cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rcpsmd7dth.1
title: Propriedades sensoras de nanocompósitos à base de rGO-ZnO com diferentes morfologias para detecção de O3

description: Esse estudo visa analisar as propriedades sensoras de nanocompósitos à base de rGO-ZnO com diferentes morfologias para detecção de gás ozônio. Na primeira etapa do projeto, as amostras de ZnO e de rGO foram caracterizadas estrutural e morfologicamente. Para avaliar comparativamente as propriedades sensoras do compósito de rGO-ZnO, foram analisadas primeiramente as medidas de gás obtidas pelos sensores de ZnO nas duas morfologias estudadas: agulhas e donuts.
DOI: 10.17632/6sxb6x2dmt.1
title: Trust in Bureaucracy , Expectation and Intention to Work as Government Employee in Indonesia

description: This study aims to investigate the relationship between expectation and intention to work as a government employee among Public Administration students at Sriwijaya University. The study also explores the potential moderating effect of trust in bureaucracy on this relationship. Data were collected from 238 Public Administration students.
DOI: 10.17632/zbkxr687sx.1
title: COVID-19 Subvariant XBB.1.5  scrapped from Twitter 

description: The data present COVID-19 Subvariant XBB.1.5 data extracted using the Twitter application program interface (API).
DOI: 10.17632/bs9wdkj6fy.1
title: AVs_minority

description: the data contains two experiments
DOI: 10.17632/xf8vj4ff34.1
title: Digital transformation and FDI

description: This data is a combination of variables that define the extent of digitalisation and its effect on foreign direct investment.
DOI: 10.5281/zenodo.7706667
title: IODP Expedition 385 Whole-round core section images

description: Images of the outside of hard rock whole-round sections were acquired using a linescan imager (Section Half Imaging Logger [SHIL]) and a special holder that allows each 90 degree segment of the outer surface to be positioned properly. The images were taken at a resolution of 20 lines/mm (50 micropixels). JRSO staff take these quadrant images and compile them into a side-by-side rollout photograph of the section. Composite images are available as both JPG and TIF image formats. Individual quadrant images are available as JPG images only through this report; contact the IODP-JRSO Data Librarian if quadrant TIF files (~160 MB) are needed.
DOI: 10.5281/zenodo.7706666
title: IODP Expedition 385 Whole-round core section images

description: Images of the outside of hard rock whole-round sections were acquired using a linescan imager (Section Half Imaging Logger [SHIL]) and a special holder that allows each 90 degree segment of the outer surface to be positioned properly. The images were taken at a resolution of 20 lines/mm (50 micropixels). JRSO staff take these quadrant images and compile them into a side-by-side rollout photograph of the section. Composite images are available as both JPG and TIF image formats. Individual quadrant images are available as JPG images only through this report; contact the IODP-JRSO Data Librarian if quadrant TIF files (~160 MB) are needed.
DOI: 10.5281/zenodo.7371701
title: Optimal Catastrophe Risk Pooling

description: This repository contains the code to reproduce the analysis in the paper: "Increasing countries’ financial resilience through global catastrophe risk pooling" from Ciullo et al..
DOI: 10.5281/zenodo.7371702
title: Optimal Catastrophe Risk Pooling

description: This repository contains the code to reproduce the analysis in the paper: "Increasing countries’ financial resilience through global catastrophe risk pooling" from Ciullo et al..
DOI: 10.5281/zenodo.7371742
title: Optimal Catastrophe Risk Pooling

description: This repository contains the code to reproduce the analysis in the paper: "Increasing countries’ financial resilience through global catastrophe risk pooling" from Ciullo et al..
DOI: 10.5281/zenodo.7713080
title: Optimal Catastrophe Risk Pooling

description: This repository contains the code to reproduce the analysis in the paper: "Increasing countries’ financial resilience through global catastrophe risk pooling" from Ciullo et al..
DOI: 10.5281/zenodo.7713087
title: Optimal Catastrophe Risk Pooling

