Kantor, Rose · Shakya, Migun · Ruth, Nelson · et al.

2,095 rows · 907 KB · fasta, tsv

A virus genome database representing 21,015 near-complete virus genomes collected from untargeted ultra-deep RNA/DNA combined sequencing of wastewater. Sequence data was provided by the CASPER consortium and raw data may be found on NCBI SRA under bioprojects PRJNA1247874 and PRJNA1198001. Data underwent read trimming, rRNA and human read removal, de novo assembly, and selection of high-quality viral contigs. Contigs were clustered at 95% identity and 85% query coverage to dereplicate. Chimera-checking required at least two independent assemblies of the same viral genome or presence of the genome in another reference database. Annotation made use of RdRpCATCH, geNomad, checkV, BLASTN against NCBI core-nt, and RNAVirHost. The RdRp fasta files contain representative RdRp sequences identified through homology to major RdRp reference databases and clustered at 90% sequence identity over 75% sequence coverage. Included sequences contain all three conserved RdRp motifs (A, B, and C) arranged in either the canonical ABC configuration or the permuted CAB configuration.

Robert Koch-Institut · AKTIN-Notaufnahmeregister

5 files · 10 KB · pdf, tsv, zip

Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.

guo, na · pan, jiachen · li, tiantian · et al.

14 files · 100 MB · csv, rar, tsv

ADM_LSIR is a physics-inspired laparoscopic aerosol degradation dataset for aerosol-aware surgical image analysis and image restoration. The v1.0.0 release contains: - 21,916 clean clinical laparoscopic frames (clean/) - 9,562 real intraoperative aerosol-degraded frames (degraded/) - 36,052 simulated aerosol masks, including 19,701 smoke-like masks and 16,351 trajectory masks (mask/) - Blender simulation/cache materials (ADM_LSIR_Blender_simulation_files_v1.0.rar) - metadata_quality_report_v1.0.csv - recommended_splits_v1.0.csv - video_mapping_v1.0.csv - parts_manifest.txt - checksums_v1.0.tsv - release_manifest_v1.0.json All released clinical frames are de-identified and stored as lossless PNG files. Filenames use anonymized video identifiers, e.g., C-V##-####.png for clean frames and D-V##-####.png for degraded frames. The recommended split is defined at the source_video_id/public_video_label level to reduce leakage across frames from the same source video. The public video labels in video_mapping_v1.0.csv provide privacy-safe source-video identifiers (video1-video19). The Blender archive documents the smoke and trajectory mask simulation setup and supports reuse, but it is not a guaranteed exact per-mask reproduction package. The released pre-rendered mask library is the primary reusable dataset component. Source code for synthesis and quality screening is available at: https://github.com/SweetDeathh/ADM_LSIR

Manghi, Paolo

2 files · 8.0 MB · gzip, tsv

Using gene-level and species-level shotgun metagenomics, we provide the first characterization of the rural, Bolivian microbiome; we identified microbial genes which strongly correlate (rho>0.45) with arsenic in urine, and that overall contribute to substantiate that the gut microbiome helps tolerate arsenic via a evict-out-of-house mechanism. Mediation analysis, followed by phylogenetic investigation of metagenomic-assembled genomes, further strengthens this observation. This study elucidates the role of the microbiome in helping to tolerate arsenic-rich environments, and paves the way for probiotic interventions that may mitigate the effects of this toxic metal. This repository contains 2,478 HQ MAGs from the MicroToxBol cohort in fasta format and a descriptive table comprising taxonomic annotation, quality-checks, and coverage estimation.

Lee, Kanghwi

2 files · 100 MB · sevenzip

Trained variational autoencoder (VAE) checkpoints and per-vocalization latent representations for three developing zebra finches (183K-274K vocalizations each, 40-101 days post-hatch), accompanying the Interspeech 2026 paper "Trajectory Variance: An Unsupervised Measure of Developmental Vocal Plasticity in Birdsong." With the code at https://github.com/hwiora/trajectory_variance , these files reproduce the paper's evaluation tables. The raw audio recordings are not included; they are available from the authors on request and will be released in a future study. See ZENODO_README.md for details.

Kovaliov, Michael

1 files · 100 MB · parquet

Madhusudan, Gujral

6 files · 29 MB · parquetdeclared

Large language models (LLMs) are trained on massive, publicly available text datasets comprising trillions of tokens, enabling them to excel at general language tasks like next-token prediction. However, LLMs often struggle with domain-specific prompts, exhibiting reduced accuracy or generating inaccurate information (hallucinations). This is because they lack sufficient subject matter expertise. Two primary approaches exist to address this limitation for augmenting LLMs knowledge: Retrieval-Augmented Generation (RAG) and fine-tuning. This presentation focuses on fine-tuning smaller LLMs with domain-specific instruct datasets using the LoRA (Low-Rank Adaptation) technique on Gaudi hardware. We will leverage publicly available LLMs and datasets from the Hugging Face Hub for this demonstration. Though it is possible to fine tune LLMs with plain text data - sourced from documents, articles, and other materials.

