cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8202001
title: An analytical study of capillary rise dynamics: Critical conditions and hidden oscillations - Research Data

description: This dataset provides the research data and software for the publication: M. Fricke, E. Ouro-Koura, S. Raju, R. von Klitzing, J. De Coninck, D. Bothe: An analytical study of capillary rise dynamics:<br> Critical conditions and hidden oscillations which was published in the Journal Physica D: Nonlinear Phenomena. The experimental data for the capillary rise of silicon oil, ethanol and ether has been extracted from the publication D. Quéré: Inertial capillarity, EPL 39 533, DOI:10.1209/epl/i1997-00389-2 (1997) using image analysis methods. It is stored in the csv files Silicon_Oil_Quere1997, Ethanol_Quere1997.csv and Ether_Quere1997. Please use the Python scripts silicon-oil.py, ethanol.py and ether.py to solve the ordinary differential equation model and to generate the plots presented in our publication. The Python library matplotlib was used for plotting. A simple explicit Euler scheme proved sufficient to solve the ordinary differential equation in its dimensionless form. It is implemented in the file capRiseOdeSolver.py.
DOI: 10.5281/zenodo.8202000
title: An analytical study of capillary rise dynamics: Critical conditions and hidden oscillations - Research Data

description: This dataset provides the research data and software for the publication: M. Fricke, E. Ouro-Koura, S. Raju, R. von Klitzing, J. De Coninck, D. Bothe: An analytical study of capillary rise dynamics:<br> Critical conditions and hidden oscillations which was published in the Journal Physica D: Nonlinear Phenomena. The experimental data for the capillary rise of silicon oil, ethanol and ether has been extracted from the publication D. Quéré: Inertial capillarity, EPL 39 533, DOI:10.1209/epl/i1997-00389-2 (1997) using image analysis methods. It is stored in the csv files Silicon_Oil_Quere1997, Ethanol_Quere1997.csv and Ether_Quere1997. Please use the Python scripts silicon-oil.py, ethanol.py and ether.py to solve the ordinary differential equation model and to generate the plots presented in our publication. The Python library matplotlib was used for plotting. A simple explicit Euler scheme proved sufficient to solve the ordinary differential equation in its dimensionless form. It is implemented in the file capRiseOdeSolver.py.
DOI: 10.5258/soton/d2536
title: Dataset in support of the Southampton doctoral thesis : The study of bismuth doped fibres and the development of broadband bismuth doped fibre amplifiers.

description: The Excel files contain all experimental data used for generating figures in this thesis.
DOI: 10.5255/ukda-sn-856637
title: Small Party MP Appearances and Contributions Pre and Post-Coronavirus Pandemic, 2019 - 2021

description: This dataset maps the parliamentary activity of House of Commons MPs from x small parties during the first year of the coronavirus pandemic (March 2020 - March 2021). To enable comparisons it also includes the year prior to the pandemic (March 2019 - March 2020). The parties included here are: Alliance, DUP, Green, Liberal Democrat, Plaid Cymru, SDLP, SNP. It firstly includes a mapping document showing which contributions were made virtually and which were made in person on the floor of the House of Commons. Similar information is shown here also for Scottish Labour and Conservative Party MPs. Secondly, it includes all contributions made by these small party MPs across the March 2019 - March 2021 period. This includes: party, name of MP, date of contribution, contribution period (relating to different rules for parliamentary business during the pandemic), type of contribution (virtual/physical) and venue (Commons chamber, Westminster Hall).
DOI: 10.48510/fk2/1ja7ar/kowhze
title: Methodology_employees_survey_2009_2010_lv.pdf

description: :unav
DOI: 10.48510/fk2/1ja7ar/c0zzjf
title: Data_DN_PN_survey_2009_2010_lv.tab

description: :unav
DOI: 10.48510/fk2/1ja7ar/dxslvb
title: Data_DN_PN_survey_2009_2010.csv

description: :unav
DOI: 10.48510/fk2/1ja7ar
title: Working Conditions and Risks in Latvia 2009 - 2010: Survey of Employees and Self-Employed

