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This thermochronological fission-track dataset was collected along the Bhagirathi Valley in the NW Himalaya, India. The data belong to the part of the PhD work of Sanjeeb Behera and are an outcome of a Ministry of Earth Sciences (MoES) funded project. All analytical work was conducted at the National Facility for Low-Temperature Thermochronology, Kurukshetra University, Kurukshetra, Haryana, India. The dataset corresponds to the research article titled “Episodic thrusting and extension-controlled exhumation of the Higher Himalayan Crystalline in the Bhagirathi Valley, NW Himalaya.” We employed 3D thermo-kinematic modeling to constrain exhumation patterns, controls, and fault parameters. This repository includes the forward and inverse modeling tables, relevant figures, and a compilation table of cooling ages. These supplementary materials are version 3.

This dataset contains the raw data of a 20-day feeding trial in which Nile tilapia (Oreochromis niloticus) juveniles received either a control diet or the same diet with tryptophan at approximately eight times the recommended level ([fill: exact inclusion, g/kg]). Twelve hapas (six per treatment) were stocked with seven fish each, and the hapa was the experimental unit. The data include growth performance, feed intake, feed conversion, fillet weight and yield, mortality and survival (hapa means); fillet CIELAB color, pH and proximate composition; erythrocyte parameters (RBC, hematocrit and MCV); fillet fatty acid profile and the fatty acid profile of the diet; Ct values of qPCR for beta-actin, pla2, hsp70, fads2, scd, acca, cpt1 and acox1 in fillet; and untargeted LC-MS lipidomics of the fillet (148 annotated features, of which 136 lipids were retained after removal of contaminants and non-lipid metabolites). Hematology, fatty acids, qPCR and lipidomics were measured in the same fish (one per hapa). The data are provided as one Excel workbook (one sheet per analysis, a README sheet and a Variables sheet describing every variable and its unit) and as CSV files with the same content. The Python script supplied with the data reproduces all statistical analyses, tables and figures of the related article.

BnPostDuo is a Bengali multimodal social media dataset of 4,708 Facebook image posts across eight content categories: Educational (593), Entertainment (597), Marketing (581), Motivational (600), News (598), Political (598), Religious (551), and Social Awareness (590). Posts were manually collected from publicly accessible Facebook pages and groups during 2025–2026. An initial balanced collection of 4,800 posts (600 per category) was reduced to 4,708 after perceptual-hash (pHash) duplicate screening, manual visual inspection, and removal of 92 confirmed duplicates. Each record links the user-written Bengali caption with text embedded in the post image. Image text was extracted with EasyOCR (raw_ocr) and then manually reviewed against the original images to correct recognition errors and retain the meaningful visible text (main_ocr). Category labels were assigned by human annotators. A stratified subset of 480 posts (60 per category) was independently relabelled by three annotators with the original labels hidden, giving a Fleiss' kappa of 0.8905 (411 unanimous, 69 two-to-one decisions). Files: - BnPostDuo_combined.csv: all 4,708 records (image_id given as category/filename, e.g. marketing/1.jpg) - educational.csv, entertainment.csv, marketing.csv, motivational.csv, news.csv, political.csv, religious.csv, socialawareness.csv: one file per category (image_id given as filename only) Fields: image_id, caption, raw_ocr, main_ocr, phash (64-bit perceptual hash, hex), image_width, image_height (pixels), label. The original Facebook images are not redistributed, out of respect for content creators' rights; only text and image metadata are released. The dataset supports Bengali social media topic classification from captions, OCR text, or both; analysis of OCR errors (raw vs. curated text); and few-shot or zero-shot evaluation of LLMs and VLMs. Processing scripts and documentation: https://github.com/Azu2Bro/BnPostDuo. For academic and research use.

Replication package for Eldar, Kirmse and Wittry, "The Rise of Anti-Activist Poison Pills," Journal of Financial Economics (forthcoming). The package has two parts. 1. Real Kit (Real_Kit_code_and_shareable_data.zip). All Stata and Python programs that build the analysis datasets and produce every table and figure in the paper and the Internet Appendix, run in order by 00_Run_All.do. It also includes the README, ORIGINAL_DATA_SOURCES.md, and the inputs we are allowed to share (the SEC ticker–CIK map, the EDGAR surveillance files and the hand-collected takeover-rumor file). The remaining inputs come from licensed databases (CRSP, Compustat, Thomson Reuters 13F, BoardEx, ISS, SDC, FactSet, Bloomberg) or were shared with the authors privately (the hedge-fund activism data of Brav and Jiang, and of Boyson). These are not included. ORIGINAL_DATA_SOURCES.md lists each input with its source and vintage. The Hoberg–Phillips TNIC files are public and must be downloaded from the Hoberg–Phillips Data Library. The hand-collected poison-pill dataset (PillsFinal) is withheld for two years after publication. 2. Pseudo Kit (Pseudo_Kit_part1 to part5, with part 4 split into 4a and 4b). A complete, runnable copy of the replication kit in which every non-shareable input is replaced by pseudo data. In the pseudo data, identifiers are replaced, values are shuffled within period, and event data are de-linked from real firms and funds. Unzip all six archives into one folder and run 00_Run_All.do. Every program runs end to end, but the numbers it produces are meaningless by design. README_PSEUDO.md explains how the pseudo data were built and how to run them. The full run takes about 11 hours and was tested in Stata 19 MP and Stata SE 16.1. MANIFEST and SHA256SUMS files list the contents and checksums of each archive. Version 2 (Oct 30, 2026): added source line numbers to the README table and figure crosswalks at the data editor's request.

