cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5803544
title: Electron Diffraction (MicroED) Datasets for C16H21FN5OS - D-malate (Glacios TEM with a CETA-D)

description: Electron diffraction datasets collected from a chiral pharmaceutical compound cocrystallized with D-malic acid. Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services) Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode) Collection Software: Leginon (Cheng, et. al. 2021)* Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, nano probe mode, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded) Grid: Ted Pella 01840 Sample: C<sub>16</sub>H<sub>21</sub>FN<sub>5</sub>OS • D-malate, (N‐(5‐{[(3R)‐3‐[(5‐fluoropyrimidin‐2‐yl)methyl]piperidin‐1‐yl]methyl}‐1,3‐thiazol‐2‐yl)acetamide • D-malate, 483.51 g/mol Structure: CCDC 2132512 * Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value. A data processing tutorial is available for processing data collected with this setup using DIALS: https://dials.github.io/documentation/tutorials/3DED/Biotin.html
DOI: 10.5281/zenodo.3246705
title: TwitCID: a Collection of Data Sets for Studies on Information Diffusion on Social Networks

description: The TwitCID collection consists of five Twitter datasets which were extracted from the 1 percent of tweets from Twitter API. The Firstweek and Secondweek data set were collected during the first week and second week of January 2017 while the Iphone, Gucci and Galaxy data sets were collected from 21 September 2015 to 31 May 2017 using the keywords “iphone”, “gucci” and “galaxys” respectively. We publish these datasets on behalf of our academic institution – IRIT, France and for the sole purpose of non-commercial research under the license CC BY-NC-SA (Attribution-NonCommercial-ShareAlike). In accordance with Twitter's Terms of Service, we only provide identifiers of tweets. In order to collect the actual tweets in JSON, you could use the script Collect_JSONtweets.py attached. If you would like to use this collection, please cite our paper: Hoang, T. B. N., Mothe, J., & Baillon, M. (2019, September). TwitCID: a collection of data sets for studies on information diffusion on social networks. In <em>International Conference of the Cross-Language Evaluation Forum for European Languages</em> (pp. 88-100). Springer, Cham.
DOI: 10.5281/zenodo.3246704
title: TwitCID: a Collection of Data Sets for Studies on Information Diffusion on Social Networks

description: The TwitCID collection consists of five Twitter datasets which were extracted from the 1 percent of tweets from Twitter API. The Firstweek and Secondweek data set were collected during the first week and second week of January 2017 while the Iphone, Gucci and Galaxy data sets were collected from 21 September 2015 to 31 May 2017 using the keywords “iphone”, “gucci” and “galaxys” respectively. We publish these datasets on behalf of our academic institution – IRIT, France and for the sole purpose of non-commercial research under the license CC BY-NC-SA (Attribution-NonCommercial-ShareAlike). In accordance with Twitter's Terms of Service, we only provide identifiers of tweets. In order to collect the actual tweets in JSON, you could use the script Collect_JSONtweets.py attached. If you would like to use this collection, please cite our paper: Hoang, T. B. N., Mothe, J., & Baillon, M. (2019, September). TwitCID: a collection of data sets for studies on information diffusion on social networks. In <em>International Conference of the Cross-Language Evaluation Forum for European Languages</em> (pp. 88-100). Springer, Cham.
DOI: 10.5255/ukda-sn-855617
title: The Impact of COVID-19 on Travel Behaviour, Transport, Lifestyles and Residential Location Choices in Scotland Dataset, 2021

description: In response to the COVID-19 pandemic, Edinburgh Napier University’s Transport Research Institute has been undertaking a study, funded by the Scottish Funding Council (SFC), into its impact on transport and travel in Scotland. As part of this research, a travel behaviour questionnaire was developed focusing on daily travel as well as people’s long-term travel habits, attitudes and preferences during the different phases of the pandemic outbreak. The associated questionnaires were completed by participants between 3rd February 2021 and 17th February 2021 using the online platform, Qualtrics. The survey was restricted to Scottish residents and involved enforcing quota constraints for age, gender and household income. A total of 994 responses were collected. Perceptions of risk, trust in information sources and compliance with COVID-19 regulations were determined together with changes in levels of ‘life satisfaction’ and modal choice following the onset of COVID-19. In addition, survey responses were used to identify anticipated travel mode use in the future. Consideration was also given to the effects of COVID-19 on transport related lifestyle issues such as ‘working from home’, online shopping and the expectations of moving residences in the future. The research provided an insight into both the relationships between the levels of non-compliance with COVID-19 regulations and demographic variables and the respondent attributes which might affect future public transport usage. In general, the study confirmed significant reductions in traffic activity, amongst respondents during the COVID 19 pandemic associated with walking, driving a car and either using a bus or train. The respondents also indicated that they anticipated they would continue to make less use of buses and trains at the end of the pandemic.
DOI: 10.5281/zenodo.5799657
title: Electron Diffraction (MicroED) Datasets for C16H20FN5OS (Glacios TEM with a CETA-D)

