cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5255/ukda-sn-855575
title: Negotiating Toilet Access for Couriers and Food Delivery Drivers, 2021

description: This is a pilot project from an ESRC postdoctoral research fellowship entitled 'Everyday Life with Irritable Bowel Syndrome: Mobilities, Accessibility and Belonging'. This postdoctoral fellowship was dedicated to dissemination, engagement and developing new research. This dataset is a pilot study exploring toilet access for couriers and food delivery drivers. 8 people who identified as working within parcel or food delivery took part in the research. This included keeping a diary and a follow up interview. A selection of diaries and interviews have been uploaded to this dataset. The project explored issues of toilet access for couriers and food delivery drivers and was conducted from January 2021-April 2021. Ethics approval was granted by the Department of Sociological Studies at the University of Sheffield (number: 037321)
DOI: 10.18742/18007769
title: Protecting Children at a Distance Delphi Quantitative Data 2021

description: The following dataset consists of a spreadsheet file containing survey data from the second-stage of the Protecting Children at a Distance study. The study utilised a two-stage modified Delphi methodology to elicit responses from safeguarding leaders from all professional disciplines involved in child safeguarding and protection. The first stage, which took place between June and September 2020, comprised 67 interviews with London-based safeguarding and child protection leaders within seven professional groups: Children’s Social Care, Health, Mental Health, Police, Education, Law and Safeguarding Partnerships. Interviewees’ priorities and responses informed the questions and response options for the second stage, a national survey distributed to similar professional groups in February–March 2021, which elicited 417 responses for analysis. Respondents represented all regions in England, with London and the South East accounting for 45% of overall survey representation. Respondents were a very senior and experienced group of respondents with a predominantly strategic perspective, including Directors of Children’s Social Care, Safeguarding Partnership Independent Scrutineers/Business Managers, headteachers or Designated Safeguarding Leads, Designated and Named Health and Mental Health Professionals, Police safeguarding leads at area level, and local authority and children’s panel lawyers.<br>Ethical approval for the study was granted by the King’s College London Research Ethics Committee [LRS-19/20-19420]. Stage 1 was deemed a service evaluation by participating NHS organisations. The Health Research Agency (HRA) confirmed that NHS ethical approval was not needed for stage 2 on 13th January 2021. The study is funded by the King’s Together: Multi & Interdisciplinary Research Scheme and the Economic & Social Research Council Impact Acceleration Accounts Social Science Impact Fund.<br>Survey respondents were provided with a study information sheet and provided consent prior to starting the survey.<br>
DOI: 10.18742/18007769.v1
title: Protecting Children at a Distance Delphi Quantitative Data 2021

description: The following dataset consists of a spreadsheet file containing survey data from the second-stage of the Protecting Children at a Distance study. The study utilised a two-stage modified Delphi methodology to elicit responses from safeguarding leaders from all professional disciplines involved in child safeguarding and protection. The first stage, which took place between June and September 2020, comprised 67 interviews with London-based safeguarding and child protection leaders within seven professional groups: Children’s Social Care, Health, Mental Health, Police, Education, Law and Safeguarding Partnerships. Interviewees’ priorities and responses informed the questions and response options for the second stage, a national survey distributed to similar professional groups in February–March 2021, which elicited 417 responses for analysis. Respondents represented all regions in England, with London and the South East accounting for 45% of overall survey representation. Respondents were a very senior and experienced group of respondents with a predominantly strategic perspective, including Directors of Children’s Social Care, Safeguarding Partnership Independent Scrutineers/Business Managers, headteachers or Designated Safeguarding Leads, Designated and Named Health and Mental Health Professionals, Police safeguarding leads at area level, and local authority and children’s panel lawyers.<br>Ethical approval for the study was granted by the King’s College London Research Ethics Committee [LRS-19/20-19420]. Stage 1 was deemed a service evaluation by participating NHS organisations. The Health Research Agency (HRA) confirmed that NHS ethical approval was not needed for stage 2 on 13th January 2021. The study is funded by the King’s Together: Multi & Interdisciplinary Research Scheme and the Economic & Social Research Council Impact Acceleration Accounts Social Science Impact Fund.<br>Survey respondents were provided with a study information sheet and provided consent prior to starting the survey.<br>
DOI: 10.18742/18009470
title: Protecting Children at a Distance Qualitative Data 2020

