cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/peqhirfakiasbk-uhfffaoysa-n.2
title: Tetraphenylmenthan
title: InChI=1S/C25H20/c1-5-13-21(14-6-1)25(22-15-7-2-8-16-22,23-17-9-3-10-18-23)24-19-11-4-12-20-24/h1-20H

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C25H20/c1-5-13-21(14-6-1)25(22-15-7-2-8-16-22,23-17-9-3-10-18-23)24-19-11-4-12-20-24/h1-20H, and canonical SMILES descriptor[cheminf_000007]: c1ccc(cc1)C(c1ccccc1)(c1ccccc1)c1ccccc1, and by the IUPAC name[cheminf_000107]: tritylbenzene. The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-33571 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 274.0 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0000563 | fast-atom bombardment mass spectrometry (FABMS) CHMO:0000498 | high-resolution mass spectrometry (HRMS) CHMO:0000630 | infrared absorption spectroscopy (IR) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.14272/peqhirfakiasbk-uhfffaoysa-n/chmo0000563
title: fast-atom bombardment mass spectrometry (FABMS) (tritylbenzene)
title: InChI=1S/C25H20/c1-5-13-21(14-6-1)25(22-15-7-2-8-16-22,23-17-9-3-10-18-23)24-19-11-4-12-20-24/h1-20H

description: dataset for fast-atom bombardment mass spectrometry (FABMS) MS (FAB, 3-NBA), m/z (%): 320 (1) [M]+, 309 (3), 308 (10), 307 (36), 292 (3), 291 (4), 290 (6), 289 (13), 273 (2),260 (2), 244 (2), 243 (4), 242 (2), 195 (8), 169 (2), 168 (2), 167 (4), 166 (5), 165 (5), 156 (7), 155 (32), 154 (100), 153 (6), 152 (7), 151 (3), 150 (3), 149 (2), 140 (3), 139 (15), 138 (36), 137 (71), 136 (60), 135 (9), 128 (2), 25 (2), 124 (9), 123 (5), 122 (4), 121 (7), 120 (10), 119 (5), 115 (3), 109 (2), 108 (6), 107 (17), 106 (5), 105 (5), 97 (2), 95 (3), 94 (2), 93 (2), 92 (2), 91 (9), 90 (9), 89 (14).
DOI: 10.14272/peqhirfakiasbk-uhfffaoysa-n/chmo0000630.1
title: infrared absorption spectroscopy (IR) (tritylbenzene)
title: InChI=1S/C25H20/c1-5-13-21(14-6-1)25(22-15-7-2-8-16-22,23-17-9-3-10-18-23)24-19-11-4-12-20-24/h1-20H

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3085 (vw), 3055 (vw), 3029 (vw), 1679 (w), 1592 (w), 1492 (w), 1441 (w), 1385 (vw), 1183 (w), 1153 (vw), 1112 (vw), 1082 (w), 1035 (w), 1001 (w), 990 (vw), 891 (vw), 765 (m), 749 (s), 700 (vs), 633 (s), 620 (w), 524 (w), 492 (w) cm–1.
DOI: 10.14272/peqhirfakiasbk-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) (tritylbenzene)
title: InChI=1S/C25H20/c1-5-13-21(14-6-1)25(22-15-7-2-8-16-22,23-17-9-3-10-18-23)24-19-11-4-12-20-24/h1-20H

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–FAB (m/z): [M]+ calcd for C25H20 320.1560; found 320.1558.
DOI: 10.14272/peqhirfakiasbk-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (tritylbenzene)
title: InChI=1S/C25H20/c1-5-13-21(14-6-1)25(22-15-7-2-8-16-22,23-17-9-3-10-18-23)24-19-11-4-12-20-24/h1-20H

