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724 results for “german”
Gene expression data of mRNA from liver sample of F2 population based German Landrace (DL) and Pietrain (Pi) pig breeds
GEO Series GSE202677. Sus scrofa. 24 samples. Type: Expression profiling by array.
Adrenal cortex expression data of a German Holstein X Charolaise cross
GEO Series GSE75371. Bos taurus. 147 samples. Type: Expression profiling by array.
Gene expression data of mRNA from mesenchymal stem cells derived from two different sorts of synovial membrane of German Landrace (DL) and Angeln Saddleback (AS) pigs II
GEO Series GSE219289. Sus scrofa. 72 samples. Type: Expression profiling by array.
Gene expression data of mRNA from adrenal gland sample of pig breed German Landrace with different coping behavior haplotype
GEO Series GSE109153. Sus scrofa. 20 samples. Type: Expression profiling by array.
Gene expression data of mRNA from hypothalamus sample of pig breed German Landrace with different coping behavior haplotype
GEO Series GSE109154. Sus scrofa. 20 samples. Type: Expression profiling by array.
Gene expression data of mRNA from hippocampus sample of pig breed German Landrace with different coping behavior haplotype
GEO Series GSE125079. Sus scrofa. 20 samples. Type: Expression profiling by array.
Gene expression data of mRNA from longissimus muscle sample of F2 population based German Landrace (DL) and Pietrain (Pi) pig breeds
GEO Series GSE162754. Sus scrofa. 118 samples. Type: Expression profiling by array.
Gene expression data of micro RNA from skeletal muscle sample of F2 population based German Landrace (DL) and Pietrain (Pi) pig breeds
GEO Series GSE162755. Sus scrofa. 118 samples. Type: Non-coding RNA profiling by array.
Gene expression data of the adipogenesis process of mesenchymal stem cells derived from two different types of synovial membranes of German Landrace (DL) and Angeln Saddleback (AS) pigs.
GEO Series GSE232501. Sus scrofa. 72 samples. Type: Expression profiling by array.
STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions
<p>We present STT4SG-350 (Speech-to-Text for Swiss German), a corpus of Swiss German speech, annotated with Standard German text at the sentence level. The data is collected using a web app in which the speakers are shown Standard German sentences, which they translate to Swiss German and record. We make the corpus publicly available. It contains 343 hours of speech from all dialect regions and is the largest public speech corpus for Swiss German to date. Application areas include automatic speech recognition (ASR), text-to-speech, dialect identification, and speaker recognition. Dialect information, age group, and gender of the 316 speakers are provided. Genders are equally represented and the corpus includes speakers of all ages. Roughly the same amount of speech is provided per dialect region, which makes the corpus ideally suited for experiments with speech technology for different dialects. We provide training, validation, and test splits of the data. The test set consists of the same spoken sentences for each dialect region and allows a fair evaluation of the quality of speech technologies in different dialects. We train an ASR model on the training set and achieve an average BLEU score of 74.7 on the test set. The model beats the best published BLEU scores on 2 other Swiss German ASR test sets, demonstrating the quality of the corpus.</p>
Automatic Transcription of English and German Qualitative Interviews - Appendix 2: Audio Files
<p>Contains clips from the interviews that were used to test the automatic transcription services.</p>
Annotation Scheme for Continuous Data in Swiss German Sign Language
<p>Annotation scheme described in the paper "Advancing Annotation for Continuous Data in Swiss German Sign Language" to annotate sentences in Swiss German Sign Language. The annotations are in both German and English.</p>
HERIEXPERT Dataset: Local experts in Polish and German World Heritage Cities: understanding their role in polycentric governance of heritage sites
<p>This dataset is part of the project <em>“Local experts in Polish and German World Heritage Cities: understanding their role in polycentric governance of heritage sites”</em> (HERIEXPERT).</p> <ul> <li><strong>Duration of the Project:</strong> 24 months (Start date: 2022-10-01, End date: 2024-09-30)</li> <li><strong>Principal Investigator:</strong> Dr. rer. pol. Iuliia Eremenko</li> <li><strong>Funding Statement:</strong> This research is part of the project No. 2021/43/P/HS5/02926, co-funded by the National Science Centre and the European Union Framework Programme for Research and Innovation Horizon 2020 under the Marie Skłodowska-Curie grant agreement no. 945339.</li> </ul> <p><strong>Access Restrictions</strong></p> <p>Access to the transcripts of expert interviews and associated data collected in this study is restricted to members of the research team in accordance with the recommendation of the Rector's Committee for the Ethics of Research Involving Human Participants at the University of Warsaw. These materials are not publicly accessible due to confidentiality concerns and the need to uphold ethical standards related to participant anonymity.</p> <p>This study involves expert interviews conducted in small and medium-sized cities. Given the limited number of experts involved in decision-making processes regarding World Heritage sites, there is an increased risk that participants could be indirectly identified, even after anonymization. This is due to the specificity of their roles and the local contexts in which they operate.</p> <p>To mitigate this risk and ensure ethical compliance, access to the data is limited to the research team. This approach safeguards participant identities, upholds confidentiality, and maintains the trust established during the research process.</p>
Environmental temperatures in the Australian and German professional football leagues.
