cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26050/wdcc/ar6.c6cmicsae
title: IPCC DDC: CSIRO ACCESS-ESM1.5 model output prepared for CMIP6 C4MIP

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.C4MIP.CSIRO.ACCESS-ESM1-5' 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 Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 climate model, released in 2019, includes the following components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run by the Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (CSIRO) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6cmicsaehb
title: IPCC DDC: CSIRO ACCESS-ESM1.5 model output prepared for CMIP6 C4MIP hist-bgc

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.C4MIP.CSIRO.ACCESS-ESM1-5.hist-bgc' 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 Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 climate model, released in 2019, includes the following components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run by the Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (CSIRO) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.17632/n66rp59tr7.2
title: Priced risk in corporate bonds replication package

description: The code in this replication package generates Tables 1 to 6 and Figures 1 to 2 in the paper titled “Priced risk in corporate bonds,” by Dickerson, Mueller, and Robotti (2023, henceforth DMR). The code to generate Tables 1 to 5 and Figures 1 to 2 are written in Matlab. Table 6 is generated with Python only. The file RunAllResults.m, the ‘one-push-button’, takes about 2 minutes to execute, and will produce all of the results in the paper except for Table 6. These results are printed to the Matlab console, saved as AllTablesReport and also stored in Matlab arrays such that they can be exported to other file formats. The results for Table 6 are produced by executing the Python script Table6.py. The authors have set up a dedicated replication/companion website (Open Source Bond Asset Pricing) which can be accessed here: https://openbondassetpricing.com/. This README file guides the user through replicating the results of the paper as well as constructing the main database from scratch.
DOI: 10.5281/zenodo.4707476
title: VRCR dataset clean

description: Data collected on the sound-only version of the VRCR virtual reality platform. The first row contains a json-like header reporting the parameters used to clean the raw kinematic data and extract the kinematic measures. Data cleaning has been performed in MATLAB with custom code.
DOI: 10.5281/zenodo.4707477
title: VRCR dataset clean

description: Data collected on the sound-only version of the VRCR virtual reality platform. The first row contains a json-like header reporting the parameters used to clean the raw kinematic data and extract the kinematic measures. Data cleaning has been performed in MATLAB with custom code.
DOI: 10.6084/m9.figshare.23904516
title: Electron–ion relaxation times in warm dense aluminum and gold

description: Temperature evolution and relaxation times of warm dense aluminum and gold.
DOI: 10.6084/m9.figshare.23904516.v1
title: Electron–ion relaxation times in warm dense aluminum and gold

description: Temperature evolution and relaxation times of warm dense aluminum and gold.
DOI: 10.6084/m9.figshare.22292479
title: HNSCC data and code

description: We characterized the immune context in HPV+ and HPV− HNSCC by integrating scRNA-seq and bulk RNA-seq data.
DOI: 10.6084/m9.figshare.23912856
title: Posture_4520_my_yolo_dataset contains 4520 images——val

description: The Posture_4520_my_yolo_dataset contains 4520 images. According to the ratio of 8:1:1, the training set (3616), the verification set (452), the test set (452).
DOI: 10.6084/m9.figshare.23912856.v2
title: Posture_4520_my_yolo_dataset contains 4520 images——val

description: The Posture_4520_my_yolo_dataset contains 4520 images. According to the ratio of 8:1:1, the training set (3616), the verification set (452), the test set (452).
DOI: 10.6084/m9.figshare.23912856.v1
title: Posture_4520_my_yolo_dataset contains 4520 images——train10

description: The Posture_4520_my_yolo_dataset contains 4520 images. According to the ratio of 8:1:1, the training set (3616), the verification set (452), the test set (452).
DOI: 10.6084/m9.figshare.23912541
title: The Posture_4520_my_yolo_dataset contains 4520 images——train7

description: The Posture_4520_my_yolo_dataset contains 4520 images. According to the ratio of 8:1:1, the training set (3616), the verification set (452), the test set (452).
DOI: 10.6084/m9.figshare.23921976
title: Supplementary Data for Nature submission

description: Supplementary Data for Nature submission
DOI: 10.6084/m9.figshare.23921976.v1
title: Supplementary Data for Nature submission

