cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17414931
title: The Influence of Room Acoustics on Auditory Selective Attention in a Virtual Classroom Scene

description: General

The audio-visual Auditory Selective Attention VR - Roomacoustics (avASAroomacoustics) project serves to investigate the effect of roomacoustic simulations on a paradigm on the auditory selective attention switch in a close-to-real-life classroom setting. This dataset consists of a Unity project and Matlab code used to collect data on the voluntary switching of auditory selective attention in a virtual reality classroom scenario.

The dataset contains:

    Unity project for audiovisual display and the experiment structure    Matlab code for experiment preparation and HpFT measurement    Data collected in the experiment (experiment performance, head tracking)

Experiment preparation using Matlab

The code and software used to prepare the experiment is provided in the folder "matlab_avASAroomacoustics".

The Matlab code used to prepare the trials for each participant as well as to measure the HpTFs. For the HpTF measurements, the  ITA Toolbox for Matlab was used and is provided (https://git.rwth-aachen.de/ita/toolbox). A developmental version of Virtual acoustics (VA) 2021a (https://www.virtualacoustics.org/VA/overview/) is provided.

Note that the listening experiment was conducted using RAVEN. However, RAVEN is only free to use for research purposes. If you would like to work with RAVEN, contact raven@akustik.rwth-aachen.de Look at the RAVEN website for more details: https://www.virtualacoustics.org/RAVEN/

Software requirements:

    Matlab 2020a or higher    ITA Toolbox for Matlab installed

Experiment conduction in Unity

The Unity project is provided in the folder "unity_avASAroomacoustics".

Therefore, a virtual classroom with some basic furniture is provided. The used models, prefabs and plugins can be found in the Assets folder.

The acoustic stimuli for the task were created using Voicemaker (https://voicemaker.in/).

This Unity project was intended for the use in virtual reality using an HMD and respective controllers for input. However, it can also be used on a desktop pc. The mode can be changed using the "VRMode" toggle as described below.The audio reproduction is realized using the Unity plugin for Virtual Acoustics (VA, http://www.virtualacoustics.org/ and https://git.rwth-aachen.de/ita/vaunity_package).

Software requirements:

    Unity 2019.4.21.f1.    SteamVR 1.19.7    Virtual Acoustics v2021a, VAUnity: https://git.rwth-aachen.de/ita/VAUnity    RAVEN https://www.virtualacoustics.org/RAVEN/

Data evaluation

The collected data is provided in the folder "dataEvaluation_avASAroomacoustics". This folder contains two types of data: the raw data collected in the experiment (reaction times and error rates) and the data collected from the questionnaires on perceived speech intelligibility, listening effort, and presence.
DOI: 10.5281/zenodo.17414933
title: The Influence of Room Acoustics on Auditory Selective Attention in a Virtual Classroom Scene

description: General

The audio-visual Auditory Selective Attention VR - Roomacoustics (avASAroomacoustics) project serves to investigate the effect of roomacoustic simulations on a paradigm on the auditory selective attention switch in a close-to-real-life classroom setting. This dataset consists of a Unity project and Matlab code used to collect data on the voluntary switching of auditory selective attention in a virtual reality classroom scenario.

The dataset contains:

    Unity project for audiovisual display and the experiment structure    Matlab code for experiment preparation and HpFT measurement    Data collected in the experiment (experiment performance, head tracking)

Experiment preparation using Matlab

The code and software used to prepare the experiment is provided in the folder "matlab_avASAroomacoustics".

The Matlab code used to prepare the trials for each participant as well as to measure the HpTFs. For the HpTF measurements, the  ITA Toolbox for Matlab was used and is provided (https://git.rwth-aachen.de/ita/toolbox). A developmental version of Virtual acoustics (VA) 2021a (https://www.virtualacoustics.org/VA/overview/) is provided.