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, Chloroform-d [77.0 ppm], ppm) δ = 146.8 (4C, Cq), 131.2 (8C, +, CArH), 127.4 (8C, +, CArH), 125.9 (4C, +, CArH), 65.0 (Cq).
DOI: 10.48510/fk2/xcrk4h/dstotj
title: Data_employers_survey_2009_2010_lv.csv

description: :unav
DOI: 10.48510/fk2/xcrk4h/k71qu6
title: questionnaire_employers_survey_2009_2010_lv.pdf

description: :unav
DOI: 10.48510/fk2/xcrk4h/8grdgh
title: Data_employers_survey_2009_2010_lv.tab

description: :unav
DOI: 10.48510/fk2/xcrk4h/r5ymkk
title: Methodology_employers_survey_2009_2010_lv.pdf

description: :unav
DOI: 10.48510/fk2/xcrk4h
title: Working Conditions and Risks in Latvia 2009 - 2010: Survey of Employers

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: 10.6084/m9.figshare.23294666
title: Supplementary Material for: Clinical Prediction Models and Predictors for Death or Adverse Neurodevelopmental Outcome in Term Newborns with Hypoxic-Ischemic Encephalopathy: A Systematic Review of the Literature

description: <b><i>Background:</i></b> Although many predictive parameters have been studied, an internationally accepted, validated predictive model to predict the clinical outcome of asphyxiated infants suffering from hypoxic-ischemic encephalopathy is currently lacking. The aim of this study was to identify, appraise and summarize available clinical prediction models, and provide an overview of all investigated predictors for the outcome death or neurodevelopmental impairment in this population. <b><i>Methods:</i></b> A systematic literature search was performed in Medline and Embase. Two reviewers independently included eligible studies and extracted data. The quality was assessed using PROBAST for prediction model studies and QUIPS assessment tools for predictor studies. <b><i>Results:</i></b> A total of nine prediction models were included. These models were very heterogeneous in number of predictors assessed, methods of model derivation, and primary outcomes. All studies had a high risk of bias following the PROBAST assessment and low applicability due to complex model presentation. A total of 104 predictor studies were included investigating various predictors, showing tremendous heterogeneity in investigated predictors, timing of predictors, primary outcomes, results, and methodological quality according to QUIPS. Selected high-quality studies with accurate discriminating performance provide clinicians and researchers an evidence map of predictors for prognostication after HIE in newborns. <b><i>Conclusion:</i></b> Given the low methodological quality of the currently published clinical prediction models, implementation into clinical practice is not yet possible. Therefore, there is an urgent need to develop a prediction model which complies with the PROBAST guideline. An overview of potential predictors to include in a prediction model is presented.
DOI: 10.6084/m9.figshare.23294666.v1
title: Supplementary Material for: Clinical Prediction Models and Predictors for Death or Adverse Neurodevelopmental Outcome in Term Newborns with Hypoxic-Ischemic Encephalopathy: A Systematic Review of the Literature

description: <b><i>Background:</i></b> Although many predictive parameters have been studied, an internationally accepted, validated predictive model to predict the clinical outcome of asphyxiated infants suffering from hypoxic-ischemic encephalopathy is currently lacking. The aim of this study was to identify, appraise and summarize available clinical prediction models, and provide an overview of all investigated predictors for the outcome death or neurodevelopmental impairment in this population. <b><i>Methods:</i></b> A systematic literature search was performed in Medline and Embase. Two reviewers independently included eligible studies and extracted data. The quality was assessed using PROBAST for prediction model studies and QUIPS assessment tools for predictor studies. <b><i>Results:</i></b> A total of nine prediction models were included. These models were very heterogeneous in number of predictors assessed, methods of model derivation, and primary outcomes. All studies had a high risk of bias following the PROBAST assessment and low applicability due to complex model presentation. A total of 104 predictor studies were included investigating various predictors, showing tremendous heterogeneity in investigated predictors, timing of predictors, primary outcomes, results, and methodological quality according to QUIPS. Selected high-quality studies with accurate discriminating performance provide clinicians and researchers an evidence map of predictors for prognostication after HIE in newborns. <b><i>Conclusion:</i></b> Given the low methodological quality of the currently published clinical prediction models, implementation into clinical practice is not yet possible. Therefore, there is an urgent need to develop a prediction model which complies with the PROBAST guideline. An overview of potential predictors to include in a prediction model is presented.
DOI: 10.4121/ef3d2f15-ebf8-48c3-aeb4-629e176f9d05.v2
title: Raw data to "The role of the current in reverse bias degradation of perovskite solar cells"