description: Electron diffraction datasets collected from a chiral pharmaceutical compound. Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services) Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode) Collection Software: Leginon (Cheng, et. al. 2021)* Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded) Grid: Ted Pella 01840 Sample: C<sub>16</sub>H<sub>20</sub>FN<sub>5</sub>OS, (N‐(5‐{[(3R)‐3‐[(5‐fluoropyrimidin‐2‐yl)methyl]piperidin‐1‐yl]methyl}‐1,3‐thiazol‐2‐yl)acetamide, 349.43 g/mol Structure: CCDC 2130868 * Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value. A data processing tutorial is available for processing data collected with this setup using DIALS: https://dials.github.io/documentation/tutorials/3DED/Biotin.html
DOI: 10.5281/zenodo.5799656
title: Electron Diffraction (MicroED) Datasets for C16H20FN5OS (Glacios TEM with a CETA-D)

description: Electron diffraction datasets collected from a chiral pharmaceutical compound. Microscope: Thermo Fisher Scientific Glacios Transmission Electron Microscope (SDC1G at NanoImaging Services) Camera: Ceta-D camera (bin 2x2, rolling shutter, noise reduction mode) Collection Software: Leginon (Cheng, et. al. 2021)* Collection Parameters: 200keV, -193C, 20um C2, gun lens 7.1, spot size 10, parallel beam, calibrated camera length 1065.7mm (1100 in UI), oscillation per frame 0.89deg, 222ms exposure time, tilt speed 4 deg/s, rotation -60 to +60 (first ~8 degrees not recorded) Grid: Ted Pella 01840 Sample: C<sub>16</sub>H<sub>20</sub>FN<sub>5</sub>OS, (N‐(5‐{[(3R)‐3‐[(5‐fluoropyrimidin‐2‐yl)methyl]piperidin‐1‐yl]methyl}‐1,3‐thiazol‐2‐yl)acetamide, 349.43 g/mol Structure: CCDC 2130868 * Data have been converted to SMV format with the addition of an offset value to remove negative pixel values. This offset value can be found in the image headers, along with a suggested pedestal value. A data processing tutorial is available for processing data collected with this setup using DIALS: https://dials.github.io/documentation/tutorials/3DED/Biotin.html
DOI: 10.5517/ccdc.csd.cc25h2g7
title: CCDC 2010488: Experimental Crystal Structure Determination

description: Related Article: Hamad H. Al Mamari, Uroš Grošelj, Franc Požgan, Helena Brodnik|2021|J.Org.Chem.|86|3138|doi:10.1021/acs.joc.0c01983
DOI: 10.5517/ccdc.csd.cc25h2kb
title: CCDC 2010491: Experimental Crystal Structure Determination

description: Related Article: Hamad H. Al Mamari, Uroš Grošelj, Franc Požgan, Helena Brodnik|2021|J.Org.Chem.|86|3138|doi:10.1021/acs.joc.0c01983
DOI: 10.5517/ccdc.csd.cc25j271
title: CCDC 2011442: Experimental Crystal Structure Determination

description: Related Article: Hamad H. Al Mamari, Uroš Grošelj, Franc Požgan, Helena Brodnik|2021|J.Org.Chem.|86|3138|doi:10.1021/acs.joc.0c01983
DOI: 10.5517/ccdc.csd.cc277bpj
title: CCDC 2062637: Experimental Crystal Structure Determination

