cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4899251
title: Supplementary material for Khaldy et al. 2021; Compass cue integration and its relation to the visual ecology of three tribes of ball-rolling dung beetles

description: <strong>Supplementary Materials:</strong> <strong>Supplementary Table 1:</strong> Eye area and step size for <em>K. nigroaeneus, G. unicolor </em>and <em>S. fasciculatus. </em> <strong>Supplementary Table 2:</strong> Exit angles (0-359°) of ten exit rolls of ten individuals of <em>K. nigroaeneus</em>, <em>G. unicolor </em>and <em>S. fasciculatus, </em>respectively,<em> </em>and the corresponding calculated mean vector length (R) <strong>Supplementary Table 3: </strong>Absolute angular difference in exit bearing of each manipulation (<em>test: </em>first and second exit bearing; <em>control: </em>first and third exit bearing) for each individual beetle, in each paradigm. Species: <em>K. nigroaeneus; G. unicolor; G. nitens; S. fasciculatus.</em> <strong>Supplementary Figure 1. </strong>Response to directional change of compass cues in <em>Garreta nitens</em>.
DOI: 10.5281/zenodo.4744755
title: Supplementary material for Khaldy et al. 2021; Compass cue integration and its relation to the visual ecology of three tribes of ball-rolling dung beetles

description: <strong>Supplementary Materials:</strong> <strong>Supplementary Table 1:</strong> Eye area and step size for <em>K. nigroaeneus, G. unicolor </em>and <em>S. fasciculatus. </em> <strong>Supplementary Table 2:</strong> Exit angles (0-359°) of ten exit rolls of ten individuals of <em>K. nigroaeneus</em>, <em>G. unicolor </em>and <em>S. fasciculatus, </em>respectively,<em> </em>and the corresponding calculated mean vector length (R) <strong>Supplementary Table 3: </strong>Absolute angular difference in exit bearing of each manipulation (<em>test: </em>first and second exit bearing; <em>control: </em>first and third exit bearing) for each individual beetle, in each paradigm. Species: <em>K. nigroaeneus; G. unicolor; G. nitens; S. fasciculatus.</em> <strong>Supplementary Figure 1. </strong>Response to directional change of compass cues in <em>Garreta nitens</em>.
DOI: 10.6084/m9.figshare.14730954.v1
title: catalyst design

description: data supporting the manuscript "Globally Optimized Molecular Embeddings for Dynamic Reaction Solvate Shell Optimization and Active Site Design -- From abstract catalyst design via electric field optimization back to the real world", by Dominik Behrens and Bernd Hartke, submitted to "Topics in Catalysis" on 2021-06-04.For the Menshutkin SN2 reaction in acetone, and for ketosteroid isomerase, globally optimized structures (as xyz files, without and with partial charges) and NEB log files.<br>
DOI: 10.6084/m9.figshare.14730954
title: catalyst design

description: data supporting the manuscript "Globally Optimized Molecular Embeddings for Dynamic Reaction Solvate Shell Optimization and Active Site Design -- From abstract catalyst design via electric field optimization back to the real world", by Dominik Behrens and Bernd Hartke, submitted to "Topics in Catalysis" on 2021-06-04.For the Menshutkin SN2 reaction in acetone, and for ketosteroid isomerase, globally optimized structures (as xyz files, without and with partial charges) and NEB log files.<br>
DOI: 10.6084/m9.figshare.14730969
title: Supplement_Data_Daytime.xlsx

description: Dataset for the Paper <br>"Daytime fluctuations of endurance performance in young soccer players: A randomized cross-over trial"
DOI: 10.6084/m9.figshare.14730969.v1
title: Supplement_Data_Daytime.xlsx

description: Dataset for the Paper <br>"Daytime fluctuations of endurance performance in young soccer players: A randomized cross-over trial"
DOI: 10.5281/zenodo.4899334
title: Recording transcriptional histories using Record-seq

description: Data underlying the figures in the publication “Recording transcriptional histories using Record-seq” published in <em>Nat Protoc,</em> <strong>2020</strong>, 15, 513–539. The dataset contains a .zip folder with the python scripts and a R package for analysing datasets generated using the Record-seq workflow. It can also be found in the following github repository: https://github.com/plattlab/Transcriptional-Recording.
DOI: 10.5281/zenodo.4899333
title: Recording transcriptional histories using Record-seq

