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Dataset for article "Determination of interatomic coupling between two-dimensional crystals using angle-resolved photoemission spectroscopy"
No full textThis dataset contains information about the results of angle-resolved photoemission spectroscopy (ARPES) measurements of twisted bilayer graphene as well as theoretical modelling of this experiment. It accompanies a peer reviewed academic publication in which the experiment and theoretical model are described in more detail.The ARPES measurements were performed at the Spectromicroscopy beamline at the Elettra synchrotron (Trieste, Italy). Before measurements, the samples were annealed at 350 °C for 30 minutes. The experiment was then performed at a base pressure of 10^-10 mbar in ultrahigh vacuum and at the temperature of 110 K. We used photons with energy of 74 eV and estimate our energy and angular resolution as 50 meV and 0.5°, respectively. For each sample, we determined the twist angle by measuring the distance between the nearest BZ corners of the two layers. The theoretical graphs and spectra were produced using equations given in the text of the manuscript.Experimental ARPES data was transferred to Matlab for further analysis and processing. Theoretical simulations were also performed using Matlab. All the enclosed data is saved in Matlab formats.The following describes content of the files in the archive (below, "(x)" stands for numerical part of the name of one of the files in the archive; figure numbers refer to figures in the accompanying publication):
- Cut_9_64.mat - experimental ARPES map for Fig 2(a).
- couplinggraphs.mat - plots in Fig 2(b).
- Cut_9_06.mat - experimental ARPES map for Fig 3(a).
- Cut_19.mat – experimental ARPES mao for Fig. 3(b).
- (x)energyworkspace.mat - calculated ARPES maps for Fig 4 at energy (x).
- experimental(x)workspace.mat - experimental data for Fig 4 at energy (x).
- Bilayer_19_1.mat – original experimental ARPES data for twisted bilayer graphene in Fig 3 (b); workspace is organised in the same way as “E_contour_(x).mat” described below.
- E_contour_(x).mat - original experimental ARPES data for twisted trilayer with twist angle (x); within this file, the structures "SMPM12058_(x)" contain information about photoelectrons with energy (x); the variables "x" and "y" correspond to kx and ky, respectively, and "value" to measured ARPES intensity; also contained within these structure is variable "info" which describes experimental details of the ARPES measurement.
- IntensityCutTBLG134 and IntensityCutTBLG096 correspond to the supplementary figure 1, sub-figures (a) and (b) respectively
DynaRev - Dynamic Coastal Protection: Resilience of Dynamic Revetments Under Sea Level Rise
No full textThis dataset contains processed data from the DynaRev experiments carried out in the Large Wave Flume (Grosser Wellenkanal, GWK) from 14-08-2017 to 29-09-2017 as a Transnational Access project within the EU funded project HYDRALAB+ (654110). The dataset provided under this DOI includes the post-processed data detailed in the article submitted to Scientific Data titled "High-resolution, prototype-scale laboratory measurements of nearshore wave processes and morphological evolution of a sandy beach with and without a dynamic cobble berm revetment".
The overall aim of this project was to construct a prototype-scale beach and investigate the response of the beach to a rising sea level and storms with and without a cobble berm dynamic revetment structure (a gravel or shingle ridge placed around the wave runup limit). The response of two beach configurations was investigated under erosive wave conditions (Hs=0.8m, Tp=6.0s) and a total sea-level rise, SLR = 0.4 m:
i) an unmodified sand beach with an initially plane slope of 1:15, and
ii) a natural beach profile with a dynamic revetment installed at the location of the natural berm before imposing SLR.
SLR was imposed in 4 steps of 0.1 m with an initial water depth of 4.5 m above the flume base. Each phase ran for a total of 58 hours, after which resilience testing under storm waves and accretive conditions was undertaken for a further 12 hours in each case.
