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Data from UK Pension Reforms (1997-2015)
No full textThis dataset contains video content created and documents collected by the Institute for Policy Research at the University of Bath for the research project ‘Pension Reforms in the UK: 1997 to 2015’, funded by the National Employment Savings Trust (Nest) Insight.
The pension reforms that were initiated in the early 2000s with the 'Turner' Pensions Commission, and implemented during the 2010s, represent a milestone in the history of UK pensions provision. The ‘Pension Reforms in the UK’ project is about bringing together existing information on these reforms and augmenting it with new material and content. This dataset is part of that work and aims ultimately to contribute to a UK Pension Reforms Archive.
The dataset contains 24 elite semi-structured video interviews with former UK prime ministers, secretaries of state, ministers, special advisers, Pensions Commission’s members, civil servants, stakeholders, academics and journalists, and 97 documents related to the reforms. The files are freely available for researchers and anyone who is interested in the UK's pension reforms or policy change more widely, to review and use in an appropriate manner.
The dataset is divided into four stages of reform:
- Stage 1: Pensions in the later 1990s and early 2000s;
- Stage 2: The Pensions Commission (2002-2006);
- Stage 3: Policy enactment (2006-2010);
- Stage 4: Implementation (2010-2015).
You can also watch a 10-minute summary video with highlights of the interviews with participants
Interview with Helen Dean
No full textHelen Dean, Director of Product and Policy Development at Personal Accounts Delivery Authority (2009-2010) and current NEST CEO shares her views on the reform process, including the application of behavioural economics to pension policy and consensus-building towards the creation of a national pensions savings scheme (currently National Employment Savings Trust
Dataset for journal article "Moving to a green building: indoor environmental quality, thermal comfort and health"
No full textThis dataset includes:
1- longitudinal objective sensor data for both thermal conditions and Indoor Air Quality (IAQ).
2- Cross section data for thermal conditions.
3- subjective data for occupants' satisfaction, thermal comfort, and sick building syndrome.
4- Subjective data of occupants’ response of environment attitude inventory.It is a longitudinal research design with repeated measures. We followed the same occupants working in the same organisation, a commercial company in Jordan, as they moved from four conventional buildings to a single JGBG-certified “green” building. The repeated measures cover buildings' parameters (thermal conditions + CO2) and occupant aspect (satisfaction, thermal comfort, and perceived health). We did the measurements in three rounds: one in the old conventional buildings and twice in green building (6-month + 12-month after transition).The continuous data were collected using Raspberry-Pi based sensors. the cross-sectional data were collected used ISO7726 and ISO7730 compliant equipment ‘SWEMA’. We used the R programming language for analysis
Dataset for "Zeolites fit for a Crown: Probing Host-Guest Interactions with Thermogravimetric Methods"
No full textThis dataset contains the relevant data for the article "Zeolites fit for a Crown: Probing Host-Guest Interactions with Thermogravimetric Methods". This includes the following. Powder X-ray diffraction (PXRD) data used to identify and confirm the structure of the zeolites samples prepared. Thermogravimetric (TG) data of how the mass% of the zeolite samples vary with increasing temperature, in addition to the mass spectrometry (MS) signals of the gases liberated from the samples. Differential thermal analysis (DTA) data, used to observe the change in heat flow in the samples with temperature, to observe the enthalpy changes. Also included are .tiff files of the figures present in the article.The powder X-ray diffraction (PXRD) data were collected using a Bruker D8 Advance X-ray powder diffractometer in the University of Bath CCAF. This instrument used Cu Ka radiation of a 1.5418 A wavelength.
The thermogravimetric (TG) and differential thermal analysis (DTA) were collected using a Setaram Setsys Evolution TGA 16/18 instrument at the University of Bath CCAF. This was equipped with a Pfeiffer Vacuum Omnistar GSD 320, with a quadrupole mass analyser and a SEM detector for mass spectrometry (MS) of the evolved gases.
TG and DTA analysis were performed by heating the sample in an air atmosphere (flow rate 20 mlmin-1) from 30C to 600C using a ramp rate of 5 Kmin-1. Ramp rates of 2 and 10 Kmin-1 were also used. For zeolite samples Na-X and EMC-2 intermediate static heating stages were used, being 60 minutes at 130C for the former and 20 minutes at 180C for the later.
MS was performed by scanning the m/z ion range from 0-200. This was followed by specifically tracking the m/z ions of 18, 32 and 44, which correspond to water, oxygen and carbon dioxide respectively.Data was processed using Microsoft Excel and Origin Pro 9.0.
For DTA analysis, the background was removed manually using a polynomial function. The signals were then scaled accordingly by the total mass% of organic 18C6 material present in the samples.
The determination of the activation energy is detailed in the "Additional Information".The activation energy was calculated following the European Standard ISO 11358-3:2014.