description: Data underlying the figures in the publication “Recording transcriptional histories using Record-seq” published in <em>Nat Protoc,</em> <strong>2020</strong>, 15, 513–539. The dataset contains a .zip folder with the python scripts and a R package for analysing datasets generated using the Record-seq workflow. It can also be found in the following github repository: https://github.com/plattlab/Transcriptional-Recording.
DOI: 10.5525/gla.researchdata.1106
title: Edge Computing enabled Deep Learning for Smart Mobile DNA Malaria Diagnostics
DOI: 10.5281/zenodo.4899364
title: TopoFilter: a MATLAB package for mechanistic model identification in systems biology

description: Data underlying the figures in the publication “TopoFilter: a MATLAB package for mechanistic model identification in systems biology” published in <em>BMC Bioinformatics,</em> <strong>2020</strong>, 21, 34. The .zip folder with the datasets generated and/or analyzed during the study. They are also available in the gitlab repository, https://gitlab.com/csb.ethz/TopoFilter.
DOI: 10.5281/zenodo.4899363
title: TopoFilter: a MATLAB package for mechanistic model identification in systems biology

description: Data underlying the figures in the publication “TopoFilter: a MATLAB package for mechanistic model identification in systems biology” published in <em>BMC Bioinformatics,</em> <strong>2020</strong>, 21, 34. The .zip folder with the datasets generated and/or analyzed during the study. They are also available in the gitlab repository, https://gitlab.com/csb.ethz/TopoFilter.
DOI: 10.5281/zenodo.4899270
title: Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning

description: Data underlying the figures in the publication “Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning” published in <em>Nat Biomed Eng, <strong>2021,</strong> https://doi.org/10.1038/s41551-021-00699-9</em> The dataset contains a .zip folder with the scripts to perform therapeutic antibody optimization with deep learning, as described in Mason et al., 2019 [https://doi.org/10.1101/617860]. The detail description of the code availability, preparation, and usage can be found in the following github repository: https://github.com/dahjan/DMS_opt.
DOI: 10.6084/m9.figshare.14731029
title: Associations between smoking to relieve stress, motivation to stop and future quit attempts across the social spectrum: A population survey in England

description: Dataset underpinning the analyses in the paper titled "Associations between smoking to relieve stress, motivation to stop and future quit attempts across the social spectrum: A population survey in England".
DOI: 10.5525/gla.researchdata.1142
title: RAL GTPases mediate EGFR-driven intestinal stem cell hyperproliferation and tumourigenesis
DOI: 10.25646/8587
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5281/zenodo.4899478
title: Nemertea, Brachiopoda, Phoronida transcriptomes and proneuropeptide clustermap

description: Proneuropeptide clustermap and transcriptomes of nemertean (Baseodiscus unicolor, Cerebratulus spec., Lineus longissimus, Lineus ruber, Nipponemertes spec., Riseriellus occultus), brachiopod (Novocrania anomala, Terebratalia transversa) and phoronid (Phoronopsis harmeri) species.<br> This dataset was uploaded as part of a project to identify proneuropeptides and neuropeptide GPCRs in nemerteans, brachiopods and phoronids.<br> Proneuropeptide clustermap was created at the Living Systems Institute (University of Exeter, UK)using the program "CLANS" for protein clustering.<br> Transcriptomes were assembled at the Sars International Centre for Marine Molecular Biology (University of Bergen, Norway) using the assembly program "Trinity".<br> Assemblies of Baseodiscus unicolor, Cerebratulus spec., Nipponemertes spec. and Riseriellus occultus were done according to the assembly pipeline published on https://github.com/JekelyLab/Thiel_Yanez-Guerra_et_al_2021.<br> Assemblies of the other transcriptomes was described in Cannon JT, Vellutini BC, Smith J, Ronquist F, Jondelius U, Hejnol A (2016): Xenacoelomorpha is the sistergroup to Nephrozoa. Nature, 530: 89-93.
DOI: 10.5281/zenodo.4556027
title: Nemertea, Brachiopoda, Phoronida transcriptomes and proneuropeptide clustermap