Hackl, Jürgen

6 files · 132 MB · parquet, tiffdeclared

EuroFlood is an open, cloud-native index over the JRC/Copernicus CEMS-EFAS Satellite-Derived Flood Depth Maps for Europe (Betterle & Salamon, 2025; CC-BY-4.0) - ~3,280 satellite-derived observed flood-depth maps across Europe, 2015-2024. The bundle is a sparse Cloud-Optimized GeoTIFF encoding, per pixel, the set of flood events that inundated it, plus a combo_id -sorted GeoParquet dictionary and a small events table. Query by region and time via HTTP range reads (GDAL /vsicurl + DuckDB) to retrieve matching events, then fetch only the source depth rasters needed. Built with the open-source EuroFlood Python package ( pip install euroflood ).

Fry, Lauren · Seglenieks, Frank · Shrestha, Narayan Kumar · et al.

3 files · 22 MB · sevenzipdeclared

In response to flooding on Lake Ontario and the St. Lawrence River in 2017 and 2019, the U.S. and Canadian governments directed the Great Lakes - St. Lawrence River Adaptive Management (GLAM) Committee to expedite review of Lake Ontario outflow regulation Plan 2014 ahead of its usual 15-year review cycle. The dataset includes (1) a baseline record based on data from 1961-2020, (2) a set of stochastic scenarios that incorporates extremes that may not be in the historical record but are plausible under current hydroclimate conditions, and (3) a set of climate change scenarios to support evaluation of the plan under plausible decadal-scale hydroclimate changes. All data required to simulate Lake Ontario water levels, outflows, and downstream water levels are provided for each scenario. The data have been compressed into the following files: Baseline.7z - Baseline hydroclimate record from 1961-2020 Climate.7z - 8 future climate hydroclimate records Stochastic.7z - 500 stochastic hydroclimate records Within each compressed file are subdirectories that contain the files for each water supply sequence. The following table lists the files that are provided for each of the water supply sequences. For each file there is a description of the variable contained in the file, the location of the data in the file, and the unit of the data in the file if applicable. Filename Variable Location Units dpmi_flw_cms_qm48_na.csv Flow Des Prairies and Mille Iles River cms rich_flw_cms_qm48_na.csv Flow Richelieu River at Rapides Fryer cms stfr_flw_cms_qm48_na.csv Flow St. Francois River at Chut Hemming cms stmc_flw_cms_qm48_na.csv Flow St. Maurice River at La Gabelle cms ont_nbs_cms_qm48_na.csv Net Basin Supply Lake Ontario cms ont_nbs_cms_qm48_na_spinup.csv Net Basin Supply Lake Ontario cms eri_flw_cms_qm48_na.csv Outflow Lake Erie cms eri_flw_cms_qm48_na_spinup.csv Outflow (one year spinup) Lake Erie cms slon_flw_cms_qm48_na.csv SLON flow St. Lawrence River (Lake St. Louis) cms slon_flw_cms_qm48_na_spinup.csv SLON flow (one year spinup) St. Lawrence River (Lake St. Louis) cms stl_icw_cms_qm48_na.csv Ice/weed retardation St. Lawrence River cms stl_tde_m_qm48_na.csv Tidal Signal St. Lawrence River m ont_mlv_m_qm48_na_spinup.csv Water Level (one year spinup) Lake Ontario m stl_ics_xx_qm48_na.csv Ice status indicator St. Lawrence River N/A bati_rgh_xx_qm48_na.csv Ice/weed roughness factor Batiscan N/A card_rgh_xx_qm48_na.csv Ice/weed roughness factor Cardinal N/A corn_rgh_xx_qm48_na.csv Ice/weed roughness factor Cornwall N/A intw_rgh_xx_qm48_na.csv Ice/weed roughness factor International Tail Water N/A irhw_rgh_xx_qm48_na.csv Ice/weed roughness factor Iroquois Head Water N/A irtw_rgh_xx_qm48_na.csv Ice/weed roughness factor Iroquois Tail Water N/A jty1_rgh_xx_qm48_na.csv Ice/weed roughness factor Montreal Jetty No. 1 N/A lspr_rgh_xx_qm48_na.csv Ice/weed roughness factor Lake St. Pierre N/A lstd_rgh_xx_qm48_na.csv Ice/weed roughness factor Long Sault Dam N/A morr_rgh_xx_qm48_na.csv Ice/weed roughness factor Morrisburg N/A ogde_rgh_xx_qm48_na.csv Ice/weed roughness factor Odgensburg N/A ptcl_rgh_xx_qm48_na.csv Ice/weed roughness factor Pointe - Claire N/A sahw_rgh_xx_qm48_na.csv Ice/weed roughness factor Saunders Head Water N/A sorl_rgh_xx_qm48_na.csv Ice/weed roughness factor Sorel N/A summ_rgh_xx_qm48_na.csv Ice/weed roughness factor Summerstown N/A triv_rgh_xx_qm48_na.csv Ice/weed roughness factor Trois Rivières N/A vare_rgh_xx_qm48_na.csv Ice/weed roughness factor Varennes N/A na_fst_xx_qm48_na.csv Forecast indicator N/A N/A