Original imaging WB data

Data package for manuscript “Experimental insights into early Solar System silicate magmatism: petrogenesis and low-pressure emplacement of Erg Chech 002” including all main text tables (Tables 1-2) and supplementery tables (Tables S1-S6).

The dataset [12] consists of one Microsoft Excel workbook, “Roof_Thermal_Performance_Full_Year_BT_incl.xlsx” (about 2 MB), containing six worksheets named BC, SC, SS, ST, TC and BT (Table 1). Each worksheet holds the complete hourly record of one roof configuration. Fig. 1 shows the organisation and Table 2 lists the seven columns, which are identical in all worksheets. The campaign covers 1 June 2025 00:00 to 18 May 2026 23:00 (local time, India Standard Time) with strictly one record per hour: 352 days × 24 h = 8,448 records per worksheet and 50,688 records in total.

The database corresponds to the research study entitled Acute effect of Lavandula angustifolia essential oil on withdrawal syndrome symptoms in smokers, which aimed to evaluate the acute effect of lavender essential oil on anxiety and craving in smokers during nicotine withdrawal. The hypothesis was that inhalation of the essential oil could reduce anxiety and the intense urge to smoke. The study included 60 participants divided into three groups of 20 individuals: GE; (Experimental Group), subjected to inhalation of Lavandula angustifolia essential oil; GCN (Negative Control Group), which received distilled water as a placebo; and GCP (Positive Control Group), treated with transdermal nicotine. Data were collected through pre-test and post-test assessments using validated questionnaires. The pre-test collected sociodemographic information, smoking history, nicotine dependence, anxiety, emotional state, and craving. In the post-test, these indicators were reassessed to identify changes following the interventions. In the GE and GCN groups, assessments were conducted after five minutes of inhalation, whereas in the GCP group, they were performed after four days of transdermal nicotine treatment. The degree of nicotine dependence (GRAUDEP) was measured using the FTND (Fagerström Test for Nicotine Dependence), which classifies dependence into five levels: very low (0–2 points), low (3–4), moderate (5), high (6–7), and very high (8–10). Anxiety was assessed using the State-Trait Anxiety Inventoryo (STAI), comprising two dimensions: IDATE-Traço (STAI-T; Trait Anxiety), which identifies an individual's tendency to respond with anxiety to threatening situations, and IDATE-Estado (STAI-S; State Anxiety), which assesses anxiety experienced at a specific moment. Each dimension contains 20 questions, with responses ranging from 1 to 4 points and total scores from 20 to 80, classified as low (20–40), moderate (41–60), and high (61–80) anxiety. IDATE-E was used to compare anxiety levels before and after the interventions. Craving, defined as an intense and urgent desire to smoke during withdrawal, was measured using the Questionnaire of Smoking Urges-Brief (QSU-B), consisting of ten questions rated on a seven-point Likert scale. The instrument assesses the desire and intention to smoke, anticipation of pleasure, and expectation of relief from withdrawal symptoms. Scores were classified as minimal craving (0–13 points), mild (14–26), moderate (27–42), and intense (43 or more). Its administration during the pre-test and post-test allowed the identification of changes in the urge to smoke. Emotional state was measured using the Escala Analógica do Humor (EAH; Visual Analog Mood Scale), consisting of 16 items assessed on visual scales ranging from 0 to 10. The instrument evaluates four factors: anxiety, sedation, cognitive impairment, and discomfort, reflecting subjective mood experiences during nicotine withdrawal.

This dataset contains the data and code used in Section 6 of the article "Exact solutions and a shrinkage threshold for a tumour response model of FLASH and conventional radiotherapy" by H. Oncu Tigrek and G. Gün Polat. No new experimental data were generated. The data were extracted from Fig. 4 of González-Crespo et al., Phys. Med. Biol. 69 (2024) 215016 (https://doi.org/10.1088/1361-6560/ad8291; open access, CC BY 4.0), which shows the preclinical tumour growth data of Diffenderfer et al. (2020; proton CONV-RT and FLASH-RT, 12 and 18 Gy) and Zhu et al. (2023; X-ray CONV-RT and FLASH-RT, 9.5 Gy, two tumour lines), together with the model curves computed numerically by González-Crespo et al. The values were read from the vector graphics of the published PDF, not from a raster image. Contents: - digitized_tumour_volumes.csv: group mean tumour volumes and standard deviations (mm³) for the control, CONV-RT and FLASH-RT groups of four data sets (122 points). Individual animal measurements were not available. - gc_model_curves.csv: model curves of González-Crespo et al. (Fig. 4). - model_parameters.csv: parameters fitted by González-Crespo et al. (their Table S1), kept fixed in our fits. - OncuTigrek_GunPolat_data.xlsx: all of the above in one workbook, together with Tables 2 and 3 of the article. - Python code that reproduces Tables 2–3 and Figures 2–7 of the article (code/run_all.py) and the extraction procedure (code/extract_from_pdf.py). - README.md: description of the extraction method, the files and the usage. Software: Python 3 with numpy, scipy, pandas, matplotlib (pdfplumber only for the extraction script).

data used in the manuscript named Spatial interpolation and pollution assessment of Cd in surface soil of a lake watershed in a resource-exhausted city