description: Proneuropeptide clustermap and transcriptomes of nemertean (Baseodiscus unicolor, Cerebratulus spec., Lineus longissimus, Lineus ruber, Nipponemertes spec., Riseriellus occultus), brachiopod (Novocrania anomala, Terebratalia transversa) and phoronid (Phoronopsis harmeri) species.<br> This dataset was uploaded as part of a project to identify proneuropeptides and neuropeptide GPCRs in nemerteans, brachiopods and phoronids.<br> Proneuropeptide clustermap was created at the Living Systems Institute (University of Exeter, UK)using the program "CLANS" for protein clustering.<br> Transcriptomes were assembled at the Sars International Centre for Marine Molecular Biology (University of Bergen, Norway) using the assembly program "Trinity".<br> Assemblies of Baseodiscus unicolor, Cerebratulus spec., Nipponemertes spec. and Riseriellus occultus were done according to the assembly pipeline published on https://github.com/JekelyLab/Thiel_Yanez-Guerra_et_al_2021.<br> Assemblies of the other transcriptomes was described in Cannon JT, Vellutini BC, Smith J, Ronquist F, Jondelius U, Hejnol A (2016): Xenacoelomorpha is the sistergroup to Nephrozoa. Nature, 530: 89-93.
DOI: 10.5281/zenodo.4897867
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4897866
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4899494
title: dataset_for_fig_ 4

description: File for creating figure 4
DOI: 10.5281/zenodo.4899493
title: dataset_for_fig_ 4

description: File for creating figure 4
DOI: 10.5286/isis.e.rb2000280
title: Metastable liquid structure of the most polymorphic organic molecule

description: The main goal of the proposed work is to measure the neutron structure factors of organic molecular liquid 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile (ROY) over a wide temperature range, from above the melting point (Tm = 388 K), in the supercooled liquid region, and below the glass transition at Tg = 259 K. This work will provide direct insight into conformer distribution and intermolecular interactions governing the properties of the liquid and the glass, along with valuable, stringent constraints for modelling of this enigmatic material. Such information goes to the heart of central questions in condensed matter physics and pharmaceutical science regarding non-classical crystal nucleation, polymorphism and diffusionless crystal growth.
DOI: 10.5286/isis.e.rb2000280-1
title: Metastable liquid structure of the most polymorphic organic molecule

description: The main goal of the proposed work is to measure the neutron structure factors of organic molecular liquid 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile (ROY) over a wide temperature range, from above the melting point (Tm = 388 K), in the supercooled liquid region, and below the glass transition at Tg = 259 K. This work will provide direct insight into conformer distribution and intermolecular interactions governing the properties of the liquid and the glass, along with valuable, stringent constraints for modelling of this enigmatic material. Such information goes to the heart of central questions in condensed matter physics and pharmaceutical science regarding non-classical crystal nucleation, polymorphism and diffusionless crystal growth.
DOI: 10.5281/zenodo.4899510
title: Data Availability for urban historical expansion study

description: This is a data set used in the submission of a research paper on the historical expansion of cities.
DOI: 10.5281/zenodo.4899509
title: Data Availability for urban historical expansion study

description: This is a data set used in the submission of a research paper on the historical expansion of cities.
DOI: 10.5281/zenodo.4899208
title: Russian Open Speech To Text (STT/ASR) Dataset

description: <strong>Russian Open Speech To Text (STT/ASR) Dataset</strong> Arguably the largest public Russian STT dataset up to date.
description: https://github.com/snakers4/open_stt
DOI: 10.5281/zenodo.4899207
title: Russian Open Speech To Text (STT/ASR) Dataset

description: <strong>Russian Open Speech To Text (STT/ASR) Dataset</strong> Arguably the largest public Russian STT dataset up to date.
description: https://github.com/snakers4/open_stt
DOI: 10.5281/zenodo.4897944
title: COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

description: This dataset release contains the execution traces and training data correponding to the paper<br> "COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments", by S. Tuli, S. Poojara, S. N. Srirama, G.Casale and N. R. jennings, accepted in IEEE Trasnsactions on Parallel and Distributed Systems (TPDS), 2021. When referring to the dataset please cite the above paper. The code implementation is available at https://github.com/imperial-qore/COSCO.
DOI: 10.5281/zenodo.4897943
title: COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

