cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5522/04/25188935.v1
title: Qualitative dataset on safety-seeking behaviours in older crime victims: data from the Person-Reported Safety-Seeking Behaviour Measure (PRSBM)

description: Qualitative dataset for the study: <i>Safety-Seeking Behaviors and Psychological Distress in Older Victims of Community-Crime: A Cross-Sectional Study Using a Novel Person-Reported Measure</i><br>This dataset is for the qualitative component of the Person-Reported Safety-Seeking Behavior Measure (PRSBM). Older victims of community crime were asked whether they engaged in six types of behaviors since the crime: (checking, reassurance-seeking, rumination, avoidance, rituals, hypervigilance). If so, they were asked to describe their behaviors. Older victims were also asked to rate how frequently they engaged in each behavior and how much of change it was since the crime; the data for this is available in the corresponding quantitative dataset.
DOI: 10.17632/vygp3d5xv9.1
title: Emotional State analysis with Yoga Practice

description: Statistical analysis for the visual representation involves examining the trends and relationships within the data. Here, we're dealing with a conceptual model rather than real-world data, so the analysis is more qualitative. However, we can perform some basic analysis and provide interpretations:

1. Decay Constant (k):
• The decay constant affects the rate at which emotional state decreases over time. Higher values of k will result in faster emotional decay.
2. Yoga Effect (alpha):
• The yoga effect is a linear term that represents the positive impact of yoga practice on emotional well-being. A higher alpha implies a more significant positive effect of yoga.
3. Time (independent variable):
• Time is the independent variable representing the duration of the emotional evolution.
4. Emotional Evolution (dependent variable):
• Emotional Evolution is the dependent variable representing the emotional state over time.

Analysis:

• The plot shows an initial exponential decay in emotional state, representing a natural decline over time.
• The positive linear term (alpha * yoga_effect * time) introduces a positive impact of yoga. As time progresses, the effect of yoga becomes more prominent, contributing to an increase in emotional well-being.
• Key points (Start Yoga, Determination, Equanimity) are highlighted, emphasizing the potential positive milestones in the emotional well-being journey through yoga practice.

Interpretation:

• The model suggests that the emotional state naturally declines over time, but this decline is mitigated and even reversed by the positive impact of yoga.
• The effectiveness of yoga is demonstrated by the increasing emotional state as time elapses, especially during key periods like the initiation of yoga practice, determination to continue, and achieving equanimity.
DOI: 10.5258/soton/d2820
title: Dataset supporting the publication "Adopting a reductionist approach to advance acoustic deterrents in fish conservation"

description: This dataset supporting the publication "Adopting a reductionist approach to advance acoustic deterrents in fish conservation" in Frontiers in Freshwater Science.The assigned DOI for this article is 10.3389/ffwsc.2024.1320582

The data includes:
-Signal_Detection_Theory_V4.xlsx
-Trial_Results_Exp2_V2.xlsx
DOI: 10.6084/m9.figshare.6727271
title: The global impacts of US climate policy: a model simulation using GCAM-TU and MAGICC

description: To assess the potential impacts of the US withdrawal from the Paris Agreement, this study applied GCAM-TU (an updated version of the Global Change Assessment Model) to simulate global and regional emission pathways of energy-related CO<sub>2</sub>, which show that US emissions in 2100 would reduce to −2.4 Gt, −0.7 Gt and −0.2 Gt under scenarios of RCP2.6, RCP3.7 and RCP4.5, respectively. Two unfavourable policy scenarios were designed, assuming a temporary delay and a complete stop for US mitigation actions after 2015. Simulations by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) indicate that the temperature increase by 2100 would rise by 0.081°C–0.161°C compared to the three original RCPs (Representative Concentration Pathways) if US emissions were kept at their 2015 levels until 2100. The probability of staying below 2°C would decrease by 6–9% even if the US resumes mitigation efforts for achieving its Nationally Determined Contribution (NDC) target after 2025. It is estimated by GCAM-TU that, without US participation, increased reduction efforts are required for the rest of the world, including developing countries, in order to achieve the 2°C goal, resulting in 18% higher global cumulative mitigation costs from 2015 to 2100. <b>Key policy insights</b>President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target.To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas.Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government. President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target. To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas. Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government.
DOI: 10.6084/m9.figshare.6727271.v1
title: The global impacts of US climate policy: a model simulation using GCAM-TU and MAGICC