<p>This is environmental data for each match of the German Bundesliga (seasons 2014-21) and Australian A-League (seasons 2016-20). </p> <p>Environmental conditions in the form of temperature and WBGT were collated retrospectively for each match. Whereas temperature refers to the commonly known and easily accessible ambient air temperature, WBGT is a feels-like temperature adding the influence of relative humidity, wind, and solar radiation, for a more detailed interpretation of the observed heat stress. The use, advantages, and disadvantages of WBGT have been described extensively in previous research.<sup>1-3</sup> Despite its widespread use, the black globe temperature (radiative heat gain) and natural wet-bulb temperature (evaporative heat loss) measurements are criticized as not representing human thermoregulation, thereby underestimating heat stress in many settings.<sup>1,4</sup> It should also be mentioned, that WBGT is a heat stress index and is not validated for colder conditions. Therefore, to interpret the effects of colder environments on injury occurrence temperature was also used in our analyses. Although more modern and sophisticated thermal indexes exist <sup>4,5</sup>, WBGT remains widely used, especially in sports federation heat policies. Specifically, this index is also used in the heat policy introduced by FIFA, which recommends the use of drinking breaks at 32 °C WBGT<sup>6</sup>.</p> <p>For Bundesliga matches, weather data was obtained from Meteostat.net.<sup>7</sup> This is an open-source service, providing hourly meteorological data for any given coordinates. Data is obtained as a weighted interpolation depending on the distance and elevation difference from the four closest weather stations to a geological location. They provide the following data: temperature, relative humidity, dew point, wind speed, air pressure, total precipitation, and the current weather condition. Based on this, WBGT can be estimated in a variety of ways according to previous research.<sup>2</sup> We used the estimation developed by Liljegren et al. (2008).<sup>3</sup> This is validated and reliable in different environmental settings and is described as the best estimate for WBGT from different methods.<sup>8</sup> The R code needed to implement these calculations has been provided and used in previous research.<sup>9</sup> Wind speed was assumed to be a minimum of 1 m/s, as moving players generate airflow of at least equivalent to that. Solar radiation was estimated using the solar angle at the time and location of the match<sup>10</sup>. As Meteostat.net provides hourly data, two time points (the kick-off time and one hour later) were used per match and averaged. If the match did not start at a full hour, but at 15 or 30 minutes past the hour, the previous full hour was used as a starting point and the following hour as a second time point. For A-League matches, environmental conditions were provided by UBIMET.com.<sup>11</sup> This commercial provider uses artificial intelligence and data input from multiple weather stations, radar, and satellite data, to estimate meteorological data at given ground locations. They provide temperature, relative humidity, solar radiation, and WBGT measurements for the starting times of the first and second half, which were then averaged to create one value per match. To validate the WBGT data based on Meteostat.net data, the WBGT estimation method used for the Bundesliga data was also performed with the A-League data. As internal validation, results were then compared to the WBGT reported from UBIMET.com. There was a very good linear association (correlation coefficient r = 0.93).</p> <p>1. Brocherie F, Millet G. Is the Wet-Bulb Globe Temperature (WBGT) Index Relevant for Exercise in the Heat? . <em>Sports Med</em>. 2015;45:1619-1621.</p> <p>2. Lemke B, Kjellstrom T. Calculating Workplace WBGT from Meteorological Data: A Tool for Climate Change Assessment. <em>Ind Health</em>. 2012;50:267-278.</p> <p>3. Liljegren J, Carhart RA, Lawday P, Tschopp S, Sharp R. Modelling the Wet Bulb Globe Temperature Using Standard Meteorological Measurements. <em>J Occup Environ Hyg</em>. 