cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.11583/dtu.12783389
title: EMPIR 15SIB07 PhotoLED - Database of LED product spectra

description: This dataset consists of 1494 relative spectral power distributions (SPD) collected by the partners and collaborators of project EMPIR 15SIB07 PhotoLED - Future Photometry Based on Solid-State Lighting Products. The SPDs of LED products of different types were measured; including AC- and DC-operated bulbs, spots, tubes, street lamps, LED strips, downlight luminaires, prints and textures by a large number of manufacturers. The measurements of the products were carried out in various laboratories, including manufacturers of LED products, test laboratories, and National Metrology Institutes (NMI). The products included in the study were manufactured in the timespan of 2009–2016. Due to the sensitivity of the data, the individual sources of data have been anonymized, the authors retain this information as confidential. The SPDs are numbered S with n between 1 and 1495, sorted by the correlated color temperature (CCT) calculated using equation published by MacCamy in 1992. The data was used in the analysis of LED illuminants and reference spectra for photometer calibration that has been published as a scientific paper Alexander Kokka et al. [1].<br> <br> <strong>Note to version 2 of the database</strong> <br> The initial release of the dataset included approximate CCT values calculated for the spectra using the equation by MacCamy[2], with the purpose of enabling sorting of the data based on CCT. It is known that the MacCamy method produces deviations from calculations using the CIE definition[3]. With some of the spectra, these were considered to be so large as to cause confusion. Therefore the CCT values calculated using the CIE definition have been added to the data. The numbering of the SPDs has been kept, and the CCT calculated with the MacCamy method has been kept for data consistency. An SPD with only zero values (S1240) was removed, from the dataset. It should further be noted that since the dataset includes measurements dating back to 2009, many sources do not comply with modern regulation and requirements for color rendering index and chromaticity. Regarding the derived quantities Rf, Ra, R9, Duv, these have been added for each SPD. A few editorial changes have been made to the accompanying meta data. <br> <strong>Update of metadata</strong> <br> Editorial changes to include information on the support from EMPIR project 19NRM02 RevStdLED. The datafile itself was not changed. <br> <strong>References</strong> <br> [1] A. Kokka et al., “Development of white LED illuminants for colorimetry and recommendation of white LED reference spectrum for photometry,” Metrologia, vol. 55, no. 4, pp. 526–534, Aug. 2018. https://doi.org/10.1088/1681-7575/aacae7 <br> [2] C. S. McCamy, “Correlated color temperature as an explicit function of chromaticity coordinates,” Color Res. Appl., vol. 17, no. 2, pp. 142–144, Apr. 1992. https://doi.org/10.1002/col.5080170211 <br> [3] correlated colour temperature CCT, Term 17-23-068 of the CIE S 017:2020 ILV: International Lighting Vocabulary, 2nd edition. https://cie.co.at/eilvterm/17-23-068<br>
DOI: 10.11583/dtu.12783389.v1
title: EMPIR 15SIB07 PhotoLED - Database of LED product spectra

description: This dataset consists of 1495 relative spectral power distributions (SPD) collected by the partners and collaborators of project EMPIR 15SIB07 PhotoLED - Future Photometry Based on Solid-State Lighting Products. The SPDs of LED products of different types were measured; including AC- and DC-operated bulbs, spots, tubes, street lamps, LED strips, downlight luminaires, prints and textures by a large number of manufacturers. The measurements of the products were carried out in various laboratories, including manufacturers of LED products, test laboratories, and National Metrology Institutes (NMIs). The products included in the study were manufactured in the timespan of 2009–2016. Due to the sensitivity of the data, the individual sources of data have been anonymized, the authors retain this information as confidential. The SPDs are numbered S with n going from 1 to 1495, sorted by the correlated color temperature (CCT) calculated using equation published by MacCamy et al. The data was used in the analysis of LED illuminants and reference spectra for photometer calibration that has been published as a scientific paper Alexander Kokka et al 2018 Metrologia 55 526:
DOI: 10.11583/dtu.12783389.v2
title: EMPIR 15SIB07 PhotoLED - Database of LED product spectra

