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hybrid · semantic + lexical · 37 datasets ranked · 1.13s

Structurecomposite2
Depthcataloged35measured2
Licenseopen29unknown6non commercial1share alike1
Accessopen37
Formattar31csv18tsv16fits15bzip25
Sourcezenodo37
clear
1-20 of 37sortrelevancemeasured firstqualitysize
composite

Stimuli-Responsive Silsesquioxane Nanozymes for Organocatalysis in Water and Prodrug Activation in Cells

0.00

Zahid, R · Lázaro, A · Moreno‐Alcántar, G · et al.

1 files · 82 KB · tar

docx4
pdf2
zip2
fasta1
netcdf1
png1
sqlite1
xlsx1

Synthetic nanozymes have emerged as promising alternatives to natural enzymes for catalytic and therapeutic applications, yet their limited stability, aqueous compatibility, and catalytic scope impede broader utilization. Here, we report a mild, one-step sol-gel synthesis that yields ultrasmall, water-stable octa-amino silsesquioxanes functioning as metal-free nanozymes. These minimalistic nanostructures exhibit aldolase-like organocatalytic activity in water and enable dynamic, stimuli-responsive modulation of catalysis through reversible supramolecular aggregation and disaggregation triggered by specific chemical inputs, thus forming a multifunctional platform for tunable catalysis and biomedical applications. Structural simplicity, stability, and functional versatility together permit tunable, enzyme-like catalysis in water without auxiliary surfactants or phase-transfer additives. Furthermore, the nanozymes display high biocompatibility and efficient cellular internalization, enabling their use in living cells, for instance, as intracellular prodrug activators via retro-aldol activation of a doxorubicin prodrug in human glioblastoma and metastatic melanoma cells, resulting in selective cytotoxicity. This system provides a cost-effective, sustainable, and scalable platform for water-compatible, metal-free organocatalysis that bridges abiotic catalysis and biological function. These findings demonstrate how rationally designed silsesquioxane frameworks can emulate natural enzyme reactivity while integrating adaptive, stimuli-responsive behavior, broadening the applicability of synthetic nanozymes to catalytic and therapeutic contexts.

open·CC0-1.0·Zenodo·completeSource
composite

Fast Breakdowns Observed in the Initial Leaders of Two Energetic Compact Strokes

0.00

Yang, Qingliu

6 files · 8.0 MB · bzip2

Dataset Description This dataset contains 3D lightning location results, DALMA and FALMA waveform for two Energetic Compact Stroke (ECS) events. location results are included: HF3D_1732785151.dat - 3D lightning locations for the ECS leader A flash. HF3D_1734785454.dat - 3D lightning locations for the ECS leader B flash. The timestamp 1734785454 and 1732785151 corresponds to the occurrence time of the lightning flash in Japan Standard Time. File format and parameters The first row contains the lightning occurrence time. Column descriptions: Time (ms) - time relative to the lightning source. X, Y, Z (m) - 3D spatial coordinates relative to ground level. The origin (0, 0, 0) corresponds to latitude 36.76°N and longitude 136.76°E. FALMA and DALMA waveform ECSLeaderA_DALMA_waveform.bz2 is DALMA waveform of Leader A. ECSLeaderA_FALMA_waveform.bz2 is FALMA waveform of Leader A. ECSLeaderB_DALMA_waveform.bz2 is DALMA waveform of Leader B. ECSLeaderB_FALMA_waveform.bz2 is FALMA waveform of Leader B. This dataset allows analysis of the spatial and temporal development of these two ECS flashes.

open·CC-BY-4.0·Zenodo·completeSource
declared

Planet4Health Project: mHM Model Runs in South African domain at 0.015625deg resolution - Soil Moisture Layers 4, 5 & 6

