1056 research outputs found
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Dataset from the Survey on Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice
No full textThis database contains all the responses from the participants in the survey: Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice.
The main purpose of this survey was to explore how the Architecture, Engineering, Construction, Management, Operation, and Conservation (AECMO&C) industry can adapt and better prepare to embrace the innovative principles and enabling technologies of Industry 5.0. This could ultimately result in enhanced conservation practices for built cultural heritage
Dataset for "Advanced paramedics' restraint decision-making when managing acute behavioural disturbance (ABD): A UK based qualitative investigation"
No full textAn exploratory study of the factors which influence decisions made by paramedics and advanced paramedics when treating suspected ABD patients in the pre-hospital setting where a decision is required as to whether a patient should be restrained.
This dataset consists of anonymised semi-structured interview transcripts from interviews with 7 advanced paramedics whose scope of practice includes chemical restraint.Semi structured interviews with participants sampled from one NHS Ambulance Trust in England. All participants were volunteers and part of a convenience sample, responding to an internal advertisement.Interviews were recorded using MS Teams and transcribed intelligent verbatim using MS Word. Transcripts were anonymised prior to analysis.MS Word was used to create the transcripts
Dataset for "VibroTact: Soft piezo vibration fingertip sensor for recognition of texture roughness via robotic sliding exploratory procedures"
No full textThis file contains data collected with the VibroTact sensor from eight artificial textures with different roughness.
The data is collected using five different sliding exploratory procedures.
The main folder is composed of eight folders where the folder name indicates the texture roughness as follows:
- Folder name: 2_5mm -> texture roughness 2.5mm
- Folder name: 5mm -> texture roughness 5.0mm
- Folder name: 7_5mm -> texture roughness 7.5mm
- Folder name: 10mm -> texture roughness 10.0mm
- Folder name: 12_5mm -> texture roughness 12.5mm
- Folder name: 15mm -> texture roughness 15.0mm
- Folder name: 17_5mm -> texture roughness 17.5mm
- Folder name: 20mm -> texture roughness 20.0mm
Each of these files contains five folders with the data collected from the artificial textures using five different types of sliding exploratory procedures. These sliding procedures are as follows:
- horizontal_sliding: the VibroTact sensor slides horizontally from left to right directions and backwards.
- vertical_sliding: the VibroTact sensor slides vertically up to down and backwards.
- left_diagonal_sliding: the VibroTact sensor slides from the bottom right corner of the texture to the top left corner and backwards.
- right_diagonal_sliding: the VibroTact sensor slides from the bottom left corner of the texture to the top right corner and backwards.
- square_sliding: the VibroTact sensor slides along the four sides of the textures.
Each of these folders contains CSV files (between 100 to 120) with the actual data from the four piezo vibration sensors (channel A, channel B, channel C, channel D) embedded in the soft fingertip of the VibroTact. This data can be used together with Machine Learning methods for exploration and recognition processes.The methodology can be found in the associated paper
Dataset for Fast Sintering of Titania Monoliths for Photocatalytic Degradation of Organic Micropollutants
No full textRaw data files for X-ray diffraction (XRD), high-performance liquid chromatography (HPLC) alongside data and calculations of quantum yield (QY), electrical energy per order (EEO) end measured UV lamp irradiance associated with the paper "Fast Sintering of Titania Monoliths for Photocatalytic Degradation of Organic Micropollutants". XRD contains raw data of XRD spectra. HPLC contains the raw data used to produce degradation profiles of primidone when exposed to the photocatalyst.HPLC — Degradation experiments used 1 mL samples taken every 15 or 30 minutes. Analysis was performed on a Thermo Scientific Ultimate 3000 liquid chromatograph with a UV detector. Primidone analysis used a Thermo Scientific Acclaim 120 C18 column (3.0 × 75.0 mm, particle size 3.0 µm) and a Thermo Scientific Acclaim 120 C18 guard column (R) 120 C18 (3.0 × 10.0 mm, particle size 5.0 µm). The mobile phase was made up using 5.0 mM phosphoric acid and acetonitrile 85:15 (v:v) with a flow rate of 0.8 mL min⁻¹, injection volume of 20 µL and detection wavelength of 225 nm.