2008;5(10):645-655.</p> <p>4. Blazejczyk K, Epstein Y, Jendritzky G, Staiger H, Tinz B. Comparison of UTCI to selected thermal indicies. <em>Int J Biometeorol</em>. 2012;56:515-535. doi:<a href="https://doi.org/10.1007/s00484-011-0453-2">https://doi.org/10.1007/s00484-011-0453-2</a></p> <p>5. Jendritzky G, de Dear R, Havenith G. UTCI - Why another thermal index? <em>Int J Biometeorol</em>. 2012;56:421-428. doi:<a href="https://doi.org/10.1007/s00484-011-0513-7">https://doi.org/10.1007/s00484-011-0513-7</a></p> <p>6. Brown H, Chalmers S, Topham T, et al. Efficacy of the FIFA cooling break heat policy during an intermittent treadmill football simulation in hot conditions in trained males. <em>Br J Sports Med</em>. 2024;doi:10.1136/bjsports-2024-108131</p> <p>7. Meteostat.net. The Weather’s Record Keeper. <a href="https://meteostat.net/en/">https://meteostat.net/en/</a></p> <p>8. Patel T, Mullen SP, Santee WR. Comparison of Methods for Estimating Wet-Bulb Globe Temperature Index From Standard Meteorological Measurements. <em>Military Medicine</em>. 2013;178(8):926-933.</p> <p>9. <em>HeatStress</em>. Casanueva, A; 2019. <a href="https://zenodo.org/records/3264930">https://zenodo.org/records/3264930</a></p> <p>10. Duffie J, Beckman W. <em>Solar Engineering of Thermal Processes</em>. 4th ed. John Wiley & Sons, Inc.; 2013.</p> <p>11. UBIMET GmbH. UBIMET WEATHER MATTERS. <a href="https://www.ubimet.com/en/">https://www.ubimet.com/en/</a> </p>
French: Minioptére soeur / German: Schwesterchen-Langfligelfledermaus / Spanish: Minidéptero de Goodman Other common names: Malagasy Long-fingered Bat, Sororcula Bent-winged Bat Taxonomy. Miniopterus sororculus Goodman et al., 2007, "Madagascar: Province de Fianarantsoa, 3 km south of Ambatofinandrahana, in unnamed cave, 20°34.321°S, 46°48.530'F, 1,450. m." Miniopterus sororculus was formerly included in M. fraterculus of eastern Africa. Monotypic. Distribution. Highlands of C Madagascar. in Miniopteridae
French: Minioptére soeur / German: Schwesterchen-Langfligelfledermaus / Spanish: Minidéptero de Goodman Other common names: Malagasy Long-fingered Bat, Sororcula Bent-winged Bat Taxonomy. Miniopterus sororculus Goodman et al., 2007, "Madagascar: Province de Fianarantsoa, 3 km south of Ambatofinandrahana, in unnamed cave, 20°34.321°S, 46°48.530'F, 1,450. m." Miniopterus sororculus was formerly included in M. fraterculus of eastern Africa. Monotypic. Distribution. Highlands of C Madagascar.
On following pages: 281. Mirza's Eastern Moss Rat (Mirzamys norahae); 282. New Guinea Waterside Rat (Parahydromys asper); 283. Northern Water Rat (Paraleptomys rufilatus); 284. Short-haired Water Rat (Paraleptomys wilhelmina): 285. Gressitt's Mosaic-tailed Rat (Paramelomys gressitt); 286. Papuan Lowland Mosaic-tailed Rat (Paramelomys levipes); 287. Lorentz's Mosaic-tailed Rat (Paramelomys lorentzil); 288. Montane Soft-furred Mosaic-tailed Rat (Paramelomys mollis); 289. Monckton's Mosaic-tailed Rat (Paramelomys moncktoni); 290. Long-nosed Mosaic-tailed Rat (Paramelomys naso); 291. Common Lowland Mosaic-tailed Rat (Paramelomys platyops); 292. Mountain Mosaic-tailed Rat (Paramelomys rubex); 293. Stein's Mosaic-tailed Rat (Paramelomys stein); 294. Brass's Brush Mouse (Pogonomelomys brassi); 295. Bruijn's Brush Mouse (Pogonomelomys bruijnii); 296. Shaw Mayer's Brush Mouse (Pogonomelomys mayer); 297. Champion's Tree Mouse (Pogonomys championi); 298. D'Entrecasteaux Archipelago Tree Mouse (Pogonomys fergussoniensis); 299. Chestnut Tree Mouse (Pogonomys macrourus); 300. Gray-bellied Tree Mouse (Pogonomys sylvestris); 301. Loria's Tree Mouse (Pogonomysloriae); 302. Papuan Mosaic-tailed Rat (Protochromys fellows); 303. Bishop Moss Mouse (Pseudohydromys berniceae), 304. Huon Small-toothed Moss Mouse (Pseudohydromys carlae); 305. Laurie's Moss Mouse (Pseudohydromys eleanorae); 306. Shaw Mayer's Shrew Mouse (Pseudohydromys ellermani); 307. Mottled-tailed Shrew Mouse (Pseudohydromys fuscus); 308. German's One-toothed Moss Mouse (Pseudohydromys germani); 309. Eastern New Guinea Shrew Mouse (Pseudohydromys murinus); 310. Torricelli Mountains Shrew Mouse (Pseudohydromys musseri); 311. Western New Guinea Shrew Mouse (Pseudohydromys occidentalis); 312. Woolley's Moss Mouse (Pseudohydromys patriciae); 313. Southern Small-toothed Moss Mouse (Pseudohydromys pumehanae); 314. White-bellied Moss Mouse (Pseudohydromys sandrae). in Muridae
