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Dataset for "The design and delivery of a workshop to support curriculum development, education for sustainability and students as partners: Sustainability in your curriculum – identify, improve, inspire!"
Get PDFThese resources form part of an off-the-shelf workshop that challenges participants to reconsider their understanding of sustainability and to recognise its vast scope. Subsequently, participants are better able to identify sustainability concepts already embedded within their course, as well as contribute to curriculum design discussions in terms of embedding sustainability.
The resources include the workshop PowerPoint, a facilitation guide and two print-in-advance resources
Dataset for "Structure of As-Se glasses by neutron diffraction with isotope substitution"
No full textData sets used to prepare Figures 1-7 in the Journal of Chemical Physics article entitled "Structure of As-Se glasses by neutron diffraction with isotope substitution." The data sets refer to the measured or modelled structure of As-Se glasses with compositions at or near to As_{0.30}Se_{0.70}, As_{0.35}Se_{0.65} and As_{0.40}Se_{0.60}.
Figure 1 shows the total structure factors F(k) for as-prepared glassy (a) As_{0.30}Se_{0.70}, (b) As_{0.35}Se_{0.65} and (c) As_{0.40}Se_{0.60}. The points with vertical error bars show the measured functions and the solid curves show spline fits. The error bars are smaller than the line thickness at most k values. The GEM data sets extend to k_{max} = 40 A^{-1} but are shown over a smaller k-range for clarity of presentation. In (c) a comparison is made between the ^{nat}F(k) functions measured using D4c (black curve) versus GEM (red curve).
Figure 2 shows the total pair-distribution functions G(r) for glassy (a) As_{0.30}Se_{0.70}, (b) As_{0.35}Se_{0.65} and (c) As_{0.40}Se_{0.60}. The broken curves show the Fourier transforms of the spline-fitted F(k) functions shown in Fig. 1. The solid curves show the same functions after the low-r oscillations have been set to the G(0) limit and the GEM data beyond the first peak have been smoothed by Fourier transforming F(k) after the application of a Lorch modification function with k_{max} = 40 A^{-1}. In (c) a comparison is made between the ^{nat}G(r) functions measured using D4c (black curves) versus GEM (red curves).
Figure 3 shows the difference functions Delta F_{gamma}(k) for glassy (a) As_{0.30}Se_{0.70}, (b) As_{0.35}Se_{0.65} and (c) As_{0.40}Se_{0.60}. The points with vertical error bars show the measured functions and the solid curves show the back Fourier transforms of the Delta G_{gamma}(r) functions given by the solid curves in Fig. 4. The error bars are smaller than the line thickness at most k values.
Figure 4 shows the difference functions Delta G_{gamma}(r) for glassy (a) As_{0.30}Se_{0.70}, (b) As_{0.35}Se_{0.65} and (c) As_{0.40}Se_{0.60}. The broken curves show the Fourier transforms of the spline-fitted Delta F_{gamma}(k) functions shown in Fig. 3. The solid curves show the same functions after the low-r oscillations have been set to the Delta G_{gamma}(0) limit and the data beyond the first peak have been smoothed by Fourier transforming Delta F_{gamma}(k) after the application of a Lorch modification function with k_{max} = 30 A^{-1} (GEM) or 23.45 A^{-1} (D4c).
Figure 5 shows a comparison between the difference functions (a) Delta F_{Se}(k), (b) Delta F_X(k) and (c) Delta F_{As}(k) obtained from FPMD (solid red curves), AXS-RMC (broken blue curves) and neutron diffraction (solid black curves). In the AXS-RMC work, the difference functions do not extend beyond k_{max} = 11.4 A^{-1}, and the curves labelled As_{0.30}Se_{0.70} and As_{0.35}Se_{0.66} correspond to actual compositions of As_{0.29}Se_{0.71} and As_{0.33}Se_{0.67}, respectively. Several of the curves have been offset vertically for clarity of presentation and the magnitude of the offset is indicated in parenthesis.
Figure 6 shows a comparison between the difference functions (a) Delta G_{Se}(r), (b) Delta G_X(r) and (c) Delta G_{As}(r) obtained from FPMD (solid red curves), AXS-RMC (broken blue curves) and neutron diffraction. In the AXS-RMC work, the curves labelled As_{0.30}Se_{0.70} and As_{0.35}Se_{0.66} correspond to actual compositions of As_{0.29}Se_{0.71} and As_{0.33}Se_{0.67}, respectively. Several of the curves have been offset vertically for clarity of presentation and the magnitude of the offset is indicated in parenthesis.