Walsh, Calum · Srinivas, Meghana · Stinear, Timothy · et al.

100 files · 2.7 GB · gzip, tsvdeclared

GROND (Genome-derived Ribosomal OperoN Database) A quality-checked and publicly-available database of 16S-ITS-23S RRNA operon sequences and their constituent 16S and 23S genes. Based on GTDB release R232.

Geisler, Jan · Rakhimberdiev, Eldar · Boom, Michiel P. · et al.

29 files · 124 MB · csv, shapefiledeclared

1. Many migratory birds now reach their Arctic breeding grounds earlier in order to keep pace with advancing springs and shifting nutrient peaks, either by departing earlier from non-breeding grounds or by travelling faster. For dark-bellied brent geese, there is limited potential to travel faster, as their migration to the Siberian breeding grounds is already among the fastest of Arctic geese and swans. Earlier departure would require reaching departure body mass earlier, either through a faster accumulation of energy stores during spring staging or via adjustments earlier in the annual cycle. 2. We examined long-term shifts in spring staging phenology and changes in winter and spring body mass trajectories of brent geese at the population level, with particular emphasis on the effects of winter temperature on body mass and spring body mass on departure timing. 3. We used more than five decades of body mass measurements from individuals caught in the United Kingdom and France, and in the Dutch Wadden Sea to reconstruct changes in spring and winter mass trajectories, respectively. These data were combined with over five decades of migration counts in the Netherlands and more than two decades of counts in Denmark to quantify changes in spring staging phenology. 4. We found that brent geese have not shifted their spring arrival in the Wadden Sea but have advanced departure timing. Furthermore, brent geese were heavier during and after milder winters, and have changed mass trajectories over recent decades. They no longer lose mass during winter and the second spring staging phase, and fuelling rates in the first spring staging phase have declined. Annual variation in body mass was not related to annual departure timing. 5. These results suggest that milder winters have relaxed energetic constraints and improved body condition in brent geese throughout the non-breeding season. Our findings highlight the importance of considering the full annual cycle when assessing how animals with limited capacity to adjust migration timing or speed respond to global change.

Robert Koch-Institut · AKTIN-Notaufnahmeregister

5 files · 24 MB · pdf, tsv, zipdeclared

Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.

Filippova, Nina · Bulyonkova, Tatiana · Zvyagina, Elena · et al.

1 files · 1.4 MB · tsvdeclared

Best hit results with analytical parameters

Tolksdorf, Kristin · Goerlitz, Luise · Staat, Doreen · et al.

4 files · 309 KB · pdf, tsv, zipdeclared

Im Datensatz "SARI-Hospitalisierungsinzidenz" des Robert Koch-Instituts werden die wöchentlichen Inzidenzen schwerer akuter respiratorischer Infektionen (SARI) auf Bundesebene in Deutschland bereitgestellt. Die Daten stammen aus der syndromischen Krankenhaussurveillance ICOSARI, die auf ICD-10-Diagnosecodes aus etwa 70 Sentinelkliniken basiert. Der Datensatz umfasst Hospitalisierungsinzidenzen pro 100.000 Einwohner, aufgeschlüsselt nach Altersgruppen, Saison und Kalenderwoche. Neben der Gesamtheit aller SARI-Fälle werden auch Fälle mit zusätzlicher COVID-19-, Influenza- oder RSV-Diagnose separat erfasst. Die Surveillance liefert entscheidende Informationen zur Krankheitslast akuter respiratorischer Erkrankungen und dient als Grundlage für epidemiologische Bewertungen und Empfehlungen für gesundheitspolitische Maßnahmen.

Buchholz, Udo · Lehfeld, Ann-Sophie · Loenenbach, Anna · et al.