description: This repository contains the code to reproduce the analysis in the paper: "Increasing countries’ financial resilience through global catastrophe risk pooling" from Ciullo et al..
DOI: 10.6084/m9.figshare.22242253
title: 2025-2060中国年龄结构预测结果（省级） 2025-2060 China Age Structure Projection Results (Provincial)

description: 此数据集为2025-2060中国省级年龄结构预测结果，格式为xlsx。 This dataset is the results of the 2025-2060 China provincial age structure projections in xlsx format. <br> 当目前人类活动已经成为全球环境变化的主要驱动力。作为世界上人口最多的国家，中国应当在世界的可持续发展与气候变化领域做出更多的贡献。2020年9月22日，国家主席习近平提出了中国的“双碳发展目标”，为中国未来的发展指明了方向。城市是人类生产生活最为集中的区域，中国的城市能源消耗占据了全国能源消耗的85%，因此我们认为中国的低碳转型关键在于城市。进一步，城市的发展关键在于人口的变化，不同年龄结构，不同社会背景的人有着不同的城市管理服务与能源利用的需求，进而影响着未来的城市管理和城市建设。中国正处于城镇化的下半场，在人口老龄化背景下不同区域的人口结构将发生重大变化，如何对未来的人口结构进行判定，进而对未来的社会需求做出判断，以实现未来中国的低碳发展，是非常值得探索的议题。在这样的背景下，能源基金会资助清华大学建筑学院龙瀛团队与中国人民大学环境学院王克团队，针对上述问题开展深入分析。在前期项目中，龙瀛团队基于全球空间人口网格数据和中国政府统计数据，对中国的未来人口分布进行了情景预测。但是人口分布的预测，缺乏人口结构的相关信息，因此不能更精确更量化地判断不同人的需求。 因此在本项目中，项目组希望进一步地完善人口结构方面的预测，同现有人口分布数据相匹配，进而为碳排放、环境治理等研究方向提供更精确更细致的数据支持。 Human activities have now become a major driver of global environmental change. As the world's most populous country, China should make more contributions to the world's sustainable development and climate change. On September 22, 2020, President Xi Jinping proposed China's "Two Carbon Development Goals", which will set the direction for China's future development. Cities are the most concentrated areas of human production and life, so we believe that the key to China's low-carbon transition lies in cities. Further, cities are for people, so human needs determine the energy consumption of the city. People of different age structures and social backgrounds have different needs for urban management services and energy use, which in turn affects future urban management and urban construction. It is worthwhile to explore how to determine the future demographic structure and then make a judgment on the future social needs to realize the future low-carbon development of China. <br>
DOI: 10.17632/9rhgdh3cdn.1
title: Mental health and associated risk factors of Puerto Rico Post-Hurricane María

description: Background: Mental health disorders have an increased prevalence in communities that experienced devastating natural disasters. Maria, a category 5 hurricane, struck Puerto Rico on September 20, 2017, weakening the island’s power grid, destroying buildings and homes, and limiting access to water, food, and health care services. This study characterized sociodemographic and behavioral variables and their association with mental health outcomes in the aftermath of Hurricane Maria.  
Methods: A sample of 998 Puerto Ricans affected by Hurricane Maria was surveyed between December 2017 and September 2018.   Participants completed a 5-tool questionnaire: Post Hurricane Distress Scale, Kessler K6, Patient Health Questionnaire 9, Generalized Anxiety Disorder (GAD) 7, and Post Traumatic Stress Disorder checklist for DSM-V. The associations of sociodemographic variables and risk factors with mental health disorder risk outcomes were analyzed using logistic regression analysis. 
Results: Most respondents reported experiencing hurricane-related stressors. Urban respondents reported a higher incidence of exposure to stressors when compared to rural respondents. Low income (OR=3.66; 95% CI=1.34-11.400; p<0.05) and level of education (OR=4.38; 95% CI=1.20-15.800; p<0.05) were associated with increased risk for severe mental illness (SMI), while being employed was correlated with lower risk for GAD (OR=0.48; 95% CI=0.275-0.811; p<0.01) and lower risk for SIM (OR=0.68; 95% CI=0.483-0.952; p<0.05). Abuse of prescribed narcotics was associated with an increased risk for depression (OR=2.94; 95% CI=1.101-7.721; p<0.05), while illicit drug use was associated with increased risk for GAD (OR=6.56; 95% CI=1.414-39.54; p<0.05). 
Conclusion: Findings underline the necessity for implementing a post-natural disaster response plan to address mental health with community-based social interventions.
DOI: 10.25573/data.22096553
title: Supplemental Data for "Gene expression reveals immune response strategies of naïve Hawaiian honeycreepers experimentally infected with introduced avian malaria"

