cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17863/cam.56683
title: Research data supporting "Photoactive organic-inorganic hybrid polymer waveguides for optical device technologies"

description: Research data supporting SPIE Raw Data. zip file contains the high resolution figures, original contact angle images and experimental data in the main text of the manuscript. In the folder labelled ‘Figures’, Figures 1-5 from the SPIE proceedings are included as high resolution PNG files, as well as the data from each figure in their respective folders. Figure 1. Figure 1 ureasil reaction scheme.png file contains the reaction scheme used in Figure 1. Figure 2. ‘Ureasils UV Transmittance.txt’ contains the XY data used for the graphs of % UV-Vis transmittance of DU(400) tU(403) and dU(600), which was plotted against wavelength from 200-800 nm. DU400 photo-luminescence emission and excitation spectra data are in respective .txt files. The XY data is in both normalised and un-normalised form. They measure the excitation and emission over a range of wavelengths 300-430 nm. Normalised graphs were used in the manuscript. Figure 3. FTIR-ATR XY data: dU600 DU400 and tU403 in the Amide I region from 1740-1600 cm-1 are presented in ‘FTIR Data tU(403).txt , ‘FTIR Data dU(600).txt , and FTIR Data DU(400).txt’. Peaks were fitted using origin in a mixture of Gaussian and Voigt fits. A .png file labelled ‘Summary of the FTIR fitting data’ is provided with information on peak width, area and fit model used. Figure 4. Mechanical testing: .txt files containing the XY data from tensile testing of dU(600), DU(400) and tU(403) are listed as: Stress strain (Ureasil) (a/b/c/d/e), with a/b/c/d/e referring to the number of repeat measurements taken. The same format is used for the 4-point bending tests, which are labelled as 4-point bending of (ureasil) (a/b/c/d/e). In all cases, at least 3 repeats were used. Figure 5. The XY data from the measurements are presented in ‘Contact Angle dU(600).txt, Contact Angle DU(400).txt, and Contact Angle tU(403).txt’. The folder labelled Contact Angle Snapshots contains jpeg files of snapshots taken during contact angle measurements on the surfaces of the ureasils (dU600, DU400 and tU403). Text files can be opened with any text editor. PNG or JPEG or TIFF files can be opened with any imaging editor.
DOI: 10.5281/zenodo.14510196
title: Homologous Recombination Shapes the Architecture and Evolution of Bacterial Genomes

description: Table for each reference genome of each species containing gene annotation information. Tables also contain recombination rate data and associated statistics for each gene with an estimable rate.
DOI: 10.5281/zenodo.14510197
title: Homologous Recombination Shapes the Architecture and Evolution of Bacterial Genomes

description: Table for each reference genome of each species containing gene annotation information. Tables also contain recombination rate data and associated statistics for each gene with an estimable rate.
DOI: 10.17863/cam.109299
title: Research data supporting "Fast Transfer of Triplet to Doublet Excitons from Organometallic Host to Organic Radical Semiconductors"

description: Contains 1 zip file within which there are 20 csv or xlsx datasets as follows: Fig_1b and Fig_1c contain steady-state absorption and photoluminescence measurements (x-axis wavelength in nm, y-axis counts), Fig_1d contains normalised transient photoluminescence data (x-axis time in s, y-axis counts) of TTM-3PCz and CMA-CF3 molecular emitters. Fig_2a is the complete 2D transient absorption dataset from which exciton dynamics in 3% TTM-3PCz in CMA-CF3 blend are studied (x-axis time in s, y-axis probe wavelength in nm, z-axis deltaT/T signal). Fig_2b contains spectra extracted from the same 2D dataset (x-axis wavelength in nm, y-axis counts). Fig_2c contains populations of excited states extracted from several 2D TA datasets (x-axis time in s, y-axis counts). Fig_3 contains temperature dependent transient photoluminescence measurements within which a series is the blend and b series is pristine CMA-CF3; and Main (x-axis time in us, y-axis counts) and Inset presents the same data but integrated (x-axis time in s, y-axis normalised integrated counts). Temperatures labelled in K. Fig_4b contains the EQE curve of the OLED device (x-axis current density in mA/cm2, y-axis EQE), Fig_4c contains current density vs. voltage and radiance vs. voltage data, Fig_4d contains electroluminescence spectra at several voltages.
DOI: 10.17863/cam.10805
title: Research data supporting "Studying design fixation with a computer-based task"