5 files · 953 KB · pdf, tsv, zipdeclared

Im Datensatz "GrippeWeb - Daten des Wochenberichts" des Robert Koch-Instituts werden wöchentliche, bevölkerungsbasierte Schätzungen zur Inzidenz akuter respiratorischer Erkrankungen (ARE) und grippeähnlicher Erkrankungen (ILI) in Deutschland bereitgestellt. GrippeWeb als Online-Portal zur partizipativen syndromischen Surveillance nutzt Selbstauskünfte freiwilliger, pseudonym registrierter Teilnehmender ab 16 Jahren zu Symptomen wie Husten, Fieber und Halsschmerzen. Daraus werden Inzidenzen nach Altersgruppen und Regionen errechnet. Die erhobenen Daten unterstützen die Überwachung saisonaler Infektionen und dienen der Risikobewertung in Pandemien wie COVID-19.

Goerlitz, Luise · Tolksdorf, Kristin · Prahm, Kerstin · et al.

4 files · 1.0 MB · pdf, tsv, zipdeclared

Im Datensatz "ARE-Konsultationsinzidenz" des Robert Koch-Instituts werden wöchentliche Inzidenzen von ambulanten Konsultationen mit akuter respiratorischer Erkrankung (ARE) in Deutschland bereitgestellt. Die Daten stammen vom ARE-Praxis-Sentinel des RKI. Hier werden aus Sentinelpraxen Daten von gesetzlich versicherten Patientinnen und Patienten mit einer akuten Atemwegserkrankung entweder einzelfallbasiert anhand von ICD-10-Diagnosecodes mit dem SEED/ARE-Modul oder aggregiert nach Altersgruppen über eine Online-Eingabemaske erfasst. Die ARE-Konsultationsinzidenz wird pro 100.000 Einwohner und nach Altersgruppen und Bundesländern ausgewiesen. Ziel ist es, die Krankheitslast und den saisonalen Verlauf von Atemwegserkrankungen wie Influenza, COVID-19 und RSV-Erkrankungen zu bewerten sowie epidemiologische Entwicklungen frühzeitig zu erkennen

Robert Koch-Institut

5 files · 1.5 MB · pdf, tsv, zipdeclared

Im Datensatz "Respiratorische Synzytialvirusfälle in Deutschland" des Robert Koch-Instituts werden die Daten basierend auf Meldungen zu Infektionen mit dem Respiratorischen Synzytial-Virus (RSV) nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Darin enthalten sind Informationen auf Bundeslandebene zu Infektionen nach Falldefinition des Robert Koch-Instituts, differenziert nach Altersgruppen. Diese Daten dienen als Grundlage für epidemiologische Bewertungen und gesundheitspolitische Maßnahmen.

Robert Koch-Institut

5 files · 2.1 MB · pdf, tsv, zipdeclared

Im Datensatz "Laborbestätigte Influenzafälle in Deutschland" des Robert Koch-Instituts werden die Daten basierend auf Meldungen zu Infektionen mit dem Influenzavirus nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Darin enthalten sind Informationen auf Bundeslandebene zu Infektionen nach Falldefinition des Robert Koch-Instituts, differenziert nach Altersgruppen. Diese Daten dienen als Grundlage für epidemiologische Bewertungen und gesundheitspolitische Maßnahmen.

Vanstreels, Ralph E. T. · Serafini, Patricia P. · Giacinti, Jolene · et al.

3 files · 55 KB · tsvdeclared

High pathogenicity avian influenza (HPAI) viruses have rapidly emerged as a major global threat to wildlife, with severe consequences for seabird populations. Albatrosses and petrels (order Procellariiformes) are particularly vulnerable due to their long lifespan, low reproductive rates and strong site fidelity. Since 2021, HPAI viruses have caused unprecedented mortality in seabird communities worldwide and have expanded into the core range of procellariiform species, including sub-Antarctic and Antarctic regions. In response to the urgent need for timely, species-relevant information, the Agreement on the Conservation of Albatrosses and Petrels (ACAP) established the High Pathogenicity H5Nx Avian Influenza Intersessional Correspondence Group (HPAI-ICG), which developed the ACAP HPAI database - an openly accessible, regularly updated resource that consolidates all known suspected and confirmed HPAI events involving procellariiform birds. The database compiles information from global and national reporting systems, scientific literature, genetic repositories, government communications and direct expert notifications. Events are standardised using transparent case definitions, cross-referenced and validated by subject-matter experts and complemented by additional data on case impacts and viral characteristics. The database provides a critical decision-support tool for governments, researchers, conservation practitioners and tourism operators, contributing to the planning and implementation of HPAI biosafety, surveillance, monitoring and outbreak response activities.