cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8360024
title: Supplementary Information

description: Supplementary information of "Key drivers and pressures of global water scarcity hotspots". Supplementary table A - SCOPUS search strings Supplementary table B - DPSIR definitions Supplementary table C - Data resources Supplementary figures D - Lineplots of historical data analysis Supplementary table E - DPSIR case study results Supplementary figures F - Circular barplots DPSIR analysis per hotspot
DOI: 10.5517/ccdc.csd.cc2bp56f
title: CCDC 2165294: Experimental Crystal Structure Determination

description: Related Article: Nikita V. Muravyev, Kyrill Yu. Suponitsky, Ivan V. Fedyanin, Igor V. Fomenkov, Alla N. Pivkina, Igor L. Dalinger|2022|Chem.Eng.Journal|449|137816|doi:10.1016/j.cej.2022.137816
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bp57g
title: CCDC 2165295: Experimental Crystal Structure Determination

description: Related Article: Nikita V. Muravyev, Kyrill Yu. Suponitsky, Ivan V. Fedyanin, Igor V. Fomenkov, Alla N. Pivkina, Igor L. Dalinger|2022|Chem.Eng.Journal|449|137816|doi:10.1016/j.cej.2022.137816
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d1z6n
title: CCDC 2206431: Experimental Crystal Structure Determination

description: Related Article: Akshaya Keerthi C. S, Sandip Das, Kulbir, Prabhakar Bhardwaj, Md Palashuddin Sk, Pankaj Kumar|2023|Dalton Trans.|52|16492|doi:10.1039/D3DT03177B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f9z3v
title: CCDC 2243907: Experimental Crystal Structure Determination

description: Related Article: Asong Byun, Dohyun Moon, Byeongchan Lee, Jinhee Park|2023|J.Mater.Chem.A|11|24591|doi:10.1039/D3TA05626K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10591459
title: IMMERSE PYC Dataset
DOI: 10.5281/zenodo.10591477
title: IMMERSE T Dataset
DOI: 10.5281/zenodo.10591490
title: IMMERSE R Dataset
DOI: 10.48432/pmezy5
title: Forest Inventory on 10 hectares in Fazenda Tanguro, Mato Grosso, Brasil in 2012.

description: The Forest Inventory data set Fazenda Tanguro (TAN_A01_2012_Inventory) refers to the inventory carried out in Canarana and Querência municipalities, Mato Grosso state, Brazil to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5281/zenodo.10591487
title: YHSeqY3000 panel captures all founding lineages in the Chinese paternal genomic diversity database

description: Advances in second/third-generation sequencing and computational innovations revolutionized our understanding of the genomic structure of Y-chromosomes and their unique phylogenetic features. However, the construction of population-specific high-resolution Y-chromosome panels and databases in anthropological and forensic translational applications is limited due to the unavailability of the population-scale genomic database. We developed the highest-resolution Y-targeted sequencing panel based on the screened time-stamped core phylogenetic informative mutations from high-coverage sequences in the YanHuang cohort to explore ethnolinguistically diverse Chinese people's fine-scale paternal evolutionary history. The evaluated sequencing performance of the 2999-core SNP variant calling observed in this East-Asian-specific Y-chromosomal panel was robust and reliable. The YHSeqY3000 panel was designed to capture the genetic diversity of Chinese 3500-year-ago paternal lineages and identified 408 terminal lineages in 2097 individuals from 41 genetically and geographically different populations. We identified fine-scale paternal substructure correlated with ancient population migrations and expansions and reported new evidence of the extensive gene flow events between minority ethnic groups and Han Chinese people based on the integrative Chinese paternal genomic diversity database (CPGDD). This work effectively integrated the Y-chromosome-related basis science and translational utilization, underscoring the necessity and importance of comprehensive characterization of Y-chromosome genomic diversity based on the dense sampling strategies in the second phase of population-specific medical or anthropological cohorts.
DOI: 10.5281/zenodo.10591488
title: YHSeqY3000 panel captures all founding lineages in the Chinese paternal genomic diversity database

description: Advances in second/third-generation sequencing and computational innovations revolutionized our understanding of the genomic structure of Y-chromosomes and their unique phylogenetic features. However, the construction of population-specific high-resolution Y-chromosome panels and databases in anthropological and forensic translational applications is limited due to the unavailability of the population-scale genomic database. We developed the highest-resolution Y-targeted sequencing panel based on the screened time-stamped core phylogenetic informative mutations from high-coverage sequences in the YanHuang cohort to explore ethnolinguistically diverse Chinese people's fine-scale paternal evolutionary history. The evaluated sequencing performance of the 2999-core SNP variant calling observed in this East-Asian-specific Y-chromosomal panel was robust and reliable. The YHSeqY3000 panel was designed to capture the genetic diversity of Chinese 3500-year-ago paternal lineages and identified 408 terminal lineages in 2097 individuals from 41 genetically and geographically different populations. We identified fine-scale paternal substructure correlated with ancient population migrations and expansions and reported new evidence of the extensive gene flow events between minority ethnic groups and Han Chinese people based on the integrative Chinese paternal genomic diversity database (CPGDD). This work effectively integrated the Y-chromosome-related basis science and translational utilization, underscoring the necessity and importance of comprehensive characterization of Y-chromosome genomic diversity based on the dense sampling strategies in the second phase of population-specific medical or anthropological cohorts.
DOI: 10.25502/0apf-2230/d
title: BD North-Bangladesh Household processed survey 2023 CIMMYT
DOI: 10.5281/zenodo.10581902
title: Data from: The interacting effect of climate change and herbivory can trigger large-scale transformations of European temperate forests