description: This dataset contains the raw data that is used in the letter "The role of the current in reverse bias degradation of perovskite solar cells".It includes the results of the two characterization steps 1 and 2 (before/after reverse bias degradation), consisting of IV curves, solar cells parameters from IV measurements, dark IV curves (DIV), extended dark IV curves (DIVext), maximum-power-point-tracking (MPPT), and reverse bias currents (RevBiasCurrents). The samples were perovskite solar cells that had a cell area of 0.16 cm2. Four cells were on one glass superstrate which had an area of 3x3 cm2. Further details about the cells can be found in the letter and its accompanying supporting information.
DOI: 10.26050/wdcc/ar6.c6spdkme2
title: IPCC DDC: DKRZ MPI-ESM1.2-HR model output prepared for CMIP6 ScenarioMIP

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.DKRZ.MPI-ESM1-2-HR' 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-HR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 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 Deutsches Klimarechenzentrum, Hamburg 20146, Germany (DKRZ) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, landIce: none, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.
DOI: 10.6084/m9.figshare.23831049.v2
title: Supplementary data for: Excessive free fatty acids sensing in pituitary lactotrophs elicits liver steatosis by decreasing prolactin levels

description: Supplementary data for: Excessive free fatty acids sensing in pituitary lactotrophs elicits liver steatosis by decreasing prolactin levels
DOI: 10.6084/m9.figshare.23831049.v1
title: Supplementary data for: Excessive free fatty acids sensing in pituitary lactotrophs elicits liver steatosis by<i> </i>decreasing prolactin levels

description: <b>Background & Aims:</b> It has been known that overnutrition-associated elevation of serum free fatty acids (FFA) exerts toxic effects on hepatic lipid metabolism. Pituitary is the central endocrine gland with effects on lipid metabolism. However, it is not clear whether the pituitary responds to FFA toxicity. Herein, we aimed to investigate the role of FFA sensing in the pituitary, thus regulating hepatic lipid metabolism.<b>Methods:</b> A cohort including 328 biopsy-proven subjects were analyzed to investigate the association between pituitary hormones and NAFLD. Dynamic diets intervention and stereotactic FFA injection targeted to mice pituitary were performed. Lipid uptake assays and silencing-viruses transfection were used to assess the role of FFA sensing in lactotrophs. Fluorescence analysis was used to assess localization of SSO delivery system (TRH-PEG-LP-SSO) in pituitary. Virus injection in pituitary and pituitary-targeted delivery system was developed to investigate the therapeutic effects on fatty liver.<b>Results:</b> Elevated levels of FFA increased the risk of NAFLD (OR 1.645, <i>p</i> &lt; 0.05), which was mediated by decreased PRL levels with a mediation effect of 29.1% (<i>p</i> &lt; 0.05). Moreover, elevation of FFA contributed to decreased serum PRL levels, thus promoted liver steatosis <i>in vivo</i>. Mechanic studies showed that increased CD36 expression in lactotrophs enhanced FFA sensing and uptake, thus inhibited the synthesis of PRL. Importantly, silencing of pituitary CD36 by stereotactic virus injection, as well as by the targeted drug delivery system of TRH-PEG-LP-SSO, could efficiently elevate PRL levels and alleviate liver steatosis.<b>Conclusions:</b> Excessive FFA sensing in pituitary lactotrophs plays new roles in liver steatosis by decreasing PRL expression. Targeted inhibition of FFA sensing in pituitary may be a potential therapeutic target for liver steatosis.
DOI: 10.6084/m9.figshare.23741541
title: <strong>Older adults’ experience of neuropsychological assessments for dementia screening in South India: a qualitative study.</strong>

