cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:x1-v1
title: Determination of key functional structures of an amorphous VHL-based SMARCA2 PROTAC

description: PROTACs are of high interest because of their ability to target previously challenging disease-related proteins. PROTACs promote the degradation of targets by ensuring the proximity of the E3-ligase and the target. The relation between structure and function of the ternary complex is of great interest. Of equal importance is the delivery of these drugs and determining the key interactions that stabilize the solid drug forms. Here, we determine the complete atomic-level structure of an amorphous VHL-based SMARCA2 PROTAC (PROTAC 2). The structure is solved using ultra-fast MAS, and DNP enhanced, NMR crystallography. We found that PROTAC 2 is more disordered as compared to previously studied amorphous formulations, and that the three functional units of the molecule have three distinct structural types. Overall, in contrast to structures of smaller drug molecules, where intermolecular H-bonding interactions were found to be the main stabilization mechanism for the amorphous solid form, for PROTAC 2 we postulate that, in analogy to glassy polymers, the main stabilization mechanism of the amorphous form is the entropic contribution introduced by the overall flexibility, especially in the linker region of the molecule. We also note that the most populated conformations found in the amorphous form differ from those of bound PROTAC 2 found in the ternary protein complex as determined via X-ray crystallography. Our results provide insight into key structural features that stabilize amorphous formulations, specifically for molecules that can target proteins previously considered undruggable.
DOI: 10.20392/efb3885c-9833-4b4d-bbfb-af2d6e9c11ed
title: Data and code from: Detecting Age-Related Linguistic Patterns in Dialogue: Toward Adaptive Conversational Systems

description: The github repository contains the code used for the paper, Detecting Age-Related Linguistic Patterns in Dialogue: Toward Adaptive Conversational Systems, by Lennert Jansen, Arabella Sinclair, Margot J. van der Goot, Raquel Fernández, and Sandro Pezzelle.
DOI: 10.25381/cput.30675980
title: Awareness and adoption of agricultural ecommerce applications in Bushbuckridge local municipality, Mpumalanga Province

description: This study focuses on the Awareness and Adoption of Agricultural E-commerce Applications in Bushbuckridge Local Municipality, Mpumalanga Province. The aim is to understand how much smallholder farmers know about agricultural e-commerce platforms and what influences their willingness to adopt them.<br> Data was collected using a structured questionnaire. After gathering the responses, It was coded, cleaned, and entered the data into SPSS (Version 29). Descriptive statistics were used to describe the farmers’ socio-economic characteristics such as age, gender, education level, income, access to the internet, and smartphone ownership. A chi-square test was applied to examine whether farmers’ awareness of e-commerce applications is related to their willingness to adopt them. To identify the key factors influencing adoption, I used a binary logistic regression model, which helped analyse how variables like technology access, user ability, social influence, and extension services affect the likelihood of adoption. Data collection followed all ethical requirements. Participants were informed about the purpose of the research, participation was voluntary, and no identifying personal information was recorded. Ethical and institutional approval for data collection was obtained before conducting the study.
DOI: 10.25381/cput.30675980.v1
title: Awareness and adoption of agricultural ecommerce applications in Bushbuckridge local municipality, Mpumalanga Province

description: This study focuses on the Awareness and Adoption of Agricultural E-commerce Applications in Bushbuckridge Local Municipality, Mpumalanga Province. The aim is to understand how much smallholder farmers know about agricultural e-commerce platforms and what influences their willingness to adopt them.<br> Data was collected using a structured questionnaire. After gathering the responses, It was coded, cleaned, and entered the data into SPSS (Version 29). Descriptive statistics were used to describe the farmers’ socio-economic characteristics such as age, gender, education level, income, access to the internet, and smartphone ownership. A chi-square test was applied to examine whether farmers’ awareness of e-commerce applications is related to their willingness to adopt them. To identify the key factors influencing adoption, I used a binary logistic regression model, which helped analyse how variables like technology access, user ability, social influence, and extension services affect the likelihood of adoption. Data collection followed all ethical requirements. Participants were informed about the purpose of the research, participation was voluntary, and no identifying personal information was recorded. Ethical and institutional approval for data collection was obtained before conducting the study.
DOI: 10.13140/rg.2.2.23333.56803
title: Supplementary_materials.pdf
DOI: 10.15468/dl.2snbyd
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Antarctica",
 "OccurrenceStatus is Present",
 "TaxonKey is Hypogastrura viatica"
 ]
}