description: This dataset consists of 1494 relative spectral power distributions (SPD) collected by the partners and collaborators of project EMPIR 15SIB07 PhotoLED - Future Photometry Based on Solid-State Lighting Products. The SPDs of LED products of different types were measured; including AC- and DC-operated bulbs, spots, tubes, street lamps, LED strips, downlight luminaires, prints and textures by a large number of manufacturers. The measurements of the products were carried out in various laboratories, including manufacturers of LED products, test laboratories, and National Metrology Institutes (NMI). The products included in the study were manufactured in the timespan of 2009–2016. Due to the sensitivity of the data, the individual sources of data have been anonymized, the authors retain this information as confidential. The SPDs are numbered S with n between 1 and 1495, sorted by the correlated color temperature (CCT) calculated using equation published by MacCamy in 1992. The data was used in the analysis of LED illuminants and reference spectra for photometer calibration that has been published as a scientific paper Alexander Kokka et al. [1].<br> <br> <strong>Note to version 2 of the database</strong> <br> The initial release of the dataset included approximate CCT values calculated for the spectra using the equation by MacCamy[2], with the purpose of enabling sorting of the data based on CCT. It is known that the MacCamy method produces deviations from calculations using the CIE definition[3]. With some of the spectra, these were considered to be so large as to cause confusion. Therefore the CCT values calculated using the CIE definition have been added to the data. The numbering of the SPDs has been kept, and the CCT calculated with the MacCamy method has been kept for data consistency. An SPD with only zero values (S1240) was removed, from the dataset. It should further be noted that since the dataset includes measurements dating back to 2009, many sources do not comply with modern regulation and requirements for color rendering index and chromaticity. Regarding the derived quantities Rf, Ra, R9, Duv, these have been added for each SPD. A few editorial changes have been made to the accompanying meta data. <br> <strong>Update of metadata</strong> <br> Editorial changes to include information on the support from EMPIR project 19NRM02 RevStdLED. The datafile itself was not changed. <br> <strong>References</strong> <br> [1] A. Kokka et al., “Development of white LED illuminants for colorimetry and recommendation of white LED reference spectrum for photometry,” Metrologia, vol. 55, no. 4, pp. 526–534, Aug. 2018. https://doi.org/10.1088/1681-7575/aacae7 <br> [2] C. S. McCamy, “Correlated color temperature as an explicit function of chromaticity coordinates,” Color Res. Appl., vol. 17, no. 2, pp. 142–144, Apr. 1992. https://doi.org/10.1002/col.5080170211 <br> [3] correlated colour temperature CCT, Term 17-23-068 of the CIE S 017:2020 ILV: International Lighting Vocabulary, 2nd edition. https://cie.co.at/eilvterm/17-23-068<br>
DOI: 10.11583/dtu.22347127
title: DATA for publication: "Electrochemical Impedance Spectroscopy integrated with Environmental Transmission Electron Microscopy"

description: This is EIS-TEM data presented in the publication " Electrochemical Impedance Spectroscopy integrated with Environmental Transmission Electron Microscopy" <br> Authored by Zhongtao Ma, Waynah Lou Dacayan, Christodoulos Chatzichristodoulou, Kristian Speranza Mølhave, Francesco Maria Chiabrera, Wenjing Zhang, Søren Bredmose Simonsen <br> The Data is electron microscopy images and electrochemical impedance spectra. <br> Published in Small Methods 2023
DOI: 10.11583/dtu.22347127.v1
title: DATA for publication: "Electrochemical Impedance Spectroscopy integrated with Environmental Transmission Electron Microscopy"

description: This is EIS-TEM data presented in the publication " Electrochemical Impedance Spectroscopy integrated with Environmental Transmission Electron Microscopy" <br> Authored by Zhongtao Ma, Waynah Lou Dacayan, Christodoulos Chatzichristodoulou, Kristian Speranza Mølhave, Francesco Maria Chiabrera, Wenjing Zhang, Søren Bredmose Simonsen <br> The Data is electron microscopy images and electrochemical impedance spectra. <br> Published in Small Methods 2023
DOI: 10.5281/zenodo.8135724
title: melanodrymia_aurantiaca_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8135723
title: melanodrymia_aurantiaca_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23660841.v1
title: Turdus occurrences

