cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.22cad4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.351767 -37.006808, 144.351767 -37.013545, 144.356259 -37.013545, 144.356259 -37.009054, 144.358505 -37.009054, 144.358505 -37.013545, 144.365242 -37.013545, 144.365242 -37.009054, 144.362996 -37.009054, 144.362996 -37.006808, 144.351767 -37.006808))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050989-240626123714530/datasets/export for details.
DOI: 10.5281/zenodo.13234568
title: Freiburg /Br. Apotheke d. Diakonissen-Krankenhauses

description: 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).
DOI: 10.15468/dl.cyzxfj
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.847238 -34.713847, 149.847238 -34.720584, 149.844992 -34.720584, 149.844992 -34.72283, 149.860712 -34.72283, 149.860712 -34.720584, 149.862958 -34.720584, 149.862958 -34.713847, 149.847238 -34.713847))"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050990-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13189626
title: Data and code for "Light Rain Exacerbates Extreme Humid Heat"

description: Model simulation data and the code for each figure used in the NC paper entitled "Light Rain Exacerbates Extreme Humid Heat".
DOI: 10.5281/zenodo.13189627
title: Data and code for "Light Rain Exacerbates Extreme Humid Heat"

description: Model simulation data and the code for each figure used in the NC paper entitled "Light Rain Exacerbates Extreme Humid Heat".
DOI: 10.15468/dl.ekpnpp
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.690883 -37.006808, 144.690883 -37.009054, 144.688637 -37.009054, 144.688637 -37.013545, 144.693129 -37.013545, 144.693129 -37.009054, 144.695375 -37.009054, 144.695375 -37.006808, 144.690883 -37.006808))"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050991-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13234576
title: Freiburg /Elbe Adler-Apotheke

description: 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).
DOI: 10.15468/dl.f5g5xn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.420536 -34.727322, 149.420536 -34.729568, 149.425027 -34.729568, 149.425027 -34.727322, 149.420536 -34.727322))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050992-240626123714530/datasets/export for details.
DOI: 10.14459/2024mp1740589
title: Comparative analysis of human and murine Uncoupling Protein 1 reveals essential structural features of human UCP1

description: Background: Mitochondrial uncoupling protein 1 (UCP1) is a unique protein of brown adipose tissue. Upon activation by free fatty acids, UCP1 facilitates a thermogenic net proton flux across the mitochondrial inner membrane. Non-complexed purine nucleotides inhibit this fatty acid-induced activity of UCP1. By far the most available data have been generated from rodent model systems. In the light of being a putative pharmacological target for the treatment of metabolic disease, specific aspects of human UCP1 function and its comparability to rodent orthologues are of importance. Methods: In the present study, we established a doxycycline-regulated cell model with inducible human or murine UCP1 expression and conducted functional studies using respirometry. Results: We demonstrate that human and murine UCP1 exhibit similar specific fatty acid-induced activity, but divergent inhibitory potential of purine nucleotides. Mutagenesis of non-conserved residues in human UCP1 revealed structural components in α-helix 56 and α-helix 6 crucial for uncoupling function. Conclusions: A deeper structure-function analysis of UCP1 is not only essential to understand its unique function but is also needed in the search for new UCP1 activators.
DOI: 10.15468/dl.ztdwxj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((144.699866 -37.006808, 144.699866 -37.009054, 144.702112 -37.009054, 144.702112 -37.006808, 144.699866 -37.006808)), ((144.702112 -37.009054, 144.702112 -37.013545, 144.704358 -37.013545, 144.704358 -37.009054, 144.702112 -37.009054)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050993-240626123714530/datasets/export for details.
DOI: 10.15468/dl.usyj7a
title: Occurrence Download

description: A dataset containing 125824 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vespa velutina Lepeletier, 1836"
 ]
}