description: The following dataset file contains qualitative interview data from the first-stage of the Protecting Children at a Distance study. The study utilised a two-stage modified Delphi methodology to elicit responses from safeguarding leaders from all professional disciplines involved in child safeguarding and protection.The first stage, which took place between June and September 2020, comprised 67 semi-structured interviews with London-based safeguarding and child protection leaders within seven professional groups: Children’s Social Care, Health, Mental Health, Police, Education, Law and Safeguarding Partnerships. Interviewees’ priorities and responses informed the questions and response options for the second stage, a national survey distributed to similar professional groups in February–March 2021, which elicited 417 responses for analysis.Ethical approval for the study was granted by the King’s College London Research Ethics Committee [LRS-19/20-19420]. Stage 1 was deemed a service evaluation by participating NHS organisations.The study is funded by the <i>King’s Together: Multi & Interdisciplinary Research Scheme </i>and the <i>Economic & Social Research Council Impact Acceleration Accounts Social Science Impact Fund.</i>All participants were provided with a participant information sheet and asked to consent to study participation. The information sheet noted that anonymised data will be held and publicly available in the King's College London Research Data Management System.The following files have been anonymised to protect interviewer and participant confidentiality. <br>
DOI: 10.18742/18009470.v1
title: Protecting Children at a Distance Qualitative Data 2020

description: The following dataset file contains qualitative interview data from the first-stage of the Protecting Children at a Distance study. The study utilised a two-stage modified Delphi methodology to elicit responses from safeguarding leaders from all professional disciplines involved in child safeguarding and protection.The first stage, which took place between June and September 2020, comprised 67 semi-structured interviews with London-based safeguarding and child protection leaders within seven professional groups: Children’s Social Care, Health, Mental Health, Police, Education, Law and Safeguarding Partnerships. Interviewees’ priorities and responses informed the questions and response options for the second stage, a national survey distributed to similar professional groups in February–March 2021, which elicited 417 responses for analysis.Ethical approval for the study was granted by the King’s College London Research Ethics Committee [LRS-19/20-19420]. Stage 1 was deemed a service evaluation by participating NHS organisations.The study is funded by the <i>King’s Together: Multi & Interdisciplinary Research Scheme </i>and the <i>Economic & Social Research Council Impact Acceleration Accounts Social Science Impact Fund.</i>All participants were provided with a participant information sheet and asked to consent to study participation. The information sheet noted that anonymised data will be held and publicly available in the King's College London Research Data Management System.The following files have been anonymised to protect interviewer and participant confidentiality. <br>
DOI: 10.15129/36891b98-7209-409b-b7f9-8f68ac119ed8
title: Data for: "Polyhydroxybutyrate: a review of experimental and simulation studies on the effect of fillers on crystallinity and mechanical properties"

description: These files present a collection of data from cited published papers on polyhydroxybutyrate (PHB) composites. DOIs of the publications are included in the files. Table 1 contains a summary of the data on polymer properties (molecular weight, mw, and polydispersity), filler type and weight percent, wt%, sample preparation method, degree of crystallinity, Xc, and spherulite size from the cited papers. The table was created to compare the effect of given additive on crystallinity in PHB-based samples. Table 2 gives a summary of the data on polymer source, molecular weight, mw, sample preparation method, filler type and information, other additive information, sample name, mechanical properties (Young’s modulus, tensile strength, strain at break), degree of crystallinity, Xc, method of crystallinity measurement, and spherulite size from the cited papers. The table was created in order investigate whether introducing the additives to the system and consequent changes in sample crystallinity result in clear trends in changes in mechanical properties of PHB-based films. The files are saved as .xlsx file. To open the data, Microsoft Excel is required.
DOI: 10.21227/e9ew-jn75
title: A Novel LSTM Pipeline to Detect Anomalies in Manufacturing Production (Datasets)