description: To assess the potential impacts of the US withdrawal from the Paris Agreement, this study applied GCAM-TU (an updated version of the Global Change Assessment Model) to simulate global and regional emission pathways of energy-related CO<sub>2</sub>, which show that US emissions in 2100 would reduce to −2.4 Gt, −0.7 Gt and −0.2 Gt under scenarios of RCP2.6, RCP3.7 and RCP4.5, respectively. Two unfavourable policy scenarios were designed, assuming a temporary delay and a complete stop for US mitigation actions after 2015. Simulations by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) indicate that the temperature increase by 2100 would rise by 0.081°C–0.161°C compared to the three original RCPs (Representative Concentration Pathways) if US emissions were kept at their 2015 levels until 2100. The probability of staying below 2°C would decrease by 6–9% even if the US resumes mitigation efforts for achieving its Nationally Determined Contribution (NDC) target after 2025. It is estimated by GCAM-TU that, without US participation, increased reduction efforts are required for the rest of the world, including developing countries, in order to achieve the 2°C goal, resulting in 18% higher global cumulative mitigation costs from 2015 to 2100. <b>Key policy insights</b>President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target.To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas.Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government. President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target. To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas. Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government.
DOI: 10.6084/m9.figshare.7251563
title: Additional file 9: of Ecologically informed microbial biomarkers and accurate classification of mixed and unmixed samples in an extensive cross-study of human body sites

description: Table S5. Comprehensive information of all biomarker OTUs, including marker association types, marker strength, and meta-information such as NCBI 16S accessions and taxonomic lineages. (TSV 68 kb)
DOI: 10.6084/m9.figshare.7251563.v1
title: Additional file 9: of Ecologically informed microbial biomarkers and accurate classification of mixed and unmixed samples in an extensive cross-study of human body sites

description: Table S5. Comprehensive information of all biomarker OTUs, including marker association types, marker strength, and meta-information such as NCBI 16S accessions and taxonomic lineages. (TSV 68 kb)
DOI: 10.5517/ccdc.csd.cc2gh0yy
title: CSD 2278560: Experimental Crystal Structure Determination

description: Related Article: Isabel Grosskreuz, Yaşar Krysiak, Hermann Gies, Enrico Mugnaioli, Bernd Marler|2024|New J.Chem.|48|4030|doi:10.1039/D3NJ03424K
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gs7k2
title: CCDC 2287414: Experimental Crystal Structure Determination

description: Related Article: Hien Nguyen, Tung T. Dang, Chi P. Mai, Trung T. Do, Hung V. Tran, Luc Van Meervelt, Hai T.H. Le|2024|Polyhedron|252|116885|doi:10.1016/j.poly.2024.116885
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.cc2gs7l3
title: CCDC 2287415: Experimental Crystal Structure Determination

description: Related Article: Hien Nguyen, Tung T. Dang, Chi P. Mai, Trung T. Do, Hung V. Tran, Luc Van Meervelt, Hai T.H. Le|2024|Polyhedron|252|116885|doi:10.1016/j.poly.2024.116885
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.cc2gs7m4
title: CCDC 2287416: Experimental Crystal Structure Determination

description: Related Article: Hien Nguyen, Tung T. Dang, Chi P. Mai, Trung T. Do, Hung V. Tran, Luc Van Meervelt, Hai T.H. Le|2024|Polyhedron|252|116885|doi:10.1016/j.poly.2024.116885
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.cc2gs7n5
title: CCDC 2287417: Experimental Crystal Structure Determination

description: Related Article: Hien Nguyen, Tung T. Dang, Chi P. Mai, Trung T. Do, Hung V. Tran, Luc Van Meervelt, Hai T.H. Le|2024|Polyhedron|252|116885|doi:10.1016/j.poly.2024.116885
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.cc2gs7p6
title: CCDC 2287418: Experimental Crystal Structure Determination

