cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1419603.08fu
title: SH1419603.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419604.08fu
title: SH1419604.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419605.08fu
title: SH1419605.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419606.08fu
title: SH1419606.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419607.08fu
title: SH1419607.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419608.08fu
title: SH1419608.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25549/one-c4-34465
title: Carl B., letters (1953/1965)

description: Carl B., forms, letters (1953/1965)
DOI: 10.15156/bio/sh1419609.08fu
title: SH1419609.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419610.08fu
title: SH1419610.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1419611.08fu
title: SH1419611.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.10047638
title: Dataset for "Indoor transmission of respiratory droplets under different ventilation systems using Eulerian approach"

description: Dataset for figures and tables of the article "Indoor transmission of respiratory droplets under different ventilation systems using Eulerian approach".
DOI: 10.5281/zenodo.10055030
title: POMFinder: Identifying polyoxometalate cluster structures from pair distribution function data using explainable machine learning

description: Databases that were used to train the POMFinder ML model.
DOI: 10.5281/zenodo.10000962
title: MedFS EAS5 Bathymetry
DOI: 10.5281/zenodo.10055029
title: POMFinder: Identifying polyoxometalate cluster structures from pair distribution function data using explainable machine learning

description: Databases that were used to train the POMFinder ML model.
DOI: 10.5281/zenodo.10000961
title: MedFS EAS5 Bathymetry
DOI: 10.21954/ou.rd.24453841
title: Dataset for the 'Citizen Science Study of Overflight Noise from New and Old Generation Aircraft at London City Airport'

description: This is the dataset accompanying the paper 'Citizen Science Study of Overflight Noise from New and Old Generation Aircraft at London City Airport'.<br><br>The dataset is an Excel file of noise data collected near London City Airport using the Explane app. The dataset includes the raw data as well as the pivot tables used to generate the diagrams.
DOI: 10.21954/ou.rd.24453841.v1
title: Dataset for the 'Citizen Science Study of Overflight Noise from New and Old Generation Aircraft at London City Airport'

description: This is the dataset accompanying the paper 'Citizen Science Study of Overflight Noise from New and Old Generation Aircraft at London City Airport'.<br><br>The dataset is an Excel file of noise data collected near London City Airport using the Explane app. The dataset includes the raw data as well as the pivot tables used to generate the diagrams.
DOI: 10.5281/zenodo.10055154
title: Xie_et_al_2023_11

description: Extended Data Table 1 (Control, SA and WA  experiments):
U, Omega, precipitation  
 
Extended Data Table 2 (SHW_SS and SHW_NSexperiments):
U
 
Extended Data Table 3 (SA_CZW and WA_CZW experiments):
U
DOI: 10.5281/zenodo.10055153
title: Xie_et_al_2023_11

description: Extended Data Table 1 (Control, SA and WA  experiments):
U, Omega, precipitation  
 
Extended Data Table 2 (SHW_SS and SHW_NSexperiments):
U
 
Extended Data Table 3 (SA_CZW and WA_CZW experiments):
U
DOI: 10.17909/v0hv-8e68
title: Mapping Obscured Star Formation in the Host Galaxy of FRB 20201124A

description: HST imaging in F160W and F475X of the host galaxy of the active FRB 20201124A. The observations were used to determine the morphology, galactocentric offset, and radial light distribution of the galaxy to better understand the star formation of the FRB's galactic environment.
DOI: 10.6084/m9.figshare.24460084
title: my_traces.zip

description: Network traces used in CoNEXT 2023 paper "Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video Streaming Quality". For more details, refer to Appendix C of the paper.
DOI: 10.6084/m9.figshare.24460084.v1
title: my_traces.zip

description: Network traces used in CoNEXT 2023 paper "Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video Streaming Quality". For more details, refer to Appendix C of the paper.
DOI: 10.25934/pr00007591
title: Predictors of Placebo Response and Remission in Ulcerative Colitis and Crohn’s Disease VERSION 2.0