0.00

Modiri, Ehsan · Shrestha, Pallav Kumar · Samaniego Eguiguren, Luis Eduardo

100 files · 49 GB · netcdf, tardeclared

Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625°. The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components for soil moisture layers 4, 5 and 6, consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ). The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch (https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Spin-up: 30-year spin-up using 1990-2019 ERA5 climatology Model version: v1.0 Setup Scope: Model run for domain 1020011530, post-processed and clipped. Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline (https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables sm_l04: Volumetric soil moisture layer 4 (300-500 mm depth) [mm mm-1, fraction between 0 and 1] sm_l05: Volumetric soil moisture layer 5 (500-1000 mm depth) [mm mm-1, fraction between 0 and 1] sm_l06: Volumetric soil moisture layer 6 (1000-2000 mm depth) [mm mm-1, fraction between 0 and 1] 📫 Contact Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de Institution Helmholtz Centre for Environmental Research - UFZ, Department of Computational Hydrosystems

open·CC-BY-SA-4.0·Zenodo·completeSource
declared

WHATCHEM Version 2.1

0.00

Steinhoff, Daniel · Monaghan, Andrew

1 files · 3.5 MB · tardeclared

WHATCH'EM (Water Height and Temperature in Container Habitats Energy Model) is a physics-based model that simulates water temperature and water height in containers using an energy balance approach. The model uses meteorological inputs together with container characteristics, shading, rainfall, evaporation, and optional manual water additions to simulate container water dynamics across a range of environmental conditions.

open·CC-BY-4.0·Zenodo·completeSource
declared

Software and AMR peptide database for 'PEPTiGEN: a tool for mining antimicrobial resistance PEPTides using GENe data of public available repositories'

0.00

Meekes, Lisa · Tabaro, Francesco · Bexkens, Michiel · et al.

41 files · 8.2 GB · csv, fasta, pdfdeclared

This record contains the Python software for PEPTiGEN, a tool for generating tryptic peptides from prokaryotic gene sequences and their variants, and the associated antimicrobial resistance (AMR) peptide database. The database is provided as an SQL file and a CSV file containing all genes and predicted peptides. The README file contains explanation of the PEPTiGEN tool. The SQL database schema files contains both the database schema of the SQL database used in the PEPTiGEN analysis as the database schema of the AMR peptide datbase.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 15 of 20)

0.00

Ye, Renhao · Shen, Shiyin

65 files · 46 GB · csv, fits, tardeclared

Part 15 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 59.1-78.7°, Dec -39.9--24.9°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 14 of 20)

0.00

Ye, Renhao · Shen, Shiyin

67 files · 46 GB · csv, fits, tardeclared

Part 14 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 62-archive subset (RA 45.0-70.2°, Dec -48.1--30.1°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 13 of 20)

0.00

Ye, Renhao · Shen, Shiyin

66 files · 46 GB · csv, fits, tardeclared

Part 13 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 61-archive subset (RA 51.5-81.5°, Dec -54.3--30.0°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 12 of 20)

0.00

Ye, Renhao · Shen, Shiyin

64 files · 46 GB · csv, fits, tardeclared

Part 12 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 59-archive subset (RA 34.0-213.7°, Dec -66.5-80.4°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

NCF data of atmosphere-groundwater modulated seismic velocity variations revealed by distributed acoustic sensing

0.00

Yu, Ruofei · Wang, Baoshan · Hong, Heting · et al.

5 files · 45 GB · tar, xlsxdeclared

This dataset contains the hourly cross-correlation functions of ambient noise recorded by DAS in Hefei before the 2-D Wiener filter was applied from March 24 to June 28, 2022. The groundwater data and meterological data including temperature, barometric pressure and precipitation are also included in this dataset. Note that the times in the meterological data are in GMT+8:00. A python script used to simulate the solid earth tide is also included in this dataset.

open·CC-BY-4.0·Zenodo·completeSource
declared

Cis-xQTLs, Colocalization results, xTWAS weights, and xTWAS results from bulk RNA-seq data of ROS/MAP DLPFC tissue

