The National Superficial Deposit Thickness Model. (Version 5)

The Superficial Deposits Thickness Model (SDTM) is a raster-based dataset designed to demonstrate the variation in thickness of Quaternary-age superficial deposits across Great Britain. Quaternary deposits (all unconsolidated material deposited in the last 2.6 million years) are of particular importance to environmental scientists and consultants concerned with our landscape, environment and habitats. The BGS has been generating national models of the thickness of Quaternary-age deposits since 2001, and this latest version of the model is based upon DiGMapGB-50 Version 5 geological mapping and borehole records registered with BGS before August 2008

User guide : soil parent material 1 kilometre dataset

This document provides information for users of the Soil Parent Material 1km dataset. The Soil Parent Material 1km (SPM1k) database is part of a series of GIS maps designed to help environmental scientists and consultants assess the characteristics of the ‘near-surface’ weathered zone. In particular, the data focuses upon the material from which top soils and subsoils (A and B horizons) develop (i.e. from the base of pedological soil down to c. 2-3m). This Soil Parent Material1km resolution dataset is provided as a free-to-use dataset under the Open-Government License. The 1km dataset is derived from the standard 1:50,000 scale Soil Parent MaterialV6 dataset by spatial generalising (onto a regular vector grid of 1km cell size) the dominant Parent Material type onto a 1km resolution vector grid. Each grid cell being attributed seven fields of simple information derived from the dominant parent type. The attribution of the dataset mirrors that available within the UK Soil Observatory. www.UKSO.org. The 1km resolution makes the data an ideal vector layer to use with other freely available layers from the UKSO

Coherence of a room-temperature CW GaAs/GaAlAs injection laser

The temporal coherence of a stripe-geometry double-heterojunction GaAs/GaAlAs laser operating CW at room temperature was determined. A heterodyne detection scheme was used involving the mixing of the laser field with a frequency-shifted and time-delayed image of itself in an interferometer. Because the laser device oscillated in several longitudinal modes, the autocorrelation function of its output exhibited resonances for specific time delays. The rate at which the amplitude of these resonances decreased with increasing time delays provided a measure of an apparent coherence length associated with individual longitudinal modes. The coherence length, so defined, was found to increase linearly with drive current in excess of threshold. This observation is interpreted as evidence that the intrinsic linewidth of a longitudinal mode is inversely proportional to the coherent optical power in that mode. Apparent coherence lengths were a few centimeters for a few milliwatts of total optical power emitted per facet. For a perfectly balanced interferometer, a sharp heterodyne beat signal was also observed when the laser device was operated considerably below threshold, i.e., in the LED mode

The Implementation of an Automated Assessment Feedback and Quality Assurance System for ICT Courses

Providing detailed, constructive and helpful feedback is an important contribution to effective student learning. Quality assurance is also required to ensure consistency across all students and reduce error rates. However, with increasing workloads and student numbers these goals are becoming more difficult to achieve. An automated feedback system, referred to as the Automated Feedback Generator (AFG), has therefore been designed and developed with the aim of providing superior quality assurance and efficiency in both assessing student assignments and providing feedback. Unlike existing automated marking and feedback software, AFG aims to allow educators to perform the entire process of student feedback generation for any assessment type. The AFG system is investigated across two introductory ICT courses: general ICT and programming. The aim is to demonstrate that AFG provides a more effective means for providing student feedback than alternative manual and automated approaches. This is achieved by comparing AFG with these alternatives and demonstrating that it offers quality control, efficiency and effectiveness benefits whilst generating consistent feedback from a student perspective. An empirical approach is employed using attitudinal data. T tests are used to test hypotheses comparing three feedback generation approaches: AFG, manual and a more complex automated approach. The results show that feedback from AFG was perceived to be constructive, helpful and with error levels less than or equal to those for other course feedback approaches; students also found feedback to be consistent with that produced by the more complex alternatives

Thurstonian Scaling of Compositional Questionnaire Data

To prevent response biases, personality questionnaires may use comparative response formats. These include forced choice, where respondents choose among a number of items, and quantitative comparisons, where respondents indicate the extent to which items are preferred to each other. The present article extends Thurstonian modeling of binary choice data (Brown & Maydeu-Olivares, 2011a) to “proportion-of-total” (compositional) formats. Following Aitchison (1982), compositional item data are transformed into log-ratios, conceptualized as differences of latent item utilities. The mean and covariance structure of the log-ratios is modelled using Confirmatory Factor Analysis (CFA), where the item utilities are first-order factors, and personal attributes measured by a questionnaire are second-order factors. A simulation study with two sample sizes, N=300 and N=1000, shows that the method provides very good recovery of true parameters and near-nominal rejection rates. The approach is illustrated with empirical data from N=317 students, comparing model parameters obtained with compositional and Likert scale versions of a Big Five measure. The results show that the proposed model successfully captures the latent structures and person scores on the measured traits

User guide for the BGS Geology : 50k dataset (V8)

The British Geological Survey provides nationwide digital geological maps at a range of scales. These digital products are known by the name ‘BGS Geology’ (formerly DiGMapGB). This guide is written for users of the 1:50 000 scale digital geological map data (BGS Geology: 50k) version 8, released in 2016. It describes the basic layout and content of the dataset and provides background information as to how this version of the dataset has changed compared with previous versions. A basic appreciation of Geographical Information System (GIS) terminology is needed to understand some of the information outlined here. Users should also familiarise themselves with some of the basic principles behind geological description of our landscape; further information about how BGS has made the geological map of Great Britain can be found on the BGS website at: http://www.bgs.ac.uk/products/digitalmaps/digmapgb.htm

What to Do When the F10.7 Goes Out?

The solar radio flux at 10.7 cm, known as F10.7, is a critical operational space weather index. However, without a clear backup, any interruption to the service can result in substantial errors in model outputs. In this paper we show the impact of one such outage in March 2022 on the models TIE-GCM and NeQuick, and present a number of alternative solutions that could be used for future outages. The analysis is extended to the F10.7 time series since 1951 and the approach resulting in the smallest reconstruction error of F10.7 uses the solar radio flux observations at alternative wavelengths (the best giving a percentage error of 3.1%). Alternatively, use of Sunspot Number, a regular, robust alternative observation, results in a mean percentage error of 8.2% and is also a reliable fallback solution. Additionally, analysis of the error on the use of the conversion between the 12-month rolling sunspot number (R12) and its conversion to F10.7 is included

Fast decisions reflect biases, slow decisions do not

Decisions are often made by heterogeneous groups of individuals, each with distinct initial biases and access to information of different quality. We show that in large groups of independent agents who accumulate evidence the first to decide are those with the strongest initial biases. Their decisions align with their initial bias, regardless of the underlying truth. In contrast, agents who decide last make decisions as if they were initially unbiased, and hence make better choices. We obtain asymptotic expressions in the large population limit that quantify how agents' initial inclinations shape early decisions. Our analysis shows how bias, information quality, and decision order interact in non-trivial ways to determine the reliability of decisions in a group.Comment: 12 pages, 4 figure