description: The Work conditions and risks in Latvia national surveys were conducted in Latvia in 2006, 2010, 2013, 2018 and 2022. The aim of these surveys is to gather evidence on situations related to occupational risk factors, occupational health, safety and to analyze the dynamics of the data obtained and identify the causes of the existing problems. This data serves as a basis to develop proposals for improving the practical implementation of the legal framework and foundation for effective decision making. A more detailed description of the methods is available in the methodology file.
DOI: 10.48510/fk2/1ja7ar/dpo8je
title: questionnaire_DN_PN_survey_2009_2010_lv.pdf

description: :unav
DOI: 10.26050/wdcc/ar6.c6achcme1
title: IPCC DDC: HAMMOZ-Consortium MPI-ESM1.2-HAM model output prepared for CMIP6 AerChemMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
DOI: 10.26050/wdcc/ar6.c6sphcme1s370
title: IPCC DDC: HAMMOZ-Consortium MPI-ESM1.2-HAM model output prepared for CMIP6 ScenarioMIP ssp370

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.ssp370' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
DOI: 10.6084/m9.figshare.23862975
title: Investigating the impact of seawater intrusion on the operation cost of groundwater supply in island aquifers

description: This is the simulation code for modelling seawater intrusion in a 2D cross-section island aquifer using SEAWAT.
DOI: 10.6084/m9.figshare.23585235
title: Supplementary Material for: Observed Emotional Availability (EA) in the Early Months and Adolescence and Self-Reported EA at Any Age: A Narrative Review

description: Emotional Availability (EA) is a relational construct that encompasses the ability of a dyad to share an emotionally connected, safe relationship. EA is operationalized by the multi-dimensional framework, which includes the observational EA Scales, the observational Emotional Attachment Zones (EA-Z), as well as the EA Self-Report (EA-SR). The observational EA Scales measure the mutual interactive influences a child and parent may have on one another, through observation of their affect and behavior, and consist of 4 adult dimensions (sensitivity, structuring, nonintrusiveness, and nonhostility) and 2 child dimensions (responsiveness and involvement of the adult). The EA-Z refers to “emotional attachment styles” and are based on the summary of the observational EA Scales, assigned separately to adult and child (Emotionally Available, Complicated, Detached, Problematic/Disturbed/Traumatized or Traumatizing), with the potential that the emotional attachment perspective of the adult and child may not be the same. The EA Self Report is about parental perceptions rather than observations, which should be taken into account in interpreting its findings. Collectively, these different measurements are referred to as the EA System. In this review, we focus on the EA-SR at any age, as well as EA observations, on the earliest months and adolescence.
DOI: 10.6084/m9.figshare.23585235.v1
title: Supplementary Material for: Observed Emotional Availability (EA) in the Early Months and Adolescence and Self-Reported EA at Any Age: A Narrative Review

description: Emotional Availability (EA) is a relational construct that encompasses the ability of a dyad to share an emotionally connected, safe relationship. EA is operationalized by the multi-dimensional framework, which includes the observational EA Scales, the observational Emotional Attachment Zones (EA-Z), as well as the EA Self-Report (EA-SR). The observational EA Scales measure the mutual interactive influences a child and parent may have on one another, through observation of their affect and behavior, and consist of 4 adult dimensions (sensitivity, structuring, nonintrusiveness, and nonhostility) and 2 child dimensions (responsiveness and involvement of the adult). The EA-Z refers to “emotional attachment styles” and are based on the summary of the observational EA Scales, assigned separately to adult and child (Emotionally Available, Complicated, Detached, Problematic/Disturbed/Traumatized or Traumatizing), with the potential that the emotional attachment perspective of the adult and child may not be the same. The EA Self Report is about parental perceptions rather than observations, which should be taken into account in interpreting its findings. Collectively, these different measurements are referred to as the EA System. In this review, we focus on the EA-SR at any age, as well as EA observations, on the earliest months and adolescence.
DOI: 10.6084/m9.figshare.23276276
title: Supplementary Material for: Associations of Cerebral Small Vessel Disease on the Features of Hematoma and Hematoma Expansion in Intracerebral Hemorrhage