description: Related Article: Xianji Qiao, Kaixuan Chen, Alex J. Corkett, Damian Mroz, Xiaoying Huang, Ruimin Wang, Ryky Nelson, Richard Dronskowski|2021|Inorg.Chem.|60|12664|doi:10.1021/acs.inorgchem.1c02177
DOI: 10.5517/ccdc.csd.cc27srh9
title: CCDC 2079371: Experimental Crystal Structure Determination

description: Related Article: Sabina W. Jaros, Agnieszka Krogul-Sobczak, Barbara Bażanów, Magdalena Florek, Dominik Poradowski, Dmytro S. Nesterov, Urszula Śliwińska-Hill, Alexander M. Kirillov, Piotr Smoleński|2021|Inorg.Chem.|60|15435|doi:10.1021/acs.inorgchem.1c02110
DOI: 10.5517/ccdc.csd.cc27vttr
title: CCDC 2081365: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc27vtxv
title: CCDC 2081368: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc27vv65
title: CCDC 2081377: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc277bhb
title: CCDC 2062631: Experimental Crystal Structure Determination

description: Related Article: Xianji Qiao, Kaixuan Chen, Alex J. Corkett, Damian Mroz, Xiaoying Huang, Ruimin Wang, Ryky Nelson, Richard Dronskowski|2021|Inorg.Chem.|60|12664|doi:10.1021/acs.inorgchem.1c02177
DOI: 10.5517/ccdc.csd.cc27vtyw
title: CCDC 2081369: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc27vv54
title: CCDC 2081376: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc27vtwt
title: CCDC 2081367: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc27vv87
title: CCDC 2081379: Experimental Crystal Structure Determination

description: Related Article: Sara Fernández-Moyano, Marconi N. Peñas-Defrutos, Camino Bartolomé, Pablo Espinet|2021|Inorg.Chem.|60|14410|doi:10.1021/acs.inorgchem.1c02189
DOI: 10.5517/ccdc.csd.cc27wcm4
title: CCDC 2081886: Experimental Crystal Structure Determination

description: Related Article: Kai Sheng, Ran Wang, Xinde Tang, Marko Jagodič, Zvonko Jagličić, Laixue Pang, Jian-Min Dou, Zhi-Yong Gao, Hua-Yu Feng, Chen-Ho Tung, Di Sun|2021|Inorg.Chem.|60|14866|doi:10.1021/acs.inorgchem.1c02190
DOI: 10.5255/ukda-sn-855628
title: Metadata for Loneliness, Mental Health and Wellbeing: An Acceptability and Feasibility Study of UK Men’s Shed, 2021-2022

description: Mixed methods tested the acceptability and feasibility of measuring loneliness, mental health and wellbeing in Sheds The collection includes information related to the project and documentation. The collection does not include research data. The project did not ask for explicit consent about uploading / archiving anonymised data. Collecting retrospective consent was not possible.
DOI: 10.5255/ukda-sn-855592
title: Period Poverty: The Perceptions and Experiences of Impoverished Women Living an Inner-city Area of Northwest England, 2020

description: The menstrual needs of girls and women are important to health, education, and well-being. Unmet need and harm from poor menstrual health in low-and- middle-income countries have been documented, with little empirical research undertaken in high income countries. Continuing austerity in the UK suggests menstruators are likely more vulnerable to ‘period poverty’ than previously, with the COVID-19 pandemic assumed to exacerbate the situation. Aim To explore the menstrual experiences and perceptions of women in the UK who are living under circumstances of deprivation, alongside views of staff working in organisations supporting these women, to understand whether women’s menstrual needs are met. Methods A qualitative study was conducted in an inner-city in NW England. Three focus group discussions and 14 in-depth interviews were conducted across three study sites supporting impoverished women. Data was analysed thematically. Results Themes were: reflections on menstruation; affordability of products; access to public facilities; organisational support; potential solutions. Many women perceived menstruation as a burden in three aspects: physical discomfort and pain; psychological anxiety; and shame and stigma. Managing menstruation was difficult due to cost relative to low incomes, with food, heating and lighting prioritised, leaving women improvising with materials or wearing products for longer than desired. Most suggested that products should be free, often remarking if men required similar items this would happen. Most women were unaware supporting organisations provided free products. Staff felt the small range of products offered did not meet client needs and were ill prepared to have conversations on products and clients’ menstrual needs. Conclusion: Impoverished women lack the necessary resources to manage their menses well, which negatively impacts their health and brings stress, embarrassment, and shame. Support, including access to free products, is needed at both local and national level to help impoverished women manage their menstrual hygiene.
DOI: 10.5281/zenodo.6420882
title: Energy Market Transformation Survey