description: Supplemental tables and figures for "Gene expression reveals immune response strategies of naïve Hawaiian honeycreepers experimentally infected with introduced avian malaria"
DOI: 10.25573/data.22096553.v1
title: Supplemental Data for "Gene expression reveals immune response strategies of naïve Hawaiian honeycreepers experimentally infected with introduced avian malaria"

description: Supplemental tables and figures for "Gene expression reveals immune response strategies of naïve Hawaiian honeycreepers experimentally infected with introduced avian malaria"
DOI: 10.6084/m9.figshare.22242262
title: 2025-2060中国收入结构预测结果（省级） 2025-2060 China Income Structure projection results (Provincial)

description: 此数据集为2025-2060中国省级收入结构预测结果，格式为xlsx。 This dataset is the results of the 2025-2060 China provincial income structure projections in xlsx format. <br> 当目前人类活动已经成为全球环境变化的主要驱动力。作为世界上人口最多的国家，中国应当在世界的可持续发展与气候变化领域做出更多的贡献。2020年9月22日，国家主席习近平提出了中国的“双碳发展目标”，为中国未来的发展指明了方向。城市是人类生产生活最为集中的区域，中国的城市能源消耗占据了全国能源消耗的85%，因此我们认为中国的低碳转型关键在于城市。进一步，城市的发展关键在于人口的变化，不同年龄结构，不同社会背景的人有着不同的城市管理服务与能源利用的需求，进而影响着未来的城市管理和城市建设。中国正处于城镇化的下半场，在人口老龄化背景下不同区域的人口结构将发生重大变化，如何对未来的人口结构进行判定，进而对未来的社会需求做出判断，以实现未来中国的低碳发展，是非常值得探索的议题。在这样的背景下，能源基金会资助清华大学建筑学院龙瀛团队与中国人民大学环境学院王克团队，针对上述问题开展深入分析。在前期项目中，龙瀛团队基于全球空间人口网格数据和中国政府统计数据，对中国的未来人口分布进行了情景预测。但是人口分布的预测，缺乏人口结构的相关信息，因此不能更精确更量化地判断不同人的需求。 因此在本项目中，项目组希望进一步地完善人口结构方面的预测，同现有人口分布数据相匹配，进而为碳排放、环境治理等研究方向提供更精确更细致的数据支持。 Human activities have now become a major driver of global environmental change. As the world's most populous country, China should make more contributions to the world's sustainable development and climate change. On September 22, 2020, President Xi Jinping proposed China's "Two Carbon Development Goals", which will set the direction for China's future development. Cities are the most concentrated areas of human production and life, so we believe that the key to China's low-carbon transition lies in cities. Further, cities are for people, so human needs determine the energy consumption of the city. People of different age structures and social backgrounds have different needs for urban management services and energy use, which in turn affects future urban management and urban construction. It is worthwhile to explore how to determine the future demographic structure and then make a judgment on the future social needs to realize the future low-carbon development of China. <br>
DOI: 10.6084/m9.figshare.22242262.v1
title: 2025-2060中国收入结构预测结果（省级） 2025-2060 China Income Structure projection results (provincial)

