cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29447744
title: LC-MS/MS analysis of red and green Türkiye propolis and determination of correlations between certain phenolic compounds

description: The honey bees (<i>Apis mellifera</i>) collect propolis from the resins of the plants around the hives for various purposes. The chemical structure of propolis contains many active ingredients, including phenolic compounds. Plants, altitude, season, or climatic zone are the most important factors influencing these components. The active ingredients in propolis influence the color of the propolis as well as the composition of the propolis. The aim of this study was to investigate and compare the content of 28 phenolic compounds of red and green propolis collected from Türkiye utilizing LC-MS/MS analysis. For this purpose, 318 propolis samples were collected from apiaries. Twenty-nine red and green samples were separated and analyzed for phenolic compounds. It was found that the seasons significantly affected the color changes of propolis. While most of the red propolis was detected in the spring, most of the green propolis was detected in the autumn. Furthermore, it was determined that the color changes of propolis produced statistically significant differences in terms of phenolic components, even in the colors within themselves. In addition, the availability and amount of phenolic compounds in propolis were found to have statistically significant negative and positive relationships among themselves. In conclusion, it was noticed that the change in color of propolis can significantly alter its phenolic composition, which can affect its average chemical structure.
DOI: 10.6084/m9.figshare.29447744.v1
title: LC-MS/MS analysis of red and green Türkiye propolis and determination of correlations between certain phenolic compounds

description: The honey bees (<i>Apis mellifera</i>) collect propolis from the resins of the plants around the hives for various purposes. The chemical structure of propolis contains many active ingredients, including phenolic compounds. Plants, altitude, season, or climatic zone are the most important factors influencing these components. The active ingredients in propolis influence the color of the propolis as well as the composition of the propolis. The aim of this study was to investigate and compare the content of 28 phenolic compounds of red and green propolis collected from Türkiye utilizing LC-MS/MS analysis. For this purpose, 318 propolis samples were collected from apiaries. Twenty-nine red and green samples were separated and analyzed for phenolic compounds. It was found that the seasons significantly affected the color changes of propolis. While most of the red propolis was detected in the spring, most of the green propolis was detected in the autumn. Furthermore, it was determined that the color changes of propolis produced statistically significant differences in terms of phenolic components, even in the colors within themselves. In addition, the availability and amount of phenolic compounds in propolis were found to have statistically significant negative and positive relationships among themselves. In conclusion, it was noticed that the change in color of propolis can significantly alter its phenolic composition, which can affect its average chemical structure.
DOI: 10.15468/dl.uyqhca
title: Occurrence Download

description: A dataset containing 5024 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quelea erythrops)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 5024 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025588-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h6mq2y
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Etheostoma barrenense)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 96 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025592-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ww3hvwpw6p
title: Emission Intensity and CCTS

description: Emission Intensity and CCTS
DOI: 10.17632/ww3hvwpw6p.1
title: Emission Intensity and CCTS

description: Emission Intensity and CCTS
DOI: 10.5281/zenodo.16761901
title: Lower Fungom Koshin 225 Wordlist

description: Koshin is a variety of the Yemne-Kimbi language group (Good et al 2011) spoken in Lower Fungom in Fungom Subdivision in Menchum Division of the North West Region of Cameroon. The langauge is tonal and has nominal prefixes. In the wordlist, we observed individual lexical variation among the two consultants from whom the data was collected. The variation could be accounted for by the differences noticed in sociolinguistic profile of both consultants.
DOI: 10.17632/7p2h8pktdk
title: Dysfunction in primate dorsolateral prefrontal area 46 impacts motivation and anxiety

description: Experimental data and resting state fMRI analysis code for manuscript titled: 'Dysfunction in primate dorsolateral prefrontal area 46 impacts motivation and anxiety'
DOI: 10.17632/7p2h8pktdk.1
title: Dysfunction in primate dorsolateral prefrontal area 46 impacts motivation and anxiety

description: Experimental data and resting state fMRI analysis code for manuscript titled: 'Dysfunction in primate dorsolateral prefrontal area 46 impacts motivation and anxiety'
DOI: 10.17632/gnnnpxzhkh
title: A comparative study between the datasets of AlphaFold 3 generated 3D structures of Leishmania and Trypanosoma AMPKα, the catalytic subunit

description: Leishmania is a human protozoan parasite that causes leishmaniasis in tropical and sub-tropical regions. It displays a complex life cycle, alternating between sandfly vectors and mammalian hosts, where it encounters diverse environmental and metabolic stresses. AMP-activated protein kinase (AMPK) is an evolutionarily conserved serine/threonine kinase that regulates energy homeostasis and cellular metabolism in eukaryotes by sensing nutrient and oxygen supply in the ambience. AMPK has been shown to be involved in nutrient sensing, stress response and proliferation in Trypanosoma. Leishmania and Trypanosoma, both belong to the family Trypanosomatidae are evolutionary closely related. However, it was poorly characterized in Leishmania. AMPK is a heterotrimeric complex consisting of one catalytic α subunit and two regulatory subunits (β and γ). We identified and annotated clinically relevant orthologous Leishmania AMPK (LAMPK) protein subunit sequences from TritrypDB. Furthermore, since there were no tertiary structures available in database, we have generated these structures of Leishmania and Trypanosoma AMPKα using AlphaFold3. Determination of important parameters such as pLDDT, pTM scores indicate ‘true’ structures. Sequence and structure analyses revealed similarities and differences between Leishmania and Trypnosoma AMPKα proteins.
DOI: 10.17632/gnnnpxzhkh.1
title: A comparative study between the datasets of AlphaFold 3 generated 3D structures of Leishmania and Trypanosoma AMPKα, the catalytic subunit