description: Supplementary Data for Nature submission
DOI: 10.25592/uhhfdm.10273
title: Radiometer grid at Falkenberg and surroundings, downwelling shortwave radiation, FESSTVaL campaign

description: This dataset contains measurements of downwelling short wave irradiance, measured in a small scale grid setup at Falkenberg: 20 sensors in 4 by 5 grid with a 50 meter grid spacing. Another 4 sensors were placed in all direction about 5 km away from the main grid at Falkenberg. The sampling rate is 10 Hz, to catch all irradiance variability, and is calibrated against a high quality sun tracker. The strength of this dataset is not the absolute accuracy, but rather the spatial measurements and ability to catch variability. <strong>Quality</strong>: Accuracy is estimated to be within 5% of a conventional pyranometer. Quality varies depending on weather type, but is best for high solar elevation angles (solar noon +/- 4 hours). Data is manually quality controlled, with detailed quality flags included in the dataset. Some anomalous data is not caught, in particular noisy data due to many insects on the sensor or small dirt from birds that reduces the signal slightly. These effects are much smaller than the driving weather patterns. The data is unsuitable for calculating radiation balances, but it is particularly useful for studying variability and patterns of solar irradiance on small scales. <strong>Funding</strong>: Dutch Research Council (NWO), Shedding Light On Cloud Shadows: VI.Vidi.192.068
description: Project: FESSTVaL (Field Experiment on submesoscale spatio-temporal variability in Lindenberg), a measurement campaign initiated by the Hans-Ertel-Center for Weather Research.
DOI: 10.6084/m9.figshare.23828772.v2
title: Underlying data 'Row Data of specific activity of SULT2B1a WT and allozymes in presence of Pregnenolone (Excel files) and Figures (Prism files)'

description: The specific activity of SULT2B1a WT and allozymes in the presence of pregnenolone.<br>
DOI: 10.6084/m9.figshare.23828772
title: Underlying data 'Row Data of specific activity of SULT2B1a WT and allozymes in presence of Pregnenolone (Excel files) and Figures (Prism files)'

description: The specific activity of SULT2B1a WT and allozymes in the presence of pregnenolone.<br>
DOI: 10.6084/m9.figshare.23828772.v1
title: Row Data ( Excel ) and Figure ( Prism)

description: The specific activity of SULT2B1a WT and allozymes in the presence of pregnenolone.<br>
DOI: 10.6084/m9.figshare.23922006
title: Supplementary Material for: Childhood-onset Refractory Hypertension Results from Neurofibromatosis type 1 Caused by a Splicing NF1 mutation

description: Background: Neurofibromatosis type 1 (NF-1) is caused by mutations in the NF1 gene that encodes neurofibromin, a negative regulator of RAS proto-oncogene. Approximately one-third of the reported pathogenic mutations in NF1 are splicing mutations, but most consequences are unclear. The objective of this study was to identify the pathogenicity of splicing mutation in a Chinese family with NF-1 and determine the effects of the pre-mRNA splicing mutation by in vitro functional analysis. Methods: Next-generation sequencing was used to screen candidate mutations. We performed a minigene splicing assay to determine the effect of the splicing mutation on NF1 expression and three-dimensional structure models of neurofibromin were generated using SWISS-MODEL and PROCHECK method, respectively. Results: A pathogenic splicing mutation c.479+1G&gt;C in NF1 was found in the proband characterized by childhood-onset refractory hypertension. In vitro analysis demonstrated that c.479+1G&gt;C mutation caused skipping of exon 4, leading to a Glutamine to Valine substitution at position 97 in neurofibromin and an open reading frame shift terminating at codon 108. Protein modelling showed that several major domains were missing in the truncated neurofibromin protein. Conclusion: The splicing mutation c.479+1G&gt;C identified in a Chinese patient with NF-1 and childhood-onset refractory hypertension caused skipping of exon 4 and a truncated protein. Our findings offered new evidence for the molecular diagnosis of NF-1.
DOI: 10.6084/m9.figshare.23922006.v1
title: Supplementary Material for: Childhood-onset Refractory Hypertension Results from Neurofibromatosis type 1 Caused by a Splicing NF1 mutation