description: Ulcerative colitis (UC) and Crohn’s disease (CD) are types of inflammatory bowel disease. UC affects the large intestine and is characterized by diarrhea, rectal bleeding, abdominal pain, urgency, and tenesmus (feeling the need for a bowel movement despite an empty bowel). CD can affect any area along the gastrointestinal tract, although many patients present with disease in the ileum and colon and experience symptoms including abdominal pain, weight loss, and diarrhea. Treatments for UC and CD must demonstrate efficacy and safety to obtain regulatory approval. Clinical trials for UC and CD are designed to assess the effect of a treatment and are often placebo-controlled when assessing novel biologic drugs. Placebo treatments do not contain any ingredients of therapeutic value and are often considered ‘sugar pills’. Despite receiving placebo, patients may still experience an improvement in their condition. Although high placebo response rates in clinical trials have been previously reported, it is unclear what factors may influence the response rate. Previous meta-analyses for UC have suggested factors such as disease duration, endoscopic disease severity, rectal bleeding score at baseline, and class of treatment may play a role in placebo response and remission rates. The primary objective of this study is to evaluate predictors of clinical response among patients who received placebo treatment. Data from GEMINI 1 (NCT00783718), ACT 1 (NCT00036439), ACT 2 (NCT00096655), PURSUIT (NCT00488631), ULTRA (NCT00408629), and OCTAVE (NCT01465763, NCT01458951, and NCT01458574) will be pooled to obtain a cohort of UC patients who were treated with placebo for the entire duration of the trial. Data from UNITI-1 (NCT01369329), UNITI-2 (NCT01369342), IM-UNITI (NCT01369355), GEMINI-2 (NCT00783692), GEMINI-3 (NCT01224171), and CLASSIC-1 (NCT00055523) will be assessed for CD.
DOI: 10.13120/6r01-ad93
title: EdistoBay-GDR

description: The EdistoBay -GDR dataset is a comprehensive collection of geophysical measurements and sediment core data collected in Edisto Inlet. This inlet, situated along the north coast of Victoria Land, Antarctica (Cape Hallett), is about 15 km long and 4 km wide, bears the characteristic marks of glacial formation and is traditionally difficult to access due to persistent sea ice.
The Edisto Bay Geophysical Data Repository is organized to facilitate retrieval of geophysical data collected in the area during various projects funded by the Italian Antarctic Research Program (PNRA) and is part of a forthcoming publication based on the analysis of subsurface sub-bottom profiles (seismic data), multibeam swath bathymetry, gravity and piston sediment cores, Acoustic Doppler Current Profiles (ADCP), Conductivity Temperature Depth (CTD) measurements, and thermo- salinograph data acquired in the frame of several PNRA-funded projects. The importance of the dataset lies in its invaluable contribution to paleoclimate research in Antarctica and plays a central role in improving our understanding of ongoing environmental changes in this area. 
Seismic datasets are stored in both raw and processed formats, sub-bottom profiles were acquired using 1) a 3.5 kHz SBP GeoAcoustics Geopulse 5430-5210A aboard N/R Italica from 2002 to 2005 and 2) a hull-mounted Benthos CAP -6600 Chirp II Data Sonics on the RV OGS Explora in 2017. Geopulse chirp data were acquired in envelope mode, and additional pseudo-seismic processing was carried out prior to standard processing. The benthic chirp data sweep (with frequencies ranging from 2 to 7 kHz) was initially recorded in fullwave format, which allowed in post-cruise processing to improve the signal-to-noise ratio. These seismic datasets provided a variety of penetration depths reaching depths of up to 130 ms below the seafloor, with vertical resolutions from 30 to 10 cm.
Multibeam data were collected onboard OGS-Explora during the GLEVORS PNRA project in 2017 using a Teledyne Reson SeaBat 7150 multibeam echo sounder with a system frequency of 12 kHz and an impressive 880 beams. The dataset underwent rigorous processing, including manual editing to eliminate anomalous readings, and was subsequently gridded at 20 m to produce detailed relief maps. Multibeam data are available in both raw and processed (grid data) formats.
Cores information and positioning: data on sediment gravity and piston cores used in the publication. The cores sampled were sampled as part of PNRA projects: Anta in 2002, Baye in 2005, and GLEVORS in 2017. Comprehensive details on the acquisition and analysis of the sediment cores are carefully provided in accompanying tables. All cores are meticulously stored at the Sorting Center of the Italian National Antarctic Museum Section of Trieste and are accessible online.
In summary, the EdistoBay GDR dataset is a valuable resource for researchers interested in Antarctic paleoclimate, seafloor geology, and sediment dynamics.
DOI: 10.21227/smpm-wx08
title: 5G Positioning Simulation