description: This dataset release contains the execution traces and training data correponding to the paper<br> "COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments", by S. Tuli, S. Poojara, S. N. Srirama, G.Casale and N. R. jennings, accepted in IEEE Trasnsactions on Parallel and Distributed Systems (TPDS), 2021. When referring to the dataset please cite the above paper. The code implementation is available at https://github.com/imperial-qore/COSCO.
DOI: 10.5281/zenodo.1493301
title: Hunting behaviour in domestic cats: an exploratory study of risk and responsibility among cat owners (raw data)

description: All raw, redacted and anonymised interview transcripts.
DOI: 10.5281/zenodo.1493300
title: Hunting behaviour in domestic cats: an exploratory study of risk and responsibility among cat owners (raw data)

description: All raw, redacted and anonymised interview transcripts.
DOI: 10.5281/zenodo.4899586
title: The educational value of virtual ecologies in Red Dead Redemption 2 (Data / Code)

description: Full dataset (including raw qualitative data) and R code for quantitative analyses.
description: Details of qualitative coding structure available on request: please contact for details.
DOI: 10.5281/zenodo.4899585
title: The educational value of virtual ecologies in Red Dead Redemption 2 (Data / Code)

description: Full dataset (including raw qualitative data) and R code for quantitative analyses.
description: Details of qualitative coding structure available on request: please contact for details.
DOI: 10.17632/ntxypfsvds.1
title: ENVRI-KMS

description: The ENVRI-KMS is a cluster-level knowledge base that allows different ENVironmental Research Infrastructures (ENVRI) users, such as Research Infrastructures (RI) developers and data managers, to effectively share their technical practices, identify common data and service requirements and design patterns, and facilitate the search and analysis of existing RI solutions for environmental RI interoperability challenges.
DOI: 10.5281/zenodo.4899619
title: UAV bugs dataset and taxonomy

description: This data set contains 569 real world bugs, 168 UAV-specific bugs and their taxonomy. Our replication package consists of two maim folders:bugSet and bugTaxonomy bugSet In this folder we have placed all the bugs that we have indentified from PX4 and Ardupilot on GitHub. Data collection process is explained in detail in Section 3.1 of the paper. Each line in bugSet.xlsx provides project name and the link of 569 real-world bugs. bugTaxonomy Our manual analysis was conducted in 3 iterations(Section 3.2 in the paper). In each file(3 iterations) we provide the following information: (a) Project name;(b)Bug link; (c)bug label or bug description.
DOI: 10.34740/kaggle/dsv/2302711
title: 2021 World Population (updated daily)
DOI: 10.34740/kaggle/dsv/2302722
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.14730891
title: A Remote Sensing Driven Soil Moisture Estimator: Downscaling with Geostatistically Based Use of Ancillary Data

description: Soil moisture (SM) is a key component of ecological and hydrological models, and it's also one of the best indicators of climate change impacts. It represents the flow of water, electricity, and food, as well as being a critical component of carbon exchange between the ground, soil, and atmosphere. Despite its significance and high value, SM data is not commonly available due to the high cost of field sampling and the absence of a custodian, unlike precipitation and streamflow measurements, in many developing countries. Therefore, the accurate spatial distribution of this hydrological variable is not available for the entire catchment. In recent years, remotely sensed satellites including soil moisture active passive (SMAP) continuously monitor SM of the earth. However, the spatial resolution of the remote-sensed SM is not sufficient for hydrological applications and water resource management. In this paper, a data-driven model is utilized to capture the interaction between SM and ancillary data (AD) including normalized difference vegetation index (NDVI), altitude, slope, cumulative precipitation, and air temperature. These data along with measured SM from 158 monitoring stations in the state of Utah are collected and an artificial neural network (ANN) platform is developed for predictive measures and estimation of SM. By co-regionalization of the estimated SM from the neural network and large-scale information from the remote sensing, SM in any parts of the study area was estimated more accurately and on a finer resolution (1-km). Finally, through a linear relationship between observational SM with the ancillary up-to-date data and the downscaled satellite SM, the resulting SM values ​​were adjusted and presented by adding a stochastic term. On average, the unbiased Root Mean Square Error (UnbRMSE) between the adjusted downscaled SMAP SM data and in-situ SM observations adequately met the SMAP SM retrieval accuracy requirement of 0.04 m<sup>3</sup>/m<sup>3</sup>. In addition, the results of SM validation show that the use of this technique is able to better estimate SM for remote parts of the study area.
DOI: 10.6084/m9.figshare.14730891.v1
title: A Remote Sensing Driven Soil Moisture Estimator: Downscaling with Geostatistically Based Use of Ancillary Data