description: Background: Neurofibromatosis type 1 (NF-1) is caused by mutations in the NF1 gene that encodes neurofibromin, a negative regulator of RAS proto-oncogene. Approximately one-third of the reported pathogenic mutations in NF1 are splicing mutations, but most consequences are unclear. The objective of this study was to identify the pathogenicity of splicing mutation in a Chinese family with NF-1 and determine the effects of the pre-mRNA splicing mutation by in vitro functional analysis. Methods: Next-generation sequencing was used to screen candidate mutations. We performed a minigene splicing assay to determine the effect of the splicing mutation on NF1 expression and three-dimensional structure models of neurofibromin were generated using SWISS-MODEL and PROCHECK method, respectively. Results: A pathogenic splicing mutation c.479+1G&gt;C in NF1 was found in the proband characterized by childhood-onset refractory hypertension. In vitro analysis demonstrated that c.479+1G&gt;C mutation caused skipping of exon 4, leading to a Glutamine to Valine substitution at position 97 in neurofibromin and an open reading frame shift terminating at codon 108. Protein modelling showed that several major domains were missing in the truncated neurofibromin protein. Conclusion: The splicing mutation c.479+1G&gt;C identified in a Chinese patient with NF-1 and childhood-onset refractory hypertension caused skipping of exon 4 and a truncated protein. Our findings offered new evidence for the molecular diagnosis of NF-1.
DOI: 10.6084/m9.figshare.21119526
title: A comparison of intervertebral ligament properties utilized in a thoracic spine functional unit through kinematic evaluation

description: Ligament properties in the literature are variable, yet scarce, but needed to calibrate computational models for spine clinical research applications. A comparison of ligament stiffness properties and their effect on the kinematic behavior of a thoracic functional spinal unit (FSU) is examined in this paper. Six unique ligament property sets were utilized within a volumetric T7–T8 finite element (FE) model developed using computer-aided design (CAD) spinal geometry. A 7.5 Nm moment was applied along three anatomical planes both with and without costovertebral (CV) joints present. Range of Motion (RoM) was assessed for each property set and compared to published experimental data. Intact and serial ligament removal procedures were implemented in accordance with experimental protocol. The variance in both kinematic behavior and comparability with experimental data among property sets emphasizes the role nonlinear characterization plays in determining proper kinematic behavior in spinal FE models. Additionally, a decrease in RoM variation among property sets was exhibited when the model setup incorporated the CV joint. With proper assessment of the source and size of each ligament, the material properties considered here could be expanded and justified for implementation into thoracic spine clinical studies.
DOI: 10.6084/m9.figshare.21119526.v1
title: A comparison of intervertebral ligament properties utilized in a thoracic spine functional unit through kinematic evaluation

description: Ligament properties in the literature are variable, yet scarce, but needed to calibrate computational models for spine clinical research applications. A comparison of ligament stiffness properties and their effect on the kinematic behavior of a thoracic functional spinal unit (FSU) is examined in this paper. Six unique ligament property sets were utilized within a volumetric T7–T8 finite element (FE) model developed using computer-aided design (CAD) spinal geometry. A 7.5 Nm moment was applied along three anatomical planes both with and without costovertebral (CV) joints present. Range of Motion (RoM) was assessed for each property set and compared to published experimental data. Intact and serial ligament removal procedures were implemented in accordance with experimental protocol. The variance in both kinematic behavior and comparability with experimental data among property sets emphasizes the role nonlinear characterization plays in determining proper kinematic behavior in spinal FE models. Additionally, a decrease in RoM variation among property sets was exhibited when the model setup incorporated the CV joint. With proper assessment of the source and size of each ligament, the material properties considered here could be expanded and justified for implementation into thoracic spine clinical studies.
DOI: 10.34740/kaggle/dsv/6281133
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.8182960
title: Education- and age-specific fertility rates for 50 African and Latin American countries between 1970 and 2020

