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9,097 results for “wild”

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zenodo44/100

Johann Sebastian Wild (w1503)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Johann Sebastian Wild musiXplora-ID: w1503 musiXplora-URI: <a href="https://musixplora.de/mxp/w1503">https://musixplora.de/mxp/w1503</a> Gender: m Confessions: römisch-katholisch First Mentioned: 1693 Last Mentioned: 1739 Sectors: Kirche, Orgelbau Professions (Musical): Orgelbauer Main Place of Activity: Walderbach Other Places of Activity: Aldersbach, Bamberg, Neunburg/Wald, Straubing Herkunftsfamilie: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Eltern</td><td>Vater</td><td>Georg Carl Wild</td><td><a href="https://musixplora.de/mxp/w1504">w1504</a></td></tr></tbody></table> Ausbildung: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>LehrerInnen und AusbilderInnen</td><td>Schüler</td><td>Johann Georg Götz</td><td><a href="https://musixplora.de/mxp/g0446">g0446</a></td></tr><tr><td>LehrerInnen und AusbilderInnen</td><td>Lehrer</td><td>Georg Carl Wild</td><td><a href="https://musixplora.de/mxp/w1504">w1504</a></td></tr></tbody></table> Arbeitsumfeld: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>KollegInnen</td><td>Kollege</td><td>Georg Carl Wild</td><td><a href="https://musixplora.de/mxp/w1504">w1504</a></td></tr></tbody></table> Personal: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Leitungsfunktion</td><td>Mitarbeiter</td><td>Wild</td><td><a href="https://musixplora.de/mxp/3030855">3030855</a></td></tr></tbody></table> Titel/Medien: <table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Bernhard 2003a</td><td>Orgeldatenbank Bayern</td><td><a href="https://musixplora.de/mxp/5001131">5001131</a></td></tr><tr><td>Related</td><td>Fischer & Wohnhaas 1994</td><td>Lexikon süddeutscher Orgelbauer</td><td><a href="https://musixplora.de/mxp/5001133">5001133</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

opencc-by-4.0Jun 2024View details →

zenodo44/100

Georg Carl Wild (w1504)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Georg Carl Wild musiXplora-ID: w1504 musiXplora-URI: <a href="https://musixplora.de/mxp/w1504">https://musixplora.de/mxp/w1504</a> Gender: m First Mentioned: 1738 Last Mentioned: 1746 Sectors: Kirche, Orgelbau Professions (Musical): Orgelbauer Main Place of Activity: Walderbach Other Places of Activity: Ensdorf, Falkenstein, Stamsried Herkunftsfamilie: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Eltern</td><td>Sohn</td><td>Johann Sebastian Wild</td><td><a href="https://musixplora.de/mxp/w1503">w1503</a></td></tr></tbody></table> Ausbildung: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>LehrerInnen und AusbilderInnen</td><td>Schüler</td><td>Johann Sebastian Wild</td><td><a href="https://musixplora.de/mxp/w1503">w1503</a></td></tr></tbody></table> Arbeitsumfeld: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>KollegInnen</td><td>Kollege</td><td>Johann Sebastian Wild</td><td><a href="https://musixplora.de/mxp/w1503">w1503</a></td></tr></tbody></table> Personal: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Leitungsfunktion</td><td>Mitarbeiter</td><td>Wild</td><td><a href="https://musixplora.de/mxp/3030855">3030855</a></td></tr></tbody></table> Titel/Medien: <table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Bernhard 2003a</td><td>Orgeldatenbank Bayern</td><td><a href="https://musixplora.de/mxp/5001131">5001131</a></td></tr><tr><td>Related</td><td>Fischer & Wohnhaas 1994</td><td>Lexikon süddeutscher Orgelbauer</td><td><a href="https://musixplora.de/mxp/5001133">5001133</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

