Share your research data

This dataset contains spectral data and hydrological and water quality simulation results for the Nielba study area. It combines multispectral spectral information from WorldView-3 satellite imagery with daily outputs generated using the Soil and Water Assessment Tool (SWAT) model. The dataset is provided as an Excel workbook (XLSX format) containing two worksheets: 1. wv3_all_point_spectra This worksheet contains 40 spectral records grouped into five sub catchments (SUB), with individual sampling points identified by the point_ID attribute. Spectral values are provided for eight WorldView-3 multispectral bands: Coastal, Blue, Green, Yellow, Red, Red Edge, NIR1, and NIR2, covering the visible and near-infrared regions of the spectrum. The data represent spectral characteristics associated with individual sampling points. Remote Sensing Spectral Surface Reflectance Data: • SUB: Sub-catchment; • point_ID: Unique spatial point identifier within the sub-catchment; • Coastal / Green / Yellow / Red / Red edge / NIR1 / NIR2: Surface reflectance values for spectral bands. 2. SWAT_model_sim This worksheet contains daily SWAT model simulation outputs covering the period from 1 January 2004 to 31 December 2018. It includes five consecutive time-series datasets for five sub-catchments, each covering the entire simulation period. The following variables are provided: • SUB – sub catchment; • DATE – Simulation date; • FLOW_OUTcms – Simulated water discharge leaving the river reach, measured in cubic meters per second (m3/s); • CHLA_OUTkg – Chlorophyll-a discharge transported out of the river reach, measured in kilograms per day (kg/day); • CHLA_CON – Chlorophyll-a concentration (kg/m3). Potential Applications: The dataset provides integrated information on spectral characteristics, simulated water discharge, and chlorophyll-a dynamics. It is dedicated for research on water quality assessment, investigating the relationship between remotely sensed spectral information and water quality parameters, and the application of hydrological modeling in river monitoring.

This dataset supports research on the prediction of physicochemical properties of sustainable aviation fuel (SAF) blends using attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy and machine learning. The dataset contains raw ATR-FTIR absorbance spectra of 50 fuel samples, with 2,385 spectral variables covering approximately 3997–599 cm⁻¹. Reference measurements include density, 10% and 90% distillation temperatures (T10 and T90), and kinematic viscosities at −20 and −40 °C for all 50 samples. Freezing-point measurements are available for 33 samples. Fuel-blend composition information and sample identifiers are provided to support data interpretation and sample matching. Where included, Python scripts and outer-fold out-of-fold prediction results document the machine-learning evaluation workflow. Missing freezing-point measurements are retained as missing values rather than imputed.

This dataset contains the computational and experimental data underlying the study “Umbelliferone Enhances TRAIL-DR5 Binding in vitro at Micromolar Concentrations: a Mechanism Resolved by Staged Oligomer-State Interaction Profiling,” submitted to the Indonesian Journal of Chemistry. It lets readers reproduce the docking rankings, the interaction analysis, and the binding-assay results reported in the article and its supplementary material. The deposit is organised in four folders, accompanied by the supplementary material document (Methods S1, Text S1, Tables S1 to S8, and Figures S1 and S2). Docked structures: the four rigid-body poses of coumarin, ellagic acid, gallic acid, and umbelliferone at the dimeric DR5-TRAIL-DR5 interface, generated with Hex 8.0.0 from PDB entry 1D4V (COU_dimer_clean.pdb, EA_dimer_clean.pdb, GA_dimer_clean.pdb, UMB_dimer_clean.pdb). In every file, chains A and C are DR5 (residues 69 to 185), chain B is TRAIL (residues 119 to 281), and chain X is the docked ligand, written as UNK 1. Because residues 119 to 185 occur in both proteins under this numbering, contacts in that range must be assigned from the chain identifier, not the residue number. Interaction analysis: a workbook with Hex E-values for all fifteen compounds at the monomeric and dimeric states, the ranking sheet, and the per-compound BIOVIA Discovery Studio contact listings. These listings are unfiltered and include the chain-terminus contacts excluded from the article. Binding assay: the unmodified GloMax reader export (3 June 2026) behind the dose-response data. Vina cross-check: the AutoDock Vina versus Hex comparison table. Vina was run as a single job per ligand with no fixed random seed, so the scores are not bit-reproducible. A README in the archive root repeats this layout and the reuse caveats. The data are shared under a CC BY 4.0 licence.