description: Here we share the modeling results and post-processing scripts for the paper titled "The interacting effect of climate change and herbivory can trigger large-scale transformations of European temperate forests" in Global Change Biology.
DOI: 10.5281/zenodo.10581903
title: Data from: The interacting effect of climate change and herbivory can trigger large-scale transformations of European temperate forests

description: Here we share the modeling results and post-processing scripts for the paper titled "The interacting effect of climate change and herbivory can trigger large-scale transformations of European temperate forests" in Global Change Biology.
DOI: 10.48432/1kp9l7
title: Forest Inventory on 10 hectares in Paragominas, Pará, Brasil in 2013.

description: The Forest Inventory data set Paragominas – Fazenda Nova Neonita (PAR_A01_2013_Inventory) refers to the inventory carried out in Paragominas municipality, Pará state to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5281/zenodo.10569241
title: DATASET RELATED TO ARTICLE: "Focal Dystonic Tremor as a Prominent Feature in a Child with a CACNA1A-Related Disorder"

description: NGS files (.vcf) and segregation Sanger sequences (.abi) of CACNA1A patient and her family.
DOI: 10.5281/zenodo.10569242
title: DATASET RELATED TO ARTICLE: "Focal Dystonic Tremor as a Prominent Feature in a Child with a CACNA1A-Related Disorder"

description: NGS files (.vcf) and segregation Sanger sequences (.abi) of CACNA1A patient and her family.
DOI: 10.4121/b769cfdb-350b-4511-8a5e-79d79b9a6006
title: Analysis Code for Bachelor Thesis: Use Reinforcement Learning to Choose Activities for Preparing to Quit Smoking: How Effective a Reinforcement Learning Model is for Choosing Activities that Optimizes the Likelihood that Users Return to the Next Session and the Effort Users Spend on Their Activities?

description: Unhealthy behaviors such as smoking is the major cause for premature deaths and changing behaviors by oneself can be difficult. That is where eHealth applications come into rescue. One of the recent research explored the possibility of using a Reinforcement Learning model to choose persuasive types for a virtual coach to adopt to persuade people to prepare for smoke-quitting and it has shown advantages. However, there are still more aspects to investigate in this context except the persuasive types of the messages, and this paper intended to further look into using reinforcement learning to choose activities for preparing the users to quit smoking, To be more specific, we implemented and evaluated a reinforcement learning model to choose activities to optimize both the effort spent by the users and also the likelihood of them staying for the next session. The result suggests that reinforcement learning is a promising approach to choose activities for people to prepare for quitting smoking and it can move the users to states that they are more likely to spend a good effort on the activities and are more likely to come back to the next session. <br>This work is part of the multidisciplinary research project Perfect Fit, which is supported by several funders organized by the Netherlands Organization for Scientific Research (NWO), program Commit2Data - Big Data \& Health (project number 628.011.211). Besides NWO, the funders include the Netherlands Organisation for Health Research and Development (ZonMw), Hartstichting, the Ministry of Health, Welfare, and Sport (VWS), Health Holland, and the Netherlands eScience Center. <br><br>
DOI: 10.4121/b769cfdb-350b-4511-8a5e-79d79b9a6006.v1
title: Analysis Code for Bachelor Thesis: Use Reinforcement Learning to Choose Activities for Preparing to Quit Smoking: How Effective a Reinforcement Learning Model is for Choosing Activities that Optimizes the Likelihood that Users Return to the Next Session and the Effort Users Spend on Their Activities?

description: Unhealthy behaviors such as smoking is the major cause for premature deaths and changing behaviors by oneself can be difficult. That is where eHealth applications come into rescue. One of the recent research explored the possibility of using a Reinforcement Learning model to choose persuasive types for a virtual coach to adopt to persuade people to prepare for smoke-quitting and it has shown advantages. However, there are still more aspects to investigate in this context except the persuasive types of the messages, and this paper intended to further look into using reinforcement learning to choose activities for preparing the users to quit smoking, To be more specific, we implemented and evaluated a reinforcement learning model to choose activities to optimize both the effort spent by the users and also the likelihood of them staying for the next session. The result suggests that reinforcement learning is a promising approach to choose activities for people to prepare for quitting smoking and it can move the users to states that they are more likely to spend a good effort on the activities and are more likely to come back to the next session. <br>This work is part of the multidisciplinary research project Perfect Fit, which is supported by several funders organized by the Netherlands Organization for Scientific Research (NWO), program Commit2Data - Big Data \& Health (project number 628.011.211). Besides NWO, the funders include the Netherlands Organisation for Health Research and Development (ZonMw), Hartstichting, the Ministry of Health, Welfare, and Sport (VWS), Health Holland, and the Netherlands eScience Center. <br><br>
DOI: 10.48432/kdh4zp
title: Forest Inventory on 5.1 hectares in Tapajós, Belterra, Pará, Brasil in 2011.