description: This report presents a survey performed with stakeholders and end-users under the scope of PARITY project. The survey explores the overall patterns that will form the energy market transformation and the consumer's perspective. The survey aims to evaluate participants’ opinions on the concepts of LEM and LFM, to identify factors and barriers to the progress of local renewable energy development based on the participants’ knowledge and what would motivate people to participate in such markets. Additionally, the goal of this survey is to analyse the current market needs, as well as investigate what is driving the energy markets transformation and where it is leading.
DOI: 10.5281/zenodo.6420830
title: Energy Market Transformation Survey

description: This report presents a survey performed with stakeholders and end-users under the scope of PARITY project. The survey explores the overall patterns that will form the energy market transformation and the consumer's perspective. The survey aims to evaluate participants’ opinions on the concepts of LEM and LFM, to identify factors and barriers to the progress of local renewable energy development based on the participants’ knowledge and what would motivate people to participate in such markets. Additionally, the goal of this survey is to analyse the current market needs, as well as investigate what is driving the energy markets transformation and where it is leading.
DOI: 10.5517/ccdc.csd.cc2433n1
title: CCDC 1969202: Experimental Crystal Structure Determination

description: Related Article: K. C. Nicolaou, Santhosh Reddy Rekula, S. Mothish Kumar, Ananda Rao Podilapu, Ryan P. Matuszak, Paul M. Jung, Lloyd T. Lam, Andrew C. Phillips, Joseph Lyssikatos, Stefan Munneke, Christine Gu, Hetal Sarvaiya, Joseph Sandoval, Mikhail Hammond, Monette Aujay, James W. Purcell, Regina M. Reilly, Julia Gavrilyuk|2021|J.Org.Chem.|86|2499|doi:10.1021/acs.joc.0c02643
DOI: 10.5281/zenodo.6425646
title: Histidine ligated iron-sulfur peptides

description: Data set of the paper "Histidine ligated iron-sulfur peptides" from Luca Valer et al.
DOI: 10.5281/zenodo.6425641
title: conocetusfuentes_04_22

description: Información de todas las fichas en formato HTML de las fuentes y manantaiales catalogadas en el proyecto "Conoce tus Fuentes" de la Agencia Andaluza del Agua de la Consejería de Medio Ambiente y la Universidad de Granada.
DOI: 10.5281/zenodo.6425640
title: conocetusfuentes_04_22

description: Información de todas las fichas en formato HTML de las fuentes y manantaiales catalogadas en el proyecto "Conoce tus Fuentes" de la Agencia Andaluza del Agua de la Consejería de Medio Ambiente y la Universidad de Granada.
DOI: 10.6084/m9.figshare.19552441
title: AMIGOS III data (usage examples and benchmark analysis)

description: This entry includes all materials used to generate the figures and tables in the AMIGOS III publication (Shine et al., 2022). <br> AMIGOSIII-plugin-code.zip contains the code for the AMIGOS III PyMOL plugin, which can also be found at the following page: https://github.com/pylelab/AMIGOSIII. <br> Files beginning with "4en5" were used to generate Figure 1. This includes the 4en5.pdb file, which was used as an input for the AMIGOS III PyMOL plugin, and the following five output files, which were generated using the AMIGOS III NARama feature: 4en5_eta_theta_plot.png (an eta vs theta plot), 4en5_eta_theta_prime_plot.png (an eta' vs theta' plot), 4en5_nucleic_worm_plot.png (a 3D plot of nucleotide position, eta, and theta), 4en5_eta_theta.csv (a spreadsheet of eta and theta values), and 4en5_eta_theta_prime.csv (a spreadsheet of eta' and theta' values). <br> Files beginning with "7mk1-chainC" were used to generate Figure S2. This includes the 7mk1.pdb file, which was used as an input for the AMIGOS III PyMOL plugin, and the following five output files, which were generated using the AMIGOS III NARama feature: 7mk1-chainC_eta_theta_plot.png (an eta vs theta plot), 7mk1-chainC_eta_theta_prime_plot.png (an eta' vs theta' plot), 7mk1-chainC_nucleic_worm_plot.png (a 3D plot of nucleotide position, eta, and theta), 7mk1-chainC_eta_theta.csv (a spreadsheet of eta and theta values), and 7mk1-chainC_eta_theta_prime.csv (a spreadsheet of eta' and theta' values). <br> The AMIGOSIII-TableS1-FigureS1-ata.xlsx file contains the benchmark data underlying TableS1 and FigureS1, which compares the performance of the motif searching feature of AMIGOS III with the Perl program PRIMOS. <br>
DOI: 10.6084/m9.figshare.19552441.v1
title: AMIGOS III Data