description: 此数据集为2025-2060中国省级收入结构预测结果，格式为xlsx。 This dataset is the results of the 2025-2060 China provincial income structure projections in xlsx format. <br> 当目前人类活动已经成为全球环境变化的主要驱动力。作为世界上人口最多的国家，中国应当在世界的可持续发展与气候变化领域做出更多的贡献。2020年9月22日，国家主席习近平提出了中国的“双碳发展目标”，为中国未来的发展指明了方向。城市是人类生产生活最为集中的区域，中国的城市能源消耗占据了全国能源消耗的85%，因此我们认为中国的低碳转型关键在于城市。进一步，城市的发展关键在于人口的变化，不同年龄结构，不同社会背景的人有着不同的城市管理服务与能源利用的需求，进而影响着未来的城市管理和城市建设。中国正处于城镇化的下半场，在人口老龄化背景下不同区域的人口结构将发生重大变化，如何对未来的人口结构进行判定，进而对未来的社会需求做出判断，以实现未来中国的低碳发展，是非常值得探索的议题。在这样的背景下，能源基金会资助清华大学建筑学院龙瀛团队与中国人民大学环境学院王克团队，针对上述问题开展深入分析。在前期项目中，龙瀛团队基于全球空间人口网格数据和中国政府统计数据，对中国的未来人口分布进行了情景预测。但是人口分布的预测，缺乏人口结构的相关信息，因此不能更精确更量化地判断不同人的需求。 因此在本项目中，项目组希望进一步地完善人口结构方面的预测，同现有人口分布数据相匹配，进而为碳排放、环境治理等研究方向提供更精确更细致的数据支持。 Human activities have now become a major driver of global environmental change. As the world's most populous country, China should make more contributions to the world's sustainable development and climate change. On September 22, 2020, President Xi Jinping proposed China's "Two Carbon Development Goals", which will set the direction for China's future development. Cities are the most concentrated areas of human production and life, so we believe that the key to China's low-carbon transition lies in cities. Further, cities are for people, so human needs determine the energy consumption of the city. People of different age structures and social backgrounds have different needs for urban management services and energy use, which in turn affects future urban management and urban construction. It is worthwhile to explore how to determine the future demographic structure and then make a judgment on the future social needs to realize the future low-carbon development of China. <br>
DOI: 10.5281/zenodo.7705638
title: IODP Expedition 385 Section-half images

description: Digital section images were taken of the flat face of split cores on the Section Half Imaging Logger (SHIL) using a linescan camera at a resolution of 20 lines/mm (50 micron pixels). Cores were imaged as soon as possible after splitting to minimize color changes that occur through oxidation and drying. The SHIL produces TIF files as well as reduced-size JPG files. The TIF files are not kept online but users may request them from the IODP-JRSO Data Librarian.
DOI: 10.5281/zenodo.7705637
title: IODP Expedition 385 Section-half images

description: Digital section images were taken of the flat face of split cores on the Section Half Imaging Logger (SHIL) using a linescan camera at a resolution of 20 lines/mm (50 micron pixels). Cores were imaged as soon as possible after splitting to minimize color changes that occur through oxidation and drying. The SHIL produces TIF files as well as reduced-size JPG files. The TIF files are not kept online but users may request them from the IODP-JRSO Data Librarian.
DOI: 10.6084/m9.figshare.22242022
title: Porridge development

description: Porridge development recipe, based on nutritional need and the analysis of raw material performed at Aberty Univesity
DOI: 10.6084/m9.figshare.22242022.v1
title: Porridge development

description: Porridge development recipe, based on nutritional need and the analysis of raw material performed at Aberty Univesity
DOI: 10.6084/m9.figshare.21094264.v1
title: CMIP6 spring onset data for Li et al. (2023): "Diverging Northern Hemisphere Trends in Meteorological Versus Ecological Indicators of Spring Onset in CMIP6"