 The dataset includes 125824 records from 841 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050988-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nwcusy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.506496 -34.729568, 148.506496 -34.731813, 148.513233 -34.731813, 148.513233 -34.729568, 148.506496 -34.729568))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050994-240626123714530/datasets/export for details.
DOI: 10.25345/c5wh2ds18
title: MassIVE MSV000095521 - CoV 3'UTR cis-acting element interactome
title: Comparison of CoV 3'UTR cis-acting element interactome to link the cis-acting element to coronavirus replication by LC-MS/MS. The study is performed by in vitro-transcribed RNA followed by RNA-protein pull-down assay. In addition, the concluded results are decided by comparison between the biological processes derived from analysis of interactome and the replication efficiency.
DOI: 10.26050/wdcc/primavera_hist
title: PRIMAVERA: Eddy Rich version of the Max Planck Institute Earth System Model (MPI-ESM1.2-ER) - historical run

description: Project: PRIMAVERA - Development of a new generation of advanced and well-evaluated high-resolution global climate models, capable of simulating and predicting regional climate with unprecedented fidelity, for the benefit of governments, business and society in general.
https://www.primavera-h2020.eu/
Summary: The MPI-ESM1.2-ER configuration is designed to facilitate research on ocean eddies that are explicitly resolved. Three realizations of the historical experiment exist. The natural forcing includes variations of the Earth orbit, variability in spectral solar irradiance, seasonally varying natural tropospheric aerosols, and stratospheric aerosols from volcanic eruptions. The anthropogenic forcing includes five well-mixed greenhouse gases CO2, CH4, N2O, CFC-11, and CFC-12 as well as O3 and anthropogenic sulfate aerosols. 

The MPI-ESM1.2-ER climate model includes the following components: 
aerosol: none, 
prescribed MACv2-SP, 
atmos: ECHAM6.3 (spectral T127/L95; 384 × 192 longitude/latitude; 95 levels; top level 0.01 hPa), 
land: none, 
landIce: none/prescribed, 
ocean: MPIOM1.63 (TP6M, approximately 0.1deg; 3602x2394 longitude/latitude; 40 levels; top grid cell 0-6 m), 
ocnBgchem: none, 
seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). 

The model was run by the Max Planck Institute for Meteorology, Hamburg 20146, Germany (MPI-M) in native nominal resolutions: 
aerosol: 100 km, 
atmos: 100 km, 
land: none, 
landIce: none, 
ocean: 10 km, 
ocnBgchem: none, 
seaIce: 10 km.

MPI-ESM-ER is a coupled climate model that is conducted following the HighResMIP protocol. Atmospheric component (ECHAM6.3) and ocean component (MPIOM) of the MPI-ESM-ER are coupled with a coupling frequency of 1hr (via OASIS3 coupler). MPI-ESM-ER includes dynamic vegetation, and interactive carbon cycle, as well as advanced representations of atmosphere and ocean processes (Stevens et al., 2013).
DOI: 10.15468/dl.xzbesy
title: Occurrence Download

description: A dataset containing 28044 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((118.36803 31.54983,119.75282 31.53924,119.71564 32.61587,118.28077 32.62788,118.36803 31.54983))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 28044 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050995-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.efh6ps
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.726816 -37.009054, 144.726816 -37.013545, 144.731307 -37.013545, 144.731307 -37.009054, 144.726816 -37.009054))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050996-240626123714530/datasets/export for details.
DOI: 10.5281/zenodo.12720783
title: An Autonomous Drone Swarm for Detecting and Tracking Anomalies among Dense Vegetation

description: Abstract: 

Swarms of drones offer an increased sensing aperture, and having them mimic behaviors of natural swarms enhances sampling by adapting the aperture to local conditions. We demonstrate that such an approach makes detecting and tracking heavily occluded targets practically feasible. While object classification applied to conventional aerial images generalizes poorly the randomness of occlusion and is therefore inefficient even under lightly occluded conditions, anomaly detection applied to synthetic aperture integral images is robust for dense vegetation, such as forests, and is independent of pre-trained classes. Our autonomous swarm searches the environment for occurrences of the unknown or unexpected, tracking them while continuously adapting its sampling pattern to optimize for local viewing conditions. We achieved an average positional accuracy of 0.39 m with an average precision of 93.2% and an average recall of 95.9%. Here, adapted particle swarm optimization considers detection confidences and predicted target appearance. We show that sensor noise can effectively be included in the synthetic aperture image integration process, removing the need for a computationally costly optimization of high-dimensional parameter spaces. Finally, we present a complete hard- and software framework that supports low-latency transmission and fast processing of extensive video and telemetry data.
DOI: 10.5281/zenodo.12720784
title: An Autonomous Drone Swarm for Detecting and Tracking Anomalies in Dense Vegetation