description: Soil moisture (SM) is a key component of ecological and hydrological models, and it's also one of the best indicators of climate change impacts. It represents the flow of water, electricity, and food, as well as being a critical component of carbon exchange between the ground, soil, and atmosphere. Despite its significance and high value, SM data is not commonly available due to the high cost of field sampling and the absence of a custodian, unlike precipitation and streamflow measurements, in many developing countries. Therefore, the accurate spatial distribution of this hydrological variable is not available for the entire catchment. In recent years, remotely sensed satellites including soil moisture active passive (SMAP) continuously monitor SM of the earth. However, the spatial resolution of the remote-sensed SM is not sufficient for hydrological applications and water resource management. In this paper, a data-driven model is utilized to capture the interaction between SM and ancillary data (AD) including normalized difference vegetation index (NDVI), altitude, slope, cumulative precipitation, and air temperature. These data along with measured SM from 158 monitoring stations in the state of Utah are collected and an artificial neural network (ANN) platform is developed for predictive measures and estimation of SM. By co-regionalization of the estimated SM from the neural network and large-scale information from the remote sensing, SM in any parts of the study area was estimated more accurately and on a finer resolution (1-km). Finally, through a linear relationship between observational SM with the ancillary up-to-date data and the downscaled satellite SM, the resulting SM values ​​were adjusted and presented by adding a stochastic term. On average, the unbiased Root Mean Square Error (UnbRMSE) between the adjusted downscaled SMAP SM data and in-situ SM observations adequately met the SMAP SM retrieval accuracy requirement of 0.04 m<sup>3</sup>/m<sup>3</sup>. In addition, the results of SM validation show that the use of this technique is able to better estimate SM for remote parts of the study area.
DOI: 10.6084/m9.figshare.14731289.v1
title: <i>Weltersia obscura</i>, a new slug from the island of Montecristo (Tuscan Archipelago, Italy): a hitherto undiscovered endemic or a recent alien? (Mollusca, Pulmonata, Limacidae)

description: Unexpectedly, an unknown limacid slug was found in damp meadows and granite trails on the western side of Montecristo, a small island of the Tuscan Archipelago (N Tyrrhenian Sea, Italy), the malacofauna of which has been extensively studied in the last 50 years. It is distinguished from all other anatomically studied limacid species: its duct of the bursa copulatrix joins to the female distal genitalia while in all other limacids except <i>Limacus flavus</i>, it joins to the penis (or the genital atrium). Several other features distinguish the Montecristo slug from <i>L. flavus</i>: body colour, structure of ovispermiduct and free oviduct (with a peculiar sphincter in the new slug), internal structure of the penis and female distal genitalia. Analysis of the nucleotide sequences of several mitochondrial (COI, 16S rDNA) and nuclear (ITS2, 28S rDNA) gene fragments supported the assignation of the Montecristo slug to the family Limacidae, but also its distinction from all molecularly characterized species from the genera <i>Limax</i>, <i>Ambigolimax</i>, <i>Bielzia</i>, <i>Lehmannia</i>, <i>Limacus</i> and <i>Malacolimax</i>. Therefore we decided to describe it within a new genus as <i>Weltersia obscura</i> sp. nov. The origin of this slug is obscure – it is not clear if it is an endemic species overlooked in previous field studies or an alien species introduced to the island very recently. http://zoobank.org/urn:lsid:zoobank.org:act:0C5A2CC2-A94D-4B1D-8DF9-04FA54374E93: http://zoobank.org/urn:lsid:zoobank.org:act:0C6E4F69-E3E3-494F-BC1E-F7F49E9B529F