description: <strong>Education- and age-specific fertility rates for 50 African and Latin American countries between 1970 and 2020</strong>. The fertility rates are consistent with the United Nation's World Population Prospects (UN WPP) 2022 fertility rates. The Bayesian model developed to reconstruct the fertility rates using Demographic and Health Surveys and the UN WPP is published in a working paper. <strong>Abstract:</strong> Consistent and reliable time series of education- and age-specific fertility rates for the past are difficult to obtain in developing countries, although they are needed to evaluate the impact of women’s education on fertility along periods and cohorts. In this paper, we propose a Bayesian framework to reconstruct age-specific fertility rates by level of education using prior information from the birth history module of the Demographic and Health Surveys (DHS) and the UN World Population Prospects. In our case study regions, we reconstruct age- and education-specific fertility rates which are consistent with the UN age specific fertility rates by four levels of education for 50 African and Latin American countries from 1970 to 2020 in five-year steps. Our results show that the Bayesian approach allows for estimating reliable education- and age-specific fertility rates using multiple rounds of the DHS surveys. The time series obtained confirm the main findings of the literature on fertility trends, and age and education specific differentials. <strong>Funding:</strong> These data sets are part of the BayesEdu Project at Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna) funded from the “Innovation Fund Research, Science and Society” by the Austrian Academy of Sciences (ÖAW). <strong>Variables:</strong> Country: Country names Education: Four education levels, No Education, Primary Education, Secondary Education and Higher Education. Age group: Five-year age groups between 15-19 and 45-49. Year: Five-year periods between 1970 and 2020. Median: Median education and age-specific fertility rate estimate Upper_CI: 95% Upper Credible Interval Lower_CI: 95% Lower Credible Interval <strong>List of countries:</strong> Angola Benin Brazil Burkina Faso Burundi Cameroon Central African Republic Chad Colombia Comoros Congo Côte D'Ivoire DR Congo Ecuador Egypt Eswatini Ethiopia Gabon Gambia Ghana Guatemala Guinea Honduras Kenya Lesotho Liberia Madagascar Malawi Mali Mexico Morocco Mozambique Namibia Nicaragua Niger Nigeria Paraguay Peru Rwanda Sao Tome and Principe Senegal Sierra Leone South Africa Sudan Tanzania Togo Tunisia Uganda Zambia Zimbabwe
description: {"references": ["Durowaa-Boatend, A., Yildiz, D. , & Goujon, A. (2023). A Bayesian model for the reconstruction of education- and age-specific fertility rates: An application to African and Latin American countries. IIASA Working Paper. Laxenburg, Austria: WP-23-007"]}
DOI: 10.5517/ccdc.csd.cc1yv2mh
title: CCDC 1812527: Experimental Crystal Structure Determination

description: Related Article: Barry M. Trost, Chao-I Hung, Tanguy Saget, Elumalai Gnanamani|2018|Nat. Catal.|1|523|doi:10.1038/s41929-018-0093-6
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: 10.6084/m9.figshare.23922381
title: Supplementary Material for: Childhood-onset Refractory Hypertension Results from Neurofibromatosis type 1 Caused by a Splicing NF1 mutation

description: Background: Neurofibromatosis type 1 (NF-1) is caused by mutations in the NF1 gene that encodes neurofibromin, a negative regulator of RAS proto-oncogene. Approximately one-third of the reported pathogenic mutations in NF1 are splicing mutations, but most consequences are unclear. The objective of this study was to identify the pathogenicity of splicing mutation in a Chinese family with NF-1 and determine the effects of the pre-mRNA splicing mutation by in vitro functional analysis. Methods: Next-generation sequencing was used to screen candidate mutations. We performed a minigene splicing assay to determine the effect of the splicing mutation on NF1 expression and three-dimensional structure models of neurofibromin were generated using SWISS-MODEL and PROCHECK method, respectively. Results: A pathogenic splicing mutation c.479+1G&gt;C in NF1 was found in the proband characterized by childhood-onset refractory hypertension. In vitro analysis demonstrated that c.479+1G&gt;C mutation caused skipping of exon 4, leading to a Glutamine to Valine substitution at position 97 in neurofibromin and an open reading frame shift terminating at codon 108. Protein modelling showed that several major domains were missing in the truncated neurofibromin protein. Conclusion: The splicing mutation c.479+1G&gt;C identified in a Chinese patient with NF-1 and childhood-onset refractory hypertension caused skipping of exon 4 and a truncated protein. Our findings offered new evidence for the molecular diagnosis of NF-1.