cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16726207.v2
title: STOKES local reflection FITS files

description: Attached tables (v1) to the paper "Spectral and polarization properties of reflected X-ray emission from black-hole accretion discs", Podgorny et al. 2022, MNRAS, Vol. 510, pg. 4723. Any newer version of the tables will be also provided here in the future.
DOI: 10.5281/zenodo.10036858
title: Data Augmentation Dataset
DOI: 10.5281/zenodo.10036857
title: Data Augmentation Dataset
DOI: 10.34740/kaggle/dsv/6783924
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5258/soton/d2830
title: UKRI return 2022-2023 University of Southampton

description: List of articles acknowledging UKRI funding that the University of Southampton paid for with UKRI open access block grant monies, or included in an open access publishing agreement, during 1/4/2022 to 31/3/2023. Contains financial information, Grant numbers, dates of acceptance/publication, DOIs and licence details.
DOI: 10.5517/ccdc.csd.cc21ts4t
title: CCDC 1901606: Experimental Crystal Structure Determination

description: Related Article: Tianrui Li, Hao Zhang, Jinling Miao, Chunyue Xu, Yong Nie, Guangning Liu, Guoxin Sun, Xuchuan Jiang|2023|New J.Chem.|47|18243|doi:10.1039/D3NJ03431C
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: 10.5258/soton/d2259
title: Data underpinning results and conclusions formed in thesis entitled "Analysis of expedited chromatographic separation systems for application to the decommissioning of nuclear facilities".

description: Data is underpinning results and conclusions formed in thesis entitled "Analysis of expedited chromatographic separation systems for application to the decommissioning of nuclear facilities". Thesis is formed of three research chapters (chapters 4-6). Chapter 4 consists of research into the separation and purification of Sr-90 from cementitious matrices by extraction chromatography at elevated flow rates. Chapter 5 is a study of the kinetic control on the uptake of major actinides and Th on different chromatographic materials. Chapter 6 is an analysis of a sample preparation method for the separation of multiple radionuclides from a single sample. Data consists of ICP-QQQ-MS, MC-ICP-MS, Gamma spec, Alpha spec, Liquid scintillation as well as sample masses for each test. These are tabulated and processed in excel, however the raw data from the radiometric analysis is in various other forms. Alpha spec data is in Ortec spectral form as well as RPT notepad format for the ROI data. RAW LSC/Cherenkov count data is present as plain text documents. Raw gamma spec data is present in scanned document PDFs which are then transposed to the relevant excel files. All ICP-MS data is present in excel format. Data can be accessed under licence: CC BY 4.0
DOI: 10.5281/zenodo.7777261
title: An association sequence suitable for producing ground-state RbCs molecules in optical lattices

description: The data that support the findings of this study are uploaded here. All the data files are self-explanatory. They contain individual column names. 


The experimental data for Fig. 4(a) are in Fig4a_experimental_data.csv under the folders Fig_4>Fig_4a. To convert to binding energy there is a fitting algorithm in the Python code Feshbach_Fit.py .
description: 1. DFG-FWF Forschergruppe FOR2247 under the FWF project number I4343-N36.
2. Wittgenstein prize grant under project number Z336-N36
3. UK Engineering and Physical Sciences Research Council (EPSRC) Grants EP/W00299X/1.
DOI: 10.5281/zenodo.7777262
title: An association sequence suitable for producing ground-state RbCs molecules in optical lattices

description: The data that support the findings of this study are uploaded here. All the data files are self-explanatory. They contain individual column names. The experimental data for Fig. 4(a) are in Fig4a_experimental_data.csv. To convert to binding energy there is a fitting algorithm in the Python code Feshbach_Fit.py .
description: 1. DFG-FWF Forschergruppe FOR2247 under the FWF project number I4343-N36. 2. Wittgenstein prize grant under project number Z336-N36 3. UK Engineering and Physical Sciences Research Council (EPSRC) Grants EP/W00299X/1.
DOI: 10.5281/zenodo.8412500
title: An association sequence suitable for producing ground-state RbCs molecules in optical lattices

description: The data that support the findings of this study are uploaded here. All the data files are self-explanatory. They contain individual column names. 