description: This dataset contains the day of year (DOY) data of the extended spring indices (SI-x leaf) and LAI 25% threshold (LAI25%) used in the analysis presented in Li et al. "Diverging Northern Hemisphere Trends in Meteorological Versus Ecological Indicators of Spring Onset in CMIP6" (previously titled "Growing uncertainty in projected spring onset variability in the Northern Hemisphere"). The paper has been accepted by Geophysical Research Letters (doi: 10.1029/2023GL102833). The CMIP6 model outputs (maximum and minimum daily temperature, tasmax and tasmin, and leaf area index, lai) used to calculate these spring onset indicators are publicly available through the Earth System Grid Federation (ESGF): https://esgf-node.llnl.gov/projects/cmip6/.
DOI: 10.17632/jjn4ht687d.1
title: JMuBEN 3

description: JMuBEN 3 Contains a file of sweet potato datasets affected by rust. The images were collected in Kakamega County-Kenya, using a digital camera and with the help of plant pathologist for easy disease identification. Dataset contains 2003 images affected by leaf spot compressed in one folder. JMuBEN 3 also contains code for a model that was adopted for sweet potato leaf spot detection. The model can also be used for other plant leaf diseases classification.
DOI: 10.17632/jjn4ht687d.2
title: JMuBEN 3

description: JMuBEN 3 Contains a file of sweet potato datasets affected by rust. The images were collected in Kakamega County-Kenya, using a digital camera and with the help of plant pathologist for easy disease identification. Dataset contains 2003 images affected by leaf spot compressed in one folder. JMuBEN 3 also contains code for a model that was adopted for sweet potato leaf spot detection. The model can also be used for other plant leaf diseases classification.
DOI: 10.17632/jjn4ht687d.3
title: JMuBEN 3

description: JMuBEN 3 Contains  a file of sweet potato datasets affected by rust. The images were collected in Kakamega County-Kenya, using a digital camera and with the help of plant pathologist for easy disease identification. Dataset contains 1383 images affected by leaf rust compressed in one folder. JMuBEN 3 also contains code for a model that was adopted for sweet potato leaf rust detection. The model can also be used for other plant leaf diseases classification.
DOI: 10.17632/jjn4ht687d.4
title: JMuBEN 3

description: JMuBEN 3 Contains  a file of sweet potato datasets affected by rust. The images were collected in Kakamega County-Kenya, using a digital camera and with the help of plant pathologist for easy disease identification. Dataset contains 1383 images affected by leaf rust compressed in one folder. JMuBEN 3 also contains code for a model that was adopted for sweet potato leaf rust detection. The model can also be used for other plant leaf diseases classification.
DOI: 10.5255/ukda-sn-856210
title: Data From the Development and Acceptability Testing of the Carers-ID Online Support Programme, 2021-2022

description: In order explore the experiences of family carers of people with profound and multiple learning disabilities and voluntary sector organisations during the COVID-19 pandemic, we conducted 38 focus groups – 6 voluntary sector and 32 carer (data includes 38 transcripts). There were a total of 24 participants in the voluntary sector focus groups and 126 in the carer focus groups. Participants were from Northern Ireland, Ireland, Scotland, England and Wales. Based on these findings and with the help of the co-design group, we developed the Carers-ID online support programme. To test the acceptability of the programme among family carers we conducted an online survey which was distributed to family carers. We received 70 responses to our survey (data includes SPSS data file), of which 10 participants conducted follow up interviews (data includes 10 transcripts).
DOI: 10.6084/m9.figshare.19694872.v1
title: Datasets of survival, growth and water status responses to soil water availability and atmospheric drought of two year old seedlings of Picea glauca (Moench) Voss, Picea mariana (Mill.) B.S.P and Pinus strobus L.

description: This dataset covers the clean data (and their metadata) of the following article: Urli M., Périé C., Thiffault N., Coyea M. R., Pepin S., Logan T. and Munson A. D. (submitted) High drought-induced mortality of major conifer species in northern temperate forests under future climates. <br> <br>
DOI: 10.5281/zenodo.7705345
title: IODP Expedition 385 Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.5281/zenodo.7705344
title: IODP Expedition 385 Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.5281/zenodo.7713096
title: The use of digital technologies among older adults during the COVID-19 Pandemic: A descriptive study in Turkey