Note that the listening experiment was conducted using RAVEN. However, RAVEN is only free to use for research purposes. If you would like to work with RAVEN, contact raven@akustik.rwth-aachen.de Look at the RAVEN website for more details: https://www.virtualacoustics.org/RAVEN/

Software requirements:

    Matlab 2020a or higher    ITA Toolbox for Matlab installed

Experiment conduction in Unity

The Unity project is provided in the folder "unity_avASAroomacoustics".

Therefore, a virtual classroom with some basic furniture is provided. The used models, prefabs and plugins can be found in the Assets folder.

The acoustic stimuli for the task were created using Voicemaker (https://voicemaker.in/).

This Unity project was intended for the use in virtual reality using an HMD and respective controllers for input. However, it can also be used on a desktop pc. The mode can be changed using the "VRMode" toggle as described below.The audio reproduction is realized using the Unity plugin for Virtual Acoustics (VA, http://www.virtualacoustics.org/ and https://git.rwth-aachen.de/ita/vaunity_package).

Software requirements:

    Unity 2019.4.21.f1.    SteamVR 1.19.7    Virtual Acoustics v2021a, VAUnity: https://git.rwth-aachen.de/ita/VAUnity    RAVEN https://www.virtualacoustics.org/RAVEN/

Data evaluation

The collected data is provided in the folder "dataEvaluation_avASAroomacoustics". This folder contains two types of data: the raw data collected in the experiment (reaction times and error rates) and the data collected from the questionnaires on perceived speech intelligibility, listening effort, and presence.
DOI: 10.34740/kaggle/dsv/13955676
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.15468/dl.dmtvfx
title: Occurrence Download

description: A dataset containing 358 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Abies chensiensis"
 ]
}

 The dataset includes 358 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021788-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6u5rf8
title: Occurrence Download

description: A dataset containing 5130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Actinodaphne trichocarpa, Actinodaphne tsaii, Adenanthera microsperma, Adenanthera pavonina, Adina pilulifera)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5130 records from 195 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021789-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/wn9jez
title: PAN-00177160 - button with solid convex head and flat base, loop-shaped shank, decorated

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00177160&lt;/p&gt;
description: Modified: 2025-08-07T09:29:29+02:00
DOI: 10.5281/zenodo.17787032
title: supplementary materials
DOI: 10.5281/zenodo.17787147
title: supplementary materials
DOI: 10.15468/dl.ycswg9
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Ghana",
 "OccurrenceStatus is Present",
 "TaxonKey is Avicennia germinans"
 ]
}

 The dataset includes 61 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021790-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17735476
title: Predicting Resting Metabolic Rate in healthy adults: A Comparative Analysis Using the enable cohort

description: Background: Resting metabolic rate (RMR) is modulated by a variety of factors. Accurate prediction of RMR is essential for planning energy requirements but remains challenging due to inter-individual variability. 

Objective: This study aimed to develop and evaluate machine learning models for predicting RMR using comprehensive data from the cross-sectional enable study and to identify the most predictive and stable features across different study populations.

Methods: RMR was predicted using data from 454 participants of the enable phenotyping platform (Freising and Nuremberg cohort). We systematically compared linear and nonlinear machine learning models trained on either the full set of 94 predictors or a reduced set of routinely accessible variables, including sex, age, body weight, fat mass, and fat-free mass. Model performance was assessed by cross-validation. The best-performing model (Lasso) was further evaluated on independent test datasets from other cohorts. Feature importance and stability were assessed using repeated cross-validation and marginal variance decomposition.

Results: Lasso regression consistently outperformed other models, particularly when trained on the enable cohort feature set. The final model explained 76.8% of RMR variance in the Freising cohort. Key predictive features included fat-free mass, body weight, and mean outdoor temperature. Blood-based features contributed marginally, whereas microbiota and fecal short chain fatty acids variables did not contribute to explaining RMR.