description: This entry includes all materials used to generate the figures and tables in the AMIGOS III publication (Shine et al., 2022). <br> AMIGOSIII-plugin-code.zip contains the code for the AMIGOS III PyMOL plugin, which can also be found at the following page: https://github.com/pylelab/AMIGOSIII. <br> Files beginning with "4en5" were used to generate Figure 1. This includes the 4en5.pdb file, which was used an an input for the AMIGOS III PyMOL plugin, and the following five output files, which were generated using the AMIGOS III NARama feature: 4en5_eta_theta_plot.png (an eta vs theta plot), 4en5_eta_theta_prime_plot.png (an eta' vs theta' plot), 4en5_nucleic_worm_plot.png (a 3D plot of nucleotide position, eta, and theta), 4en5_eta_theta.csv (a spreadsheet of eta and theta values), and 4en5_eta_theta_prime.csv (a spreadsheet of eta' and theta' values). <br> Files beginning with "7mk1-chainC" were used to generate Figure S2. This includes the 7mk1.pdb file, which was used an an input for the AMIGOS III PyMOL plugin, and the following five output files, which were generated using the AMIGOS III NARama feature: 7mk1-chainC_eta_theta_plot.png (an eta vs theta plot), 7mk1-chainC_eta_theta_prime_plot.png (an eta' vs theta' plot), 7mk1-chainC_nucleic_worm_plot.png (a 3D plot of nucleotide position, eta, and theta), 7mk1-chainC_eta_theta.csv (a spreadsheet of eta and theta values), and 7mk1-chainC_eta_theta_prime.csv (a spreadsheet of eta' and theta' values). <br> The AMIGOSIII-TableS1-FigureS1-ata.xlsx file contains the benchmark data underlying TableS1 and FigureS1, which compares the performance of the motif searching feature of AMIGOS III with the Perl program PRIMOS. <br>
DOI: 10.6084/m9.figshare.19087538
title: An Epidemiological Survey of Avian Influenza Knowledge and Practices among Poultry Farm Workers in Indonesia

description: <b>Background:</b>Avian influenza poses a serious threat to global public health. Awareness and protective behaviors among the general public, as well as high-risk populations, are essential for prevention and control. The purpose of this study is to determine the avian influenza knowledge and practices of poultry farm workers in Indonesia.<b>Methods:</b> This online cross-sectional study included 200 men and women aged &lt;20–50 years working on poultry farms in Indonesia. The study used a pre-designed standardized questionnaire containing 6 demographic questions, 14 questions for knowledge, and seven questions for practices. The questionnaire was distributed via WhatsApp and email. The Chi-square and Fisher Exact tests were used to analyze the data.<b>Results:</b>The study finding depicted that more than half (67%) of the respondents had heard of AI and the primary sources of information were health workers (36%) and TV (34%). The majority of the study participants (91.33%) had good knowledge regarding AI as a contagious infection that transmits between animals to animals and birds to birds. 76.8% of the respondents believe that poultry workers and veterinarians were at high risk of contracting AI infection. An average of (74.2%) the participants believe that using of face mask and washing hands with soap and water is a good practice to prevent AI infection. It is reported that 78.5% of respondents believe that properly disposing of dead birds prevents AI infection.<b></b><b>Conclusions:</b> This study revealed that the poultry workers had good knowledge that was similarly expressed in practices. Primary sources of information regarding AI were health workers and TV. The level of knowledge and practices had a significant relationship among respondents.