description: Related Article: Hien Nguyen, Tung T. Dang, Chi P. Mai, Trung T. Do, Hung V. Tran, Luc Van Meervelt, Hai T.H. Le|2024|Polyhedron|252|116885|doi:10.1016/j.poly.2024.116885
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.cc2gwyv5
title: CCDC 2290988: Experimental Crystal Structure Determination

description: Related Article: Chetan Chauhan, Santosh Kumar, Rajesh Kumar, Anju Saini, Thammarat Aree|2024|New J.Chem.|48|3829|doi:10.1039/D3NJ05361J
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.cc2gwyw6
title: CCDC 2290989: Experimental Crystal Structure Determination

description: Related Article: Chetan Chauhan, Santosh Kumar, Rajesh Kumar, Anju Saini, Thammarat Aree|2024|New J.Chem.|48|3829|doi:10.1039/D3NJ05361J
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.cc2gwyx7
title: CCDC 2290990: Experimental Crystal Structure Determination

description: Related Article: Chetan Chauhan, Santosh Kumar, Rajesh Kumar, Anju Saini, Thammarat Aree|2024|New J.Chem.|48|3829|doi:10.1039/D3NJ05361J
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.cc2gyjrq
title: CCDC 2292504: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chem.-Eur.J.|29|e202302903|doi:10.1002/chem.202302903
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.cc2gyjzy
title: CCDC 2292511: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chem.-Eur.J.|29|e202302903|doi:10.1002/chem.202302903
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.10689924
title: genetic_linkage dataset and results

description: Dataset and results of https://github.com/gael-millot/genetic_linkage
DOI: 10.34740/kaggle/dsv/7705396
title: COVID Vaccination in World (updated daily)
DOI: 10.6084/m9.figshare.5678797.v2
title: SS-31 peptide enables mitochondrial targeting drug delivery: a promising therapeutic alteration to prevent hair cell damage from aminoglycosides

description: Aminoglycoside-induced hearing loss stems from damage or loss of mechanosensory hair cells in the inner ear. Intrinsic mitochondrial cell death pathway plays a key role in that cellular dysfunction for which no proven effective therapies against oto-toxicities exist. Therefore, the aim of the present study was to develop a new mitochondrial targeting drug delivery system (DDS) that provided improved protection from gentamicin. Particularly, SS-31 peptide-conjugated geranylgeranylacetone (GGA) loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles were constructed successfully via emulsion-solvent evaporation method. The zebrafish lateral line sensory system was used as an <i>in vivo</i> evaluating platform to investigate the protective efficiency against gentamicin. SS-31 modification significantly reduced the activity of mechanoelectrical transduction (MET) channel and gentamicin uptake in zebrafish lateral line hair cells. As expected, SS-31 conjugated nanoparticles showed mitochondrial specific accumulation in hair cells when compared with unconjugated formulations. Furthermore, intracellular SS-31 modified PLGA NPs slightly enhanced mitochondrial membrane potential (MMP, ΔΨ<sub>m</sub>) and then returned to a steady-state, indicating their effect on the respiratory chain complexes in mitochondria. GGA loaded SS-31 conjugated nanoparticles demonstrated the most favorable hair cells survivals against gentamicin when compared with unconjugated groups whereas blank formulations failed to exhibit potency, indicating that the efficiency was attributed to drug delivery of GGA. These results suggest that our constructed mitochondria-targeting PLGA based DDS have potential application in protecting hair cells from ototoxic agents.
DOI: 10.5258/soton/d2964
title: Dataset in support of the University of Southampton Doctoral Thesis 'Financial hardship and mental health: A review of this relationship during the COVID-19 pandemic and an exploration of the roles of compassion, self-criticism and self-reassurance'

description: Dataset in support of the University of Southampton Doctoral Thesis 'Financial hardship and mental health: A review of this relationship during the COVID-19 pandemic and an exploration of the roles of compassion, self-criticism and self-reassurance'.