description: Data set from the article "The use of digital technologies among older adults during the COVID-19 Pandemic: A descriptive study in Turkey"
DOI: 10.5281/zenodo.7713095
title: The use of digital technologies among older adults during the COVID-19 Pandemic: A descriptive study in Turkey

description: Data set from the article "The use of digital technologies among older adults during the COVID-19 Pandemic: A descriptive study in Turkey"
DOI: 10.5281/zenodo.7704367
title: 2021 VPHi clinical community survey

description: 2021 VPHi clinical community survey questionnaire and data in csv file format.
DOI: 10.5281/zenodo.7704366
title: 2021 VPHi clinical community survey

description: 2021 VPHi clinical community survey questionnaire and data in csv file format.
DOI: 10.5281/zenodo.7613121
title: Dataset Digital Competence

description: The dataset contains data on demographics (gender, age), education (type of study program, enrolled year, affiliation of studies to a scientific field, daily use of computer) and data on the self-assessed level of digital competence of the respondents.
DOI: 10.5281/zenodo.7613122
title: Dataset Digital Competence

description: The dataset contains data on demographics (gender, age), education (type of study program, enrolled year, affiliation of studies to a scientific field, daily use of computer) and data on the self-assessed level of digital competence of the respondents.
DOI: 10.5281/zenodo.7713130
title: Dataset Digital Competence

description: The dataset contains data on demographics (gender, age), education (type of study program, enrolled year, affiliation of studies to a scientific field, daily use of computer) and data on the self-assessed level of digital competence of the respondents.
DOI: 10.5281/zenodo.7702229
title: Correcting for probe wandering by precession path segmentation

description: Scanning precession electron diffraction datasets and processing scripts used in the journal publication "<strong>Correcting for probe wandering by precession path segmentation</strong>". DOI link to publication: https://doi.org/10.1016/j.ultramic.2023.113715 <strong>Prerequisites</strong> To run the scripts necessary to process the data, the open source packages JupyterLab and HyperSpy need to be installed. These notebooks were created with these package versions: hyperspy 1.6.4 jupyterlab 3.2.0 <strong>Data files</strong> There are three data types: Scanning precession electron diffraction (SPED) datasets contain the .hspy extension. There are two SPED datasets acquired by precession path segmentation, and one regular dataset: <em>SPED_256x256_22x22_10186nm_NBD_a5_spot1nm_CL20cm_125msExp_3000msFB_subframing_x8_pivotoff_01.hspy</em> is a precession path segmentation dataset presented in figure 2 in the article. <em>SPED_zoom1_256x256_12x12_5556nm_NBD_a5_spot1nm_CL20cm_10msExp_3000msFB_subframing_x8.hspy</em> is a precession path segmentation dataset presented in figures 1 and 3 in the article. <em>SPED_zoom1_256x256_12x12_5556nm_NBD_a5_spot1nm_CL20cm_10msExp_300msFB.hspy</em> is a regular SPED dataset of the same region as the dataset just above (also containing "zoom1" in its name). A series of diffraction patterns with de-rocking switched off can be found in the <em>eight_segments.npy</em> file. This dataset was recorded by Dr. Tina Bergh at Department of Chemical Engineering, Norwegian University of Science and Technology, and is meant to be used as an illustration of the precession segments used in figure 1 in the article. Virtual bright field images of the precession path segmented scans, before and after rigid correction in SmartAlign, can be found with the .png extension. The files starting with "pivot01..." are images from the precession path segmentation scan with an intentional pivot point misalignment, while the files starting with "small..." are from the well aligned scan. The files ending with "_reg" are regular, i.e., non-corrected compound VBF images, while the files ending with "_cor" are SmartAlign rigidly corrected VBF images. <strong>Processing scripts</strong> There are two processing scripts: <em>p01_slicing_segments.ipynb</em> is used to process the precession path segmentation datasets, from slicing of the raw data to constructing virtual bright field images. <em>p02_image_processing.ipynb</em> is used to create the images found in the article and for image analysis. The latter includes blur quantification and measuring edge sharpness.