description: De-identified interview transcripts and the interview questionnaire used for the research in India with title <strong>Older adults’ experience of neuropsychological assessments for dementia screening in South India: a qualitative study.</strong>
DOI: 10.6084/m9.figshare.23741541.v1
title: <strong>Older adults’ experience of neuropsychological assessments for dementia screening in South India: a qualitative study.</strong>

description: De-identified interview transcripts and the interview questionnaire used for the research in India with title <strong>Older adults’ experience of neuropsychological assessments for dementia screening in South India: a qualitative study.</strong>
DOI: 10.6084/m9.figshare.23826297
title: RNA-seq: differential expression of dopaminergic neurons treated with Glucocerebrosides.

description: RNA-seq differential expression of human stem cell (WA09) derived dopaminergic neurons treated with DMSO (ctrl) or Glucocerebrosides (2.5 uM or 40 uM) for 7days.
DOI: 10.6084/m9.figshare.23826297.v1
title: RNA-seq: differential expression of dopaminergic neurons treated with Glucocerebrosides.

description: RNA-seq differential expression of human stem cell (WA09) derived dopaminergic neurons treated with DMSO (ctrl) or Glucocerebrosides (2.5 uM or 40 uM) for 7days.
DOI: 10.23728/b2share.8fdc439ba4aa4980ac86e6a2d9a702e6
title: DICE: Final report on Communications & Dissemination

description: The document is the final report on the activities that were carried out during the project to steer the DICE users’ engagement according to the communication and dissemination strategy.
DOI: 10.23728/b2share.9050a9f63c664e808505d2484724c424
title: DICE: Training Final Report

description: The document is the final report on the activities that were carried out during the project in the area of training. It includes reporting on the events (hackathons and datathon) as well as the training materials prepared and packaged as a legacy from the project.
DOI: 10.20383/103.0786
title: Organizational Structure around Web-scale Discovery Services in Canadian Academic Libraries

description: An online survey was created in a Canadian instance of Survey Monkey to solicit responses from academic library staff in Canada to share insights and observations related to web-scale discovery services. At the end of the survey, respondents could volunteer to participate in semi-structured interviews by adding their contact details to a separate webform. Survey participation requests were sent via several Canadian consortia email lists related to academic library collections in late September 2019 and again in November 2019. Six (6) semi-structured interviews were conducted between October 2019 and January 2020. The interviews were recorded using Voice Memos and then transcribed by the principal investigator.
DOI: 10.5281/zenodo.6651751
title: LocScale-EMmerNet deep learning models for contrast optimisation of cryo-EM maps

description: EMmerNet deep learning models local optimisation of cryo-EM map contrast using LocScale.
description: {"references": ["Bharadwaj, A and Jakobi, AJ: LocScale - reference-based sharpening of cryo-EM maps. (2022); https://gitlab.tudelft.nl/aj-lab/locscale", "Bharadwaj A and Jakobi AJ: Electron scattering properties of biological macromolecules and their use in cryo-EM map sharpening (2022). Faraday Discussions, DOI https://doi.org/10.1039/D2FD00078D"]}
DOI: 10.5281/zenodo.6651750
title: LocScale-EMmerNet deep learning models for contrast optimisation of cryo-EM maps

description: EMmerNet deep learning models for local optimisation of cryo-EM map contrast using LocScale.
description: {"references": ["Bharadwaj, A and Jakobi, AJ: LocScale - reference-based sharpening of cryo-EM maps. (2022); https://gitlab.tudelft.nl/aj-lab/locscale", "Bharadwaj A and Jakobi AJ: Electron scattering properties of biological macromolecules and their use in cryo-EM map sharpening (2022). Faraday Discussions, DOI https://doi.org/10.1039/D2FD00078D"]}
DOI: 10.5281/zenodo.6651990
title: LocScale-EMmerNet deep learning models for contrast optimisation of cryo-EM maps