description: This dataset includes the relevant data for the journal article titled 'A Novel LSTM Pipeline to Detect Anomalies in Manufacturing Production'. In this paper, we present a novel anomaly detection method using a semi-supervised LSTM forecasting approach to highlight process anomalies in a complex, real-world dataset in an automotive manufacturing setting. This data includes two time-series subsets, each with 5000 labeled observations. Both subsets were recorded using an inbuilt torque-time sensor within a DC nut runner tool used to fasten nuts onto various parts throughout the assembly line. The resultant torque time data was labeled by a test engineer and domain expert using the methods outlined in the paper. The labels are denoted in column 1, where 1 = Nominal, 2 = Anomaly No Concern, and -1 = True Anomaly.
DOI: 10.6084/m9.figshare.19140272
title: XIM_representationsMatterData.csv

description: Study 1 data includes data from elementary students (Y4, Y5, Y6) answering to paper-based functional thinking tasks presented in tabular or diagrammatic formats, with or without realistic context.<br>Study 2 data includes data from elementary students (Y4, Y5, Y6) answering to the with-context version of the tabular and diagrammatic tasks of Study 1, including behavioral responses and eye-tracking measures (fixation times)
DOI: 10.6084/m9.figshare.19140272.v1
title: XIM_representationsMatterData.csv

description: Study 1 data includes data from elementary students (Y4, Y5, Y6) answering to paper-based functional thinking tasks presented in tabular or diagrammatic formats, with or without realistic context.<br>Study 2 data includes data from elementary students (Y4, Y5, Y6) answering to the with-context version of the tabular and diagrammatic tasks of Study 1, including behavioral responses and eye-tracking measures (fixation times)
DOI: 10.34740/kaggle/dsv/3417165
title: Mahanagar Yatayat Dataset
DOI: 10.6084/m9.figshare.19145181
title: In silico design of novel anticancer drugs with amino acid and carbohydrate building blocks to inhibit PIM kinases

description: PIM-1 is a serine-threonine kinase mainly expressed in tissues like the Thymus, spleen, bone marrow, and liver. Overexpression of PIM kinases occurs in various types of human tumours, such as lymphomas, prostate cancer, and oral cancer. As a result, the design of drugs to inhibit PIM-1 in cancerous cells has attracted much attention in recent years. This study aimed to design the alternative inhibitors for PIM-1 kinase, which are based on carbohydrates and amino acids and are expected to be non-toxic with the same chemotherapeutic effects as the traditional known anticancer drugs. The combinatorial use of quantum mechanics (QM) and molecular dynamic simulation (MD) has enabled us to precisely predict the inhibition of PIM-1 kinase by the novel designed drugs and compare them with the recently synthesized chemotherapeutic drugs such as DBC (Table 1). All designed structures were optimized at the B3LYP/6-311++G(d,p) level. The designed structure UNK4 (Table 1) was the most similar structure to DBC in terms of volumes, areas, and electrostatic potential map to DBC. The results obtained in this research represented that UNK4, with the building blocks of amino acid and cyclic carbohydrates could be considered an alternative anticancer drug for DBC.
DOI: 10.6084/m9.figshare.19145181.v1
title: In silico design of novel anticancer drugs with amino acid and carbohydrate building blocks to inhibit PIM kinases