XRD — Sampling between 2θ of 20–3
Dataset for Mixed-Phase Titania foams via 3D-Printing for Pharmaceutical Degradation
No full textRaw data files for X-ray diffraction (XRD), high-performance liquid chromatography (HPLC), Nuclear Magnetic Resonance (NMR), Rheometry and Thermogravimetric analysis (TGA) associated with the paper "Mixed-Phase Titania foams via 3D-Printing for Pharmaceutical Degradation." XRD contains raw data of XRD spectra used to analyse crystallinity and crystal phase of TiO2 samples. HPLC contains the raw data used to produce degradation profiles of carbamazepine when exposed to the photocatalyst. NMR contains the maestranova files used to monitor the reaction and synthesis of photoresist. Rheometry contains the data used to analyse the viscosity of the resins before and after modifications. RAMAN contains the raw data used to analyse the crystal phases of the samples. TGA contains the raw data used to assess minimum required temperature for sintering and conversion to TiO2.XRD — Sampling between 2θ of 20–90 with Cu K alpha X-rays.
HPLC — Degradation experiments used 1 mL samples taken every 15 or 30 minutes. Analysis was performed on a Thermo Scientific Ultimate 3000 liquid chromatograph with a UV detector. CBZ analysis used a Thermo Scientific Acclaim 120 C18 column (3.0 × 75.0 mm, particle size 3.0 µm) and a Thermo Scientific Acclaim 120 C18 guard column (R) 120 C18 (3.0 × 10.0 mm, particle size 5.0 µm). The mobile phase was made up using 5.0 mM phosphoric acid and acetonitrile 70:30 (v:v) with a flow rate of 0.8 mL min⁻¹, injection volume of 20 µL and detection wavelength of 285 nm.
NMR analysis of the titania photoresist was conducted as the orange product (Ti(IV) acrylate) and acrylic acid precursor were dissolved in deuterated chloroform (CDCl3) for analysis on a 400 MHz Bruker Avance III NMR spectrometer
Thermogravimetric analysis was conducted using a Setsys Evolution TGA 16/18 by Setaram, with the acquisition program Calisto. 20 mg of sample was loaded in an open alumina crucible. Prior to the analysis, samples were degassed at 90 °C for 1h and 350 °C for 8h at 10 °C min-1 to remove water from the surface. Analysis was performed under air or argon atmosphere (20 mL min-1) and heated up to 800 °C for 1h at a rate of 10 °C min-1.
The rheometry of all resins used in this study was conducted on a Brookfield HADV-III Ultra-Viscometer with a CP52 cone spindle.
Raman spectra used in this work were collected using a Renishaw InVia Confocal Raman microscope, excitation laser wavelength 532 nm, 100% laser power at 74 mW on the sample with 2.6 s exposure time, and a diffraction grating of size 1800 I/ mm with slit opening of 65 mm. Detector used was a 1040 × 256 pixel CCD camera.NMR data requires use of MaestReNova 15 (Mnova 15.0.0)
Download available using https://mestrelab.com/download/mnova
Data sets for "Transformations to the aluminum coordination environment and network polymerization in amorphous aluminosilicates under pressure"
No full textData sets used to prepare Figures 1, 3-22, S1 and S3-S13 in the Journal of Chemical Physics article entitled "Transformations to the aluminum coordination environment and network polymerization in amorphous aluminosilicates under pressure." The data sets describe the structure of amorphous aluminosilicates under, or recovered from, high-pressure conditions. They were obtained by using in situ high-pressure neutron diffraction and solid-state 27Al nuclear magnetic resonance (NMR) spectrocopy. The results are discussed by reference to those obtained from in situ high-pressure x-ray diffraction and solid-state 17O, 27Al, 29Si NMR experiments.The data sets were collected using the methods described in the published paper.The data sets were analysed using the methods described in the published paper.The figures were prepared using QtGrace (https://sourceforge.net/projects/qtgrace/). The data set corresponding to a plotted curve within an QtGrace file can be identified by clicking on that curve.The files are labelled according to the corresponding figure numbers. The units for each axis are identified on the plots
Dataset for "Systematic Design and Characterisation of Photoelectrodes for Light-Driven Water Splitting", a PhD Thesis