description: Abstract: Swarms of drones offer an increased sensing aperture, and by mimicking the behavior observed in natural swarms allows adapting the aperture to local conditions for enhancing sampling. Here we demonstrate that detecting and tracking heavily occluded targets is feasible in practice with such an approach. While object classification applied to conventional aerial images cannot generalize well the randomness of occlusion and is therefore inefficient even under sparse conditions, anomaly detection applied to synthetic aperture integral images is robust for dense vegetation, such as forest, and independent of pre-trained classes. Our autonomous swarm explores the environment for unknown or unexpected appearances and tracks them while continuously adapting its sampling pattern to optimize for local viewing conditions. In our real-life field experiments with a swarm of six drones, we achieve an average positional accuracy of 0.39m with an average precision 93.2% and an average recall of 95.9%. Here, adapted particle swarm optimization considers detection confidences and predicted target appearance. We show that sensor noise can be effectively included in the synthetic aperture image integration process without a computationally costly optimization of high-dimensional parameter spaces. Finally, we present a complete hard- and software framework that supports low-latency transmission (approx. 80ms round-trip-time) and fast processing (approx, 600ms per formation step) of extensive (70-120 Mbits/s) video and telemetry data, and swarm control for swarms of up to ten drones.
DOI: 10.5281/zenodo.13234552
title: An Autonomous Drone Swarm for Detecting and Tracking Anomalies among Dense Vegetation

description: Abstract: 

Swarms of drones offer an increased sensing aperture, and having them mimic behaviors of natural swarms enhances sampling by adapting the aperture to local conditions. We demonstrate that such an approach makes detecting and tracking heavily occluded targets practically feasible. While object classification applied to conventional aerial images generalizes poorly the randomness of occlusion and is therefore inefficient even under lightly occluded conditions, anomaly detection applied to synthetic aperture integral images is robust for dense vegetation, such as forests, and is independent of pre-trained classes. Our autonomous swarm searches the environment for occurrences of the unknown or unexpected, tracking them while continuously adapting its sampling pattern to optimize for local viewing conditions. We achieved an average positional accuracy of 0.39 m with an average precision of 93.2% and an average recall of 95.9%. Here, adapted particle swarm optimization considers detection confidences and predicted target appearance. We show that sensor noise can effectively be included in the synthetic aperture image integration process, removing the need for a computationally costly optimization of high-dimensional parameter spaces. Finally, we present a complete hard- and software framework that supports low-latency transmission and fast processing of extensive video and telemetry data.
DOI: 10.15468/dl.kk2nj6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.549166 -34.731813, 148.549166 -34.736305, 148.551412 -34.736305, 148.551412 -34.731813, 148.549166 -34.731813))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050997-240626123714530/datasets/export for details.
DOI: 10.13016/mmxa-chbd
title: A Better Understanding of Atmospheric Methane Sources Using 13CH3D and 12CH2D2 Clumped Isotopes