The onset of decomposition was determined as the midpoint between the peaks in the derivative TG curves (dTG) for water desorption and decomposition. The offset of decomposition was accepted as the final measurement in the TG data at 600C. The mass% values within this range were converted into parameter "Alpha", whereby the value is '0.0' at the onset decomposition, and '1.0' at the offset. This was performed for the three ramp rates: 2, 5 and 10 Kmin-1.
At '0.1' intervals of Alpha, the logarithm of the ramp rate used was plotted against the inverse of the temperature. This produces a straight for each Alpha value, of which the gradient corresponds to the activation energy.
For zeolites RHO and ZK-5, the activation energies were calculated using Alpha values of 0.1, 0.2 and 0.3, followed by taking an average. For zeolite Na-X two events were detected, and the Alpha values used were 0.1, 0.15 and 0.2 for the first event, and 0.8, 0.85 and 0.9 for the second event, with averages taken. For zeolite EMC-2 two events were also observed, with Alpha values of 0.1, 0.15 and 0.2 taken for the first event, and 0.7, 0.75 and 0.8 taken for the second event, with averages taken
Dataset for "Resource-efficient frequency conversion for quantum networks via sequential four-wave mixing"
No full textThis dataset contains the raw data files, and the Matlab analysis and plotting scripts, used to produce the experimental results presented in the manuscript "Resource-efficient frequency conversion for quantum networks via sequential four-wave mixing". The data within include seeded and unseeded degenerate four-wave-mixing spectra, Bragg-scattering four-wave-mixing spectra, and oscilloscope traces monitoring four-wave mixing sideband intensity. Numerical analysis of this data is performed to calculate Bragg-Scattering up- and down-conversion efficiencies as well as to investigate the pulse-to-pulse stability of degenerate FWM sidebands.Full details of the methodology may be found in the associated manuscript
Dataset for "The effect of acute citalopram on self-referential emotional processing and social cognition in healthy volunteers"
Get PDFThis dataset is for a study examining whether acute administration of citalopram is associated with an increase in positive affective learning biases about the self and increases in prosocial behaviour. 41 healthy volunteers were randomised to either an acute 20 mg dose of citalopram (n = 20) or matched placebo (n = 21) in a between-subjects double-blind design. Participants completed computer-based cognitive tasks designed to measure referential affective processing, social cognition and expression of prosocial behaviours. This included a prisoners' dilemma task, the social evaluation learning task, a referential categorisation and recall task, an affective go/no-go association task and simple associative learning tasks. Participants also completed trait measures of mood and personality at baseline, and state measures of mood and side effects at baseline, post-drug and post-testing timepoints. Data for all questionnaire and cognitive task measures are included in this dataset in both raw and aggregated formats.This study was pre-registered on Open Science Framework (https://osf.io/rn79v), which details the study methodology and data analysis plans. Briefly, this study used a randomised between-subject double-blind design where participants were allocated to receive an acute dose of citalopram (20 mg) or placebo. Participants completed a number of cognitive tasks and self-report questionnaires of mood and personality.Data files were anonymised by generating hashed IDs to replace participant unique identifiers using the digest package in R. Variables which could potentially identify participants were removed, including specific employment details, specific language spoken as a first language, and age in years and months (only years were retained).R version 3.6 was used to clean and analyse the data. Full details of the process for cleaning the data can be found in the Raw anonymised data R scripts. Full details for analysing the data can be found in the Acute_Citalopram_Paper_Statistics.Rmd file.The data for this study has been separated into two parts (1) the merged raw files produced by each of the cognitive tasks / questionnaires, (2) the cleaned data files and scripts that reflect the data analysis reported in our paper.
For the raw data I have provided both .xlsx and .csv files, although I imported the data into R using .xlsx so there may be some discrepancies when using the .csv files with the R scripts. For the cleaned data for analysis I have provided the R dataframe files and .csv files. I imported the data into R using the dataframe files so again there may be discrepancies when using the R script with the .csv files. It is therefore recommended to use the .xlsx files for the raw data and the R dataframe files for the cleaned data if also using the accompanying R scripts
Data for Arylboronic Acid-Catalyzed C-Alkylation and Allylation Reactions Using Benzylic Alcohols
No full textOriginal, unprocessed data for all novel compounds in the associated paper. Data available includes 1H, 13C, 19F, and 11B Nuclear Magnetic Resonance (NMR) data, copies of mass spectrometry data, and copies of infra-red (IR) spectra.Full experimental details for the preparation of each compound can be found in the Supplementary Information of the associated paper.
Infrared spectra were recorded on either a Shimadzu IRAffinity-1 Fourier transform IR spectrophotometer fitted with a Specac Quest ATR accessory (diamond puck) or on a Perkin-Elmer PerkinElmer Spectrum 100 ATR-FTIR spectrometer. Spectra were recorded of either thin films or solids, with characteristic absorption wavenumbers (νmax) reported in cm–1.