description: EMmerNet deep learning models local optimisation of cryo-EM map contrast using LocScale.
description: {"references": ["Bharadwaj, A and Jakobi, AJ: LocScale - reference-based sharpening of cryo-EM maps. (2022); https://gitlab.tudelft.nl/aj-lab/locscale", "Bharadwaj A and Jakobi AJ: Electron scattering properties of biological macromolecules and their use in cryo-EM map sharpening (2022). Faraday Discussions, DOI https://doi.org/10.1039/D2FD00078D"]}
DOI: 10.5281/zenodo.6651995
title: LocScale-EMmerNet deep learning models for contrast optimisation of cryo-EM maps

description: EMmerNet deep learning models for local optimisation of cryo-EM map contrast using LocScale.
description: {"references": ["Bharadwaj, A and Jakobi, AJ: LocScale - reference-based sharpening of cryo-EM maps. (2022); https://gitlab.tudelft.nl/aj-lab/locscale", "Bharadwaj A and Jakobi AJ: Electron scattering properties of biological macromolecules and their use in cryo-EM map sharpening (2022). Faraday Discussions, DOI https://doi.org/10.1039/D2FD00078D"]}
DOI: 10.5281/zenodo.8211668
title: LocScale-EMmerNet deep learning models for contrast optimisation of cryo-EM maps

description: EMmerNet deep learning models for local optimisation of cryo-EM map contrast using LocScale.
description: {"references": ["Bharadwaj, A and Jakobi, AJ: LocScale - reference-based sharpening of cryo-EM maps. (2022); https://gitlab.tudelft.nl/aj-lab/locscale", "Bharadwaj A and Jakobi AJ: Electron scattering properties of biological macromolecules and their use in cryo-EM map sharpening (2022). Faraday Discussions, DOI https://doi.org/10.1039/D2FD00078D"]}
DOI: 10.6084/m9.figshare.23833140
title: Phase diagram and permeability evolution in a dissolving vertical fracture

description: This is the dataset for "Phase diagram and permeability evolution in a dissolving vertical fracture" by Li et al., including experimental data and numerical results.
DOI: 10.21227/d5rx-hf51
title: DSDCVGG19 video data

description: With the development and implementation of convolutional neural networks in pattern recognition, there are large number of parameters needs to calculate and storage, which makes the algorithm hard to run in common computer. For the mine vehicle refinement recognition project we are currently studying, how to obtain and analyze the feature information of the target in the image on top of the limited computer arithmetic power, and maximize the accuracy and efficiency of the experimental research become the main purpose of the research. In this paper we propose a dense connectivity and deeply separable  VGG19  network model with three tricks to overcome this problem. The three tricks are convolution instead of full connectivity; the deeply separable convolutions; dense connectivity network module. The first two methods could reduce the parameters and calculate. The third trick makes the model have more features in limited parameters. The combination of the three improved methods achieves a better result in vehicle head and tail recognition. The experimental results show that the optimized model improves the recognition accuracy (4.41% compared to VGG19) while drastically reducing the parameters (71% compared to VGG19).
DOI: 10.5281/zenodo.7814297
title: APOGEE-TESS Verification

description: This dataset contains stars from NASA's TESS mission and APOGEE to test TESS's calibration comparatively to the Kepler scale. Link to publication: Arxiv: https://arxiv.org/abs/2307.13853 RNAAS: https://iopscience.iop.org/article/10.3847/2515-5172/ace7af
DOI: 10.5281/zenodo.7814296
title: APOGEE-TESS Verification

description: This dataset contains stars from NASA's TESS mission and APOGEE to test TESS's calibration comparatively to the Kepler scale. Link to publication: Arxiv: https://arxiv.org/abs/2307.13853 RNAAS: https://iopscience.iop.org/article/10.3847/2515-5172/ace7af
DOI: 10.5517/ccdc.csd.cc28zs02
title: CCDC 2114944: Experimental Crystal Structure Determination

description: Related Article: Qi Li, Yuting Liu, Lijuan Liang, Xiangyu Zhang, Kun Huang, Dabin Qin|2023|Spectrochim.Acta,Part A|302|123124|doi:10.1016/j.saa.2023.123124
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.