Full combined dataset of participants from both timepoints; Time 1 data and Time 2 data; consent forms (online and paper)
DOI: 10.6084/m9.figshare.5678998
title: K-edge XANES spectra data

description: K-edge XANES spectra data computed using FEFF9.
DOI: 10.6084/m9.figshare.5678998.v1
title: K-edge XANES spectra data

description: K-edge XANES spectra data computed using FEFF9.
DOI: 10.17632/d4gs7d8wy3.1
title: Linear Regression analysis – Inner Resilience, Detachment, Equanimity, Modern Yoga, Inner Equipoise and well-being

description: Interpreting the Graphs and Statistics: A Dive into Mathematical Portraits

1. Inner Resilience:

• Graph: A sinuous wave gracefully oscillates, embodying inner resilience. It reflects the strength to endure challenges.
• Statistics: The mean is around 0, indicating a balance in the sine curve. The skewness is close to 0, suggesting a symmetric distribution. The kurtosis is negative, revealing slightly flattened peaks.

2. Detachment from Outcomes:
• Graph: A sharp V-shaped curve symbolises detachment, a visual detachment from predefined outcomes.
• Statistics: The mean is around 0.5, the midpoint of the V. The skewness is 0, showcasing symmetry. The kurtosis is negative, emphasising the V's sharpness.

3. Embracing Equanimity:
• Graph: A cos wave brings a sense of equilibrium, capturing the essence of equanimity in its rhythmic highs and lows.
• Statistics: The mean hovers around 0, signifying balance. The skewness is 0, indicating symmetry. A negative kurtosis highlights a gentle peak.
4. Modern Application of Yoga:
• Graph: A more intricate sin curve suggests a modern interpretation of yoga, blending complexity and balance.
• Statistics: The mean aligns with 0, reflecting balance. The skewness is close to 0, showing symmetry. Negative kurtosis hints at a smoother curve.
5. Navigating Work and Life:
• Graph: A straight line illustrates navigating work and life with equipoise, a visual guide for maintaining balance.
• Statistics: The mean and median are linearly increasing, depicting a balanced progression. The skewness is 0, signifying symmetry.
6. Stress Reduction and Well-being:
• Graph: An exponential decay curve embodies stress reduction, descending into a serene well-being space.
• Statistics: The mean is around 0.5, showcasing central tendency. The skewness is negative, emphasising a longer tail on the left. Negative kurtosis denotes a flatter curve.
DOI: 10.6084/m9.figshare.20359080
title: An investigation of physicians' prescribing behaviors related to antidiabetic agents for Type 2 diabetes mellitus patients and associated factors in Taiwan

description: This study aimed to examine the factors that may influence physicians’ choice of antidiabetic agents. In addition, we investigated physicians’ decision-making process and treatment of T2DM patients with chronic kidney disease (CKD). Finally, we wanted to determine whether physicians knew the latest recommendations for T2DM treatment. The study was conducted as a cross-sectional survey using an online self-administered questionnaire to collect data from physicians in Taiwan. We enrolled licensed physicians who worked in hospitals or clinics with an average monthly T2DM patient load of 100 patients. Descriptive statistics, the independent samples <i>t</i>-test, and the Chi-square test were used for data analysis. Moreover, the association was examined between respondents’ demographics and the proportion of respondents who answered each T2DM treatment question correctly. A total of 986 invitations were sent out, and 324 completed questionnaires were received. The most important factors that may influence physicians’ choice of antidiabetic agents in each factor category were major comorbidities of patients, coverage of insurance, guideline recommendations, cardiovascular disease benefit, and whether a drug is the brand-name drug, respectively. When choosing second-line antidiabetic agents for T2DM patients with CKD, the most common reasons for doing so were recommendations of clinical guidelines (83.6%) and patients' renal function (59.6%) while SGLT2is were respondents’ most commonly chosen treatment. Respondents were more familiar with ADA recommendations for patients with certain major comorbidities than with the drugs’ labeled indications. Moreover, physicians who were younger, female, specialty in diabetes, or working in medical centers were more likely to give correct answers to certain questions about ADA guidelines (all <i>p</i> &lt; .05). This study provides a better understanding of the influential factors, treatment choices, and reasoning related to physicians’ prescribing of antidiabetic agents in Taiwan. In addition, knowledge gaps in various physician groups were identified.