description: We evaluate the use of clumped isotopes of methane (CH4) to fingerprint local atmospheric sources of methane. We focus on a regenerative stormwater conveyance (RSC) stream wetland site running through the University of Maryland campus, which emits methane due to its engineering. Air samples in the RSC were collected at different heights above the surface and at different times of the day including both early in the morning, after methane accumulated below the nocturnal boundary layer, and late in the afternoon when convection mixed air to the cloud layer. Measured Δ12CH2D2 values of air samples record mixing between locally produced methane with low D/H and ambient air. The Δ12CH2D2 of the near surface air collected at the RSC during the early morning ranges from ~+23‰ to ~+35‰ which is lower than the ~+50‰ values of tropospheric air. Mixing between background air (with Δ12CH2D2 ~+50‰) and methane captured from chamber and bubble samples, as well as produced in incubation (all with negative Δ12CH2D2), explains the observed values of Δ12CH2D2 and Δ13CH3D of near surface RSC air samples. The effect of mixing with biogenic sources on Δ13CH3D is much smaller. The findings demonstrate how methane isotopologues can be used as a tool not only to fingerprint local contributions to these greenhouse gas emissions but also to identify sources of near-surface methane hot spots.
DOI: 10.15468/dl.ua9vqh
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((143.415269 -36.997825, 143.415269 -37.002316, 143.419761 -37.002316, 143.419761 -37.006808, 143.424252 -37.006808, 143.424252 -37.009054, 143.433236 -37.009054, 143.433236 -37.011299, 143.437727 -37.011299, 143.437727 -37.013545, 143.451202 -37.013545, 143.451202 -37.015791, 143.455694 -37.015791, 143.455694 -37.013545, 143.460185 -37.013545, 143.460185 -37.011299, 143.455694 -37.011299, 143.455694 -37.009054, 143.451202 -37.009054, 143.451202 -37.006808, 143.44671 -37.006808, 143.44671 -37.004562, 143.444465 -37.004562, 143.444465 -37.006808, 143.442219 -37.006808, 143.442219 -37.002316, 143.433236 -37.002316, 143.433236 -37.00007, 143.428744 -37.00007, 143.428744 -36.997825, 143.415269 -36.997825))"
 ]
}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050998-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mcyumv
title: Occurrence Download

description: A dataset containing 555 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ursus arctos arctos"
 ]
}

 The dataset includes 555 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050999-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvdexk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.442994 -34.731813, 149.442994 -34.738551, 149.451977 -34.738551, 149.451977 -34.736305, 149.447485 -34.736305, 149.447485 -34.731813, 149.442994 -34.731813))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051001-240626123714530/datasets/export for details.
DOI: 10.57754/fdat.jy474-fv283
title: Tokenized OFAI Million Post Corpus

description: This corpus is based on the Million Post Corpus created by the OFAI. It contains the tokenized comments and articles in plain text without association of comments to their articles. The text has been tokenized using the SoMaJo tokenizer.
description: Research carried out in work package A03 of the SFB 833.
DOI: 10.15468/dl.h38grk
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((144.800927 -36.986596, 144.800927 -36.993333, 144.803173 -36.993333, 144.803173 -36.988841, 144.807665 -36.988841, 144.807665 -36.997825, 144.803173 -36.997825, 144.803173 -37.00007, 144.800927 -37.00007, 144.800927 -37.004562, 144.803173 -37.004562, 144.803173 -37.006808, 144.807665 -37.006808, 144.807665 -37.015791, 144.80991 -37.015791, 144.80991 -37.009054, 144.812156 -37.009054, 144.812156 -37.006808, 144.830123 -37.006808, 144.830123 -37.009054, 144.834614 -37.009054, 144.834614 -37.004562, 144.830123 -37.004562, 144.830123 -37.00007, 144.818894 -37.00007, 144.818894 -36.991087, 144.812156 -36.991087, 144.812156 -36.986596, 144.800927 -36.986596)), ((144.818894 -36.991087, 144.823385 -36.991087, 144.823385 -36.988841, 144.825631 -36.988841, 144.825631 -36.986596, 144.818894 -36.986596, 144.818894 -36.991087)))"
 ]
}

 The dataset includes 181 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051002-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kunh88
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.544674 -34.736305, 148.544674 -34.738551, 148.54692 -34.738551, 148.54692 -34.736305, 148.544674 -34.736305))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051004-240626123714530/datasets/export for details.
DOI: 10.15468/dl.jvhn6z
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((142.323811 -37.006808, 142.323811 -37.015791, 142.326057 -37.015791, 142.326057 -37.006808, 142.323811 -37.006808))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051005-240626123714530/datasets/export for details.
DOI: 10.15468/dl.a37r3x
title: Occurrence Download

description: A dataset containing 13231 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is FRA.11_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Alnus Mill."
 ]
}

 The dataset includes 13231 records from 200 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051000-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mypj8h
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.442994 -34.743042, 149.442994 -34.74978, 149.447485 -34.74978, 149.447485 -34.743042, 149.442994 -34.743042))"
 ]
}

 The dataset includes 13 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051006-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.