description: This is an excel file containing the numerical data resulting from the scoring of the videos recorded during each experimental session. The videos are not available for ethical reasons. The excel file includes several spreadsheets, whose naming corresponds to the various set of results reported in the publication (Open-ended ‘mental set’ tasks: An alternative approach to studying design fixation). In each spreadsheet, the column headings are self-explanatory, provided you also have the corresponding publication given above as a reference. The data was collected from July to October 2016 from 40 undergraduate and postgraduate students with an engineering background at the University of Cambridge, UK. Participants were tested individually and received £10 for your participation. They were initially told that the study aimed at investigating how people played computer games. The real aim of the study was revealed to the participants at the end of each experimental session, during the debriefing phase. Demographic data was collected from the participants and are reported in the first spreadsheet of the file. The study was approved by the local Ethical Committee and the participants signed a Consent Form before starting with the experiment.
DOI: 10.17863/cam.80129
title: Research data supporting: "Extracting Quantitative Dielectric Properties from Pump-Probe Spectroscopy"

description: This data set contains all data underlying the figures in the main text and supporting information. The information on how the data was acquired and processed is detailed in the open access manuscript + SI which has been deposited in this repository and is also available open-access via the publisher Nature Communications under the title "Extracting Quantitative Dielectric Properties from Pump-Probe Spectroscopy". All the extracted data can also be generated from the experimental data by running the codes on the GitHub repository, the link to which is available in the Main text. Main Figures: Figure 1 - Differential transmission slices of the data presented in Figure 3 along with explicit data slices of the transient dielectric function also presented in Figure 3. Figure 2 - a) Differential transmission map of CsPbBr3 which when run through our analysis code (available on GitHub) produces the 'transient dielectric function' plotted in b) along with unnormalised slices of the differential transmission map, c) Computed transient reflectivity and dielectric function slices and d) Slices of the real refractive index and measure Frequency Domain Interferometry data Figure 3 - Same as Figure 2 but on Pentacene. Figure 4 - a) Differential reflectivity map of GaAs wafer and the extracted transient imaginary dielectric function (b). All analysis was performed using Python, the interactive Jupyter notebooks are available in the GitHub repository linked in the paper.
DOI: 10.17863/cam.99953
title: Dataset for: Targeted multispectral filter array design for endoscopic cancer detection in the gastrointestinal tract

description: Description of methods used for collection/generation of data: Datasets were previously published and were collected as described in https://doi.org/10.1117/1.JBO.26.10.106002 and https://doi.org/10.1002/jbio.202100078). The folder “Datasets” contains curated spectral datasets used based on previous clinical trials for Oesophageal and Colon tissues these are read by the respective Python notebooks The folder “Optimization” includes the Python notebooks used to generate the optimal filter arrays Resulting variables saved to file: [classification method]_[tissue type]¬_varibles.npz ( eg. “kNN_Ose_variables.npz”) The saved variables include: for each number of bands N ‘bands_[N]' centre wavelengths of the selected bands (nM) 'bws_[N]' FWHM of bandwidths of the selected bands (nM) ' pattern_[N]' optimal arrangement of selected bands ' accu_[N]' spectral classification accuracy for optimal bands 'spatial_acc_[N]' spatial classification accuracy for optimal bands 'labels_pred_[N]' classification labels These variables were condensed in “Band Optimization Summary 23 July 23.xlsx” for easier interpretation “Band Optimization Summary 23 July 23.xlsx” is a summary of the optimized filters “Summary.ipynb” plots the figures used in the paper and SI All information is summarised in the readme.doc file.
DOI: 10.17863/cam.16931
title: Research data supporting the publication "Choose your path wisely: gradient descent in a Bregman distance framework"