On following pages: 281. Mirza's Eastern Moss Rat (Mirzamys norahae); 282. New Guinea Waterside Rat (Parahydromys asper); 283. Northern Water Rat (Paraleptomys rufilatus); 284. Short-haired Water Rat (Paraleptomys wilhelmina): 285. Gressitt's Mosaic-tailed Rat (Paramelomys gressitt); 286. Papuan Lowland Mosaic-tailed Rat (Paramelomys levipes); 287. Lorentz's Mosaic-tailed Rat (Paramelomys lorentzil); 288. Montane Soft-furred Mosaic-tailed Rat (Paramelomys mollis); 289. Monckton's Mosaic-tailed Rat (Paramelomys moncktoni); 290. Long-nosed Mosaic-tailed Rat (Paramelomys naso); 291. Common Lowland Mosaic-tailed Rat (Paramelomys platyops); 292. Mountain Mosaic-tailed Rat (Paramelomys rubex); 293. Stein's Mosaic-tailed Rat (Paramelomys stein); 294. Brass's Brush Mouse (Pogonomelomys brassi); 295. Bruijn's Brush Mouse (Pogonomelomys bruijnii); 296. Shaw Mayer's Brush Mouse (Pogonomelomys mayer); 297. Champion's Tree Mouse (Pogonomys championi); 298. D'Entrecasteaux Archipelago Tree Mouse (Pogonomys fergussoniensis); 299. Chestnut Tree Mouse (Pogonomys macrourus); 300. Gray-bellied Tree Mouse (Pogonomys sylvestris); 301. Loria's Tree Mouse (Pogonomysloriae); 302. Papuan Mosaic-tailed Rat (Protochromys fellows); 303. Bishop Moss Mouse (Pseudohydromys berniceae), 304. Huon Small-toothed Moss Mouse (Pseudohydromys carlae); 305. Laurie's Moss Mouse (Pseudohydromys eleanorae); 306. Shaw Mayer's Shrew Mouse (Pseudohydromys ellermani); 307. Mottled-tailed Shrew Mouse (Pseudohydromys fuscus); 308. German's One-toothed Moss Mouse (Pseudohydromys germani); 309. Eastern New Guinea Shrew Mouse (Pseudohydromys murinus); 310. Torricelli Mountains Shrew Mouse (Pseudohydromys musseri); 311. Western New Guinea Shrew Mouse (Pseudohydromys occidentalis); 312. Woolley's Moss Mouse (Pseudohydromys patriciae); 313. Southern Small-toothed Moss Mouse (Pseudohydromys pumehanae); 314. White-bellied Moss Mouse (Pseudohydromys sandrae).
Analysis of 570 statutes of German energy cooperatives
Open the record for dataset details and reuse information.
German nobleman
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1653128228.4212.jpg">https://4dcity.org/imgupload/1653128228.4212.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=http%3A%2F%2Frepos.europeanafashion.eu%2Fmomu%2Fimages%2FBlatterFurKostumkunde_0021.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=http%3A%2F%2Frepos.europeanafashion.eu%2Fmomu%2Fimages%2FBlatterFurKostumkunde_0021.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1653128228.4212.jpg<br>Image Dimensions: 400x600<br>Megapixels: 0.24 MP<br>Filesize: 282.34 KB<br>
German noblewoman
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1653128137.9929.jpg">https://4dcity.org/imgupload/1653128137.9929.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=http%3A%2F%2Frepos.europeanafashion.eu%2Fmomu%2Fimages%2FBlatterFurKostumkunde_0014.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=http%3A%2F%2Frepos.europeanafashion.eu%2Fmomu%2Fimages%2FBlatterFurKostumkunde_0014.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1653128137.9929.jpg<br>Image Dimensions: 400x600<br>Megapixels: 0.24 MP<br>Filesize: 277.13 KB<br>
DRF Luftrettung (German Air Rescue) / Airbus Helicopters H145 / D-HDSY
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665337850.7295.jpg">https://4dcity.org/imgupload/1665337850.7295.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51119400999_8f78c807a4_m.jpg">https://live.staticflickr.com/65535/51119400999_8f78c807a4_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665337850.7295.jpg<br>Image Dimensions: 240x160<br>Megapixels: 0.04 MP<br>Filesize: 26.19 KB<br><br>ExifOffset: 26
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.