Radiological Characterization of a Uranium Processing Facility

This document describes the plan that was developed and is being carried out at the Oak Ridge Y-12 Plant to provide data needed for radiological characterization of the site in anticipation of new posting regulations provided in Title 10, Code of Federal Regulations, Part 835, as codified from Volume 58, Number 238 of the Federal Register. The characterization plan addresses the entire site in terms of three categories: 1) Outdoor paved surfaces, 2) buildings, and 3) outdoor non-paved surfaces. Instruments chosen for use in this project are described, as well as survey techniques and the data management scheme. A quantitative assessment of the effectiveness and adequacy of the survey plan for paved surfaces is also provided

Generalised Elliptic Functions

We consider multiply periodic functions, sometimes called Abelian functions, defined with respect to the period matrices associated with classes of algebraic curves. We realise them as generalisations of the Weierstras P-function using two different approaches. These functions arise naturally as solutions to some of the important equations of mathematical physics and their differential equations, addition formulae, and applications have all been recent topics of study. The first approach discussed sees the functions defined as logarithmic derivatives of the sigma-function, a modified Riemann theta-function. We can make use of known properties of the sigma function to derive power series expansions and in turn the properties mentioned above. This approach has been extended to a wide range of non hyperelliptic and higher genus curves and an overview of recent results is given. The second approach defines the functions algebraically, after first modifying the curve into its equivariant form. This approach allows the use of representation theory to derive a range of results at lower computational cost. We discuss the development of this theory for hyperelliptic curves and how it may be extended in the future.Comment: 16 page

Deriving bases for Abelian functions

We present a new method to explicitly define Abelian functions associated with algebraic curves, for the purpose of finding bases for the relevant vector spaces of such functions. We demonstrate the procedure with the functions associated with a trigonal curve of genus four. The main motivation for the construction of such bases is that it allows systematic methods for the derivation of the addition formulae and differential equations satisfied by the functions. We present a new 3-term 2-variable addition formulae and a complete set of differential equations to generalise the classic Weierstrass identities for the case of the trigonal curve of genus four.Comment: 35page

Reviewing research evidence and the case of participation in sport and physical recreation by black and minority ethnic communities

The paper addresses the implications of using the process of systematic review in the many areas of leisure where there is a dearth of material that would be admitted into conventional Cochrane Reviews. This raises important questions about what constitutes legitimate knowledge, questions that are of critical import not just to leisure scholars, but to the formulation of policy. The search for certainty in an area that lacks conceptual consensus results in an epistemological imperialism that takes a geocentric form. While clearly, there is a need for good research design whatever the style of research, we contend that the wholesale rejection of insightful research is profligate and foolhardy. A mechanism has to be found to capitalise on good quality research of whatever form. In that search, we draw upon our experience of conducting a review of the material available on participation in sport and physical recreation by people from Black and minority ethnic groups. The paper concludes with a proposal for a more productive review process that makes better use of the full panoply of good quality research available. © 2012 © 2012 Taylor & Francis

Capital structure and its determinants in the United Kingdom – a decompositional analysis

Prior research on capital structure by Rajan and Zingales (1995) suggests that the level of gearing in UK companies is positively related to size and tangibility, and negatively correlated with profitability and the level of growth opportunities. However, as argued by Harris and Raviv (1991), 'The interpretation of results must be tempered by an awareness of the difficulties involved in measuring both leverage and the explanatory variables of interest'. In this study the focus is on the difficulties of measuring gearing, and the sensitivity of Rajan and Zingales' results to variations in gearing measures are tested. Based on an analysis of the capital structure of 822 UK companies, Rajan and Zingales' results are found to be highly definitional-dependent. The determinants of gearing appear to vary significantly, depending upon which component of debt is being analysed. In particular, significant differences are found in the determinants of long- and short-term forms of debt. Given that trade credit and equivalent, on average, accounts for more than 62% of total debt, the results are particularly sensitive to whether such debt is included in the gearing measure. It is argued, therefore, that analysis of capital structure is incomplete without a detailed examination of all forms of corporate debt