The changing profile of the sand beach and revetment was monitored throughout the experiments using a traditional profiler and a LiDAR array. Additional hydrodynamic measurements were obtained at the location of the offshore sandbar to investigate the process of bar formation and migration with SLR.The model set-up and experimental program are explained in the submitted Scientific Data paper.The data structure is explained in the submitted Scientific Data paper. The data files are organised as detailed in "DynaRev_Data_Structure.doc"
Dataset for "Pharmacy professionals' experiences and perceptions of providing NHS patient medicines helpline services: A qualitative study"
Get PDFTranscripts of interviews with thirty-four pharmacy professionals about their experiences and perceptions of providing a National Health Service patient medicines helpline service.An interview schedule was developed for the purpose of interviewing participants regarding their experiences and perceptions of their PMHS, and was informed by the RE-AIM evaluation framework. RE-AIM comprises five dimensions that are considered important for evaluating the impact of healthcare interventions: Reach, Effectiveness, Adoption, Implementation, and Maintenance. We ensured that questions pertaining to each of the five RE-AIM dimensions were included in the schedule. During data collection, the interview schedule served as a flexible guide for interviews, enabling participants to discuss aspects of their PMHS that were important to them. All interviews were audio-recorded. After their interview, the following background data were collected from each participant over the telephone: age, gender, ethnicity, job title, number of years employed as a pharmacy professional, and number of years’ experience of operating or providing a PMHS. All audio-recorded interviews were transcribed verbatim into separate Microsoft Word documents. Framework analysis (FA) was used to analyse the transcribed data. Analysis involved the standard FA stages, as outlined by Ritchie and Spencer (the developers of FA): familiarisation with the data, coding, developing an analytical framework, indexing, charting, and interpretation. The only deviation to the FA stages was that Iterative Categorisation (IC) was used in place of charting. The choice to use IC was made in order to increase transparency and rigour.Data were analysed using NVivo version 12
Dataset for "Ensilicated tetanus antigen retains immunogenicity: in vivo study and time-resolved SAXS characterization"
Get PDFThis dataset contains the SAXS data obtained at i22 (Diamond Light Source) and ID02 beamline (ESRF). Other data such as ELISA and Circular Dichroism are also included. All data is organised by figures presented in the research paper. Majority of data is stored in excel or csv format with processing done in MatLab for graphical presentation.Time-resolved (ultra) SAXS (ID02, ESRF):
Small Angle X-Ray Scattering (SAXS)21 measurements were performed on the Time-Resolved Ultra Small-Angle Scattering beamline ID02 at the ESRF, Grenoble, France. The incident X-ray energy was 12.46 keV and two sample-detector distances were employed: 1.5 m (SAXS) and 10 m (USAXS). SAXS data were acquired using the Rayonix MX-170HS detector with exposure times between 0.01 and 0.03 seconds at room temperature (20 °C).
Pre-hydrolysed TEOS was added to 10 ml of 1 mg/ml TTCF solution at 1:50 (v/v) ratio at pH 7 ex situ, initiating the ensilication reaction. Using a sterile syringe, 1 ml of this ensilication mixture was injected into a quartz capillary (figure S2) after which the beamline hutch was checked for safety and closed for the start of measurement. We measured the delay on hutch closure to be approximately 1 minute. As a result, the total time delay between the start of the reaction and the first measurements was between 1 and 2 minutes.
The measured 2D patterns, after normalisation by incident flux, sample transmission, and solid angle, were azimuthally averaged to obtain the 1D static scattering profiles as a function of the magnitude of the scattering vector q=4π/λ sin(θ/2), with λ the incident X-ray wavelength (=0.996 Å-1) and θ the scattering angle. This gave two overlapping q-ranges of 0.0008≤q≤0.008 and 0.006≤q≤0.5 Å-1. The scattering background in each case was measured using Tris buffer and the normalised background subtracted data are represented by I(q).
Fitting of SAXS data:
Data fitting was done using several models within SASview to probe the various changes observed in the scattering signal. Good residual fits were found using a combination of power law, ellipsoid, broad peak and mass fractal models at different stages of the ensilication process. The ellipsoid model provided shape information (the polar and equatorial radii, Rpolar and Requatorial respectively) on the protein and the initial growth of its silica coating. The broad peak model gave a characteristic length scale for scattering consistent with the particle sizes from the ellipsoid fits, and was utilised as a transition model towards the mass fractal growth. The latter provided the fractal radius of silica particulates and fractal dimension, Rfrac and Df respectively, which are indicative of reaction type. All models were assessed on χ2 as a goodness-of-fit indicator. Detailed information about the fitting parameters are presented in the Supplementary Information.
in situ time-resolved SAXS (i22, Diamond Light Source):
Small Angle X-Ray Scattering (SAXS) measurements during ensilication in situ were performed on the Time-Resolved Small-Angle Scattering beamline i22 at Diamond Light Source, Didcot, UK.
TTCF at 1 mg/ml in (50 mM Tris pH 7.0) buffer, 25 ml volume, was circulated using a peristaltic pump at 2 ml / min through Teflon tubing with an internal diameter of 1.6 mm. The sample solution passed through a 1.5 mm capillary flow cell in a loop before addition of hydrolysed TEOS via a syringe injector. Both pump and injector were remotely controlled (figure S3).
SAXS frames were taken at 1 frame/sec for 120 seconds. Pre-hydrolysed TEOS was added to the sample at 1:50 (v/v) ratio after 3 seconds from start of measurement, so that data on the native protein could be acquired before ensilication began. The incident X-ray energy was 12.4 keV. SAXS data were acquired using the Pilatus P3-2M detector at 2.2 m sample distance with 0.8 seconds exposure time. The collected 2D data were processed using a pipeline setup in the Data Analysis WorkbeNch (DAWN) software27. The pipeline was set up with detector calibration, SAXS mask, Poisson error, time with flux and transmission correction. Azimuthal integration produced 1D data in I vs q, where q=4π/λ sin(θ/2), with λ the incident X-ray wavelength (0.9998 Å) and θ the scattering angle. The q range was between 0.008≤q≤0.75 Å-1.