description: INTRODUCTION: Several early noncontrast CT (NCCT) signs of spontaneous intracerebral hemorrhage (ICH) can predict hematoma expansion (HE). However, the associations of underlying cerebral small vessel disease (SVD) on early NCCT signs and HE have been less explored. METHODS: We conducted an analysis of all patients with spontaneous supratentorial ICH and received follow-up imaging between 2016-2020 at a stroke center. The early NCCT signs were categorized as shape or density signs. HE was defined as an increase in hematoma volume ≥6 ml or 33% from baseline. The severity of SVD was assessed by both a 3-point CT-based and a 4-point MRI-based SVD scores. Regression models were used to examine the associations between SVD score and hematoma volume, NCCT signs, and HE. RESULTS: A total of 328 patients (median age: 64 years; 38% female) were included. The median baseline ICH volume was 8.6 ml, with 38% of the patients had shape signs and 52% had density signs on the initial NCCT. Higher MRI-SVD scores were associated with smaller ICH volumes (P = 0.0006), fewer shape (P = 0.001) or density signs (P = 0.0003). Overall, 16% of patients experienced HE. A higher MRI-SVD score was inversely associated with HE (adjusted odds ratio 0.71, 95% CI 0.53 – 0.96). Subgroup analysis revealed that this association was primarily observed in patients who were younger (&lt; 65 years), male, had deep hemorrhage, or did not meet the criteria for cerebral amyloid angiopathy diagnosis. CONCLUSIONS: In patients with spontaneous ICH, a more severe SVD was associated with smaller hematoma volume, fewer NCCT signs, and a lower risk of HE. Further research is required to investigate why a higher burden of severely diseased cerebral small blood vessels is associated with less bleeding.
DOI: 10.6084/m9.figshare.23276276.v1
title: Supplementary Material for: Associations of Cerebral Small Vessel Disease on the Features of Hematoma and Hematoma Expansion in Intracerebral Hemorrhage

description: INTRODUCTION: Several early noncontrast CT (NCCT) signs of spontaneous intracerebral hemorrhage (ICH) can predict hematoma expansion (HE). However, the associations of underlying cerebral small vessel disease (SVD) on early NCCT signs and HE have been less explored. METHODS: We conducted an analysis of all patients with spontaneous supratentorial ICH and received follow-up imaging between 2016-2020 at a stroke center. The early NCCT signs were categorized as shape or density signs. HE was defined as an increase in hematoma volume ≥6 ml or 33% from baseline. The severity of SVD was assessed by both a 3-point CT-based and a 4-point MRI-based SVD scores. Regression models were used to examine the associations between SVD score and hematoma volume, NCCT signs, and HE. RESULTS: A total of 328 patients (median age: 64 years; 38% female) were included. The median baseline ICH volume was 8.6 ml, with 38% of the patients had shape signs and 52% had density signs on the initial NCCT. Higher MRI-SVD scores were associated with smaller ICH volumes (P = 0.0006), fewer shape (P = 0.001) or density signs (P = 0.0003). Overall, 16% of patients experienced HE. A higher MRI-SVD score was inversely associated with HE (adjusted odds ratio 0.71, 95% CI 0.53 – 0.96). Subgroup analysis revealed that this association was primarily observed in patients who were younger (&lt; 65 years), male, had deep hemorrhage, or did not meet the criteria for cerebral amyloid angiopathy diagnosis. CONCLUSIONS: In patients with spontaneous ICH, a more severe SVD was associated with smaller hematoma volume, fewer NCCT signs, and a lower risk of HE. Further research is required to investigate why a higher burden of severely diseased cerebral small blood vessels is associated with less bleeding.
DOI: 10.6084/m9.figshare.23592312
title: Supplementary Material for: Evaluation of C4 gene copy number in Pediatric Acute Neuropsychiatric Syndrome

description: Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) is an abrupt-onset neuropsychiatric disorder. PANS patients have an increased prevalence of co-morbid autoimmune illness, most commonly arthritis. In addition, an estimated one-third of PANS patients present with low serum C4 protein, suggesting decreased production or increased consumption of C4 protein. To test the possibility that copy number (CN) variation contributes to risk of PANS illness, we compared mean total C4A and total C4B CN in ethnically-matched subjects from PANS DNA samples and controls (192 cases and 182 controls). Longitudinal data from the Stanford PANS cohort (n = 121) was used to assess whether the time to Juvenile Idiopathic Arthritis (JIA) or Autoimmune Disease (AI) onset was a function of total C4A or C4B. Lastly, we performed several hypothesis-generating analyses to explore the correlation between individual C4 gene variants, sex, specific genotypes and age of PANS onset. Although the mean total C4A or C4B CN did not differ in PANS compared to controls, PANS patients with low C4B CN were at increased risk for subsequent JIA diagnosis (Hazard Ratio = 27, p-value = 0004). We also observed a possible increase in risk for AI in PANS patients and a possible correlation between lower C4B and PANS age of onset. An association between rheumatoid arthritis and low C4B CN has been reported previously. However, patients with PANS develop different types of JIA: enthesitis-related arthritis, spondyloarthritis and psoriatic arthritis. This suggests that C4B plays a role that spans these arthritis types.
DOI: 10.6084/m9.figshare.23629152.v1
title: Genomics of <i>Acinetobacter baumannii </i>iron uptake