Figure 7 shows differences between the measured coordination numbers bar{n} or bar{n}_{gamma} and those calculated using the CON (black markers) and RCN (red markers) models for glassy As_{0.30}Se_{0.70} (squares), As_{0.35}Se_{0.65} (circles) and As_{0.40}Se_{0.60} (triangles). The bar{n} values for the samples containing ^{nat}Se and ^{76}Se are denoted by bar{n}_{nat} and bar{n}_{76}, respectively, and are highlighted in yellow and blue, respectively. The bar{n}_{Se}, bar{n}_X and bar{n}_{As}$ values are highlighted in green, cyan and magenta, respectively.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.Figures 1 - 6 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.
Figure 7 was prepared using Origin (http://www.originlab.com/). The data set corresponding to a plotted curve within an Origin 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 "Microstructural, thermal, crystallization and water absorption properties of films prepared from never-dried and freeze-dried cellulose nanocrystals"
Get PDFSelf-assembled cellulose film was prepared from a stable aqueous dispersion of ND CNCs using the air-drying process at room temperature. For comparison, another pure cellulose film was prepared from the FD CNCs (which also produced from the same ND CNC suspension after quickly freezing using liquid nitrogen followed by freeze-drying) via casting from their aqueous suspension. The dataset contains the raw data highlighting the influence of the microstructures created during the air and freeze-drying processes on nanoscale structure (measured by small-angle x-ray scattering (SAXS)), light transparency (UV-visible), chemical (FTIR), thermal (TGA, DSC), crystallization (XRD) and water contact angle properties of the cellulose nanocrystal films.Small angle x-ray scattering (SAXS) analysis
SAXS measurements on the ND and FD CNC suspensions with various concentrations (0.05, 0.1, 0.5 and 1.0 wt%) in DI water were conducted at Diamond Light Source (Didcot, Oxfordshire, UK), on the I22 beamline (x-ray wavelength of 1 Å and beam energy of E = 12.4 keV) equipped with a PILATUS P3-2M detector (Silicon hybrid pixel detector, DECTRIS). The FD CNC suspension was dispersed using a sonication probe (1 s on, 1 s off pulsed mode for a net time of 10 min at 30 % amplitude, Ultrasonic Processor, FB-505) and then loaded in special glass capillary tubes (nominal diameter 1.5 mm, Capillary Tube Supplies Ltd, Bodmin, UK) and sealed. The scattering pattern from an empty capillary and a capillary containing DI water were also recorded for solvent background subtraction. The probed q-range was 0.005–0.2 Å−1. Data are provided in absolute scaling.
The intensity I(q) can be written as follows:
I(q)∝P(q)S(q)…………(1)
with P(q) the form factor of the objects studied, giving information about their shape and S(q) the structure factor associated with the interactions between the objects probed.
SAXS measurements of the film samples were performed on an Anton-Paar SAXSpoint 2.0 provided by the Material and Chemical Characterisation Facility (MC²) equipped with a copper source (Cu K-α, λ=1.542 Å) and a 2D EIGER R series Hybrid Photon Counting (HPC) detector. The distance between the film sample holder (containing ND and FD CNC films) and the detector was 556.9 mm and the data were collected at 25°C in one frame, with 900 s exposure covering the q range of about 0.07-1.8 Å-1. SASView software (version 4.1.2) was used to fit the SAXS data using a rigid elliptical cylindrical and mass fractal models.
Light Transmittance:
Light transparency properties of the ND CNC and FD CNC films were determined by measuring the light transmittance using a UV-Vis spectrometer (PerkinElmer, Lambda-25) over the wavelength range of 200 to 800 nm.
Fourier transform infrared spectroscopy (FTIR):
The principal chemical groups present in ND CNC and FD CNC films were identified using an FTIR spectroscopy (PerkinElmer, Spectrum 100, USA) equipped with a standard attenuated total reflectance (ATR) cell. The films were scanned in transmittance mode over the wavenumber range from 4000 to 650 cm-1, and the obtained spectra were analyzed using OPUS™ software (version 5.5).
Thermogravimetric analysis (TGA):
TGA was performed on a TGA Q500 (TA Instruments) from 25oC to 500oC with a heating rate of 10oC min-1 under airflow. TA Universal Analysis 2000 software was used to calculate the weight loss (%) and the derivative weight loss of the films with temperature from the TGA scans.
Differential scanning calorimetry (DSC):
DSC analysis was conducted utilizing a DSC Q20 (V24.10 Build 122) from TA Instruments over a temperature range from 25 to 300oC at a heating rate of 10°C min-1 under argon gas flow (18 mL min 1). A blank pan measurement was conducted for background, and at least two tests were done for each film (~5 mg) to ensure repeatability.