description: Occurrence localities for thrushes (genus<em>Turdus</em>). Records came from eBird, GBIF and VertNet
DOI: 10.6084/m9.figshare.23660841
title: Turdus occurrences

description: Occurrence localities for thrushes (genus<em>Turdus</em>). Records came from eBird, GBIF and VertNet
DOI: 10.5517/ccdc.csd.cc2fkll6
title: CCDC 2251238: Experimental Crystal Structure Determination

description: Related Article: Turan Karibov, Boris Lichitskii, Andrey Komogortsev, Valeriya Melekhina|2023|Tetrahedron|141|133497|doi:10.1016/j.tet.2023.133497
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.8135755
title: pachydermia_laevis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8135754
title: pachydermia_laevis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7956442
title: Telemedicine for cancer pain management: CTGAN application and ML classification

description: Background: The utilization of artificial intelligence (AI) in healthcare has significant potential to revolutionize the delivery of medical services, particularly in the field of telemedicine. In this article, we investigate the capabilities of a specific deep learning model, a Generative Adversarial Network (GAN), and explore its potential for enhancing the telemedicine approach to cancer pain management. Materials and Methods: We implemented a structured dataset comprising demographic and clinical variables from 226 patients and 489 telemedicine visits for cancer pain management. The deep learning model, specifically a conditional GAN, was employed to generate synthetic samples from our dataset that closely resemble real individuals in terms of their characteristics. Subsequently, four machine learning algorithms were implemented to assess the variables associated with a higher number of remote visits. Results: The generated dataset exhibits a distribution comparable to the reference dataset for all considered variables, including age, number of visits, tumor type, performance status, characteristics of metastasis, opioid dosage, and type of pain. Among the algorithms tested, Random Forest demonstrated the highest performance in predicting a higher number of remote visits, achieving an accuracy of 0.8 on the test data. Conclusion: As the advancement of healthcare processes relies on scientific evidence, AI techniques such as GANs can play a vital role in bridging knowledge gaps and accelerating the integration of telemedicine into clinical practice. Nonetheless, it is crucial to carefully address the limitations associated with these approaches.
description: Cite us if interested to use this data
DOI: 10.5281/zenodo.7956441
title: Telemedicine for cancer pain management: CTGAN application and ML classification

description: Background: The utilization of artificial intelligence (AI) in healthcare has significant potential to revolutionize the delivery of medical services, particularly in the field of telemedicine. In this article, we investigate the capabilities of a specific deep learning model, a Generative Adversarial Network (GAN), and explore its potential for enhancing the telemedicine approach to cancer pain management. Materials and Methods: We implemented a structured dataset comprising demographic and clinical variables from 226 patients and 489 telemedicine visits for cancer pain management. The deep learning model, specifically a conditional GAN, was employed to generate synthetic samples from our dataset that closely resemble real individuals in terms of their characteristics. Subsequently, four machine learning algorithms were implemented to assess the variables associated with a higher number of remote visits. Results: The generated dataset exhibits a distribution comparable to the reference dataset for all considered variables, including age, number of visits, tumor type, performance status, characteristics of metastasis, opioid dosage, and type of pain. Among the algorithms tested, Random Forest demonstrated the highest performance in predicting a higher number of remote visits, achieving an accuracy of 0.8 on the test data. Conclusion: As the advancement of healthcare processes relies on scientific evidence, AI techniques such as GANs can play a vital role in bridging knowledge gaps and accelerating the integration of telemedicine into clinical practice. Nonetheless, it is crucial to carefully address the limitations associated with these approaches.
description: Cite us if interested to use this data
DOI: 10.6084/m9.figshare.23660281.v1
title: continuumDescriptionOfBucklingSpheresSUPPLEMENTAL.nb from A continuum description of the buckling of a line of spheres in a transverse harmonic confining potential

description: Mathematica file
DOI: 10.25403/upresearchdata.23653758.v1
title: Activated carbon from polymers for energy storage applications