opencc-by-4.0Jun 2024View details →

zenodo44/100

Johann Wilde (w0664)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Johann Wilde musiXplora-ID: w0664 musiXplora-URI: <a href="https://musixplora.de/mxp/w0664">https://musixplora.de/mxp/w0664</a> Gender: m Date of Death: 1770 Place of Death: Undefined First Mentioned: 1748 Sectors: Instrumentenbau Professions (Musical): Geiger, Instrumentalist, Instrumentenbauer Other Places of Activity: St. Petersburg Portfolio: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Sortimente</td><td>Sortiment</td><td>Pochette</td><td><a href="https://musixplora.de/mxp/2001476">2001476</a></td></tr><tr><td>Sortimente</td><td>Sortiment</td><td>Stockgeige</td><td><a href="https://musixplora.de/mxp/2003686">2003686</a></td></tr></tbody></table> Titel/Medien: <table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Hader et al. 2000</td><td>Lexikon zur deutschen Musikkultur. Böhmen, Mähren, Sudetenschlesien. Sudetendeutsches Musikinstitut</td><td><a href="https://musixplora.de/mxp/5001127">5001127</a></td></tr><tr><td>Related</td><td>Sachs 1913</td><td>Real-Lexikon der Musikinstrumente. zugleich ein Polyglossar für das gesamte Instrumentengebiet. Mit 200 Abbildungen</td><td><a href="https://musixplora.de/mxp/5040221">5040221</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

opencc-by-4.0Jun 2024View details →

zenodo44/100

Multiple DJI drone flights with thermal camera over Lithuanian forests in winter for wild boar detection

5 Flight over multiple days in the evening time for better thermal conditions for boar detection. Flight were conducted with DJI thermal cameras filmed at the speed of about 5m/s.  Flights 1, 2, 4 and 5 were filmed at from 90m height with camera pointing straight down. Flight 3 was filmed at 120m height.   Link for Dataset download: <a title="Thermal imaging dataset over Lithuanian forests in winter" href="https://art21-icaerus.s3.eu-central-1.amazonaws.com/Boars.zip" target="_blank" rel="noopener">https://art21-icaerus.s3.eu-central-1.amazonaws.com/Boars.zip</a>

opencc-by-4.0Jul 2024View details →

zenodo44/100

CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks

This repository contains the CNN Wild Park dataset from the paper: <blockquote> Graph Neural Networks for Learning Equivariant Representations of Neural Networks <a href="https://mkofinas.github.io/">Miltiadis Kofinas</a>*, <a href="https://bknyaz.github.io/">Boris Knyazev</a>, <a href="https://www.cyanogenoid.com/">Yan Zhang</a>, <a href="https://yunlu-chen.github.io/">Yunlu Chen</a>, <a href="https://gertjanburghouts.github.io/">Gertjan J. Burghouts</a>, <a href="https://egavves.com/">Efstratios Gavves</a>, <a href="https://www.ceessnoek.info/">Cees G. M. Snoek</a>, <a href="https://davzha.netlify.app/">David W. Zhang</a>* ICLR 2024 (oral) <a href="https://arxiv.org/abs/2403.12143">https://arxiv.org/abs/2403.12143</a> <a href="https://github.com/mkofinas/neural-graphs">https://github.com/mkofinas/neural-graphs</a> *Joint first and last authors </blockquote> We introduce a new dataset of CNNs, which we term CNN Wild Park. The dataset consists of 117,241 checkpoints from 2,800 CNNs, trained for up to 1,000 epochs on CIFAR10. The CNNs vary in the number of layers, kernel sizes, activation functions, and residual connections between arbitrary layers. More specifically, we construct the CNN Wild Park dataset by training 2,800 small CNNs with different architectures for 200 to 1,000 epochs on CIFAR10. We retain a checkpoint of its parameters every 10 steps and also record the test accuracy. The CNNs vary by: <ul> <li>Number of layers L in [2, 3, 4, 5] (note that this does not count the input layer).</li> <li>Number of channels per layer c_l in [4, 8, 16, 32].</li> <li>Kernel size of each convolution k_l in [3, 5, 7].</li> <li>Activation functions at each layer are one of ReLU, GeLU, tanh, sigmoid, leaky ReLU, or the identity function.</li> <li>Skip connections between two layers with at least one layer in between. Each layer can have at most one incoming skip connection. We allow for skip connections even in the case when the number of channels differ, to increase the variety of architectures and ensure independence between different architectural choices. We enable this by adding the skip connection only to the min(c_n, c_m) nodes.</li> </ul> We divide the dataset into train/val/test splits such that checkpoints from the same run are not contained in both the train and test splits.  <div> </div> <div> </div>

opencc-by-4.0May 2024View details →

zenodo44/100

Individual-based body sizes of wild bees along elevational gradients on Mt. Kilimanjaro