The experiment was performed at room temperature (20 °C). Background subtraction scattering was done using a double subtraction method (figure S4 & table S1). Empty capillary scattering was subtracted from Tris buffer scattering. The sample SAXS was then processed by subtracting Tris buffer (minus capillary scattering) and capillary scattering only (table S1).Diamond Light Source data was processed via DAWN. ESRF data was processed using SAXSutilities. SASview was used to analyse the datasets.Data are stored per figure presented in the original work and supplementary information. MatLab code is supplemented for generating figures
Data set for "UK Passivhaus and the energy performance gap"
No full textThis is a data set of space heating demand from 97 certified Passivhaus homes in the UK . The dataset is used to compare measured space heating demand with the predicted space heating demand generated at design stage using Passive House Planning Package. This comparison was used to demonstrate there is no performance gap ( difference between predicted and measured energy use) in Passivhaus homes. This is of interest as many new and existing homes in the UK use much more energy than predicted.
This evidence has been used to add weight to the argument that the Passivhaus standard should become the norm for the UK.This data collates data from three sources
1. Data from the Technlogy Strategy Board's Building Performance Evaluation Program, which is available on the
2. Data from Passivhaus consultants - this is not public data
3. Data from home owners - this is not public data.
Data was collected using a variety of the methods, outline in the paperData was collated in R softwar
Data for thesis "Diagnostic and Theranostic Sensor Systems"
No full textThis repository contains the experimental data discussed in the thesis entitled ‘Diagnostic and Theranostic Sensor Systems’. The data includes; 1H nuclear magnetic resonance (NMR) data and 13C NMR data (as Bruker Aspect NMR FID files and PDF files), mass spectra (as PDF files) and infrared spectra (as MS Word documents) images for all intermediates and probes synthesised and discussed in the experimental section of thesis. Raw data of Fluorescence and UV-VIS analysis (Excel) are included for each fluorescent probe.Full details of the methodology may be found in the associated thesis.All raw NMR data was processed using MNova NMR processing software. This software reads all FID files
Dataset for "Self-assembly of amphiphilic polyoxometalates for the preparation of mesoporous polyoxometalate-titania catalysts"
No full textThe dataset contains ASCII files for small-angle neutron scattering (SANS) curves and fits for polyoxometalate-headed surfactant (POM-2Cn, n=12, 14, 16 and 18) solution as a function of surfactant concentrations. Solutions are prepared in two different solvents: deuterium dioxide, 7:3 deuterium dioxide and H2O mixture.
The dataset also contains Igor files for the following:
- the plot of determination of critical micelle concentrations (CMC) of the POM-2Cn H2O system through conductivity measurements;
- the plot of 13C NMR, 31P NMR of POM-2Cn;
- the plot of UV-vis spectra and IR of POM-2Cn;
- the degradation line of RhB by nPOM-TiO2 catalysts and the corresponding rate constants;
- the plot of TGA for POM-2Cn;
- the XRD patterns of nPOM-TiO2 and TiO2.Full details of the methodology used may be found in the Experimental section of the associated paper.This work benefited from DANSE software developed under NSF award DMR-0520547.The SANS data are recorded in plain text files. The remaining data are provided in Igor Pro Packed Experiment (.pxp) format
Datasets and Analyses for "Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming"
No full textDatasets and analyses for the paper "Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming" published at CHI 2020.
We present the datasets of two experiments that investigate the use of different sensors for affect recognition in a VR exergame. The first experiment compares the impact of physical exertion and gamification on psychophysiological measurements during rest, conventional exercise, VR exergaming, and sedentary VR gaming. The second experiment compares underwhelming, overwhelming and optimal VR exergaming scenarios. We identify gaze fixations, eye blinks, pupil diameter and skin conductivity as psychophysiological measures suitable for affect recognition in VR exergaming and analyse their utility in determining affective valence and arousal. Our findings provide guidelines for researchers of affective VR exergames.
The datasets and analyses consist of the following:
1. two CSV sheets containing the quantitative and qualitative data of the Experiments I and II;
2. two JASP files with ANOVAS and t-tests for Experiments I and II;
3. two R scripts with correlation and regression analyses for Experiments I and II.We used a Lode Excalibur Sport exercise bike and an FOVE HMD. They were connected to a PC running Unity with an Intel Xeon E5 2680 processor, 64 gigabytes of RAM, and two NVIDIA Titan X graphics cards. We measured blink rate in blinks per minute (Blinks) with the eye gaze tracker built into the FOVE HMD, recording pupillometry data with FOVE’s Unity plugin at 160Hz and counting blinks as periods with zero pupil diameter. We measured the tonic skin conductance (Conductivity) using the Shimmer3 Consensys GSR development kit in microsiemens (μS) at 128 Hz. Furthermore, we recorded the average power output (Power) in Watts during the sprint phases in conditions.