description: The world’s energy demand is increasing significantly due to population growth and industrial evolution. It raised interest in the efficient energy storage device’s research and design. This can be achieved through designing and developing novel electrode materials for high electrochemical capacitor performance. The data focuses on a synthesis of highly porous carbon derived from cross-linked polymers with improved electrochemical properties for sustainable and renewable energy storage device electrodes. It highlights successful approaches developed to enhance their electrochemical properties through the incorporation of two-dimensional materials reduced graphene oxide, a nitrogen-phosphorous dual-doping route and transition metal cobalt incorporation into the porous carbon from cross-linked polymers polyvinyl alcohol and polyvinyl pyrrolidone. The electrochemical performance of symmetric devices in neutral 2.5 molar potassium nitrate aqueous electrolytes within the cell potential of 1.6 V, revealed good specific energy and power in the range of 19.5 to 32.0 W h kg-1 and 400 to 401 W kg-1, respectively. Thus, doped porous carbon from cross-linked polymers is a promising electrode material for wide use in energy storage systems.
DOI: 10.25403/upresearchdata.23653758
title: Activated carbon from polymers for energy storage applications

description: The world’s energy demand is increasing significantly due to population growth and industrial evolution. It raised interest in the efficient energy storage device’s research and design. This can be achieved through designing and developing novel electrode materials for high electrochemical capacitor performance. The data focuses on a synthesis of highly porous carbon derived from cross-linked polymers with improved electrochemical properties for sustainable and renewable energy storage device electrodes. It highlights successful approaches developed to enhance their electrochemical properties through the incorporation of two-dimensional materials reduced graphene oxide, a nitrogen-phosphorous dual-doping route and transition metal cobalt incorporation into the porous carbon from cross-linked polymers polyvinyl alcohol and polyvinyl pyrrolidone. The electrochemical performance of symmetric devices in neutral 2.5 molar potassium nitrate aqueous electrolytes within the cell potential of 1.6 V, revealed good specific energy and power in the range of 19.5 to 32.0 W h kg-1 and 400 to 401 W kg-1, respectively. Thus, doped porous carbon from cross-linked polymers is a promising electrode material for wide use in energy storage systems.
DOI: 10.5281/zenodo.6322994
title: New approach to implement cancer patients care: The ValPeROC experience from an Italian oncology network

description: Objective: Primary goal of the Oncology Campania Network (ROC) was to reduce cancer delay and care fragmentation through the establishment of cancer-specific Multidisciplinary Oncologic Groups (GOM) and therapeutic and diagnostic assistance paths (PDTA). Methods: five Cancer Centers of the ROC, with their own cancer specific GOM were selected. In our analysis we have focused on four neoplasms: lung, colon, ovarian and prostate cancers. The median time for pre-GOM and GOM Times were calculated for each tumor site. Univariate and Multivariate logistic regressions were performed to individuate risk factors for pre-GOM and GOM Time. Results: Significant differences were observed for prostate cancer compared to other patients either for pre-GOM or GOM Times. Significant risks were found for ovarian and prostate cancer in pre-GOM time and for prostate cancer in GOM-Time. Conclusions: This experience will produce knowledge and data to guide decision-making and to manage more effectively the challenges of fighting cancer in Campania region. The ValPeROC study evaluates, for the first time, the ROC activity, through the analysis of key performance indices. Pre-GOM and GOM Time represent the quality of the entire regional health system and are useful to define models which can evaluate the performance of the ROC over time.
DOI: 10.5281/zenodo.6322993
title: New approach to implement cancer patients care: The ValPeROC experience from an Italian oncology network

description: Objective: Primary goal of the Oncology Campania Network (ROC) was to reduce cancer delay and care fragmentation through the establishment of cancer-specific Multidisciplinary Oncologic Groups (GOM) and therapeutic and diagnostic assistance paths (PDTA). Methods: five Cancer Centers of the ROC, with their own cancer specific GOM were selected. In our analysis we have focused on four neoplasms: lung, colon, ovarian and prostate cancers. The median time for pre-GOM and GOM Times were calculated for each tumor site. Univariate and Multivariate logistic regressions were performed to individuate risk factors for pre-GOM and GOM Time. Results: Significant differences were observed for prostate cancer compared to other patients either for pre-GOM or GOM Times. Significant risks were found for ovarian and prostate cancer in pre-GOM time and for prostate cancer in GOM-Time. Conclusions: This experience will produce knowledge and data to guide decision-making and to manage more effectively the challenges of fighting cancer in Campania region. The ValPeROC study evaluates, for the first time, the ROC activity, through the analysis of key performance indices. Pre-GOM and GOM Time represent the quality of the entire regional health system and are useful to define models which can evaluate the performance of the ROC over time.
DOI: 10.17632/27kywgfynh.1
title: VCF files of LD-pruned genome-wide SNPs and InDels in abaca (Musa textilis Née)