0.00

Kim, Kyurhi

10 files · 9.6 GB · bzip2, zipdeclared

This repository contains cis-xQTL mapping results, colocalization analysis results, and transcriptome-wide association study (xTWAS) weights and association test statistics for six transcriptomic modalities generated from bulk RNA-seq data of dorsolateral prefrontal cortex (DLPFC) tissue from the ROS/MAP cohorts (n = 1,035). The RNA trait tables (BED format) used for cis-xQTL mapping and xTWAS model training were generated using the Pantry pipeline but are not included in this repository. Colocalization and xTWAS analyses were performed using the publicly available Alzheimer's disease (AD) dementia GWAS summary statistics from Bellenguez et al. ( Nature Genetics , 2022).

open·CC-BY-4.0·Zenodo·completeSource
declared

Efficient Uniform Negative Edge Weights: Supplemental Material

0.00

Allendorf, Daniel · Bläsius, Thomas · Leonhardt, Alexander · et al.

2 files · 12 GB · bzip2, zipdeclared

About this Repository This repository contains the software, datasets, and experimental data to reproduce the experiments in the above mentioned article. Please refer to the README file for more details and instructions. Article Abstract We consider a maximum entropy edge weight model that allows for negative weights. Given a graph Gand possible weights W typically consisting of positive and negative values, the model selects edge weights w ∈ W^m uniformly at random from all weights that do not introduce a negative cycle. We propose an MCMC process and show that it converges to the required distribution. We then engineer an implementation of the process using a dynamic version of Johnson's algorithm in connection with a bidirectional Dijkstra search as well as an innovative resampling method. We empirically study the performance characteristics of these novel sampling algorithms as well as the output produced by the model. Dataset Most of the input data (graph data) is generated dynamically via random graph models. In addition to the result data from the experiments, unew.data.tar.bz2 also contains trimmed US road networks used for the ROAD dataset in the paper. Code The code is developed at https://codeberg.org/lukasgeis/unew --- you may want to check there for updates.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 2 of 20)

0.00

Ye, Renhao · Shen, Shiyin

69 files · 47 GB · csv, fits, tardeclared

Part 2 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 64-archive subset (RA 137.7-270.0°, Dec 52.9-79.9°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 3 of 20)

0.00

Ye, Renhao · Shen, Shiyin

65 files · 46 GB · csv, fits, tardeclared

Part 3 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 180.0-270.0°, Dec 68.7-80.3°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 4 of 20)

0.00

Ye, Renhao · Shen, Shiyin

66 files · 46 GB · csv, fits, tardeclared

Part 4 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 61-archive subset (RA 84.4-285.5°, Dec -41.4-80.4°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 5 of 20)

0.00

Ye, Renhao · Shen, Shiyin

65 files · 46 GB · csv, fits, tardeclared

Part 5 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 47.7-93.4°, Dec -67.7--16.7°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 6 of 20)

0.00

Ye, Renhao · Shen, Shiyin

66 files · 46 GB · csv, fits, tardeclared

Part 6 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 61-archive subset (RA 1.2-69.9°, Dec -66.6--54.3°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 7 of 20)

0.00

Ye, Renhao · Shen, Shiyin

65 files · 46 GB · csv, fits, tardeclared

Part 7 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 32.7-60.0°, Dec -63.4--48.2°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 9 of 20)

0.00

Ye, Renhao · Shen, Shiyin

64 files · 46 GB · csv, fits, tardeclared

Part 9 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 59-archive subset (RA 60.0-89.9°, Dec -60.1--48.2°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
declared

From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures (Part 8 of 20)

0.00

Ye, Renhao · Shen, Shiyin

67 files · 46 GB · csv, fits, tardeclared

Part 8 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 62-archive subset (RA 30.0-89.2°, Dec -61.8--41.8°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.

open·CC-BY-4.0·Zenodo·completeSource
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