description: Leishmania is a human protozoan parasite that causes leishmaniasis in tropical and sub-tropical regions. It displays a complex life cycle, alternating between sandfly vectors and mammalian hosts, where it encounters diverse environmental and metabolic stresses. AMP-activated protein kinase (AMPK) is an evolutionarily conserved serine/threonine kinase that regulates energy homeostasis and cellular metabolism in eukaryotes by sensing nutrient and oxygen supply in the ambience. AMPK has been shown to be involved in nutrient sensing, stress response and proliferation in Trypanosoma. Leishmania and Trypanosoma, both belong to the family Trypanosomatidae are evolutionary closely related. However, it was poorly characterized in Leishmania. AMPK is a heterotrimeric complex consisting of one catalytic α subunit and two regulatory subunits (β and γ). We identified and annotated clinically relevant orthologous Leishmania AMPK (LAMPK) protein subunit sequences from TritrypDB. Furthermore, since there were no tertiary structures available in database, we have generated these structures of Leishmania and Trypanosoma AMPKα using AlphaFold3. Determination of important parameters such as pLDDT, pTM scores indicate ‘true’ structures. Sequence and structure analyses revealed similarities and differences between Leishmania and Trypnosoma AMPKα proteins.
DOI: 10.17632/ghvk5jtj5c
title: Dataset of knowledge and attitudes towards pain management among critical care nurse in Sabah

description: This dataset describes critical care nurses’ knowledge and attitude towards pain management in the intensive care unit of a public hospital in the West Coast division of Sabah, Malaysia. Data were collected using a structured questionnaire known as the Knowledge and Attitudes Survey Regarding Pain (KASRP), administered online to 126 critical care nurses. This dataset includes the raw data, the codebook, and the KASRP questionnaire used in the survey.
DOI: 10.17632/ghvk5jtj5c.1
title: Dataset of knowledge and attitudes towards pain management among critical care nurse in Sabah

description: This dataset describes critical care nurses’ knowledge and attitude towards pain management in the intensive care unit of a public hospital in the West Coast division of Sabah, Malaysia. Data were collected using a structured questionnaire known as the Knowledge and Attitudes Survey Regarding Pain (KASRP), administered online to 126 critical care nurses. This dataset includes the raw data, the codebook, and the KASRP questionnaire used in the survey.
DOI: 10.17632/mwndsm6p2h
title: Evaluating Provincial Disparities in Türkiye Using the Urban Health Index: A Call for Equity Based Health Policies

description: The dataset facilitated the calculation of the Urban Health Index (UHI) for all 81 provinces of Türkiye, utilizing indicators related to health, environment, economy, geography, and sociodemographics. The dataset comprises raw values, standardized scores, and UHI calculations in accordance with WHO methodology. The dataset corroborates the findings presented in the article "Evaluating Provincial Disparities in Türkiye Using the Urban Health Index: A Call for Equity-Based Health Policies."
DOI: 10.17632/mwndsm6p2h.1
title: Evaluating Provincial Disparities in Türkiye Using the Urban Health Index: A Call for Equity Based Health Policies

description: The dataset facilitated the calculation of the Urban Health Index (UHI) for all 81 provinces of Türkiye, utilizing indicators related to health, environment, economy, geography, and sociodemographics. The dataset comprises raw values, standardized scores, and UHI calculations in accordance with WHO methodology. The dataset corroborates the findings presented in the article "Evaluating Provincial Disparities in Türkiye Using the Urban Health Index: A Call for Equity-Based Health Policies."
DOI: 10.15468/dl.a9avnf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phyllomedusa vaillantii)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025595-250802193616735/datasets/export for details.
DOI: 10.15468/dl.nxs9yg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phyllomedusa vaillantii)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025594-250802193616735/datasets/export for details.
DOI: 10.15468/dl.rpbvvp
title: Occurrence Download

description: A dataset containing 699 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phyllomedusa vaillantii)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 699 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025596-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2cd6zj4jtv
title: Serum Neurofilament Light Niemann-Pick disease type C1

description: Serum Neurofilament light levels in control and NPC1 patients
DOI: 10.15468/dl.4epna9
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bryconamericus leptorhynchus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025598-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2cd6zj4jtv.1
title: Serum Neurofilament Light Niemann-Pick disease type C1

description: Serum Neurofilament light levels in control and NPC1 patients
DOI: 10.5281/zenodo.16762283
title: Appendix D of 20 years of disk winds in 4U 1630−47 - I. Long-term behavior and influence of hard X-rays