This dataset contains the gamma ray and meteorological observations used in the study of the 2024 Hualien earthquake sequence in eastern Taiwan. The data support the analysis of gamma ray variations associated with meteorological disturbances and seismic activity.

The workbook retains all 188,870 response records and 71,246 matched pairs

From risk detection to timely protection: A critical integrative review of sustainable food systems

This repository contains the coded dataset and analysis code for the paper. Every number, table and figure in the paper can be reproduced from Supplementary_Data_S1.xlsx using the three scripts below. Authors: Prabhat Ghimire, Shristi Rimal, Sijal Shahi, Bishwo Dahal (School of Engineering, Pokhara University, Nepal) Contact: prabhatghimire7@gmail.com Source reports: Ministry of Culture, Tourism and Civil Aviation (MoCTCA), Government of Nepal, Aircraft Accident Investigation page: https://tourism.gov.np/category/Aircraft-Accident-Investigation/?page=1

Processed metabolomic data underlying the manuscript. Files contain (1) the plasma LC-MS/MS feature table (317 annotated features; molecular formula, adduct, m/z, retention time, mass error, and peak areas for 40 samples), (2) the urine LC-MS/MS feature table (842 annotated features with KEGG and HMDB identifiers and chemical class, plus peak areas for 48 samples and 12 pooled QC injections), and (3) 1H-NMR quantified metabolite concentrations for plasma (39 metabolites) and urine (37 metabolites). Sample codes A1–A10, B1–B10, C1–C10 and D1–D10 correspond to YQHXF, ISMN, model and sham groups, respectively.

This dataset contains microfluidic experimental images and COMSOL Multiphysics simulation models associated with the study “Hydraulically driven metastable internal support structures in loess: Pore-scale evidence and depth-dependent hydraulic behavior.” These materials support the pore-scale investigation of hydraulically driven metastable internal support structures in loess and the analysis of depth-dependent hydraulic behavior.

This dataset contains 144 field photographs taken by the authors at the Maha Kumbh Mela 2025, Prayagraj, India, one of the largest religious gatherings in the world, during January and February 2025 (the Mela ran from 13 January to 26 February 2025). The photographs document the Mela as a temporary city. They cover religious life (akhara camps and processions, royal baths, Naga and women sannyasis, sannyas initiation at the Sangam, the Kinnar Akhada and its rituals, and kalpvas practice such as shayya-daan, daily worship and cooking on dung-cake hearths); infrastructure (pontoon bridges under construction and in use, tent cities and luxury camps); public services (the Mela Authority office, media centre, computerised lost- and-found centre, hospitals and first aid, fire and emergency services, railway arrangements, temporary bank branches and tourist information); welfare and labour (sanitation workers and the Vidya Kumbh school for their children); culture and commerce (Kala Kumbh and Kala Gram exhibitions, state pavilions, folk performances, vendors and bhandaras); and Prayagraj city during the Mela. Each image has a stable identifier (KUMBH_0104.jpg to KUMBH_0247.jpg). The numbering continues from the companion dataset of banners and hoardings (doi:10.17632/xmf482njn2.1), so identifiers are unique across both. An accompanying catalogue (XLSX and CSV) gives one row per image: event, collection details, photographers and rights, scene category, visible features, a crowd annotation (none / sparse / moderate / dense), technical details, processing applied and sharing status, together with the photographers' original Hindi captions. The original camera files are no longer available. The images come from a compilation the authors prepared after fieldwork, which had reduced the resolution (median width about 880 px) and removed camera metadata. Exact dates are therefore known only for five images that carry a GPS Map Camera stamp (8–9 February 2025). To protect privacy, the faces of real people were blurred in 75 images (217 regions); faces printed on posters and hoardings were left unchanged. Eleven images are marked "Needs review" because they show children (faces blurred) or the ritual nudity of Naga ascetics. The data can support research on religion and pilgrimage, mass-gathering management and public services, temporary urbanism, the anthropology of Hindu ascetic orders and the Kinnar Akhada, and visual culture. Companion dataset ----------------- This dataset complements: Maral, Priyaranjan; Kumar, Sumit (2026). "Mahakumbh Mela 2025 (Prayagraj) Field Photographs of Banners, Hoardings and Public Messaging". Mendeley Data, V1. doi: 10.17632/xmf482njn2.1 That dataset contains images KUMBH_0001–KUMBH_0103. This dataset continues the numbering (KUMBH_0104–KUMBH_0247), so every identifier is unique across both.