Conclusion: This novel prediction model for RMR shows improved accuracy in comparison to traditional models. While microbiota composition did not contribute to explain the residual variation in RMR, the inclusion of clinical blood parameters and outdoor temperature improved predictive performance.
DOI: 10.5281/zenodo.17735477
title: Predicting Resting Metabolic Rate in healthy adults: A Comparative Analysis Using the enable cohort

description: Background: Resting metabolic rate (RMR) is modulated by a variety of factors. Accurate prediction of RMR is essential for planning energy requirements but remains challenging due to inter-individual variability. 

Objective: This study aimed to develop and evaluate machine learning models for predicting RMR using comprehensive data from the cross-sectional enable study and to identify the most predictive and stable features across different study populations.

Methods: RMR was predicted using data from 454 participants of the enable phenotyping platform (Freising and Nuremberg cohort). We systematically compared linear and nonlinear machine learning models trained on either the full set of 94 predictors or a reduced set of routinely accessible variables, including sex, age, body weight, fat mass, and fat-free mass. Model performance was assessed by cross-validation. The best-performing model (Lasso) was further evaluated on independent test datasets from other cohorts. Feature importance and stability were assessed using repeated cross-validation and marginal variance decomposition.

Results: Lasso regression consistently outperformed other models, particularly when trained on the enable cohort feature set. The final model explained 76.8% of RMR variance in the Freising cohort. Key predictive features included fat-free mass, body weight, and mean outdoor temperature. Blood-based features contributed marginally, whereas microbiota and fecal short chain fatty acids variables did not contribute to explaining RMR.

Conclusion: This novel prediction model for RMR shows improved accuracy in comparison to traditional models. While microbiota composition did not contribute to explain the residual variation in RMR, the inclusion of clinical blood parameters and outdoor temperature improved predictive performance.
DOI: 10.17026/ar/6vwqvx
title: PAN-00126710 - coin/coin-related, Trajanus (98-117), sestertius

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00126710&lt;/p&gt;
description: Modified: 2025-09-30T07:42:33+02:00
DOI: 10.15468/dl.tee99m
title: Occurrence Download

description: A dataset containing 804 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Russian Federation",
 "TaxonKey is Euonymus verrucosus"
 ]
}

 The dataset includes 804 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021791-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17714885
title: Climatic chamber results- biostimulation

description: Dataset from climate-chamber trials evaluating the biostimulant and biopesticide activity of an onion (Allium cepa) extract on olive plantlets under non-stressful conditions. Olive plants received foliar or irrigation applications of a commercial onion extract formulation versus untreated controls. The dataset includes measurements of oxidative stress (MDA), antioxidant capacity (FRAP), and growth parameters (leaf biomass and root length).
DOI: 10.5281/zenodo.17714884
title: Climatic chamber results- biostimulation

description: Dataset from climate-chamber trials evaluating the biostimulant and biopesticide activity of an onion (Allium cepa) extract on olive plantlets under non-stressful conditions. Olive plants received foliar or irrigation applications of a commercial onion extract formulation versus untreated controls. The dataset includes measurements of oxidative stress (MDA), antioxidant capacity (FRAP), and growth parameters (leaf biomass and root length).
DOI: 10.17026/ar/tfi8vm
title: PAN-00147661 - plate (type unknown; East-Gaulish terra sigillata, II, III)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00147661&lt;/p&gt;
description: Modified: 2025-09-08T12:04:38+02:00
DOI: 10.5281/zenodo.17714251
title: Soil sanitization

description: Results on antimicrobial activity in olive grove soil of organosulfur compounds present in onion extract against soil-borne pathogens.
DOI: 10.5281/zenodo.17714252
title: Soil sanitization

description: Results on antimicrobial activity in olive grove soil of organosulfur compounds present in onion extract against soil-borne pathogens.
DOI: 10.5281/zenodo.17713594
title: HPLC SOIL

description: Soil HPLC measurements of PTS and PTSO after single and multiple applications at 100 and 500 μg/g.
DOI: 10.5281/zenodo.17713593
title: HPLC SOIL

description: Soil HPLC measurements of PTS and PTSO after single and multiple applications at 100 and 500 μg/g.
DOI: 10.5281/zenodo.17580587
title: Dataset underlying the study "Naked-Eye Molecular Testing for the Detection of Xylella fastidiosa in Mallorca (Balearic Island) Almond Orchards by Colorimetric LAMP"

description: This dataset is underlying the scientific publication titled "Naked-Eye Molecular Testing for the Detection of Xylella fastidiosa in Mallorca (Balearic Island) Almond Orchards by Colorimetric LAMP", published in the Applied Sciences journal. 