description: PIM-1 is a serine-threonine kinase mainly expressed in tissues like the Thymus, spleen, bone marrow, and liver. Overexpression of PIM kinases occurs in various types of human tumours, such as lymphomas, prostate cancer, and oral cancer. As a result, the design of drugs to inhibit PIM-1 in cancerous cells has attracted much attention in recent years. This study aimed to design the alternative inhibitors for PIM-1 kinase, which are based on carbohydrates and amino acids and are expected to be non-toxic with the same chemotherapeutic effects as the traditional known anticancer drugs. The combinatorial use of quantum mechanics (QM) and molecular dynamic simulation (MD) has enabled us to precisely predict the inhibition of PIM-1 kinase by the novel designed drugs and compare them with the recently synthesized chemotherapeutic drugs such as DBC (Table 1). All designed structures were optimized at the B3LYP/6-311++G(d,p) level. The designed structure UNK4 (Table 1) was the most similar structure to DBC in terms of volumes, areas, and electrostatic potential map to DBC. The results obtained in this research represented that UNK4, with the building blocks of amino acid and cyclic carbohydrates could be considered an alternative anticancer drug for DBC.
DOI: 10.6073/pasta/82182159d6d96d1bcff8af93ca2e0b69
title: Size-fractionated net primary productivity (NPP) estimates based on 13C uptake during cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect, ongoing since 2019

description: This dataset consists of primary production measurements based on uptake of carbon-13 added as 13C-bicarbonate during 24-h deckboard incubations of seawater. Sampling occurred on cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect during summer, fall, and winter, starting in summer 2019. Net primary production (NPP) was determined from particulate organic carbon (POC) content and associated stable isotope enrichment. Two data tables are included: 1. depth-specific primary productivity based on fractional light levels of the surface irradiance with reference to the profile of photosynthetically active radiation (PAR), and 2. integrated primary productivity. The tables derive from the raw data included as other entities.
DOI: 10.5281/zenodo.6418886
title: bibliometric

description: Bibliometric analysis
DOI: 10.5281/zenodo.6418885
title: bibliometric

description: Bibliometric analysis
DOI: 10.6084/m9.figshare.19526098.v2
title: Data supporting m6A methylation mediates LHPP acetylation as a tumour aerobic glycolysis suppressor to improve the prognosis of gastric cancer

description: Clinical Information for Tissue microarrays
DOI: 10.6084/m9.figshare.19526098.v1
title: Data supporting m6A methylation mediates LHPP acetylation as a tumour aerobic glycolysis suppressor to improve the prognosis of gastric cancer

description: Clinical Information for Tissue microarrays
DOI: 10.5281/zenodo.6414910
title: Replication Data for: Exact two-component Hamiltonians for relativistic quantum chemistry: Two-electron picture-change corrections made simple

description: Based on self-consistent field (SCF) atomic mean-field (amf) quantities, we present two simple, yet computationally efficient as well as numerically accurate algebraic approaches to remedy both scalar-relativistic <em>and</em> spin-orbit two-electron picture-change effects (PCE) arising within an exact two-component (X2C) Hamiltonian framework. Both approaches, dubbed as amfX2C and e(xtended)amfX2C, allow us to uniquely tailor PCE corrections to either mean-field models, <em>viz</em>. Hartree–Fock or Kohn–Sham DFT, in the latter case also avoiding the need of a point-wise calculation of exchange–correlation PCE corrections. We assess the numerical performance of these PCE correction models on spinor energies of group-18 (closed-shell) and group-16 (open-shell) diatomic molecules, achieving a consistent ≈ 10−5-Hartree accuracy with regard to reference four-component data. Additional tests include SCF calculations of molecular properties such as absolute contact density and contact density shifts in copernicium fluoride compounds (CnFn, n=2,4,6), as well as equation-of-motion coupled cluster calculations of X-ray core ionization energies of 5<em>d</em> and 6<em>d</em>-containing molecules where we observe an excellent agreement with reference data. To conclude, we are confident that our (e)amfX2C PCE correction models constitute a fundamental milestone towards a universal and reliable relativistic two-component quantum chemical approach, maintaining the accuracy of the parent four-component one at a fraction of its computational cost.
DOI: 10.5281/zenodo.6414909
title: Replication Data for: Exact two-component Hamiltonians for relativistic quantum chemistry: Two-electron picture-change corrections made simple

