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This dataset contains the replication package for "Time to power paces AI infrastructure: Industrial policy and scarcity rents in the United States," submitted to Structural Change and Economic Dynamics (VSI: Strategic technologies and industrial policies). The package reproduces every table and figure in the paper. It contains: (1) Raw inputs as retrieved: - Epoch AI frontier data-center census and construction timelines (CC BY 4.0) - EIA Electric Power Annual, Tables 2.8 and 2.10 (state industrial prices and retail sales, 2025) - EIA natural gas marketed production by state, 2024–2025 - HIFLD electric power transmission lines (345 kV and above) - EIA interstate and intrastate natural gas pipelines - U.S. Census Bureau cartographic boundary files and 2024 county population estimates (2) Constructed data: - Geocodes for the 77 US frontier AI campuses - State-to-market crosswalk (ERCOT, other organized markets, non-RTO) - 5,000 uniform control points - 345 kV network nodes and distance variables - Time-to-power intervals (3) Code: Python scripts 00–08 (data build, symbolic theory checks, PPML siting regressions, Monte Carlo forecast, forecast verification, figures, spatial case–control and point-pattern analysis, maps), run in sequence by run_all.sh. Script 00 retrieves the GIS layers; scripts 01–08 run offline with fixed seeds. The forecast uses 20,000 draws with seed 20261104. (4) Outputs: CSV and JSON files behind Tables 1–10 and B1–B4, and Figures 1–7 at 600 dpi. (5) Reference verification: Crossref/doi.org checks for all journal references and URL checks for grey literature. See README.md for variable construction, data sources and run instructions.

This dataset accompanies a shaking-table study of peak and root mean square (RMS) acceleration responses of pipelines in a scaled utility tunnel. A single specimen was tested under 24 loading conditions combining two input earthquake records (El Centro and Kobe), three equivalent loading angles (0°, 15°, and 30°), and four nominal peak ground acceleration (PGA) levels (0.1, 0.4, 0.7, and 1.0 g). - Accleration.csv.zip contains 24 CSV files, one per loading condition. Each file contains a time column and acceleration measurements for channels A1–A6. Missing timestamps in the original worksheets are retained as blank entries. - Figure-Source-Data.csv.zip contains 41 source-data CSV files for Figures 8–19 of the English manuscript, together with an index linking each file to its figure. These files include the soil measurement-point peak accelerations, pipeline acceleration histories, peak and RMS response metrics, support-configuration comparisons, and results from model validation and sensitivity analyses. - MATLAB-Plot-Scripts.zip contains the 12 MATLAB scripts used to generate the corresponding figures. Some scripts use relative paths to data in the original project directory, so those paths may need to be adjusted when running the scripts from the downloaded archive.

Data set of "Thermo-Hydro-Mechanical Performance of Binary Boron-Modified Ca-Bentonite Composites Under High Decay Heat"

Soil survey data

A semi handwritten financial document image dataset containing 334 Bangla financial document images with field level annotations. It includes 2001 rectangular bounding boxes of 9 kinds of field types. The fields are used to specify the vendor name, vendor date, vendor serial number, document type, goods description, quantity, unit price, total value, and truck number. The annotations are available as a Label Studio JSON export. Every record points to a single image and provides the top, left, bottom and right coordinates of each region annotated and also the region category. Such annotations can be used for training and testing models for field detection as well as for cropping specific fields prior to optical character recognition (OCR). Only the field labels and the bounding boxes are included in the JSON. There is a need for a separate set of reference transcriptions for evaluating the accuracy of text recognition. The collection has varying levels of field coverage. The most common label is Goods description, with 335 areas annotated. The document type is known in 20 regions and the truck number only in one of these. When assessing the extraction performance, the number of examples per field should be reported.