X-ray diffraction (XRD) analysis:
X-ray diffraction patterns for ND CNC and FD CNC films at different temperatures (25, 150, 200, 300 and 400oC) were determined using a Bruker D8 Advanced diffractometer equipped with a Cu-Kα radiation source (λ= 0.15406 nm) at 35 mA and 40 kV. The film samples were heated from room temperature to 400oC at a heating rate of 10oC min-1 and were equilibrated at a specific temperature for 1 min prior to scan from 7o to 30o diffraction angle (2θ) with a step size of 0.04o and 2 s time interval.
The crystallinity index (CI%) of the films was calculated according to the following Equation:
CI [%]=(I_((Crys+am) )-I_((am) ))/I_((Crys+am) ) ×100
Where ) denotes the most intense peak attributed to the combined crystalline (Crys) and amorphous (am) parts of cellulose (peak intensity at 2θ=22.8o), whereas I(am) represents the amorphous portion of cellulose (peak intensity usually appearing at 2θ=18o).
Water contact angle:
The water contact angles of the films were measured using a drop tensiometer (OCA 20, Dataphysics Co., Germany) at ambient temperature. A 10 μl of DI water drop was deposited via a microsyringe on the CNC film surface, and the contact angles were measured at different time points. The reported contact angle value was taken from an average of 5 measurements.This work benefited from the use of the SasView software (developed under NSF Award DMR-0520547) containing code developed under the EU Horizon 2020 programme (the SINE2020 project Grant 654000)
FLEXOME software suite, first release 23/11/2020
No full textThis dataset primarily contains source code and instructions for a set of protein analysis utilities collectively called FLEXOME. FLEXOME can perform the following functions on a protein structure input:
- Identification of covalent, hydrophobic and polar interactions using the atomic geometry of the input.
- Surface exposure and burial distance finding.
- Rigid Cluster Decomposition using pebble-game rigidity analysis.
- Normal mode finding with an elastic network model, one site per residue. Only the requested number of low-frequency modes are generated, using Cholesky decomposition and inverse iteration, to avoid the computational cost of fully inverting a large matrix.
- Geometric simulations of flexible motion in the all-atom structure, using the input atomic geometry as constraints and a normal mode eigenvector as a bias direction.
Source code in the form of C++ files (.h and .cpp) is in the CPP/ directory. Useful ancillary scripts are in the SCRIPTS/ directory. The HOWTO/ directory includes a detailed user manual, "FLEXOME-GUIDANCE.txt"; a fully worked example, discussed in the manual, in the LysosymeExample/ directory; and an ExpertExample/ directory showing advanced FLEXOME usage options. Each directory includes a README.txt file summarising its contents and significance.C++ code written by Dr. Stephen A Wells, University of Bath, 2020.The code was written, and should be run, in a Linux command-line environment. The development environment was Cygwin on a Windows laptop with the gcc compiler. Shell scripts are written for the Bash shell. PyMOL scripts are provided to aid visualisation.All code and compilation scripts are in the CPP/ directory. Detailed usage, user manual, and worked example are in the HOWTO/ directory
Dataset for 'Synergistic Effect of Simultaneous Doping of Ceria Nanorods with Cu and Cr on CO Oxidation and NO Reduction'
No full textThis dataset contains characterisation and catalytic data for the manuscript 'Synergistic Effect of Simultaneous Doping of Ceria Nanorods with Cu and Cr on CO Oxidation and NO Reduction'. Data includes: powder XRD (X-ray diffraction), Raman, nitrogen adsorption isotherms, hydrogen TPR (temperature-programmed reduction), XPS (X-ray photoelectron spectroscopy), and catalytic data for CO oxidation and NO reduction.Full details of the methodology may be found in the associated manuscript
Dataset for ‘Views about integrated smoking cessation and IAPT treatment’
No full textData included in this dataset contains transcripts of in-depth interviews with psychological wellbeing practitioners (PWPs), Improving Access to Psychological Therapies (IAPT) patients, and stop smoking advisors recruited from IAPT and smoking cessation services in England. Interviews aimed to understand stakeholders’ views about integrating smoking cessation treatment into outpatient psychological services for common mental illness.We conducted semi-structured interviews with IAPT psychological wellbeing practitioners (PWPs) and patients, and stop smoking service advisors.