description: This is the research data that accompanies the publication "Choose your path wisely: gradient descent in a Bregman distance framework". It contains code for all numerical examples given in the numerical results section of the associated publication. Note that the parallel MRI example and the classification example require additional external data. The corresponding URLs can be found in the associated publication
DOI: 10.17863/cam.47336
title: SI for the paper: The Lightest Beam Method - a methodology to find ultimate steel savings and reduce embodied carbon in steel framed buildings

description: This dataset contains carbon calculations, Environmental Product Declarations, and design raw data.
DOI: 10.17863/cam.107508
title: Research data supporting "Efficient near-infrared organic light-emitting diodes with emission from spin doublet excitons"

description: The zip folder contains the raw data needed to generate the figures. All files are formatted using the TXT file type. Fig. 1 files include steady-state PL and absorption data for the samples from the fluorimeter and UV-VIs spectrometer. Fig. 2 files include device data. They are generated from a Keithley 2635 sourcemeter, a Si photodiode, and a spectrometer. Fig. 3 files include transient and magneto EL data. They are obtained from ICCD with the function generator for transient EL and magnet cores with a spectrometer for magneto EL. Fig. 4 files include transient absorption and photoluminescence data. They are obtained under laser excitation, and absorption (transmitance) and photoluminescence are measured over time. See the main manuscript and supplementary information for more details.
DOI: 10.15468/dl.akyq3q
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Indonesia",
 "OccurrenceStatus is Present",
 "TaxonKey is Hylopetes sagitta (Linnaeus, 1766)"
 ]
}

 The dataset includes 32 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037909-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17863/cam.33772
title: Data supporting "The action of organoaluminium reagents on esters: alkene production and the degradation of synthetic lubricants"

description: Synthetic and analytical data (incl. NMR spectroscopic and single crystal X-ray diffraction) for new compounds and reaction mixtures studied.
DOI: 10.17863/cam.13158
title: Research data supporting: Proteins encoded by the gerP operon are localised to the inner coat in Bacillus cereus spores and are dependent on GerPA for assembly

description: Image data, image analysis software, and numerical results in support of a paper on protein location in B. cereus spores
DOI: 10.17863/cam.85042
title: Data for Mapping Short-Range Order at the Nanoscale in Metal-Organic Framework and Inorganic Glass Composites

description: Dataset and associated Jupyter Notebook for the paper 'Mapping Short-Range Order at the Nanoscale in Metal-Organic Framework and Inorganic Glass Composites' by Joonatan E. M. Laulainen, Duncan N. Johnstone, Ivan Bogachev, Louis Longley, Courtney Calahoo, Lothar Wondraczek, David A. Keen, Thomas D. Bennett, Sean M. Collins, and Paul A. Midgley. Nanoscale. 2022. Detailed instructions on how to repeat the analysis are included within (in the form of Jupyter Notebooks) as well within the Methods section of the associated publication. X-ray PDF, EDS, and SED datasets are included.
DOI: 10.17863/cam.11797
title: The data record for the primary endpoint analysis: The adaptive study of IL-2 dose frequency on regulatory T cells in type 1 diabetes (DILfrequency)

description: Supporting data for the Primary analysis of the adaptive study of IL-2 dose frequency on regulatory T cells in type 1 diabetes (DILfrequency) DILfrequency is a single-center, non-randomised, open-label, response-adaptive study of participants aged 18 to 70 with T1D. The initial learning phase allocated 12 participants to six different predefined dose-frequency regimens. Then, three cohorts of 8 participants were sequentially allocated dose-frequencies, based on repeated interim analyses of all accumulated trial data. The co-primary endpoints were percentage change in Tregs, Teffs and, CD25 (α subunit of IL-2 receptor) expression by Tregs from baseline to the average of the last three values preceding adesleukin administration at steady state. Trial registration ISRCTN40319192 and ClinicalTrials.gov (NCT02265809).The study was approved by the Health Research Authority, National Research Ethics Service, United Kingdom (14/EE/1057). While all obvious personal identifiers have been stripped from the individual-participant-level results, in our view it cannot be anonymised sufficiently to be able to put it into the public domain without risk of participant identification. Therefore, it cannot be hosted by the University of Cambridge research repository, but is instead available on application to the DILT1D Data Access Committee, contacted via fw211@cam.ac.uk, and on completion of a Data Access Agreement. The Data Access Committee consists of: the Chief Investigator; the Senior Trial Statistician; and the independent Trial Chair; with additional independent advice from the University of Cambridge School of Clinical Medicine's Information Governance team. Applications will be judged on the following criteria: 1. Has the application been submitted by bona fide researchers? 2. Is the application's purpose in line with the original aims of the trial, and the consents given? 3. Does the application run the risk of producing information that may allow individual trial participants to be identified, or may prejudice the willingness of participants to join future trials?
DOI: 10.17863/cam.24700
title: Research data supporting "A quantitative comparison of in-line coating thickness distributions obtained from a pharmaceutical tablet mixing process using discrete element method and terahertz pulsed imaging"