description: Supplementary material for the paper, including the full tables of the dataset analyzed in this work.
DOI: 10.5281/zenodo.16762284
title: Appendix D of 20 years of disk winds in 4U 1630−47 - I. Long-term behavior and influence of hard X-rays

description: Supplementary material for the paper, including the full tables of the dataset analyzed in this work.
DOI: 10.17632/2ngm848wyh.2
title: Productivity Spillover Effects of Participation in Global Value Chains and FDI Inflows

description: Replication file for Sung Hyun Son and Young-Han Kim (2025). Productivity Spillover Effects of Participation in Global Value Chains and FDI Inflows Economic Modelling
DOI: 10.17632/5d4vh4bnv3.3
title: Implementação de estratégias para reduzir o risco de transmissão da COVID-19 em um hospital psiquiátrico e avaliação dos casos confirmados no período de 2020 a 2023

description: Implementação de estratégias para reduzir o risco de transmissão da COVID-19 em um hospital psiquiátrico e avaliação dos casos confirmados no período de 2020 a 2022
DOI: 10.17632/dbntnzn77h.1
title: Westerlies and Monsoon Climate Systems Shape Holocene Moisture Patterns in the Southern Tibetan Plateau: Evidence from Aeolian Sedimentary Records

description: This dataset includes environmental magnetic, geochemical, and sediment color data from a new, well-dated aeolian section (ZD20) in the southern Tibetan Plateau, and also contains geochemical data from original and carbonate-free samples of another aeolian section (HZ) in the this region. Finally, it provides information on projected future variations in the winter mid-latitude Westerlies and the Indian summer monsoon under two emission scenarios.
DOI: 10.15468/dl.833t6p
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phyllomedusa vaillantii)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025599-250802193616735/datasets/export for details.
DOI: 10.17632/vbwgnh8d3g
title: GasEmissions

description: This file contains data of 9 input features used to train all the machine learning models.
DOI: 10.15468/dl.n63vdd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phyllomedusa vaillantii)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025600-250802193616735/datasets/export for details.
DOI: 10.17632/vbwgnh8d3g.1
title: GasEmissions

description: This file contains data of 9 input features used to train all the machine learning models.
DOI: 10.15468/dl.rsmwpr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phyllomedusa vaillantii)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025601-250802193616735/datasets/export for details.
DOI: 10.17632/6k9s86485g
title: Calcium Isotope Fractionation in Plagioclase from Mafic-Ultramafic Rocks: Implications for Magmatic Processes and Planetary Differentiation

description: Here are a total of 10 tables. Table 1 shows the whole-rock major element compositions of the Panzhihua and Xiaohaizi intrusions; Table 2 presents the calcium isotope compositions of the whole-rock, clinopyroxene, and plagioclase in the two intrusions; Table 3 is the comparison between the calculated calcium isotopic composition of whole rocks and the measured calcium isotopic composition of whole rocks. Table 4 lists the Δ44/40CaPl-cpx values of samples in the two intrusions; Table 5 is the plagioclase-melt calcium fractionation coefficient table estimated at 1000K; Table S1 shows the trace element data of clinopyroxene and plagioclase in the two intrusions; and Tables S2 to S5 respectively present the major element compositions of clinopyroxene and plagioclase in the Panzhihua and Xiaohaizi intrusions.
DOI: 10.17632/6k9s86485g.1
title: Calcium Isotope Fractionation in Plagioclase from Mafic-Ultramafic Rocks: Implications for Magmatic Processes and Planetary Differentiation

description: Here are a total of 10 tables. Table 1 shows the whole-rock major element compositions of the Panzhihua and Xiaohaizi intrusions; Table 2 presents the calcium isotope compositions of the whole-rock, clinopyroxene, and plagioclase in the two intrusions; Table 3 is the comparison between the calculated calcium isotopic composition of whole rocks and the measured calcium isotopic composition of whole rocks. Table 4 lists the Δ44/40CaPl-cpx values of samples in the two intrusions; Table 5 is the plagioclase-melt calcium fractionation coefficient table estimated at 1000K; Table S1 shows the trace element data of clinopyroxene and plagioclase in the two intrusions; and Tables S2 to S5 respectively present the major element compositions of clinopyroxene and plagioclase in the Panzhihua and Xiaohaizi intrusions.
DOI: 10.17632/7txhzhm2xz
title: hermal Imaging Flame Dataset for Internal Non-Ignition Explosion Containment Tests in Coal Mine Explosion-Proof Equipment

description: This is the original dataset for the paper:
​​"Detecting Detonation-Induced Damage in Mining Explosion-Proof Equipment via Thermal Imaging Flame Spatiotemporal Feature Fusion and an Improved LSTM Model"​
DOI: 10.17632/7txhzhm2xz.2
title: hermal Imaging Flame Dataset for Internal Non-Ignition Explosion Containment Tests in Coal Mine Explosion-Proof Equipment

description: This is the original dataset for the paper:
​​"Detecting Detonation-Induced Damage in Mining Explosion-Proof Equipment via Thermal Imaging Flame Spatiotemporal Feature Fusion and an Improved LSTM Model"​