Experiment I: We collected ground truth data for affect based on validated post-condition questionnaires. We measured intrinsic motivation with the Intrinsic Motivation Inventory (IMI) . We used the main Interest/Enjoyment
subscale (IMI Enjoy) with a scoring ranges from 1 to 7, with 7 being the highest intrinsic motivation score. Participants then performed each of the four conditions: B (Baseline), G (Game), E (Exercise) and EG (Exergame). After conditions G, E
and EG, participants completed the IMI, and left qualitative feedback about their experience.
Experiment II: In addition to recording Conductivity, Blinks and Power to determine affective state, we recorded the total time of eye gaze fixations (Fixations) on visual components of the game: the competitor, the gap between the player and the competitor, the points, prompts, the displayed RPM and the timer. We used ray casting to detect the game components corresponding to a point of gaze. A low Fixations value indicates that the player was looking more at the peripheral VR environment or ‘staring at nothing’ instead of paying attention to the game. We also recorded a participant’s pupil dilation (Pupil) during the warm up and in each of the two sprints, considering their average. Similar to Experiment I, we used the IMI Interest/Enjoyment subscale (IMI Enjoy) to measure intrinsic motivation. Lastly, the experience sampling method integrated in the exergame was used to collect ground truth values about the player’s affective state; we consider the average of all values measured in a condition (Affect). We matched the sensor data and the ground truth by taking the average of the sensor data and of the experience sampling measures over a whole gameplay session.We used a Lode Excalibur Sport exercise bike and an FOVE HMD. They were connected to a PC running Unity with an Intel Xeon E5 2680 processor, 64 gigabytes of RAM, and two NVIDIA Titan X graphics cards. We measured blink rate in blinks per minute (Blinks) with the eye gaze tracker built into the FOVE HMD, recording pupillometry data with FOVE’s Unity plugin at 160Hz and counting blinks as periods with zero pupil diameter. We measured the tonic skin conductance (Conductivity) using the Shimmer3 Consensys GSR development kit in microsiemens (μS) at 128 Hz. Furthermore, we recorded the average power output (Power) in Watts during the sprint phases in conditions. For the II Experiment, in addition to recording Conductivity, Blinks and Power to determine affective state, we recorded the total time of eye gaze fixations (Fixations) on visual components of the game: the competitor, the gap between the player and the competitor, the points, prompts, the displayed RPM and the timer.
JASP statistics software (https://jasp-stats.org/) and the R programming language were used for data analysis. For the R scripts, we recommend using the RStudio IDE (https://rstudio.com/)
Dataset for "Robotic microscopy for everyone: the OpenFlexure Microscope"
No full textThis dataset contains microscopy images collected to demonstrate imaging capabilities of the OpenFlexure Microscope. Images for bright-field transmission and reflection, polarisation contrast, and fluorescence imaging are provided. A set of images obtained from a large tile scan are provided, along with the Microsoft Image Composite Editor file used for tiling.Images were collected using the OpenFlexure Microscope as documented in the associated mansuscript.Images are in JPEG format. The .spj file is a project file for use with Microsoft Image Composite Editor v2.0 (https://www.microsoft.com/en-us/research/product/computational-photography-applications/image-composite-editor/).
Python scripts are written for Python v3.6+ and require non-standard libraries matplotlib, Numpy, opencv-python, picamera, PIL, pytest, scipy, and scikit-image, all of which are available from the Python Package Index (https://pypi.org/).
The analysis script `run_analysis.sh` requires a global installation of the Python library micat (https://gitlab.com/bath_open_instrumentation_group/micat). It may be executed directly by a UNIX-like shell, but the command invocation it contains may be used on other platforms.Additional documentation is provided within the ZIP file
Dataset for "Multi-Enzyme Cellulose Films as Sustainable and Self-Degradable Hydrogen Peroxide Producing Material"
Get PDFThis dataset contains data obtained by Enzyme activity measurements (Cellobiohydrolase and Cellobiose dehydrogenase), rheological analysis of cellulose films (uniaxial large deformation studies), H2O2 evolution in films (short term and long term), and adsorption kinetic studies of the enzymes into cellulose films. Moreover, the dataset includes a word document with the microphotographs and figures of the published paper.The obtained data were obtained with different techniques:
1. Fluorescence microscopy
2. Rheometry analysis
3. Spectrophotometry
4. Chromatography (HPLC)Microsoft office and image visualizing softwar
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