description: Supplementary material for 'Genomics of <em>Acinetobacter baumannii</em> iron uptake', as described in Microbial Genomics.
DOI: 10.6084/m9.figshare.23629152
title: Genomics of <i>Acinetobacter baumannii </i>iron uptake

description: Supplementary material for 'Genomics of <em>Acinetobacter baumannii</em> iron uptake', as described in Microbial Genomics.
DOI: 10.6084/m9.figshare.23634072.v1
title: Supplementary Material for: Clinical course of a rare Epstein–Barr virus-associated smooth muscle tumor and its genomic analysis

description: Epstein–Barr virus (EBV) can rarely induce smooth muscle tumors (SMTs). A 20-year-old female patient underwent kidney transplantation for renal failure. Since then, she has been treated with immunosuppressants, including a calcineurin inhibitor, tacrolimus, and prednisolone, owing to the immunological rejection. Three years later, she developed large liver tumors (diameter &gt; 5 cm) and multiple small lung tumors that were identified as EBV-SMTs based on the results of liver biopsy/histopathology. No intervention was performed, except for the addition of an mTOR inhibitor, everolimus, which inhibits both immune reaction and SMT growth. Finally, after 8 years, the transplanted kidney became nonfunctional and immunosuppressant administration became unnecessary as urinary dialysis was started. Under these circumstances, SMT growth was observed despite the absence of immunosuppressant administration. Three months after the cessation of the immunosuppressants, EBV-SMTs in the liver and lungs shrank slightly. To the best of our knowledge, this is the first report on the genomic profile of this rare tumor. The clinical course of our patient indicates that EBV can induce SMTs, and immunological suppression of EBV may inhibit the activity of these tumors.
DOI: 10.25392/leicester.data.22148921
title: Data for primary analysis

description: Data from 37 participants who met 60% accuracy criterion. Accuracy data from the learning and recall sessions for the wake and sleep conditions
DOI: 10.25392/leicester.data.22148921.v1
title: Data for primary analysis

description: Data from 37 participants who met 60% accuracy criterion. Accuracy data from the learning and recall sessions for the wake and sleep conditions
DOI: 10.25392/leicester.data.22148909
title: Data for exploratory analysis n=70

description: Data from exploratory analysis of scores on learning and recall sessions and sleep and wake conditions.
DOI: 10.25392/leicester.data.22148909.v1
title: Data for exploratory analysis n=70

description: Data from exploratory analysis of scores on learning and recall sessions and sleep and wake conditions.
DOI: 10.6084/m9.figshare.22822037
title: Independence Weights for Causal Inference with Continuous Treatments

description: Studying causal effects of continuous treatments is important for gaining a deeper understanding of many interventions, policies, or medications, yet researchers are often left with observational studies for doing so. In the observational setting, confounding is a barrier to the estimation of causal effects. Weighting approaches seek to control for confounding by reweighting samples so that confounders are comparable across different treatment values. Yet, for continuous treatments, weighting methods are highly sensitive to model misspecification. In this article we elucidate the key property that makes weights effective in estimating causal quantities involving continuous treatments. We show that to eliminate confounding, weights should make treatment and confounders independent on the weighted scale. We develop a measure that characterizes the degree to which a set of weights induces such independence. Further, we propose a new model-free method for weight estimation by optimizing our measure. We study the theoretical properties of our measure and our weights, and prove that our weights can explicitly mitigate treatment-confounder dependence. The empirical effectiveness of our approach is demonstrated in a suite of challenging numerical experiments, where we find that our weights are quite robust and work well under a broad range of settings. Supplementary materials for this article are available online.