The dataset includes results of qPCR detection of Xylella fastidiosa Xfm in samples collected on Summer 2023 from two experimental orchards located in Mallorca Island, Spain.The provided information in the dataset are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication.

This research was conducted through a joint action of the EU’s Horizon 2020 Projects No. 887281 ‘Biovexo; Biocontrol of Xylella and its vector in olive trees for integrated pest management’ (GA n. 887281), ‘FREE@POC; Towards an instrument-FREE future of molecular diagnostics at the Point-Of-Care’ (GA n. 862840) and also partially supported by ‘BEXYL’ (Beyond Xylella, Integrated Management Strategies for Mitigating Xylella fastidiosa impact in Europe; grant number 101060593).
DOI: 10.5281/zenodo.17580586
title: Dataset underlying the study "Naked-Eye Molecular Testing for the Detection of Xylella fastidiosa in Mallorca (Balearic Island) Almond Orchards by Colorimetric LAMP"

description: This dataset is underlying the scientific publication titled "Naked-Eye Molecular Testing for the Detection of Xylella fastidiosa in Mallorca (Balearic Island) Almond Orchards by Colorimetric LAMP", published in the Applied Sciences journal. 

The dataset includes results of qPCR detection of Xylella fastidiosa Xfm in samples collected on Summer 2023 from two experimental orchards located in Mallorca Island, Spain.The provided information in the dataset are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication.

This research was conducted through a joint action of the EU’s Horizon 2020 Projects No. 887281 ‘Biovexo; Biocontrol of Xylella and its vector in olive trees for integrated pest management’ (GA n. 887281), ‘FREE@POC; Towards an instrument-FREE future of molecular diagnostics at the Point-Of-Care’ (GA n. 862840) and also partially supported by ‘BEXYL’ (Beyond Xylella, Integrated Management Strategies for Mitigating Xylella fastidiosa impact in Europe; grant number 101060593).
DOI: 10.15468/dl.p5g7xx
title: Occurrence Download

description: A dataset containing 2171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Adinandra bockiana, Adinandra epunctata, Adinandra formosana, Adinandra glischroloma, Adinandra grandis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2171 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021792-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21242/23211.2024.00.00.1.1.0
title: Todesursachenstatistik 2024, On-Site, Version 0

description: Die Todesursachenstatistik stützt sich auf den Leichenschauschein, der von dem den Tod feststellenden Arzt ausgefüllt wird, sowie auf die Sterbefallzählkarte, die der Standesbeamte aufgrund der Todesfallanzeige erstellt. Auf dieser Basis gibt sie eine Übersicht über die vorherrschenden Todesursachen der Verstorbenen mit Wohnsitz in Deutschland. Die Todesbescheinigung enthält Angaben über die zum Tode führenden Krankheiten sowie wesentliche sonstige Krankheitszustände, die zum Tode beigetragen haben. Die Todesursachenstatistik berücksichtigt nur das Grundleiden, das heißt den Ausgangspunkt der Kausalkette aller zum Tode führenden Krankheiten und damit jene Krankheit oder Verletzung, die den Ablauf der direkt zum Tode führenden Krankheitszustände ausgelöst hat. Bei der Auswahl des Grundleidens werden die jeweils gültigen Regeln der WHO zur Verschlüsselung der Todesursachen nach der Internationalen Klassifikation der Krankheiten (ICD) angewendet. Von 1979 bis 1997 galt in Deutschland die 9. Revision der ICD (ICD-9), seit 1998 gilt die 10. Revision (ICD-10). Im Fall der Coronavirus-Krankheit erfolgt die Kodierung unter den Schlüsselnummern für besondere Zwecke U071 und U072. Neben dem Grundleiden enthält die Todesursachenstatistik demographisch relevante Merkmale, wie das Datum des Sterbefalls oder Geschlecht und Alter des Verstorbenen sowie Informationen zu Staatsangehörigkeit oder Familienstand. In Fällen, in denen der Verstorbene verheiratet war, finden sich in der Statistik zusätzlich Angaben zum Alter des überlebenden Ehegatten. Demgegenüber stehen bei Säuglingssterbefällen Informationen zu Geburtsgewicht, Körperlänge oder Säuglingsalter zur Verfügung. Für räumliche Analysen können die Merkmale Standesamt und Wohnort des Verstorbenen bis auf Gemeindeebene dienen.
DOI: 10.15468/dl.qngsuq
title: Occurrence Download

