Share your research data

Data and code to replicate Baker, Balthrop, Johnson, Kotter, and Pisciotta (JFE): Gambling Away Stability: Sports Betting's Impact on Vulnerable Households.

This dataset includes soil physical, chemical, and spectral properties used for the estimation of soil water retention curve parameters. The data were collected from soil samples and can be used for developing and evaluating predictive models of soil hydraulic properties.

Causative Medications in DRESS patients with certain medication cause (n=48)

This file contains the supplementary tables for the manuscript “Trends in cancer-related hospital utilization and mortality in Mexico by access to social security, 2004–2024: implications for policymaking”, submitted to Salud Pública de México. The tables present annual percent changes (APC) and 95% confidence intervals derived from time-series cross-sectional marginal models used to assess trends in hospital utilization and mortality for breast, cervical, prostate, colorectal cancer, and leukemia, stratified by sex and social security status. Models were estimated using Prais–Winsten regression with predefined spline terms to account for policy-related changes and temporal autocorrelation. Sensitivity analyses excluding 2020–2021 were also performed to evaluate the potential influence of the COVID-19 pandemic. These supplementary materials provide the detailed numerical results underlying the graphical findings presented in the main manuscript.

This study performs a spatiotemporal wetland change analysis for the Sangamon River Watershed, Illinois, using Landsat 5 TM between 2000–2008, Sentinel-2 Surface Reflectance, Sentinel-1 Synthetic Aperture Radar (SAR) between 2017–2025, and terrain data through an integrated machine learning (ML) and deep learning (DL) frameworks in Google Earth Engine (GEE), Google Colab (Python3) and ArcGIS Pro 3.6. We conducted a comparative assessment of DL Dense Neural Networks (DNN) and U-Net semantic segmentation, as well as three ML models including Random Forest (RF), Gradient Tree Boosting (GTB), and Support Vector Machine (SVM) through pixel-based and object-based image analysis (OBIA) methods. Reclassified National Land Cover Database (NLCD) datasets were used for training and validation using stratified random sampling for five categories namely Wetlands (1), Forest (2), Agriculture/ Grassland/ Barren land (3), Urban/Developed (4) and Water (5).

Table S1. Dietary formulation information for camel milk from Northern Xinjiang (Altay City, Xinjiang), Southern Xinjiang (Aksu City, Xinjiang), and Inner Mongolia (Alxa League, Inner Mongolia). Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia. Table S2. Dietary formulation information for bovine milk from Northern Xinjiang (Altay City, Xinjiang), Southern Xinjiang (Aksu City, Xinjiang), and Inner Mongolia (Alxa League, Inner Mongolia). Notes: XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia. Supplementary Fig.1. Standard curves for the quantification of K, Ca, Na, Mg, P, Zn, Fe, Mn, Ba, Co, Sr, and Cu (R²＞0.999). Table S3. ARRIVE Guidelines 2.0 author checklist.

A dataset of higher education students' perceptions and behavioral intentions regarding ChatGPT adoption, designed to support explainable AI and technology acceptance research in education.

The CL_Image_Processing_v21.m script processes .dm4 type cathodoluminescence data generated by Gatan Digital Micrograph software, outputted as a data cube (2 spatial axes as a constructed image, 1 spectral axes preset as wavelength or energy). It utilised a fitting algorithm for up to two gaussian response peaks, which is then mapped of all individual properties for comparisons (intensities, energies, peak widths and more). Absorptance plots are also built within each pixel and used to generate Urbach Energy maps, constrained spectrally by the peak behaviour of the CL response. In its current form, it is primarily optimised to analyse CdSeTe and CdSe semiconductor films, however the script can run wider spectral analysis to be transferrable for other materials, and can be further optimised within the script if necessary. Note: Ensure that the two additional script files (ReadDMFile.m and fire.m) are placed in the same folder as the processing script for the file to work. Additionally a wavelength/energy range must be in the data file name (the format will be displayed in an error message

Research Hypothesis The core hypothesis of this study posits that Sustainable Construction Supervision Performance (SCSP) on building sites in rapidly urbanizing regions is heavily constrained by systemic structural bottlenecks, specifically Professional Capacity Deficiencies (PCD) and Regulatory Ambiguity (RA). Conversely, it is hypothesized that proactive Professional Competence of Supervisors and structured Stakeholder Collaboration act as vital enabling mechanisms that can directly counter these barriers and significantly improve multi-pillar sustainability compliance (Environmental, Economic, Social, and Technological) in the field. What the Data Shows & How It Was Gathered sustainable_construction_supervision_raw_data.xlsx consists of empirical field metrics captured across 150 active building construction sites in Sylhet, Bangladesh. A multi-informant survey design was utilized to collect data from 597 active field practitioners, including Site Engineers, Project Managers, Contractors, and Construction Supervisors. This structural matrix features 50 distinct variables, yielding 29,850 discrete data entries with zero missing values. The dataset evaluates performance using two primary measurement structures: 5-Point Likert Scales (1 = Strongly Disagree to 5 = Strongly Agree): Used to quantify subjective operational realities, including the four pillars of sustainability (Environmental, Economic, Social, Technological), systemic barriers, and positive enabling drivers. Binary Indicators (1 = Yes, 0 = No): Deployed to map explicit on-site technical capacities and actual digital tool utilization rates. Notable Findings The Technological Deficit: The data exposes a severe gap in digital workflows. Building Information Modeling (BIM) adoption scored an industry-wide low (Mean = 1.84, SD = 0.88). Furthermore, binary tracking reveals that while mobile site communication is widespread (71%), advanced practices like cloud-based reporting (28%) and automated safety monitoring (14%) remain largely unadopted. Primary Systemic Bottlenecks: Practitioners pointed to a Lack of Qualified Professionals (Mean = 4.18, SD = 0.63) and Ambiguous Regulatory Frameworks (Mean = 4.09, SD = 0.66) as the most critical structural constraints halting sustainable transition. Acute Skills Gaps: Binary diagnostic items show that 72% of active site supervisors completely lack formal sustainability training, 64% operate with insufficient environmental compliance knowledge, and 78% have zero technical proficiency in digital engineering tools. The Core Enablers: The Professional Competence of Supervisors (Mean = 4.42, SD = 0.54) and Collaboration Among Stakeholders (Mean = 4.26, SD = 0.61) emerged with the highest baseline agreement as the most powerful drivers for project success. Data Interpretation and Use Researchers can model the direct path coefficients β & inner relationships between organizational barriers & sustainability outcomes by mapping these 50 indicators.

The Wata dataset is a semantic text classification dataset for the Sorani Kurdish Dialect. It contains 15,052 annotated text samples collected from publicly accessible social media platforms, including Facebook, Telegram, and TikTok. The dataset is organized into five semantic categories: Normal (0), Romantic (1), Advice (2), Threat (3), and Hate Speech (4). The dataset is provided in CSV format and consists of two columns: text, containing the Sorani Kurdish Dialect text, and label, containing the corresponding category identifier. Data preprocessing included noise removal, spelling verification, normalization, orthographic standardization, linguistic review, and annotation to improve consistency and usability for Natural Language Processing (NLP) research. The dataset was created to support semantic text classification and related NLP tasks in Sorani Kurdish Dialect, a low-resource language with limited publicly available benchmark datasets. The dataset contains no missing values and no duplicate text entries. Researchers can use this resource for academic and non-commercial research purposes.