description: In this compressed .zip file, the open data is provide to reproduce the data on the paper: A quantitative comparison of in-line coating thickness distributions obtained from a pharmaceutical tablet mixing process using discrete element method and terahertz pulsed imaging. The data can be divided into 3 categories: DEM input files are used to generate the dynamics of tablets in drum mixing; Ray-tracing codes and input files use the position and orientation of tablets to model the terahertz in-line sensing process; .m files are Matlab scripts for data analysis
DOI: 10.5519/qd.wshcii6o
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (110 records)
DOI: 10.17863/cam.91579
title: Research data for Influence of Ni:Co ratio and temperature on the lattice misfit of γ-γ′ Ni-Co-Al-Ti-Cr alloys

description: Original research data used in the publication "Influence of Ni:Co ratio and temperature on the lattice misfit of γ-γ′ ′ Ni-Co-Al-Ti-Cr alloys". These include: 1. Microstructural images acquired by scanning electron microscopy 2. Neutron diffraction data 3. Lattice parameters fitted to the neutron diffraction data 4. Lattice misfit data obtained from the fitted lattice parameters 5. Elemental partition coefficients between the gamma and gamma prime phases. These data and their methods of acquisition are described in the related publication.
DOI: 10.17863/cam.16678
title: Raw data supporting article: Solar H2 generation in water with a CuCrO2 photcathode modified with an organic dye and molecular Ni catalyst

description: Raw data supporting arcticle: Solar H2 generation in water with a CuCrO2 photcathode modified with an organic dye and molecular Ni catalyst
DOI: 10.17863/cam.55074
title: Research data supporting "Bend- and Twist-Insensitive Flexible Multimode Polymer Optical Interconnects"

description: Research data supporting: "Bend- and Twist-Insensitive Flexible Multimode Polymer Optical Interconnects"
DOI: 10.17632/p25744hwrc.1
title: DriVQA: A Gaze-Based Dataset for Visual Question Answering in Driving Scenarios

description: DriVQA is a novel dataset that combines gaze plots and heatmaps with visual question-answering (VQA) data from participants who were presented with driving scenarios. Visual Questioning Answering (VQA) is proposed as a part of the vehicle autonomy trustworthiness and interpretability solution. They are recently being explored in the context of autonomous driving to enhance the understanding of the environment through visual inputs and enable more intelligent decision-making by the autonomous vehicle. Collected using the Tobii Pro X3-120 eye-tracking device, the DriVQA dataset provides a comprehensive mapping of where participants direct their gaze when presented with images of driving scenes, followed by related questions and answers from every participant. The DriVQA dataset contains five key elements for each scenario: images of driving situations, associated questions, participant answers, gaze plots, and heatmaps. Each gaze plot represents the exact points of focus and their sequence on the driving images, with the size of these exact points illustrating the length of attention, while the heatmaps illustrate the number of gaze points and their durations in various areas of the scene. DriVQA is being used to study the subjectivity inherent in VQA. Its detailed gaze-tracking data offers a unique perspective on how individuals perceive and interpret visual scenes, making it an essential resource for training VQA models that rely on human-like attention. The dataset is a valuable tool for investigating human cognition and behaviour in dynamic, real-world scenarios. DriVQA is highly relevant for VQA models, as it allows the systems to learn from human-like attention behaviour when making decisions based on visual input when trained. The gaze data has the potential to guide VQA models in selecting the most relevant regions of an image for answering specific questions, much like a human would focus on key areas of a driving scene. The dataset has the potential to drive advancements in VQA research and development by improving the safety and intelligence of driving systems through enhanced visual understanding and interaction. DriVQA has significant potential for reuse in various research areas, including the development of advanced VQA models, attention analysis, and human-computer interaction studies. Its comprehensive gaze plots and heatmaps can also be leveraged to improve applications in autonomous driving, driver assistance systems, and cognitive science research, making it a versatile resource for both academic and industrial purposes.
DOI: 10.17632/p25744hwrc.2
title: DriVQA: A Gaze-Based Dataset for Visual Question Answering in Driving Scenarios

