Robert Koch-Institut · AKTIN-Notaufnahmeregister
86 rows × 8 cols · 10 KB · pdf, tsv, zip
hybrid · semantic + lexical · 137 datasets ranked · 0.69s
Robert Koch-Institut · AKTIN-Notaufnahmeregister
86 rows × 8 cols · 10 KB · pdf, tsv, zip
4 numeric · 3 categorical · 1 text
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.
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.
Melnik, Elena
13 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
7 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
4 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
25 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
40 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
19 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
25 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
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.
Melnik, Elena
25 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
25 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Melnik, Elena
37 files · 4.5 MB · tiff
This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
Gennady, Gusev
6 files · 453 KB · xls
Table 1. DC current and magnetotransport of the small Corbino device. The table contains dc current ( I dc ) data measured in a small Corbino device under a constant bias voltage of V dc = 25 mV. The first column gives the perpendicular magnetic field ( B ) in Tesla. The remaining columns provide the measured current ( I dc ) in Amperes. Each current column corresponds to a different temperature ( T ), with the temperature value given in the column header in Kelvin. The sample resistance can be calculated using R = V dc / I dc . Table 2. DC current and magnetotransport of the medium Corbino device. The table contains dc current ( I dc ) data measured in a medium Corbino device under a constant bias voltage of V dc = 15 mV. The first column gives the perpendicular magnetic field ( B ) in Tesla. The remaining columns provide the measured current ( I dc ) in Amperes. Each current column corresponds to a different temperature ( T ), with the temperature value given in the column header in Kelvin. The corresponding sample resistance can be extracted using R = V dc / I dc . Table 3. DC current and magnetotransport of the large Corbino device. The table contains dc current ( I dc ) data measured in a large Corbino device under a constant bias voltage of V dc = 15 mV. The first column gives the perpendicular magnetic field ( B ) in Tesla. The remaining columns provide the measured current ( I dc ) in Amperes. Each current column corresponds to a different temperature ( T ), with the temperature value given in the column header in Kelvin. The corresponding sample resistance can be extracted using R = V dc / I dc . Table 4. DC current and magnetotransport of the Corbino device with R b = 11 μ m . The table contains dc current ( I dc ) data measured in a Corbino device with an outer radius R b = 11 μ m under a constant bias voltage of V dc = 20 mV. The first column gives the perpendicular magnetic field ( B ) in Tesla. The remaining columns provide the measured current ( I dc ) in Amperes. Each current column corresponds to a different temperature ( T ), with the temperature value given in the column header in Kelvin. The corresponding sample resistance can be extracted using R = V dc / I dc . Table 5. DC current and magnetotransport of the Corbino device with R b = 12 μ m . The table contains dc current ( I dc ) data measured in a Corbino device with an outer radius R b = 12 μ m under a constant bias voltage of V dc = 20 mV. The first column gives the perpendicular magnetic field ( B ) in Tesla. The remaining columns provide the measured current ( I dc ) in Amperes. Each current column corresponds to a different temperature ( T ), with the temperature value given in the column header in Kelvin. The corresponding sample resistance can be extracted using R = V dc / I dc . Table 6. DC current and magnetotransport of the Corbino device with R b = 18 μ m . The table contains dc current ( I dc ) data measured in a Corbino device with an outer radius R b = 18 μ m under a constant bias voltage of V dc = 15 mV. The first column gives the perpendicular magnetic field ( B ) in Tesla. The remaining columns provide the measured current ( I dc ) in Amperes. Each current column corresponds to a different temperature ( T ), with the temperature value given in the column header in Kelvin. The corresponding sample resistance can be extracted using R = V dc / I dc .
Wolf, Gerhard · Kolbe, Georg
2 files · 14 MB · pdf, tiff
Historical questionnaire/s 1924/1948 and index cards, partly selected enclosures regarding the history of a German pharmacy, catalogued via Kalliope portal (Historischer Fragebogen 1924/1948 und Karteikarten, ggf. gemeinfreie Anlagen zur Apothekengeschichte; als Katalog dient das Nachlassportal Kalliope): https://kalliope-verbund.info/DE-611-BF-70963 [Funktion: Im Findbuch anzeigen] Please note: The Kalliope catalogue entry might indicate related material in the archival folder which cannot be published due to copyright or other legal restrictions (NB: Das Katalogisat bei Kalliope kann auch auf Materialien - teils erheblichen Umfangs - verweisen, die aus archiv- oder urheberrechtlichen Gründen nicht veröffentlicht werden dürfen).
Wang, Yafei
15 files · 129 KB · tiff
A gridded time-series dataset reconstructing population distribution across the Yellow River Basin, China, from 1000 to 2000 AD, with a temporal resolution of one century and a spatial resolution of 10 km.
Wang, Wei · Liu, Cheng · Han, Lianhuan · et al.
10 files · 211 KB · tiff
Cyclic voltammograms (CVs) obtained at the 35-nm radius gold nanoelectrode in 0.5 M H2SO4 solution deoxygenated under argon at different scan rates (from 0.3 to 1 V/s). The potential range is 0-1.75 V vs RHE. The data in the text files is given in the following format: Potential vs. RHE (V) | Current (A) Scan rate is indicated in the text file name. The figure Voltammograms.tif shows all CVs in this dataset.
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.
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.