description: The study that produced this dataset aimed to discover and analyze polymorphisms in abaca (Musa textilis) vital for varietal authentication and cross-species genotyping for advanatageous traits such as disease resistance, climate change resilience and enhanced agronomic traits. This dataset contains the resulting genotype calls in abaca (within M. textilis and between M. textilis and other Musa spp.) stored in variant call format (VCF) files. The genotypes are in the form of SNPs or InDels. 

The VCf files starting with 'Mtextilis' and 'Musa' pertain to genotypes mined within M. textilis and between Musa spp., respectively. The VCF files containing SNPs or InDels are denoted by 'SNPsonly' and 'Indelsonly' file labeles, respectively. The 'AP' label indicate that the reference genome used for mapping and variant calling is a polished version of Galvez et al. (2020)'s reference genome. The 'minQ40' label indicates that the VCF files contains only SNPs and InDels with mapping quality of at least 40. The 'geno0.1' and 'pruned' labeles indicate that genotypes having at most 10% missing genotypes and those that are pruned-in (based on linkage disequilibrium thresholds) were selected.
DOI: 10.5281/zenodo.8124748
title: First-order phase transitions in Yang-Mills theories and the density of state method---data and analysis code release

description: Data release for paper: Lucini, B., Mason, D., Piai, M., Rinaldi, E., & Vadacchino, D. (2023). First-order phase transitions in Yang-Mills theories and the density of state method. arXiv preprint arXiv:2305.07463. This data release comprises of: Importance sampling results: Input and output files for PureGauge file of HiRep (https://github.com/claudiopica/HiRep) and csv files contains analysis of results. LLR results: Input files for LLR_HB for a modified version of HiRep for the heat bath LLR algorthim with umbrella sampling (https://github.com/dave452/Hirep-LLR-SU) and some csv files containing analysis of output. Analysis code within the LLRAnalysis.zip, it contains the code and the conda environment.
description: The work of DM is supported by a studentship awarded by the Data Intensive Centre for Doctoral Training, which is funded by the STFC grant ST/P006779/1. The work of DV is partly supported by the Simons Foundation under the program "Targeted Grants to Institutes" awarded to the Hamilton Mathematics Institute. The work of BL and MP has been supported in part by the STFC Consolidated Grants No. ST/P00055X/1 and No. ST/T000813/1. BL and MP received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program under Grant Agreement No.~813942. The work of BL is further supported in part by the Royal Society Wolfson Research Merit Award WM170010 and by the Leverhulme Trust Research Fellowship No. RF-2020-4619. Numerical simulations have been performed on the Swansea SUNBIRD cluster (part of the Supercomputing Wales project) and AccelerateAI A100 GPU system, and on the DiRAC Data Intensive service at Leicester. The Swansea SUNBIRD system and AccelerateAI are part funded by the European Regional Development Fund (ERDF) via Welsh Government. The DiRAC Data Intensive service at Leicester is operated by the University of Leicester IT Services, which forms part of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The DiRAC Data Intensive service equipment at Leicester was funded by BEIS capital funding via STFC capital grants ST/K000373/1 and ST/R002363/1 and STFC DiRAC Operations grant ST/R001014/1. DiRAC is part of the National e-Infrastructure.
DOI: 10.17632/tnbptc8yff.1
title: TSC22D3 as a Novel Immune-Related Prognostic Biomarker for Acute Myeloid Leukemia

description: Original data
DOI: 10.17632/tnbptc8yff.2
title: TSC22D3 as an Immune-Related Prognostic Biomarker for Acute Myeloid Leukemia

description: Original data, statistical description and data analysis
DOI: 10.5519/qd.z9490tp1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5589459 records)