description: A dataset containing 106888 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 69.085278",
 "DecimalLatitude is less than or equal to 74.085278",
 "DecimalLongitude is greater than or equal to 15.0",
 "DecimalLongitude is less than or equal to 20.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 106888 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021773-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00186.00849
title: Output results of solving the neutron transport equation in slab/sphere geometry using deep learning
title: 深度学习求解平板/球几何中子输运方程的输出结果

description: Output results of solving the neutron transport equation in slab/sphere geometry using deep learning
description: Output results of solving the neutron transport equation in slab/sphere geometry using deep learning
DOI: 10.5525/gla.researchdata.2089
title: Global Gambling Control Scorecard (GGCS): Dataset. Version 1: November 2025

description: The Global Gambling Control Scorecard (GGCS) dataset provides a comparative overview of national gambling control systems across countries. It systematically codes policy responses embedded in legislation, policy, and other mandatory regulations across seven domains:
1. Legal status of gambling & regulatory regime
2. Actions to prevent illegal/unlicensed gambling
3. Policies to prevent gambling harms; multi-sectoral policies
4. Use of effective prevention measures; availability of treatment
5. Effective regulatory controls (legal powers; prescriptive vs voluntary regulation)
6. Systems for monitoring harms
7. Methods of funding for harm prevention

This first version focuses on 34 European jurisdictions. The current version reflects information on policy and legislation up to 1 October 2025.

Data are provided in Microsoft Excel format and include 45 indicators, accompanied by metadata on coding definitions and sources.
DOI: 10.5281/zenodo.17786999
title: Data on the exact geometric configuration of solitary-wave interactions

description: This is the original computational data corresponding to the numerical results graph in the paper "Exact geometric configuration of solitary-wave interactions."
DOI: 10.5281/zenodo.17787000
title: Data on the exact geometric configuration of solitary-wave interactions

description: This is the original computational data corresponding to the numerical results graph in the paper "Exact geometric configuration of solitary-wave interactions."
DOI: 10.15468/dl.j633hu
title: Occurrence Download

description: A dataset containing 51541 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Italy",
 "OccurrenceStatus is Present",
 "TaxonKey is Arachnida"
 ]
}

 The dataset includes 51541 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021771-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/2kkp37
title: PAN-00117943 - coin/coin-related, Vespasianus (69-79), as

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00117943&lt;/p&gt;
description: Modified: 2025-09-23T10:11:14+02:00
DOI: 10.34740/kaggle/dsv/13955718
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5517/ccdc.csd.cc2nwm17
title: CSD 2469399: Experimental Crystal Structure Determination

description: Related Article: Nick Goossens, Bensu Tunca, Michael Stuer, Per O. Å. Persson, Jin Won Seo, Shuigen Huang, Konstantina Lambrinou, Jozef Vleugels|2025|J.Am.Chem.Soc.|||doi:10.1021/jacs.5c11713
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.