 The dataset includes 82 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007448-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11588/duerer.online.692586b5b53ee
title: Dürerhaus, 187225
DOI: 10.15468/dl.pqc9pn
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Antarctica",
 "OccurrenceStatus is Present",
 "TaxonKey is Psychoda albipennis"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007449-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y56ujw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Sweden",
 "OccurrenceStatus is Present",
 "ScientificName is Gulo gulo",
 "TaxonKey is Gulo gulo",
 "Year 1980-2010"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007450-251120083545085/datasets/export for details.
DOI: 10.15468/dl.f798y6
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Antarctica",
 "OccurrenceStatus is Present",
 "TaxonKey is Hypogastrura purpurescens"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007451-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/dans-z5w-dpkm
title: Sporen in Stein
title: Inventariserend Veld Onderzoek van een nederzettingsterrein uit de vroege ijzertijd te Stein (locatie Gavarellestraat-Assevedostraat)

description: &lt;p&gt;In opdracht van Stichting Maaskant Wonen heeft Archeologisch Onderzoek Leiden BV (Archol) een Inventariserend Veld Onderzoek (IVO) in de vorm van proefsleuven uitgevoerd op de locatie Gavarellestraat-Assevedostraat in de gemeente Stein. Aanleiding voor het archeologisch onderzoek is de geplande bouw van woningen binnen het plangebied. De bouwwerkzaamheden zullen leiden tot verstoring en vernietiging van de binnen het plangebied aanwezige archeologische resten.&lt;br&gt;Doel van het onderzoek is vast te stellen welke archeologische waarden in de ondergrond van het geselecteerde terrein aanwezig zijn en wat hun fysieke en inhoudelijke kwaliteit is. De waardering van het terrein dient volgens de richtlijnen van de KNA 3.1 te gebeuren. Dit zodat een gefundeerde onderbouwing van verder beleid met betrekking tot de archeologische waarden binnen het terrein mogelijk is.&lt;br&gt;Onderzoek maakt deel uit van een campagne waarbij tevens een terrein te Elsloo-Aeslerhof wordt onderzocht voor dezelfde opdrachtgever Maaskant Wonen&lt;/p&gt;
description: Date Copyrighted: 2008
description: Date Submitted: 2011-06-10
DOI: 10.15468/dl.dyfpxv
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((94.96626 5.92499,94.29736 4.90197,95.6745 3.80026,97.62217 2.12802,99.23538 -0.40985,102.08803 -4.61996,104.27178 -6.80371,105.8063 -6.23318,107.20312 -2.65262,105.23577 -0.7443,103.99635 0.49512,102.36346 1.28206,100.2584 3.13136,97.18935 5.96433,94.96626 5.92499))",
 "TaxonKey is Bischofia"
 ]
}

 The dataset includes 68 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007452-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pcdy6y
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trimeresurus sichuanensis)",
 "Country is one of (China, India, Indonesia, Pakistan, Bangladesh, Japan, Philippines, Viet Nam, Türkiye, Iran (Islamic Republic of), Thailand, Myanmar, Korea, Republic of, Korea (Democratic People’s Republic of), Iraq, Afghanistan, Saudi Arabia, Uzbekistan, Malaysia, Yemen, Nepal, Sri Lanka, Kazakhstan, Syrian Arab Republic, Cambodia, Jordan, Azerbaijan, United Arab Emirates, Tajikistan, Israel, Lao People’s Democratic Republic, Lebanon, Kyrgyzstan, Turkmenistan, Singapore, Oman, Palestine, State of, Kuwait, Georgia, Mongolia, Armenia, Qatar, Bahrain, Timor-Leste, Cyprus, Bhutan, Maldives, Brunei Darussalam)",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007453-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7jyhx2
title: Occurrence Download

description: A dataset containing 132 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "TaxonKey is Phytophthora cinnamomi"
 ]
}

 The dataset includes 132 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007454-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8vq9pf
title: Occurrence Download

description: A dataset containing 2823 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Testudines"
 ]
}

 The dataset includes 2823 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007455-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h2c9sw
title: Occurrence Download

description: A dataset containing 1306 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((33.55216 -4.28085,39.26279 -4.28085,39.26279 1.60968,33.55216 1.60968,33.55216 -4.28085))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Loxodonta africana",
 "Year 2004-2014"
 ]
}