Sampling and recruitment:
We recruited participants from IAPT services and smoking cessation services in England until we generated adequate information power. Participants were all aged >18-years. PWPs and smoking cessation advisors were recruited using a snowballing strategy at the local service level. We interviewed a range of males and females, including those were newly qualified (at least 1 year) or who were more experienced in their role (>2 years). IAPT patients were recruited by PWPs during IAPT appointments, using a purposive approach to ensure that participants had with a variety of common mental illness (all treatable in IAPT). IAPT PWPs were non- or ex-smokers. Smoking cessation advisors had provided smoking cessation treatment to people with mental disorders, and were employed in a National Centre for Smoking Cessation Training (NCSCT) trained stop smoking service. IAPT patients had a current form of depression and/or anxiety, were currently receiving IAPT treatment or had completed treatment within a year of the interview, and had smoked daily for at least a year.
Data collection:
Interviews were conducted between September 2017 and April 2018. Participants were interviewed in-person or by telephone. All interviews were audio recorded and lasted typically 60 minutes. Topic guides were used to assist questioning during semi-structured individual interviews with flexibility to reflect emergent findings. The interviewer (GT) used open-ended questioning to elicit participants’ own experiences and views and participants were asked to provide examples to avoid reliance on ‘hypothetical’ accounts.
Data were transcribed by a third-party service. To ensure quality of data transcription a researcher did a 50% check of audio data against the transcripts. Participants were not paid for their contribution to the study, but were provided with sustenance during the interview, and travel costs were reimbursed.All transcripts were anonymised and personal identifying information removed
Datasets for “OmniPhotos: Casual 360° VR Photography”
No full textThis dataset contains the raw and processed data used to validate the results for the paper. Each subdirectory in the Preprocessed and Unprocessed folders contains a 360° video captured in a circle at different locations in the world, using an Insta360 One X 360° camera on a rotating selfie stick. These subdirectories are named after these locations. Both the proprietary (.insv) video format, as well as a stitched equirectangular (.mp4) video (used by our preprocessing pipeline), have been included. As well as these videos, each subdirectory contains the Input frames, used by our software to display the scene, a Capture directory that contains structure-from-motion data for the given scene, as well as a Config directory, which contains necessary configuration files to run our software.
In the Preprocessed directory, the subdirectories also contain a Cache directory, containing optical flow (.floss) files, a CSV file linking the floss files to the relevant images in Input, and .obj files that contain the scene-dependent proxy mesh (deformed sphere) used to render the scene.Full details of the methodology may be found in the associated paper.Version 2 corrects two issues in Version 1:
1. The first scene in Preprocessed.zip ("Ballintoy") was missing the fitted scene-adaptive proxy geometry; this has now been added.
2. The scene "Crescent" in Unpreprocessed.zip contained an incorrect number of frames in the config file, producing a warning during preprocessing
Code from the parametric analysis of masonry panels with limit analysis
No full textThis repository has a python package called "Sapienza" and two python files: 001_masonry_panels.py open_vtk.py 001_masonry_panels can be used to generate the geometry of all the tested masonry panels. It uses the functions defined in the masonry_panels module within the Sapienza package. It requires that the user specifies brick lenght, brick height, number of horizontal bricks and number of vertical bricks. The script generates the polylines in Autocad. open_vtk.py is an script used to generate .png files with the collapse mechanism of every masonry panel. The script opens the .vtk file generated with ALMA 2.0, interacts with paraview and creates a .png file
Dataset for "Effect of plain versus sugar-sweetened breakfast on energy balance and metabolic health: A randomised crossover trial"
No full textThe dataset contains data for the study investigating the effect of 3-weeks high (SWEET) versus low (PLAIN) sugar breakfast on energy balance, metabolic health, and appetite. 29 healthy adults (22 women) completed this randomised crossover study. Participants had pre- and post-intervention appetite, health and body mass outcomes measured, and recorded diet, appetite (visual analogue scales) and physical activity for 8 days during each intervention. Interventions were 3-weeks iso-energetic SWEET (30% by weight added sugar; average 32g sugar) versus PLAIN (no added sugar; average 8g sugar) porridge-based breakfast.
The main finding from the data is that energy balance, health markers, and appetite did not respond differently to 3-weeks of high or low sugar breakfasts.This was a randomised crossover study whereby participants were given a plain porridge versus a 30 % by weight sugar sweetened porridge for three weeks. Measures were taken pre- and post- each intervention, and energy balance and appetite behaviours were measured for 8 days during each intervention period
Dataset for "Freedom of information (FOI) as a data collection tool for social scientists."
Get PDFThe dataset and code contains the analysis of "Freedom of information (FOI) as a data collection tool for social scientists" which evaluates a method of generating a unique dataset that has been underused - a Freedom of Information (FOI) request.Data was collected using i) Freedom of Information requests, ii) downloaded from government websites: police force characteristics and crime statistics - Home Office; local area demographic characteristics - 2011 Census; labour market characteristics - ONS.The data and code files are in Stata format. Microsoft Excel was also used to prepare the data
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