generated using the louvain module from through kuzu and compressed using to_parquet module of pandas with gzip internal compression. The largest cluster (cluster id 5) has 81,675,241 nodes. This network was generated under the SASCA-ReS model.

This dataset contains the raw transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images used in the main figures of the paper “The Importance of Nano-edges in Atomic Stencilling and Chiroptically Active Assembly of Patchy Gold Tetrahedra (2026).” All the images were acquired at the Materials Research Laboratory, University of Illinois at Urbana-Champaign, by Qian Chen group. 1. We provide five subfolders, each named according to the corresponding figure numbers in the paper. 2. All files in the subfolders for Figures 1–3 and 5 are named as "Panel [letter]_*", where [letter] (e.g., a, b, c) represents the raw images used for the corresponding panels. 3. All files in the subfolder for Figure 4 correspond to panel f and show the configurations of patchy tetrahedra synthesized at varying concentrations of iodide and 2-naphthalenethiol. They are named "Experiment_[number]", where [number] represents the corresponding data points in the phase diagram. 4. In TEM images, the bright and dark regions indicate the polymer patches and nanoparticle cores, respectively. 5. In SEM images, the bright and dark regions indicate the nanoparticle cores and polymer patches, respectively. 6. Abbreviations in file names: HAADF-STEM (high-angle annular dark-field scanning transmission electron microscopy), PINEM (photon-induced near-field electron microscopy), and RCP/LCP (left-/right-handed circularly polarized).

Biological production of 5‐aminolevulinic acid (5‐ALA) has received growing attentionover theyears.However, thereis the tradeoff between 5‐ALA biosynthesis and cell growth because the fermentation broth will become acidic due to the production of 5‐ALA. To address this limitation, we engineered an acid‐tolerant yeast, Issatchenkia orientalis SD108, for 5‐ALA production. We first discovered that the cell growth rate of I. orientalis SD108 was boosted by 5‐ALA and its endogenous ALA synthetase (ALAS) showed higher activity than those homologs from other yeasts. The titer of 5‐ALA was improved from 28mg/L to 120‐, 150‐, and 300mg/L, by optimizing plasmid design, overexpressing a transporter, and increasing gene copy number, respectively. After redirecting the metabolic flux using the pyruvate decarboxylase (PDC) knockout strain (SD108ΔPDC) and culturing with urea, we increased the titer of 5‐ALA to 510mg/L, a 13‐fold enhancement, proving the importance of the newly identified IoALAS with higher activity and the strategic selection of nitrogen sources for knockout strains. This study demonstrates the acid‐tolerant I. orientalis SD108ΔPDC has a high potential for 5‐ALA production at a large scale in the future.

Coups d'Ètat are important events in the life of a country. They constitute an important subset of irregular transfers of political power that can have significant and enduring consequences for national well-being. There are only a limited number of datasets available to study these events (Powell and Thyne 2011, Marshall and Marshall 2019, Chin, Carter and Wright 2021). Seeking to facilitate research on post-WWII coups by compiling a more comprehensive list and categorization of these events, the Cline Center for Advanced Social Research (previously the Cline Center for Democracy) initiated the Coup d’État Project as part of its Societal Infrastructures and Development (SID) project. More specifically, this dataset identifies the outcomes of coup events (i.e., realized, unrealized, or conspiracy) the type of actor(s) who initiated the coup (i.e., military, rebels, etc.), as well as the fate of the deposed leader. Version 2.2.2 corrects an error in version 2.2.1 in which the “conspiracy” designation was mistakenly assigned to coup_id: 40411262025. Version 2.2.2 resolves this issue by removing the incorrect designation. Version 2.2.1 adds 67 additional coup events. 47 of these came from examining the Colpus dataset (Chin, Carter, and Wright 2021), and 20 of these events were added to the data set in the normal annual review of potential new coup events. This version also updates the coding to events in Mali in 2012, Serbia in 2000 and Chad in 1979. Version 2.2.0 adds 94 additional coup events. 66 of these came from examining Powell and Thyne’s “discarded” events and 28 of these events were added to the data set in the normal annual review of potential new coup events. This version also updates the coding to events in Brazil in 1945 and the Congo in 1968. Version 2.1.3 adds 19 additional coup events to the data set, corrects the date of a coup in Tunisia, and reclassifies an attempted coup in Brazil in December 2022 as a conspiracy. Version 2.1.2 added 6 additional coup events that occurred in 2022 and updated the coding of an attempted coup event in Kazakhstan in January 2022. Version 2.1.1 corrected a mistake in version 2.1.0, where the designation of “dissident coup” had been dropped in error for coup_id: 00201062021. Version 2.1.1 fixed this omission by marking the case as both a dissident coup and an auto-coup. Version 2.1.0 added 36 cases to the data set and removed two cases from the v2.0.0 data set. This update also added actor coding for 46 coup events and added executive outcomes to 18 events from version 2.0.0. A few other changes were made to correct inconsistencies in the coup ID variable and the date of the event. Version 2.0.0 improved several aspects of the previous version (v1.0.0) and incorporated additional source material to include: • Reconciling missing event data • Removing events with irreconcilable event dates • Removing events with insufficient sourcing (each event needs at least two sources) • Removing events that were inaccurately coded as coup events • Removing variables that fell below the threshold of inter-coder reliability required by the project • Removing the spreadsheet ‘CoupInventory.xls’ because of inadequate attribution and citations in the event summaries • Extending the period covered from 1945-2005 to 1945-2019 • Adding events from Powell and Thyne’s Coup Data (Powell and Thyne, 2011) Version 1.0.0 was released in 2013. This version consolidated coup data taken from the following sources: • The Center for Systemic Peace (Marshall and Marshall, 2007) • The World Handbook of Political and Social Indicators (Taylor and Jodice, 1983) • Coup d’Ètat: A Practical Handbook (Luttwak, 1979) • The Cline Center’s Social, Political and Economic Event Database (SPEED) Project (Nardulli, Althaus and Hayes, 2015) • Government Change in Authoritarian Regimes – 2010 Update (Svolik and Akcinaroglu, 2006) <br> <b>Items in this Dataset</b> 1. <i>Cline Center Coup d'État Codebook v.2.2.2 Codebook.pdf</i> - This 18-page document describes the Cline Center Coup d’État Project dataset. The first section of this codebook provides a summary of the different versions of the data. The second section provides a succinct definition of a coup d’état used by the Coup d'État Project and an overview of the categories used to differentiate the wide array of events that meet the project's definition. It also defines coup outcomes. The third section describes the methodology used to produce the data. <i>Revised February 2026</i> 2. <i>Coup Data 2.2.2.csv</i> - This CSV (Comma Separated Values) file contains all of the coup event data from the Cline Center Coup d’État Project. It contains 29 variables and 1,161 observations. <i>Revised February 2026</i> 3. <i>Source Document v2.2.2.pdf</i> - This 365-page document provides the sources used for each of the coup events identified in this dataset. Please use the value in the coup_id variable to identify the sources used to identify that particular event. <i>Revised February 2026</i> 4. <i>README.md</i> - This file contains useful information for the user about the dataset. It is a text file written in Markdown language. <i>Revised February 2026</i> <br> <b> Citation Guidelines</b> 1. To cite the codebook (or any other documentation associated with the Cline Center Coup d’État Project Dataset) please use the following citation: Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Scott Althaus. 2026. “Cline Center Coup d’État Project Dataset Codebook”. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.2.2. February 17. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V10 2. To cite data from the Cline Center Coup d’État Project Dataset please use the following citation (filling in the correct date of access): Peyton, Buddy, Joseph Bajjalieh, Michael Martin, and Andrea Gerald. 2026. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.2.2. February 17. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V10

Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteus (M×g) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N2O) and carbon dioxide (CO2) emissions, as well as key N cycling genes in soils where M×g and maize were grown. A 150-day soil incubation experiment was conducted using soils from a long-term M×g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha−1 year−1) and a contemporary amendment (60 mg N kg−1) with negative control (0 mg N kg−1). We observed significant increases in cumulative N2O emissions in Mxg soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amoA gene abundance, which plays a significant role in nitrification in nutrient-rich soils, also increased with higher legacy fertilization rates in M×g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N2O emissions, but cumulative CO2 emissions and amoA gene abundance significantly increased. The abundances of norB genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N2O emissions, particularly for perennial bioenergy crops.

This dataset contains records of four years of taxi operations in New York City and includes 697,622,444 trips. Each trip records the pickup and drop-off dates, times, and coordinates, as well as the metered distance reported by the taximeter. The trip data also includes fields such as the taxi medallion number, fare amount, and tip amount. The dataset was obtained through a Freedom of Information Law request from the New York City Taxi and Limousine Commission. The files in this dataset are optimized for use with the ‘decompress.py’ script included in this dataset. This file has additional documentation and contact information that may be of help if you run into trouble accessing the content of the zip files.

Orbitrap mass spectrometry in full scan mode enables the simultaneous detection of hundreds of metabolites and their isotope-labeled forms. Yet, sensitivity remains limiting for many metabolites, including low-concentration species, poor ionizers, and low-fractional-abundance isotope-labeled forms in isotope-tracing studies. Here, we explore selected ion monitoring (SIM) as a means of sensitivity enhancement. The analytes of interest are enriched in the orbitrap analyzer by using the quadrupole as a mass filter to select particular ions. In tissue extracts, SIM significantly enhances the detection of ions of low intensity, as indicated by improved signal-to-noise (S/N) ratios and measurement precision. In addition, SIM improves the accuracy of isotope-ratio measurements. SIM, however, must be deployed with care, as excessive accumulation in the orbitrap of similar m/z ions can lead, via space-charge effects, to decreased performance (signal loss, mass shift, and ion coalescence). Ion accumulation can be controlled by adjusting settings including injection time and target ion quantity. Overall, we suggest using a full scan to ensure broad metabolic coverage, in tandem with SIM, for the accurate quantitation of targeted low-intensity ions, and provide methods deploying this approach to enhance metabolome coverage.f

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 the values directly shown in the figures of the article "The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations". This article is in preparation for submission to the journal Atmospheric Chemistry and Physics. The dataset consists of 12 NetCDF files processed from the raw output of the PartMC model. It does not include the theoretical values of frozen fraction, which can be computed using the equations provided in the paper. *New in V2: adding data for a newly included figure (INP_spectrum.nc), removing files that are no longer used in the revised manuscript figures (e.g., UNC_A_ratio=0.9_Dp=0.1.nc, UNC_A_ratio=0.9_Dp=10.0.nc, UNC_A_ratio=0.1_Dp=0.1.nc, and UNC_A_ratio=0.1_Dp=10.0.nc), and updating README.pdf accordingly.

Raw and Processed 4D-STEM datasets organized by particles appeared in each figure in the publication. 1. Figure 1. 2. Figure 2. 3. Figure 3. 4. Figure S7. 5. Readme.txt