1H, 13C{1H}, and 19F{1H} NMR spectra were acquired on either a Bruker AV300 (1H 300 MHz; 13C{1H} 75 MHz; 19F{1H} 282 MHz), a Bruker AV400 (1H 400 MHz; 13C{1H} 101 MHz; 19F{1H} 376 MHz), a Bruker AVII 400 (1H 400 MHz; 13C{1H} 101 MHz; 19F{1H} 376 MHz), a Bruker Neo 400 (1H 400 MHz; 13C{1H} 101 MHz; 19F{1H} 376 MHz), a Bruker AVIII-HD 500 (1H 500 MHz, 13C{1H} 126 MHz, 19F{1H} 470 MHz, 11B 160 MHz), a Bruker AVIII 500 (1H 500 MHz, 13C{1H} 126 MHz, 19F{1H} 470 MHz, 11B 160 MHz), or an Agilent ProPulse 500 (1H 500 MHz, 13C{1H} 126 MHz, 19F{1H} 470 MHz) in the deuterated solvent stated. All chemical shifts are quoted in parts per million (ppm) relative to the residual solvent peak. All coupling constants, J, are quoted in Hz. Multiplicities are indicated as s (singlet), d (doublet), t (triplet), q (quartet), m (multiplet), and multiples thereof. The abbreviation Ar denotes aromatic and app denotes apparent. NMR peak assignments were confirmed using 2D 1H correlated spectroscopy (COSY), 2D 1H−13C heteronuclear multiple-bond correlation spectroscopy (HMBC), and 2D 1H−13C heteronuclear single quantum coherence (HSQC) where necessary.
Mass spectrometry (m/z) data were acquired by either electrospray ionisation (ESI), chemical ionisation (CI), electron impact (EI), atmospheric solids analysis probe (ASAP), atmospheric pressure chemical ionization (APCI) or nanospray ionisation (NSI) at either the University of St Andrews Mass Spectrometry Facility ([A] quoted), the EPSRC UK National Mass Spectrometry Facility at Swansea University ([A]+ or [A]– quoted), or at the University of Bath ([A]+ or [A]– quoted) using a TOF mass analyzer.IR spectra were processed using Shimadzu IRsolution FTIR control software. Final processed spectra are available as PDF files.
NMR data were processed using MestReNova (v.11.0.2) available from Mestrelab Research S.L. Original unprocessed FID files and processed MestReNova files are available.
Mass spectroscopy data was used as received from the managed facilities. The spectra are available as PDF files.The numbers of individual folders correspond to the compound numbers in the associated manuscript
Political Ambition in Britain Survey, 2017
No full textThe Political Ambition in Britain Survey, 2017 consists of responses to a survey regarding individual-level patterns of political ambition in Britain, fielded in 2017 to an online panel of over 10,000 respondents.
This project aimed to answer the question of why some people hold ambitions to run for political office, at any level, whilst others do not. This research examined different explanations for why some British people are politically ambitious and others are not and assess which factors hold the greatest influence over, and interrelate, to affect individuals' levels of political ambition.
The survey examines levels of political ambition (interest in running for office) across the UK and includes a range of political, social, and economic variables expected to condition ambition.
(Abstract copyright UK Data Service and data collection copyright owner.)Time dimension: Cross-sectional (one-time) study.
Sampling procedure: Quota sample.
Mode of data collection: Self-administered questionnaire: Web-based (CAWI).
Further documentation is provided within the dataset
Dataset for "The OpenFlexure Block Stage: Sub-100 nm fibre alignment with a monolithic plastic flexure stage"
No full textData archive for "The OpenFlexure Block Stage: Sub-100 nm fibre alignment with a monolithic plastic flexure stage" by Qingxin Meng, Kerrianne Harrington, Julian Stirling, and Richard Bowman. This zip archive contains the following resources:
- The data collection scripts used to characterise the mechanical performance of the OpenFlexure Block Stage.
- The raw data generated by these scripts in hdf5 format.
- The analysis scripts (iPython notebooks) used to analyse this data.
- PDFs of all figures used in the paper as generated by the analysis script and a number of supplementary figures generated by the script. See comments in the scripts for more details on the figures.
- Design files for the modified OpenFlexure Block Stages that were needed for mechanical testing. The custom attaching hardware, and a custom laser autocollimator used to measure the tilt of the stage. The only design files not included are those for the OpenFlexure Block Stage itself as this is an active project and the design and all history can be found in the project's source code repository: https://gitlab.com/openflexure/openflexure-block-stageFull details of the methodology used may be found in the README files accompanying the data within the zip file
Data from the parametric analysis of masonry panels with limit analysis
No full textFor each one of the simulations performed from the parametric analysis of masonry panels with limit analysis, this database contains a .txt, a .vtk and a .png file. In the .txt file the elapse time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry panel. Finally, the .png file presents the collapse mechanism obtained
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