The experimental data for Fig. 4(a) are in Fig4a_experimental_data.csv under the folders Fig_4>Fig_4a. To convert to binding energy there is a fitting algorithm in the Python code Feshbach_Fit.py .
description: 1. DFG-FWF Forschergruppe FOR2247 under the FWF project number I4343-N36.
2. Wittgenstein prize grant under project number Z336-N36
3. UK Engineering and Physical Sciences Research Council (EPSRC) Grants EP/W00299X/1.
DOI: 10.15129/4aa97650-ae29-4b2c-bc5f-71d54badec85
title: Data for "Influence of an Innovative Hospice Design and Care Model on Wellbeing"

description: This dataset contains appendices and was created as supplementary information to support a thesis. It contains 14 files, both .DOC and .PDF formats, containing material including tables, figures, floor plans, sample interview questions, questionnaires, consent forms, the project protocol and an ethical approval letter. Each file contains a number in the title corresponding to the appendix within the thesis. The only restricted data that isn't public is that which could impact the privacy of an organisation.
DOI: 10.5281/zenodo.10035974
title: Atrakcyjność pracodawcy w kontekście stosowanych praktyk z obszaru wewnętrznej społecznej odpowiedzialności biznesu

description: The study investigated how the employer's socially responsible activities (Corporate Social Responsibility - CSR) directed at employees affect their perception of the organisation's Employer Brand (EB) image.
Among the CSR activities examined, the author included several areas of activity implemented by organisations and described in the literature. Among them were justice and fairness, health and safety, work-life balance, accessibility to training, and employees having a say in decisions (empowerment). Employer image, on the other hand, was described by several groups of factors that, according to the literature, are most commonly used to identify employees' perceptions of an organisation's performance as an employer. These groups of factors included those related to the area of relationships with others (social), opportunities for professional growth (developmental), the use of acquired knowledge in practice (applicational), a sense of security, economic benefits, the degree to which the work is interesting to the employee, ethical behaviour of the employer's conduct (ethical) and issues relating to the effectiveness of the organisation in a particular environment (environmental).
DOI: 10.5281/zenodo.10035973
title: Atrakcyjność pracodawcy w kontekście stosowanych praktyk z obszaru wewnętrznej społecznej odpowiedzialności biznesu

description: The study investigated how the employer's socially responsible activities (Corporate Social Responsibility - CSR) directed at employees affect their perception of the organisation's Employer Brand (EB) image.
Among the CSR activities examined, the author included several areas of activity implemented by organisations and described in the literature. Among them were justice and fairness, health and safety, work-life balance, accessibility to training, and employees having a say in decisions (empowerment). Employer image, on the other hand, was described by several groups of factors that, according to the literature, are most commonly used to identify employees' perceptions of an organisation's performance as an employer. These groups of factors included those related to the area of relationships with others (social), opportunities for professional growth (developmental), the use of acquired knowledge in practice (applicational), a sense of security, economic benefits, the degree to which the work is interesting to the employee, ethical behaviour of the employer's conduct (ethical) and issues relating to the effectiveness of the organisation in a particular environment (environmental).
DOI: 10.35003/l3gxvm/lgjkw6
title: 10.1111-maps.14075Figure140750002.pptx

description: :unav
DOI: 10.35003/l3gxvm/bovvlp
title: 10.1111-maps.14075Figure140750004.pptx

description: :unav
DOI: 10.35003/l3gxvm/emxzhg
title: 10.1111-maps.14075Figure140750001.pptx

description: :unav
DOI: 10.35003/l3gxvm/h4jlgs
title: maps14075-sup-0001-supinfo.pdf