description: The Forest Inventory data set Floresta Nacional do Tapajós (TAP_A01_2011_Inventory) refers to the inventory carried out in Tapajós National Forest, Pará state to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.25345/c5bn9xd61
title: MassIVE MSV000093953 - GNPS Chromatographic data of two chemotypes of lippia alba CDF 20
title: GNPS Chromatographic data of two chemotypes of lippia alba CDF 20
DOI: 10.48432/nttwd6
title: Forest Inventory on 2 hectares in Tapajós, Belterra, Pará, Brasil in 2016.

description: The Forest Inventory data set Floresta Nacional do Tapajós (TAP_A01_2016_Inventory) refers to the inventory carried out in Tapajós National Forest, Pará state to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.6084/m9.figshare.25099817
title: Exploring the role of Music-Assisted Relaxation for re-injury anxiety in tertiary-level cheerleaders using Thematic Analysis

description: Competitive cheerleading is a dynamic sport characterised by intricate routines involving dance, stunts, and gymnastics. Athletes face the risk of injuries that not only impact their physical well-being but also introduce psychological challenges, particularly re-injury anxiety. This research explores the experiences of injury in cheerleading, focusing on sustaining injuries, responses to the thought of re-injury, skills for injury prevention, and the impact of re-injury anxiety during practice. Additionally, the study delves into mental preparedness, emphasising the development of a strong-willed mindset, the challenges of returning to practise prematurely, the unique affordances of cheerleading, and the importance of team relationships.The investigation further examines rehabilitation and psychosocial support, uncovering the benefits and challenges of the rehabilitation process and athletes' previous experiences with psychosocial support. A novel aspect of the research involves exploring personal experiences of Music-Assisted Relaxation (MAR) in music therapy, considering perceived benefits, expectations, and individual encounters with this specific technique. The potential incorporation of MAR as a psychological strategy for managing re-injury anxiety during rehabilitation is a focal point of interest.
DOI: 10.6084/m9.figshare.25099817.v1
title: Exploring the role of Music-Assisted Relaxation for re-injury anxiety in tertiary-level cheerleaders using Thematic Analysis

description: Competitive cheerleading is a dynamic sport characterised by intricate routines involving dance, stunts, and gymnastics. Athletes face the risk of injuries that not only impact their physical well-being but also introduce psychological challenges, particularly re-injury anxiety. This research explores the experiences of injury in cheerleading, focusing on sustaining injuries, responses to the thought of re-injury, skills for injury prevention, and the impact of re-injury anxiety during practice. Additionally, the study delves into mental preparedness, emphasising the development of a strong-willed mindset, the challenges of returning to practise prematurely, the unique affordances of cheerleading, and the importance of team relationships.The investigation further examines rehabilitation and psychosocial support, uncovering the benefits and challenges of the rehabilitation process and athletes' previous experiences with psychosocial support. A novel aspect of the research involves exploring personal experiences of Music-Assisted Relaxation (MAR) in music therapy, considering perceived benefits, expectations, and individual encounters with this specific technique. The potential incorporation of MAR as a psychological strategy for managing re-injury anxiety during rehabilitation is a focal point of interest.
DOI: 10.5281/zenodo.10575925
title: Automated Reasoning under Weak Memory Consistency
DOI: 10.5281/zenodo.10575926
title: Automated Reasoning under Weak Memory Consistency
DOI: 10.48432/tosgpt
title: Forest Inventory on 2.25 hectares in Tapajós, Belterra, Pará, Brasil in 2018.

description: The Forest Inventory data set Floresta Nacional do Tapajós (TAP_A01_2018_Inventory) refers to the inventory carried out in Tapajós National Forest, Pará state to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/5dpuwm
title: Forest Inventory on 1.44 hectares in São Félix do Xingu, Para, Brasil in 2011.

description: The Forest Inventory data set São Félix do Xingu (SFX_A01_2011_Inventory) refers to the inventory carried out in São Félix do Xingu municipality, Pará state to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/m2vx1z
title: Forest Inventory on 8 hectares in Belterra, Pará, Brasil in 2018.

description: The Forest Inventory data set Projeto Anambé (ANA_A01_2018_Inventory) refers to the inventory carried out in Pará state to serve the purpose of calibration and validation to the LiDAR data obtained in the same area. The United States Forest Service working in collaboration with the Brazilian Enterprise for Agricultural Research (EMBRAPA) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. A comma separated value (CSV) file format containing the data; b. A readme Portable Document file (PDF) format which provides information about the .csv file content, explanation of each section of the document and any complement necessary. c. Map of Forest Inventory Plots carried out in the area (shapefile). “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."