Development of a Hydrogeological Model of the Borrowdale Volcanics at Sellafield

International audienceThis work has arisen out of recent developments within the radioactive waste research programme managed by Her Majesty's Inspectorate of Pollution, UK (HMIP)*, to develop an integrated flow and transport model for the potential deep radioactive waste repository at Sellafield. One of the largest sources of uncertainty in model predictions, is the characterisation of the hydrogeological properties of the underlying strata, in particular, of the Borrowdale Volcanic Group (BVG) within which the repository is to be located. Analysis of the available borehole data (that released by the proponent company, Nirex, by December 1995) for the BVG formation has indicated a dual regime consisting of flow within faults and flow within the matrix (or an equivalent porous medium containing micro-fractures). Significant relationships between permeability, depth and the presence and orientation of faults have been identified; they account for a variation of up to 6 orders of magnitude in mean permeability measurements. This can be explained in part by the effect of the orientation of the current maximum principal stress directions within the BVG: however, it is likely that permeability is also dependent on the existence of fracture families, which cannot be effectively identified from the data currently available. These analyses have enabled considerable insight to be gained into the dominant features of flow within the BVG. The conceptual hydrogeological model derived here will have a significant effect on the outcome and reliability of future radionuclide transport predictions in the Sellafield area

Bayesian hierarchical model for the prediction of football results

The problem of modelling football data has become increasingly popular in the last few years and many different models have been proposed with the aim of estimating the characteristics that bring a team to lose or win a game, or to predict the score of a particular match. We propose a Bayesian hierarchical model to fulfil both these aims and test its predictive strength based on data about the Italian Serie A 1991-1992 championship. To overcome the issue of overshrinkage produced by the Bayesian hierarchical model, we specify a more complex mixture model that results in a better fit to the observed data. We test its performance using an example of the Italian Serie A 2007-2008 championship

Surplus Identification with Non-Linear Returns. ESRI WP522. December 2015

We present evidence from two experiments designed to quantify the impact of cognitive constraints on consumers' ability to identify surpluses. Participants made repeated forced-choice decisions about whether products conferred surpluses, comparing one or two plainly perceptible attributes against displayed prices. Returns to attributes varied in linearity, scale and relative weight. Despite the apparent simplicity of this task, in which participants were incentivised and able to attend fully to all relevant information, surplus identification was surprisingly imprecise and subject to systematic bias. Performance was unaffected by monotonic non-linearities in returns, but non-monotonic non-linearities reduced the likelihood of detecting a surplus. Regardless of the shape of returns, learning was minimal and largely confined to initial exposures. Although product value was objectively determined, participants exhibited biases previously observed in subjective discrete choice, suggesting common cognitive mechanisms. These findings have implications for consumer choice models and for ongoing attempts to account for cognitive constraints in applied microeconomic contexts

An experiment for regulatory policy on broadband speed advertising. ESRI WP641, November 2019

Identifying whether hyperbolic advertising claims influence consumers is important for consumer protection, but differentiating mere “puffery” from misleading advertising is not straightforward. We conducted a pre-registered experiment to determine whether pseudo-technical advertising claims about broadband speed bias consumer choice. We tested whether these claims lead consumers to (i) make suboptimal choices and (ii) choose faster, more expensive broadband packages than they otherwise would. We also tested a potential policy response, consisting of consumer information on broadband speeds and how they are advertised. One-in-five consumers chose a provider advertising “lightning fast” broadband over another offering the same speed at a cheaper price. Puffery also led consumers to choose faster, more expensive packages than consumers who saw no such claims. The information intervention (i) decreased the proportion of suboptimal decisions, (ii) increased the likelihood that consumers switched package, and (iii) improved understanding of speed descriptions. The findings suggest that a relatively soft regulatory intervention may benefit broadband consumers

Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype phenotype correlations

We have generated a mouse carrying the human G551D mutation in the cystic fibrosis transmembrane conductance regulator gene (CFTR) by a one-step gene targeting procedure. These mutant mice show cystic fibrosis pathology but have a reduced risk of fatal intestinal blockage compared with 'null' mutants, in keeping with the reduced incidence of meconium ileus in G551D patients. The G551D mutant mice show greatly reduced CFTR-related chloride transport, displaying activity intermediate between that of cftr(mlUNC) replacement ('null') and cftr(mlHGU) insertional (residual activity) mutants and equivalent to approximately 4% of wild-type CFTR activity. The long-term survival of these animals should provide an excellent model with which to study cystic fibrosis, and they illustrate the value of mouse models carrying relevant mutations for examining genotype-phenotype correlations

Dislocation Nucleation and Propagation in Semiconductor Heterostructures

This paper considers misfit dislocation nucleation and propagation in dilute magnetic semiconductor heterostructures in the CdTe-ZnTe-MnTe system. It is shown that, where the deposit is in tension, 1/2 \u3c 110 \u3e dislocations with inclined Burgers vectors propagate by glide along interfacial \u3c 110 \u3e directions and may dissociate giving intrinsic stacking faults. In cases where the deposit is in compression, 1/2 \u3c 110 \u3e dislocations show no evidence of dissociation and propagate by extensive cross-slip to give networks of dislocations close to interfacial \u3c 100 \u3e directions. Evidence for dislocation sources in ZnTe/GaSb films is presented. ZnTe films contained stacking fault pyramids, single Frank faults and a new type of diamond defect are present at densities up to about 107 cm-2. Analysis showed that the diamond defects, which were four-sided defects on {111} planes with \u3c 110 \u3e edges, were of vacancy type with 1/3 \u3c 111 \u3e Frank Burgers vectors and intrinsic stacking faults. Although faulted defects showed no tendency to grow by climb, evidence is given for an unfaulted reaction in which a glissile 1/2 \u3c 110 \u3e dislocation is generated. This new model for dislocation nucleation is discussed

Educational crowdsourcing to support the learning of computer programming

Technology has been used in the last three decades to support teaching and learning. However, educational software has frequently been under investigation to check the validity of their benefits. There is a demand for increasingly intelligent pedagogically-grounded computer technology. In this paper, we discuss adaptive, crowd sourced, and primarily educational technology; targeted at software development students. The proposed technology caters for either individual or group learning. It differentiates itself from other tutoring and programming support technologies as it will continually monitor and assess students’ performance in each phase of the educating process. It will also guide them in their learning through interactive feedback and adaptive curriculum delivery that suits both their current levels of learning and preferred learning styles. Keywords: Technology and Education; Coding; Teaching and Learning; Computer Programming; Adaptive Software

An open learning system for special needs education

The field of special needs education in case of speech and language deficiencies has seen great success, utilizing a number of paper-based systems, to help young children experiencing difficulty in language acquisition and the understanding of languages. These systems employ card and paper-based illustrations, which are combined to create scenarios for children in order to expose them to new vocabulary in context. While this success has encouraged the use of such systems for a long time, problems have been identified that need addressing. This paper presents research toward the application of an Open Learning system for special needs education that aims to provide an evolution in language learning in the context of understanding spoken instruction. Users of this Open Learning system benefit from open content with novel presentation of keywords and associated context. The learning algorithm is derived from the field of applied computing in human biology using the concept of spaced repetition and providing a novel augmentation of the memorization process for special needs education in a global Open Education setting

Surplus Identification with Non-Linear Returns. ESRI WP522. December 2015

We present evidence from two experiments designed to quantify the impact of cognitive constraints on consumers' ability to identify surpluses. Participants made repeated forced-choice decisions about whether products conferred surpluses, comparing one or two plainly perceptible attributes against displayed prices. Returns to attributes varied in linearity, scale and relative weight. Despite the apparent simplicity of this task, in which participants were incentivised and able to attend fully to all relevant information, surplus identification was surprisingly imprecise and subject to systematic bias. Performance was unaffected by monotonic non-linearities in returns, but non-monotonic non-linearities reduced the likelihood of detecting a surplus. Regardless of the shape of returns, learning was minimal and largely confined to initial exposures. Although product value was objectively determined, participants exhibited biases previously observed in subjective discrete choice, suggesting common cognitive mechanisms. These findings have implications for consumer choice models and for ongoing attempts to account for cognitive constraints in applied microeconomic contexts