description: :unav
DOI: 10.35003/l3gxvm/wkvsqr
title: 10.1111-maps.14075Figure140750003.pptx

description: :unav
DOI: 10.35003/l3gxvm/odhc1j
title: Figure_description.txt

description: :unav
DOI: 10.35003/l3gxvm/ztgzuy
title: Tables.xlsx

description: :unav
DOI: 10.5281/zenodo.10036898
title: HeatResilientCity II - work package 2.2: Influence of regional and urban climate on indoor overheating - Results of building performance simulation

description: This repository contains the results of the building performance simulations carried out in the working package 2.2 Influence of regional and urban climate on indoor overheating of the project HeatResilientCity II. The buildings under consideration are a multi-residential so-called ‘Gründerzeithaus’ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms on the top floor/attic of each building and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoors and outdoors. Further information can be found in the README of this repository. The simulations were performed for five different regions in Germany (Dresden, Hamburg, Köln, Stuttgart and Potsdam) for average present and future summers based on meteorological measurement data and under consideration of urban climate.


In addition to the ‘plain’ simulation results, some heat-indicator variables were calculated and listed in the files Calculated_Variables.txt. The calculated quantities include temperature-weighted exceedance hours (TWEH) for the limits of 25, 26 and 27 °C (defined in DIN 4108-2:2013 as ‘Übertemperaturgradstunden’) and the maximum operative temperature calculated for the period from April to September.


The used input data and building models can be found in the related repository.
description: This research was mainly funded by the Federal Ministry of Education and Research (BMBF) in the joint project "HeatResilientCity" (subproject grant number: 01LR2011A und 01LR2011F) and the European Union's Reconstruction and Resilience Facility (ARF) – NextGenerationEU.
description: This version contains some additional simulation results for the regions of Potsdam and Hamburg.
DOI: 10.5281/zenodo.8245941
title: HeatResilientCity II - work package 2.2: Influence of regional and urban climate on indoor overheating - Results of building performance simulation

description: This repository contains the <strong>results of the building performance simulations</strong> carried out in the working package 2.2 Influence of regional and urban climate on indoor overheating of the project HeatResilientCity II. The buildings under consideration are a multi-residential so-called ‘Gründerzeithaus’ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms on the top floor/attic of each building and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoors and outdoors. Further information can be found in the README of this repository. The simulations were performed for five <strong>different</strong> <strong>regions</strong> in Germany (Dresden, Hamburg, Köln, Stuttgart and Potsdam) for <strong>average present</strong> and <strong>future</strong> <strong>summers</strong> based on meteorological measurement data and under consideration of <strong>urban</strong> <strong>climate</strong>. In addition to the ‘plain’ simulation results, some <strong>heat-indicator variables</strong> were calculated and listed in the files <em>Calculated_Variables.txt</em>. The calculated quantities include temperature-weighted exceedance hours (TWEH) for the limits of 25, 26 and 27 °C (defined in DIN 4108-2:2013 as ‘Übertemperaturgradstunden’) and the maximum operative temperature calculated for the period from April to September. The used <strong>input data</strong> and <strong>building models</strong> can be found in the related repository.
description: This research was mainly funded by the Federal Ministry of Education and Research (BMBF) in the joint project "HeatResilientCity" (subproject grant number: 01LR2011A und 01LR2011F) and the European Union's Reconstruction and Resilience Facility (ARF) – NextGenerationEU.
DOI: 10.5281/zenodo.3444028
title: Hydraulic scale model experiments on the two-dimensional run-up of impulse wave trains on steep to vertical slopes

description: This dataset includes the experimental data and videos, which were generated during the study on the run-up of impulse wave trains at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.
DOI: 10.5281/zenodo.3444029
title: Hydraulic scale model experiments on the two-dimensional run-up of impulse wave trains on steep to vertical slopes