Abelian functions associated with a cyclic tetragonal curve of genus six

We develop the theory of Abelian functions defined using a tetragonal curve of genus six, discussing in detail the cyclic curve y^4 = x^5 + λ[4]x^4 + λ[3]x^3 + λ[2]x^2 + λ[1]x + λ[0]. We construct Abelian functions using the multivariate sigma-function associated with the curve, generalizing the theory of theWeierstrass℘-function. We demonstrate that such functions can give a solution to the KP-equation, outlining how a general class of solutions could be generated using a wider class of curves. We also present the associated partial differential equations satisfied by the functions, the solution of the Jacobi inversion problem, a power series expansion for σ(u) and a new addition formula

Effective lifetime radiation risk for a number of national mammography screening programmes

Background and purpose: The performance of mammography screening programmes is focussed mainly on breast cancer detection rates. However, when the benefits and risks of mammography are considered, the risk of radiation-induced cancer is calculated for only the examined breast using Mean Glandular Dose (MGD). The risk from radiation during mammography is often described as low or minimal. This study aims to evaluate the effective lifetime risk from full field digital mammography (FFDM) for a number of national screening programmes. Material and Methods: Using an ATOM phantom, radiation doses to multiple organs were measured during standard screening mammography. Sixteen FFDM machines were used and the effective lifetime risk was calculated across the female lifespan for each machine. Once the risks were calculated using the phantom, the total effective lifetime risk across 48 national screening programmes was then calculated; this assumed that all these programmes use FFDM for screening. Results: Large differences exist in effective lifetime risk, varying from 42.21 [39.12 - 45.30] cases/106 (mean [95% CI]) in the Maltese screening programme to 1099.67 [1019.25 - 1180.09] cases/106 for high breast cancer risk women in the United States of America. These differences are mainly attributed to the commencement age of screening mammography and the time interval between successive screens. Conclusions: Effective risk should be considered as an additional parameter for the assessment of screening mammography programme performance, especially for those programmes which recommend an early onset and more frequent screening mammography

Bridging the gap between the home and the hospital : a qualitative study of partnership working across housing, health and social care

Rising demand and financial challenges facing public services have increased the impetus for greater integration across housing, health and social care. To provide insight into the benefits and challenges of partnership, we interviewed 37 housing professionals and held a validation workshop with eight external agencies working within a new, integrated housing service in the United Kingdom. The strength of the initiative rests on the capacity of neighbourhood officers to conduct home visits and refer tenants to support agencies. Yet this strength poses problems in partnership building because increased referrals threaten to overwhelm already stretched health services. Despite broadly supporting the initiative, officers expressed concern over losing specialist housing knowledge whilst filling in gaps for services. Tensions over professional role boundaries between officers and social workers, poor communication, lack of capacity in external agencies and difficulties in sharing information were identified as barriers to partnership. Whilst capacity issues were acknowledged, partner agencies welcomed the initiative and called for joint meetings and colocation of services. Lack of capacity of external agencies to respond to referrals threatens integrated housing and health initiatives. Greater interprofessional collaboration and further investment across the system is required to increase capacity and ensure referrals are translated into healthcare outcomes

Comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition

There has been recent interest in the use of machine learning (ML) approaches within mathematical software to make choices that impact on the computing performance without affecting the mathematical correctness of the result. We address the problem of selecting the variable ordering for cylindrical algebraic decomposition (CAD), an important algorithm in Symbolic Computation. Prior work to apply ML on this problem implemented a Support Vector Machine (SVM) to select between three existing human-made heuristics, which did better than anyone heuristic alone. The present work extends to have ML select the variable ordering directly, and to try a wider variety of ML techniques. We experimented with the NLSAT dataset and the Regular Chains Library CAD function for Maple 2018. For each problem, the variable ordering leading to the shortest computing time was selected as the target class for ML. Features were generated from the polynomial input and used to train the following ML models: k-nearest neighbours (KNN) classifier, multi-layer perceptron (MLP), decision tree (DT) and SVM, as implemented in the Python scikit-learn package. We also compared these with the two leading human constructed heuristics for the problem: Brown's heuristic and sotd. On this dataset all of the ML approaches outperformed the human made heuristics, some by a large margin.Comment: Accepted into CICM 201