description: Based on self-consistent field (SCF) atomic mean-field (amf) quantities, we present two simple, yet computationally efficient as well as numerically accurate algebraic approaches to remedy both scalar-relativistic <em>and</em> spin-orbit two-electron picture-change effects (PCE) arising within an exact two-component (X2C) Hamiltonian framework. Both approaches, dubbed as amfX2C and e(xtended)amfX2C, allow us to uniquely tailor PCE corrections to either mean-field models, <em>viz</em>. Hartree–Fock or Kohn–Sham DFT, in the latter case also avoiding the need of a point-wise calculation of exchange–correlation PCE corrections. We assess the numerical performance of these PCE correction models on spinor energies of group-18 (closed-shell) and group-16 (open-shell) diatomic molecules, achieving a consistent ≈ 10−5-Hartree accuracy with regard to reference four-component data. Additional tests include SCF calculations of molecular properties such as absolute contact density and contact density shifts in copernicium fluoride compounds (CnFn, n=2,4,6), as well as equation-of-motion coupled cluster calculations of X-ray core ionization energies of 5<em>d</em> and 6<em>d</em>-containing molecules where we observe an excellent agreement with reference data. To conclude, we are confident that our (e)amfX2C PCE correction models constitute a fundamental milestone towards a universal and reliable relativistic two-component quantum chemical approach, maintaining the accuracy of the parent four-component one at a fraction of its computational cost.
DOI: 10.5281/zenodo.6403153
title: Single Cell Profiling of Human Dura and Meningioma Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response

description: This repository contains the single-cell RNA-seq data described in the publication “Single Cell Profiling of Human Dura and Meningioma Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response.” Data is provided as count matrices and Seurat objects.
DOI: 10.6084/m9.figshare.13567265
title: Original data of manuscript entitled "Spatial quantification of clinical biomarker pharmacokinetics through deep learning-based segmentation and signal-oriented analysis of MSOT data" by Hoffmann and Gerst et al.

description: This dataset contains all original data used in the manuscript entitled "Spatial quantification of clinical biomarker pharmacokinetics through deep learning-based segmentation and signal-oriented analysis of MSOT data" by Hoffmann and Gerst <i>et al</i>.<br><br>Contained data:<br><br>1. Anatomical_RoiSets.zip<br>This folder contains anatomical ROI sets of liver, spine and aorta regions used in the manuscript.<br>2. Annotation-comparison_ROIs.zipThis folder contains all ROI sets used for the comparison of manual and automated annotation.<br>3. Deep-learning_manual-annotation_data.zipThis folder contains the manual annotations used for the deep learning-based segmentation of animals.<br>4. Deep-learning_training.zipThis folder contains the the code and data used for training of the deep learning-based segmentation of MSOT images.<br>5. Signal-oriented_analysis_data.zip<br>This folder contains all data used for the signal-oriented analysis.<br>The data consists of two different treatments: Sham (control animals) and PCI (diseased animals). Each animal folder is identified by a unique name and contains an MSOT image in .tif file format and a region of interest (ROI) in .roi file format. The MSOT image is a time-resolved 4d image with 4 channels (water, indocyanine green, deoxygenated haemoglobin and oxygenated haemoglobin). The ROI derived by deep learning-based segmentation comprises the whole animal and is referred to as animal-ROI in the manuscript.<br><br>6. Tissue-oriented_analysis_data.zip<br>This folder contains all data used for the tissue-oriented analysis.<br>The data consists of two different treatments: Sham (control animals) and PCI (diseased animals). For each animal there exist two files prefixed with the animal identifier: a pre-processed MSOT image in .tif file format and a region of interest (ROI) in .roi file format. The MSOT image is a pre-processed, time-resolved 3d image of the indocyanine green channel (see manuscript for details on image pre-processing). The ROI comprises the liver tissue and is The third folder contains the MSOT image and the ROIs that were used to demonstrate the sensitivity of the tissue-oriented analysis towards slight changes in ROI positioning.<br><br>