description: This dataset includes the experimental data and videos, which were generated during the study on the run-up of impulse wave trains at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.
DOI: 10.5517/ccdc.csd.cc2ghgwb
title: CCDC 2278992: Experimental Crystal Structure Determination

description: Related Article: Dominik Spahr, Lkhamsuren Bayarjargal, Eiken Haussühl, Rita Luchitskaia, Alexandra Friedrich, Victor Milman, Timofey Fedotenko, Björn Winkler|2023|Chem.Commun.|59|11951|doi:10.1039/D3CC03324D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gq18j
title: CCDC 2285297: Experimental Crystal Structure Determination

description: Related Article: Z. Chen, G. Xin, P. Gao, Y. Jin|2023|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|79|424|doi:10.1107/S2053229623007994
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gq19k
title: CCDC 2285298: Experimental Crystal Structure Determination

description: Related Article: Z. Chen, G. Xin, P. Gao, Y. Jin|2023|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|79|424|doi:10.1107/S2053229623007994
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.10031801
title: RefSeq bacterial protein coding (nucleotide) sequences

description: Bacteria_Nucleotide.fas.gz
151,835,459 protein coding (nucleotide) sequences extracted from 44,831 randomly selected bacterial genomes from NCBI's RefSeq (release 220). Sequences are named by their accession number, followed by "|" and their PGAP predicted function ("protein" tag). For example, the first sequence is named:

WP_125174066.1|iron ABC transporter permease
The process of creating the file involved the following steps.Step 1. Download 318,613 faa and fna files associated with a bacterial assembly in RefSeq. The following query was used:esearch -db assembly -query '"Bacteria"[Organism] AND "latest refseq"[properties] AND "refseq has annotation"[properties]' | esummary | xtract -pattern DocumentSummary -element FtpPath_RefSeqStep 2. Verify all protein coding sequences match the expected protein sequence lengths within three codons, otherwise skip the assembly.Step 3. Remove all redundant protein coding or protein sequences in a genome. Only exact duplicates were removed, but they were removed from both nucleotides and proteins. Hence, a duplicated amino acid sequence would be discarded along with its coding sequence even if the coding sequence was unique. This was done to keep the two sets of sequences consistent.Step 4. Name sequences by their accession and PGAP predicted function, separated by a "|" character. The PGAP predicted function is generally uniform, although there are subtle difference between some taxon specific predictions. The predicted function is reasonably dependable but certainly not perfect.Step 5. Discard any sequences without a predicted function ("hypothetical protein"). These were discarded under the assumption that the protein's function would be required for downstream uses of the sequences.Step 6. Append protein and protein coding (nucleotide) sequences from randomly ordered assemblies to separate gzipped FASTA formatted files until the Zenodo file size limit was met for either file. Hence, there are many exact duplicate sequences in the set, but none for the sequences from each genome.
The final sets of sequences are intended to provide large sets of matched protein coding (nucleotide) and protein (amino acid) sequences with consistent labels. The FASTA descriptions in both files are identical. Note, the protein coding sequences do not exactly translate into the protein sequences because of slight differences in length (typically inclusion/exclusion of the first or last codon), as well as use of different translation tables depending on the organism.
See Related works for the companion file of protein (amino acid) sequences (DOI: 10.5281/zenodo.10030000).
DOI: 10.5281/zenodo.10031800
title: RefSeq bacterial protein coding (nucleotide) sequences

description: Bacteria_Nucleotide.fas.gz
151,835,459 protein coding (nucleotide) sequences extracted from 44,831 randomly selected bacterial genomes from NCBI's RefSeq (release 220). Sequences are named by their accession number, followed by "|" and their PGAP predicted function ("protein" tag). For example, the first sequence is named:

WP_125174066.1|iron ABC transporter permease
The process of creating the file involved the following steps.Step 1. Download 318,613 faa and fna files associated with a bacterial assembly in RefSeq. The following query was used:esearch -db assembly -query '"Bacteria"[Organism] AND "latest refseq"[properties] AND "refseq has annotation"[properties]' | esummary | xtract -pattern DocumentSummary -element FtpPath_RefSeqStep 2. Verify all protein coding sequences match the expected protein sequence lengths within three codons, otherwise skip the assembly.Step 3. Remove all redundant protein coding or protein sequences in a genome. Only exact duplicates were removed, but they were removed from both nucleotides and proteins. Hence, a duplicated amino acid sequence would be discarded along with its coding sequence even if the coding sequence was unique. This was done to keep the two sets of sequences consistent.Step 4. Name sequences by their accession and PGAP predicted function, separated by a "|" character. The PGAP predicted function is generally uniform, although there are subtle difference between some taxon specific predictions. The predicted function is reasonably dependable but certainly not perfect.Step 5. Discard any sequences without a predicted function ("hypothetical protein"). These were discarded under the assumption that the protein's function would be required for downstream uses of the sequences.Step 6. Append protein and protein coding (nucleotide) sequences from randomly ordered assemblies to separate gzipped FASTA formatted files until the Zenodo file size limit was met for either file. Hence, there are many exact duplicate sequences in the set, but none for the sequences from each genome.
The final sets of sequences are intended to provide large sets of matched protein coding (nucleotide) and protein (amino acid) sequences with consistent labels. The FASTA descriptions in both files are identical. Note, the protein coding sequences do not exactly translate into the protein sequences because of slight differences in length (typically inclusion/exclusion of the first or last codon), as well as use of different translation tables depending on the organism.
See Related works for the companion file of protein (amino acid) sequences (DOI: 10.5281/zenodo.10030000).
DOI: 10.5281/zenodo.10030000
title: RefSeq bacterial protein (amino acid) sequences

description: Bacteria_Protein.fas.gz
151,835,459 protein (amino acid) sequences extracted from 44,831 randomly selected bacterial genomes from NCBI's RefSeq (release 220). Sequences are named by their accession number, followed by "|" and their PGAP predicted function ("protein" tag). For example, the first sequence is named:

WP_125174066.1|iron ABC transporter permease
The process of creating the file involved the following steps.Step 1. Download 318,613 faa and fna files associated with a bacterial assembly in RefSeq. The following query was used:esearch -db assembly -query '"Bacteria"[Organism] AND "latest refseq"[properties] AND "refseq has annotation"[properties]' | esummary | xtract -pattern DocumentSummary -element FtpPath_RefSeqStep 2. Verify all protein coding sequences match the expected protein sequence lengths within three codons, otherwise skip the assembly.Step 3. Remove all redundant protein coding or protein sequences in a genome. Only exact duplicates were removed, but they were removed from both nucleotides and proteins. Hence, a duplicated amino acid sequence would be discarded along with its coding sequence even if the coding sequence was unique. This was done to keep the two sets of sequences consistent.Step 4. Name sequences by their accession and PGAP predicted function, separated by a "|" character. The PGAP predicted function is generally uniform, although there are subtle difference between some taxon specific predictions. The predicted function is reasonably dependable but certainly not perfect.Step 5. Discard any sequences without a predicted function ("hypothetical protein"). These were discarded under the assumption that the protein's function would be required for downstream uses of the sequences.Step 6. Append protein and protein coding (nucleotide) sequences from randomly ordered assemblies to separate gzipped FASTA formatted files until the Zenodo file size limit was met for either file. Hence, there are many exact duplicate sequences in the set, but none for the sequences from each genome.
The final sets of sequences are intended to provide large sets of matched protein coding (nucleotide) and protein (amino acid) sequences with consistent labels. The FASTA descriptions in both files are identical. Note, the protein coding sequences do not exactly translate into the protein sequences because of slight differences in length (typically inclusion/exclusion of the first or last codon), as well as use of different translation tables depending on the organism.
See Related works for the companion file of protein coding (nucleotide) sequences (DOI: 10.5281/zenodo.10031801).