 The dataset includes 1306 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007456-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25381/cput.30593297
title: Assessing the sustainability, cost-effectiveness, and environmental impact of solar PV panels in the Western Cape, South Africa.

description: The dataset aims to assessing the sustainability, cost -effectiveness, and environmental impact of solar PV panels in the Western Cape, South Africa. As the region turns to renewable energy, it is important to understand the complex implication of solar PV development. I mixed method approach combining quantitate and qualitative stakeholders' interviews in the energy sector was used.
DOI: 10.25381/cput.30593297.v1
title: Assessing the sustainability, cost-effectiveness, and environmental impact of solar PV panels in the Western Cape, South Africa.

description: The dataset aims to assessing the sustainability, cost -effectiveness, and environmental impact of solar PV panels in the Western Cape, South Africa. As the region turns to renewable energy, it is important to understand the complex implication of solar PV development. I mixed method approach combining quantitate and qualitative stakeholders' interviews in the energy sector was used.
DOI: 10.15468/dl.n7jynx
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "TaxonKey is Phytophthora lateralis"
 ]
}

 The dataset includes 64 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007457-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14697703
title: ROBINE-AT: Climatological hazard indicators for a ROBust and INtegrated Energy infrastructure in AusTria

description: The energy sector faces constant challenges due to the anticipated green transition and the underlaying change of climate. To be able to assess potential risks during the transition towards renewable energy sources, we present ROBINE-AT, a high-resolution climatological dataset for Austria, consisting of 41 hazard maps for the Global Warming Levels 1.0 (2001-2020), 2.0, 3.0 and 4.0. The maps cover potential dangers for Austria's energy system due to various impacts, including heat and cold stress, calm and storm days, extreme precipitation and flooding, dry spells as well as lightning strike and wildfire dangers. The data is based on six downscaled and bias-adjusted climate projections of the CMIP5 and CMIP6 generation. With its range of indicators and its fine resolution of 1 km, specifically targeted for regions with complex orography like Austria, ROBINE-AT is a ready-to-apply data set for assessing risks for the energy system by combining the provided hazards with custom exposure and vulnerability.

 

The structure is as follows:



Maps.zip contains one *.tif file per indicator and GWL, representing the actual data.

Tables.zip contains a tabular format for every indicator, where one entry for every of Austria's NUTS3 regions is shown for every GWL. Tables for maximum, minimum and average NUTS3 values are available.

Tables_percentages.zip shows similar tables, but displays the changes of the GWLs in relation to the historical GWL-1.0°C value in %. Regions, in which the historical value is zero, are set to 'nan'.

The file indicator_number_and_unit_dicts.txt includes Python-ready dictionaries, linking the indicator numbers and units to the indicator names, which are also used as file names.

Plots.zip contains one *.png file per indicator, visualising the difference between the values in the historical observations (GWL-1.0°C, 2001-2020) and the other GWLs.


The script used to generate the data is available under https://doi.org/10.5281/zenodo.14973624.

We also recommend complementary datasets originating in the same study: 



Climate Impact Maps:  https://doi.org/10.5281/zenodo.17063332 

Electricity Demand and Supply Profiles: https://doi.org/10.5281/zenodo.15681180 


Funding Information: The project ROBINE is funded by the Climate and Energy Fund (KLI.EN) through the Austrian Research Promotion Agency (FFG) under project number FO999905716, as part of the Energy Research Call 2022 (Energieforschung 2022).
DOI: 10.5281/zenodo.14697702
title: ROBINE-AT: Climatological hazard indicators for a ROBust and INtegrated Energy infrastructure in AusTria

description: The energy sector faces constant challenges due to the anticipated green transition and the underlaying change of climate. To be able to assess potential risks during the transition towards renewable energy sources, we present ROBINE-AT, a high-resolution climatological dataset for Austria, consisting of 41 hazard maps for the Global Warming Levels 1.0 (2001-2020), 2.0, 3.0 and 4.0. The maps cover potential dangers for Austria's energy system due to various impacts, including heat and cold stress, calm and storm days, extreme precipitation and flooding, dry spells as well as lightning strike and wildfire dangers. The data is based on six downscaled and bias-adjusted climate projections of the CMIP5 and CMIP6 generation. With its range of indicators and its fine resolution of 1 km, specifically targeted for regions with complex orography like Austria, ROBINE-AT is a ready-to-apply data set for assessing risks for the energy system by combining the provided hazards with custom exposure and vulnerability.