This dataset contains body size measurements of wild bees that were captured along elevational gradients on the southern slopes of Mt. Kilimanjaro (Tanzania) using standardized sampling methods (pan traps, transect walks). The dataset includes bee species identified at the species level as well as morphospecies. The bees were measured individually, meaning that intraspecific differences in body size are also represented. The intertegular distance (ITD) in millimeters was measured as a surrogate for body size. The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.

opencc-by-4.0Jul 2024View details →

zenodo44/100

Herbarium specimen image of Omphalocarpum sphaerocarpum De Wild., part of the collection of Meise Botanic Garden

Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published. Content of this deposition: - A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values. - A JPEG image file of the scanned herbarium sheet. - A lossless TIFF image from which the JPEG image has been derived.

opencc-zeroNov 2018View details →

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Herbarium specimen image of Omphalocarpum mortehanii De Wild., part of the collection of Meise Botanic Garden

opencc-zeroNov 2018View details →

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Herbarium specimen image of Omphalocarpum ghesquierei De Wild., part of the collection of Meise Botanic Garden

opencc-zeroNov 2018View details →

zenodo44/100

Herbarium specimen image of Thomandersia congolana De Wild. & T.Durand, part of the collection of Meise Botanic Garden

opencc-zeroNov 2018View details →

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Herbarium specimen image of Vitex seretii De Wild., part of the collection of Meise Botanic Garden

opencc-zeroNov 2018View details →

zenodo44/100

Herbarium specimen image of Bulbostylis congolensis De Wild., part of the collection of National Museum of Natural History, Paris

opencc-zeroNov 2018View details →

zenodo44/100

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with DHA (POSES 1-4)

Description of files in this dataset: MD_wt_CYP2J2_DHA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of docosahexaenoic acid (DHA) in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 4 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

opencc-by-4.0Oct 2019View details →

zenodo44/100

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 3 and 4)

Description of files in this dataset: MD_wt_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 4 times, hence there are 4 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

opencc-by-4.0Sep 2019View details →

zenodo44/100

Homology modelling, molecular docking and molecular dynamics simulations of wild type and mutant human CYP2J2 with three polyunsaturated fatty acids

This is the "parent" repository for the Data Note : "Molecular dynamics simulations of the interaction of wild type and mutant human CYP2J2 with polyunsaturated fatty acids" by Abelak, Bishop-Bailey and Nobeli. It contains a document (Abelak_etal_Methods.pdf) describing the methods used to produce the data here and the data in all repositories supplementing it. It also contains a shell script (create_sim4_repeats.sh) that is typical of those used to set up the molecular dynamics simulations in the repositories supplementing this one. Finally, it contains the results of the homology modelling and docking simulations that formed the starting points for the molecular dynamics simulations in this study. Description of files in this dataset: C2J2_min3_mod_noH.pdb : Homology model of the wild type CYP2J2 built from an alignment of templates with PDB ids: 1SUO, 2P85, 3EBS and 1Z10. docking_wild_type_C2J2.zip : Nine docked poses of arachidonic acid docked to the homology model of the wild type CYP2J2. Details of how this data was produced is available in the Abelak_etal_Methods.docx document.

opencc-by-4.0Sep 2019View details →

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Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 1 and 2)

opencc-by-4.0Sep 2019View details →

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Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 5 and 6)

opencc-by-4.0Oct 2019View details →

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Molecular dynamics simulations of the interaction of wild type human CYP2J2 with EPA (POSES 1-4)

Description of files in this dataset: MD_wt_CYP2J2_EPA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of eicosapentaenoic acid (EPA) in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 4 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

opencc-by-4.0Oct 2019View details →

zenodo44/100

Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning

Dataset of Javascripts used for training and testing the fingerprinting algorithms described in  Rizzo, Valentino, Stefano Traverso, and Marco Mellia. "Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning." Proceedings on Privacy Enhancing Technologies 2021.1 (2021): 43-63.

opencc-by-4.0Nov 2020View details →

zenodo44/100

Data and code for: Diurnal oscillations in gut bacterial load and composition eclipse seasonal and lifetime dynamics in wild meerkats, Suricata suricatta