description: The dataset contains 5G positioning measurements simulated using a MATLAB raytracer tool in realistic environments (outdoors and indoors).Outdoor scenarios include static and dynamic users in the urban area of Città Studi, Milan, Italy, near the Politecnico di Milano - Campus Leonardo.The indoor context is reconstructed using a LiDAR acquisition in the MADE Competence Center I4.0 located in Politecnico di Milano - Campus Durandò, Bovisa, Milan, Italy.The datasets include:Base station (BS) coordinates;User equipment (UE) coordinates;Raw measurements (TDOA/RTT/AOA/AOD).Each measurement will be marked with an integer timestamp (1,...,1000) and a boolean value (0/1) to indicate if the BS is in line of sight (LOS) or not (NLOS).The simulations comprehend a plethora of experiments. For instance, a comparison between the different numerologies (0, 1, 2, 3), methods (DL-TDOA, multi-RTT, UL-AOA, DL-AOD), and BS array (4x4, 8x8, 16x16).
DOI: 10.3886/e190167v1-142723
title: 2018 US National Justice Survey

description: The National Justice Survey asked U.S. respondents about their experiences interacting with police, their perspectives on the criminal legal system, and social attitudes. This survey is part of the National Opinion Research Center’s (NORC) AmeriSpeak Panel (NORC, 2018). Funded and operated by NORC at the University of Chicago, AmeriSpeak® is a probability-based panel designed to be representative of the US household population. Randomly selected US households are sampled with a known, non-zero probability of selection from the NORC National Frame and address-based sample, and then contacted by US mail, telephone interviewers, overnight express mailers, and field interviewers (face to face) and asked to complete a questionnaire over the web during June-August 2018. AmeriSpeak panelists participate in NORC studies or studies conducted by NORC on behalf of NORC’s clients. The current study was funded by the Russell Sage Foundation and conducted by Amerispeak. The City University of New York institutional review board approved the research and participants provided informed consent via computer. Respondents were drawn from this panel based upon age, race, education and gender. The sample is based upon the population falling within each group, adjusted for expected completion rates. The sample was weighted to reflect the national population.
description: The sample was weighted to reflect the national population.
description: Presence of Common Scales: Police legitimacy<br>Procedural justice<br>Stereotype threat<br>Essentialism<br>Theories of racism<br>Right-wing authoritarianism<br>Feeling thermometer<br>Social dominance orientation<br>IAT<br>
description: Randomly selected US households are sampled with a known, non-zero probability of selection from the NORC National Frame and address-based sample. Respondents were drawn from this panel based upon age, race, education and gender. The sample is based upon the population falling within each group, adjusted for expected completion rates.
description: Adult United States residents. Smallest Geographic Unit: state
description: web-based survey;
DOI: 10.5281/zenodo.10055192
title: Supplementary material to `Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.5'

description: This repository contains the supplementary material to the following paper: Hoffmann, L., Haghighi Mood, K., Herten, A., Hrywniak, M., Kraus, J., Clemens, J., and Liu, M., Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.5, Geoscientific Model Development, submitted, 2023.
DOI: 10.5281/zenodo.10055191
title: Supplementary material to `Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.5'

description: This repository contains the supplementary material to the following paper: Hoffmann, L., Haghighi Mood, K., Herten, A., Hrywniak, M., Kraus, J., Clemens, J., and Liu, M., Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.5, Geoscientific Model Development, submitted, 2023.