No full textElectrochemical activity movies obtained by scanning electrochemical cell microscopy (SECCM) of a porous a-MoSx thin film. The dataset contains short movies denoted Movie S1-S13, consisting of independent SECCM scans on the a-MoSx film, covering homogeneous and heterogeneous areas to characterise the local structure-activity relationship with respect to total (current) and specific (current density) electrochemical activity.Scanning electrochemical cell microscopy (SECCM) scans using voltammetric hopping mode, 500 nm diameter nanopipettes filled with 0.5 M H2SO4, with a Ag/AgCl QRCE, measuring an electrodeposited a-MoSx thin film WE
Dataset for "3D-Printed Indium Oxide Monoliths for PFAS Removal"
No full textThe paper associated with this dataset, "3D-Printed Indium Oxide Monoliths for PFAS Removal", describes the fabrication and testing of self-supported indium oxide adsorbents for PFAS removal from water. The dataset contains: a) material characterisation data for indium oxide powder and monoliths sintered at different temperatures (XRD, Raman, TGA, nitrogen sorption, particle size, mechanical testing), and b) PFOA removal data from adsorption experiments performed under different conditions.All experimental details including procedures and conditions are fully described in the associated paper
Dataset for "Validity and reliability of a method to estimate the potential harm of medication errors by considering both the likelihood and degree of harm"
Get PDFThis dataset contains the responses to two surveys that were used to assess the validity and reliability of a new 'risk score tool' that was designed to estimate the potential harm of a medication error by estimating the probability of a range of potential consequences. The risk score tool described five levels of potential harm. Judges estimated the likelihood of harm matching each level, from which a risk score (0-10) was calculated. Thirty judges (doctors, nurses and pharmacists) used this risk score and the existing Dean and Barber scale to estimate the potential harm of 50 medication errors, 15 with a known outcome (Survey 1). Two weeks later, the judges re-scored ten of the errors (Survey 2).Data collection methods are fully described in the associated open access paper "Validity and reliability of a method to estimate the potential harm of medication errors by considering both the likelihood and degree of harm".Data processing methods are fully described in the associated open access paper "Validity and reliability of a method to estimate the potential harm of medication errors by considering both the likelihood and degree of harm".No unusual software required
Dataset for "Distortion/Interaction Analysis via Machine Learning"
No full textMachine learning (ML) has previously been applied to predict reaction barriers for a variety of different chemical reactions. This is seen as the end point for this type of study however, post-reaction barrier analysis/energy decomposition approaches can provide insight into chemical reactivity. One such approach that has previously been used to provide information on chemical reactivity, for cycloaddition reactions in particular, is distortion/interaction-activation strain analysis (DIAS). We demonstrate that ML can be coupled with cheap and rapid semi-empirical quantum mechanical methods (SQM) to predict distortion and interaction energies at a fraction of the computational cost associated with running density functional theory (DFT) calculations. This dataset includes all the structural data in the form of Gaussian16 (Revision A.03 and C.01) output files for the four datasets used in this work and, the literature dataset reactions.Ground state reactant and transition state geometries for dimethyl malonate Michael addition reactions were built using Schrödinger’s R-Group Enumeration. R-groups were placed on various different positions of the Michael acceptor; the position depended upon the molecules in question. All structures were built in Gaussian16 (Revisions A.03 and C.01) and were conformationally searched using Schrödinger’s MacroModel (version 12.7). All structures were subsequently optimised using Gaussian16 (Revisions A.03 and C.01) using AM1 and wB97X-D/def2-TZVP (IEFPCM=Water)//wB97X-D/def2-TZVP.
For distortion/interaction-activation strain calculations, python code (available on the associated GitHub page: https://github.com/the-grayson-group/distortion-interaction_ML) was used to separate the distorted reactant structures before single point energies were calculated using Gaussian16 (Revision C.01) using AM1 and the DFT level of theory used in the original transition structure calculation
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