Data and code to go with our publication "Diurnal oscillations in gut bacterial load and composition eclipse seasonal and lifetime dynamics in wild meerkats, Suricata suricatta", Nature Communications (2021). FILE DESCRIPTIONS ****** DATA ****** meerkat_16S_data.tar.gz    # 16S V4 amplicon sequences  sequenced on an Illumina MiSeq platform using primer pair 515F and 806R, including all faecal samples, controls, and sand samples. Sequence identifiers and basic metadata are in sequence_identifiers.csv. sequence_identifiers.csv    # Simple metadata and identifiers for all sequences/samples (what type of sample/sequencing run, etc), required for QIIME2 processing of the raw fasta.gz files contained in meerkat_16S_data.tar.gz. It contains a column for whether the sample was included in the final analysis. Does not include sample biological metadata as generating this data requires access to Kalahari Meerkat Project database. Biological metadata for samples included in the final analysis are instead provided in processed_data_phyloseq.RDS and can be accessed via phyloseq::sample_data(processed_data_phyloseq). processed_data_phyloseq.RDS # Phyloseq object containing the processed data used in the presented analysis. Contains data for 1109 samples, and includes the ASV table, the taxonomic classification, the phylogenetic tree, and the sample metadata used in the analysis. technical_replicate_data_phyloseq.RDS # Phyloseq object containing data from the 16 technical replicates. pilot_study_data_phyloseq.RDS # Phyloseq object containing data from the pilot study on captive meerkats. ****** CODE ****** CODE1_QIIME_script.R   # QIIME2 script to generate ASV table, taxonomy, and phylo tree from meerkat_16S_data.tar.gz. Requires a reference taxonomy (SILVA) and a reference phylogeny (SEPP) for taxonomic and phylogenetic placements. CODE2_processing_QIIME_output.Rmd  # R markdown script that processes the QIIME2 output generated by CODE1_QIIME_script.R. Does not generate meerkat metadata as this requires access to the Kalahari Meerkat Project database. This metadata is provided in processed_data_phyloseq.RDS. CODE3_data_analysis_script.Rmd # R markdown script that generates data and figures presented in paper, using data from processed_data_phyloseq.RDS, technical_replicate_data_phyloseq.RDS, and pilot_study_data_phyloseq.RDS. ****** R MARKDOWN REPORTS ****** The following reports are html files that show the code output for the two RMD files above. RMARKDOWN_data_processing.html # R markdown report for CODE2_processing_QIIME_output.Rmd RMARKDOWN_data_analysis.html # R markdown report for CODE3_data_analysis_script.Rmd ***************************** For general queries, unexpected errors and/or inconsistencies, please contact riselya@gmail.com.

opencc-by-4.0Aug 2021View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record

Find research datasets worth reusing

Dataset results

Johann Sebastian Wild (w1503)

Georg Carl Wild (w1504)

Johann Wilde (w0664)

Multiple DJI drone flights with thermal camera over Lithuanian forests in winter for wild boar detection

CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks

Individual-based body sizes of wild bees along elevational gradients on Mt. Kilimanjaro

Herbarium specimen image of Omphalocarpum sphaerocarpum De Wild., part of the collection of Meise Botanic Garden

Herbarium specimen image of Omphalocarpum mortehanii De Wild., part of the collection of Meise Botanic Garden

Herbarium specimen image of Omphalocarpum ghesquierei De Wild., part of the collection of Meise Botanic Garden

Herbarium specimen image of Thomandersia congolana De Wild. & T.Durand, part of the collection of Meise Botanic Garden

Herbarium specimen image of Vitex seretii De Wild., part of the collection of Meise Botanic Garden

Herbarium specimen image of Bulbostylis congolensis De Wild., part of the collection of National Museum of Natural History, Paris

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with DHA (POSES 1-4)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 3 and 4)

Homology modelling, molecular docking and molecular dynamics simulations of wild type and mutant human CYP2J2 with three polyunsaturated fatty acids

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 1 and 2)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 5 and 6)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with EPA (POSES 1-4)

Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning

Data and code for: Diurnal oscillations in gut bacterial load and composition eclipse seasonal and lifetime dynamics in wild meerkats, Suricata suricatta

Understand access before you commit

Allen Brain Atlas

Annotated Behaviour and Observability Dataset (ABODe)

DANDI Archive for NWB datasets

International Brain Laboratory public data

OpenNeuro

Your academic CV and NIH biosketch