 

The structure is as follows:



Maps.zip contains one *.tif file per indicator and GWL, representing the actual data.

Tables.zip contains a tabular format for every indicator, where one entry for every of Austria's NUTS3 regions is shown for every GWL. Tables for maximum, minimum and average NUTS3 values are available.

Tables_percentages.zip shows similar tables, but displays the changes of the GWLs in relation to the historical GWL-1.0°C value in %. Regions, in which the historical value is zero, are set to 'nan'.

The file indicator_number_and_unit_dicts.txt includes Python-ready dictionaries, linking the indicator numbers and units to the indicator names, which are also used as file names.

Plots.zip contains one *.png file per indicator, visualising the difference between the values in the historical observations (GWL-1.0°C, 2001-2020) and the other GWLs.


The script used to generate the data is available under https://doi.org/10.5281/zenodo.14973624.

We also recommend complementary datasets originating in the same study: 



Climate Impact Maps:  https://doi.org/10.5281/zenodo.17063332 

Electricity Demand and Supply Profiles: https://doi.org/10.5281/zenodo.15681180 


Funding Information: The project ROBINE is funded by the Climate and Energy Fund (KLI.EN) through the Austrian Research Promotion Agency (FFG) under project number FO999905716, as part of the Energy Research Call 2022 (Energieforschung 2022).
DOI: 10.15468/dl.nr25er
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((45.722460887811714 3.5660957139596867, 45.72538401595877 3.5720419556965433, 45.727096760006766 3.578447363763087, 45.7275330068135 3.5850659456006926, 45.72667565550893 3.5916433959022376, 45.724557325833246 3.5979268628110828, 45.72125915450964 3.6036746776342077, 45.71690771829572 3.6086656722372763, 45.71167019568247 3.612707721470665, 45.70574794919493 3.6156451757911916, 45.699368773855575 3.6173648909230454, 45.69277811171078 3.617800615496376, 45.68622957483224 3.6169355620075248, 45.67997514782695 3.614803058487901, 45.67425545420564 3.6114852548397463, 45.66929046830282 3.6071099355226015, 45.66527103594885 3.6018455657108057, 45.662351533682845 3.595894767884394, 45.66064394961334 3.589486487077477, 45.66021361132287 3.582867153197149, 45.661076720163926 3.5762911860421327, 45.66319977986407 3.570011211673618, 45.66650093359684 3.564268367077245, 45.670853150559644 3.5592830637156414, 45.67608913339907 3.5552465602985537, 45.6820077540062 3.552313662068772, 45.68838176936584 3.5505968196783706, 45.69496652299205 3.5501618471480914, 45.70150930233202 3.551025417489785, 45.70775899931223 3.5531544284678866, 45.71347571052556 3.5564672618882116, 45.71843991568181 3.560836889963605, 45.722460887811714 3.5660957139596867))",
 "Year is one of (2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025)",
 "KingdomKey is one of (Animalia, Fungi, Plantae)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007459-251120083545085/datasets/export for details.
DOI: 10.15468/dl.6xrsas
title: Occurrence Download

description: A dataset containing 28789 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "TaxonKey is Cryphonectria parasitica"
 ]
}

 The dataset includes 28789 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007460-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.16779.96803
title: DATASET
DOI: 10.15468/dl.p3kegw
title: Occurrence Download

description: A dataset containing 782 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trimeresurus stejnegeri)",
 "Country is one of (China, India, Indonesia, Pakistan, Bangladesh, Japan, Philippines, Viet Nam, Türkiye, Iran (Islamic Republic of), Thailand, Myanmar, Korea, Republic of, Korea (Democratic People’s Republic of), Iraq, Afghanistan, Saudi Arabia, Uzbekistan, Malaysia, Yemen, Nepal, Sri Lanka, Kazakhstan, Syrian Arab Republic, Cambodia, Jordan, Azerbaijan, United Arab Emirates, Tajikistan, Israel, Lao People’s Democratic Republic, Lebanon, Kyrgyzstan, Turkmenistan, Singapore, Oman, Palestine, State of, Kuwait, Georgia, Mongolia, Armenia, Qatar, Bahrain, Timor-Leste, Cyprus, Bhutan, Maldives, Brunei Darussalam)",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 782 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007461-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.