This dataset contains nine supplementary tables (S1–S9) supporting the study entitled "Network Pharmacology and Transcriptomics Prioritize Candidate Targets and Metabolic Pathways for the Huobahuagen-Finerenone Combination in DKD." Tables S1–S5 provide candidate target gene annotations, eQTL dataset identifiers, Mendelian randomization (MR) screening status, complete MR estimates, heterogeneity and horizontal pleiotropy analyses, and SNP-level instrumental variable information. Tables S6–S9 provide single-cell RNA-sequencing results, including cluster-specific marker genes, sample-level comparisons of DPP4, CA2, and SLC12A3 expression across renal cell types, distal convoluted tubule marker expression, and cell counts by sample and annotated cell type. The analyses were based on publicly available data from GEO (GSE209781) and IEU OpenGWAS. The deposited Excel workbook provides supplementary analytical results to support the findings reported in the associated manuscript.

This repository contains the de-identified longitudinal data, analysis code, documentation, and reproducibility materials supporting the manuscript **“Within-person feedback among perfectionistic concerns, academic stress, and burnout across the first university year: A four-wave RI-CLPM study.”** The study followed 720 first-year undergraduate students across four waves over one academic year, with assessments conducted at approximately 12–13-week intervals. The primary analyses examined reciprocal within-person associations among perfectionistic concerns, academic stress, and academic burnout using random-intercept cross-lagged panel models (RI-CLPMs). Additional analyses evaluated longitudinal measurement invariance, discriminant validity, imposed and enacted academic demand, indirect effects, alternative burnout specifications, conventional CLPMs, demographic and GPA-adjusted robustness models, lag-specific sensitivity, attrition, equivalence testing, and phantom-confounder sensitivity. The repository includes de-identified participant-level data in long and wide formats, pilot-study data, recruitment and attrition information, programme-by-wave academic-demand indicators, codebooks and variable documentation, the complete R/lavaan analysis workflow, derived tables and figures, reproducibility logs, and supplementary documentation. Monte Carlo confidence intervals for the final indirect-effect analyses were generated using 200,000 draws with seed 27092026. Institution, programme, class, and participant identifiers are coded to protect confidentiality. No direct personal identifiers are included in the repository. The data and code are provided to support transparency, reproducibility, secondary verification, and methodological reuse of the analyses reported in the associated manuscript. Researchers reusing these materials should consult the README, codebook, item map, file manifest, and analysis workflow before conducting secondary analyses.

This dataset provides code and computational data supporting the development and validation of a shared Buckingham–Coulomb potential for CaCu3Ti4O12 (CCTO) and its A-site multicomponent analogue, (Ca0.25Sr0.25Bi0.25Na0.25)Cu3Ti4O12 (HECTO). It includes the baseline and optimized potential parameters, Python fitting and analysis scripts, DFT reference data, and LAMMPS input files and selected outputs for equilibrium structures, thermal expansion, elastic properties, and energy conservation. The fitting resources comprise 43 historical calibration configurations and 84 configurations used for subsequent parameter refinement. Eight additional thermal configurations are provided for independent evaluation, separately from the fitting data. For these evaluation configurations, the optimized potential yields RMSEs of 0.4657 eV/Å for atomic force components, 0.3151 GPa for stress components, and 21.45 meV/atom for relative energies. Analysis scripts regenerate these metrics and the corresponding force-comparison data, together with structural and elastic-property tables. DFT inputs and outputs for three 160-atom HECTO occupancy configurations are also included; the independent empirical-potential occupancy evaluator is not included in this release. Experimental XRD, SEM, and EDS source data are outside the scope of this computational archive. VASP pseudopotential files and software executables are not distributed. The README describes the directory structure, software requirements, execution commands, dataset roles, and remaining limitations.

The Supplementary Material includes Tables S1 and S2 and Figs. S1–S4. Table S1 presents the elemental compositions of the Ca–F phase from representative experimental runs. Table S2 provides the mass-balance calculations and apparent fluid–melt partition coefficients for Na, Ca, La, and F. Fig. S1 shows EDS and Raman spectra of the Ca–F phase, bastnäsite, and carbocernaite. Fig. S2 presents backscattered-electron image and EDS spectrum of britholite (Bri) in a representative run product. Fig. S3 presents backscattered-electron images and EDS spectra of La-rich patches and carbonatitic melt in a representative run product. Fig. S4. (A) Relationship between DNafluid/melt and DLafluid/melt. (B) Relationship between DFfluid/melt and DLafluid/melt.

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