description: DriVQA is a novel dataset that combines gaze plots and heatmaps with visual question-answering (VQA) data from participants who were presented with driving scenarios. Visual Questioning Answering (VQA) is proposed as a part of the vehicle autonomy trustworthiness and interpretability solution. They are recently being explored in the context of autonomous driving to enhance the understanding of the environment through visual inputs and enable more intelligent decision-making by the autonomous vehicle. Collected using the Tobii Pro X3-120 eye-tracking device, the DriVQA dataset provides a comprehensive mapping of where participants direct their gaze when presented with images of driving scenes, followed by related questions and answers from every participant. The DriVQA dataset contains five key elements for each scenario: images of driving situations, associated questions, participant answers, gaze plots, and heatmaps. Each gaze plot represents the exact points of focus and their sequence on the driving images, with the size of these exact points illustrating the length of attention, while the heatmaps illustrate the number of gaze points and their durations in various areas of the scene. DriVQA is being used to study the subjectivity inherent in VQA. Its detailed gaze-tracking data offers a unique perspective on how individuals perceive and interpret visual scenes, making it an essential resource for training VQA models that rely on human-like attention. The dataset is a valuable tool for investigating human cognition and behaviour in dynamic, real-world scenarios. DriVQA is highly relevant for VQA models, as it allows the systems to learn from human-like attention behaviour when making decisions based on visual input when trained. The gaze data has the potential to guide VQA models in selecting the most relevant regions of an image for answering specific questions, much like a human would focus on key areas of a driving scene. The dataset has the potential to drive advancements in VQA research and development by improving the safety and intelligence of driving systems through enhanced visual understanding and interaction. DriVQA has significant potential for reuse in various research areas, including the development of advanced VQA models, attention analysis, and human-computer interaction studies. Its comprehensive gaze plots and heatmaps can also be leveraged to improve applications in autonomous driving, driver assistance systems, and cognitive science research, making it a versatile resource for both academic and industrial purposes.
DOI: 10.17632/h9ny2yy9hs.1
title: Quantum computation of the Cobb-Douglas utility function via the 2D-Clairaut differential equation

description: This paper inserts the well-known Cobb-Douglas (CD) utility model in the context of quantum computation through the Clairaut-type differential formula. The new economic-physical model is studied from the envelope theory allowing the direct relation with the quantum entanglement that defines the emergent probabilities of the linear optimal utility function for the consumption of two goods with or without the limit of the available expenditure. Characterization of the Cobb-Douglas model with quantum computation and Clairaut differential equations also allows for the elucidation of system entropy for both the envelopes and intercepts of the optimal utility. We introduce new algorithms based on 2D-Clairaut’s differential equation to quantization formulation of the CD function expressed correctly in a circuit for one and two qubits.  Our calculations and those coded for an IBM-Q computer will converge on analytic predictions.  This approach linked the utility and the set budget of the CD function in an explicit model based on the envelope representation of the 2D-Clairaut’s differential equation and from the canonical equation of the line, whose normalized intercepts express the probabilities. The exact expressions derived here for one- and two-qubit quantum entanglement in the econometric context perform more efficiently than the calculations of the IBM-Q simulations, requiring a large number of shots to match the exact results