Forecasting UK Industrial Production Over the Business Cycle

This paper examines the information available through leading indicators for modelling and forecasting the UK quarterly index of production (seasonally adjusted). The emphasis is on one-quarter ahead prediction, especially over the 1990s recession. Linear specifications considered are univariate autoregressive models together with dynamic single indicator and multiple indicator models. Both univariate and leading indicator versions of nonlinear Markov switching specifications are also examined. In the latter case, the transition probabilities are modelled as logistic functions of the leading indicators, allowing the lead times to differ for the expansion to expansion and recession to recession probabilities. Despite general evidence that the term structure of interest rates helps regime classification in the Markov switching models, these models perform relatively poorly in forecasting the 1990s production recession. It is suggested that this poor performance may be due to the nature of that recession, which differed from previous major UK postwar recessions in having no single quarter where industrial production declined substantially. However, a three indicator linear specification does well. The leading indicator variables in this latter model are a short-term interest rate, the stock market dividend yield and the optimism balance from the quarterly survey conducted by the Confederation of British Industry.

Breast cancer risk and imprinting methylation in blood

Date of Acceptance: 17/08/2015 Acknowledgements This study was supported by the Breast Cancer Campaign (2008MayPR46) and Fraserburgh Moonlight Prowl Breast Cancer Charity. PH, GH and GWH acknowledge the support of the Scottish Government. We would like to thank Val Bain and Michela Donnarumma for help with the data and sample collection.Peer reviewedPublisher PD

Fuel resource utilisation in landscapes of settlement

One little understood aspect of the settlement and colonisation of Iceland is fuel resource use. In this paper we identify fuel ash residues from temporally constrained middens at two contrasting settlement age sites in Mývatnssveit, northern Iceland, one high status, the other low status and ultimately abandoned. Fuel residues derived from experimental combustion of historically defined fuel resources are used to provide control for thin section micromorphology and complementary image analyses of fuel residue materials found in the midden deposits. The results suggest that fuel resources utilised at the time of settlement were for both low temperature and high temperature use, and included a mix of birch and willow wood, peat, mineral-based turf and cow dung. There are, however, marked variations in the mix of fuel resources utilised at the two sites. This is considered to reflect social regulation of fuel resources and socially driven changes to local and regional environments that may have contributed to the success or failure of early settlement sites in Iceland

Evidence for the Evolution of Young Early-Type Galaxies in the GOODS/CDF-S Field

We have developed an efficient photometric technique for identifying young early-type galaxy candidates using a combination of photometric redshifts, spectral-type classification, and optical/near-infrared colors. Applying our technique to the GOODS HST/ACS and VLT/ISAAC data we have selected a complete and homogeneous sample of young elliptical candidates among early-type field galaxies. The distribution of structural parameters for these candidates shows that their selection, which is based on early spectral types, is fully consistent with early morphological types. We investigate the evolution of their luminosities and colors as a function of redshift and galaxy mass and find evidence for an increasing starburst mass fraction in these young early-type galaxy candidates at higher redshifts, which we interpret in terms of massive field galaxies experiencing more massive/intense starbursts at higher redshifts. Moreover, we find indications for a systematically larger young elliptical fraction among sub-L*/2 early-type galaxies compared to their brighter counterparts. The total fraction among the field early-type galaxies increases with redshift, irrespective of galaxy luminosity. Our results are most consistent with galaxy formation scenarios in which stars in massive early-type field galaxies are assembled earlier than in their low-mass counterparts.Comment: 11 pages, 10 figures, accepted for publication in A

Algorithm Selection Framework for Cyber Attack Detection

The number of cyber threats against both wired and wireless computer systems and other components of the Internet of Things continues to increase annually. In this work, an algorithm selection framework is employed on the NSL-KDD data set and a novel paradigm of machine learning taxonomy is presented. The framework uses a combination of user input and meta-features to select the best algorithm to detect cyber attacks on a network. Performance is compared between a rule-of-thumb strategy and a meta-learning strategy. The framework removes the conjecture of the common trial-and-error algorithm selection method. The framework recommends five algorithms from the taxonomy. Both strategies recommend a high-performing algorithm, though not the best performing. The work demonstrates the close connectedness between algorithm selection and the taxonomy for which it is premised.Comment: 6 pages, 7 figures, 1 table, accepted to WiseML '2

Historic landscape management: a validation of quantitative soil thin-section analyses

The archaeological interpretation of past land management practices can be greatly enhanced through examination of soil thin sections. Features relating to manuring practice are among those key to interpreting agricultural practices. The sources and the pro¬cesses leading to the distribution of these manure materials may further improve knowledge of the past landscape utilisation. The use of quantitative analyses to examine soil thin sections opens the possibility of considering these relationships between manured areas in greater detail and to extract more subtle spatial and temporal changes in past management. In this study the validation of this methodology has been tested with quantitative image analysis methods used to examine manure inputs to a well-documented historical landscape of Papa Stour, Shetland, where intensive manuring has been practised until the 1960s. By using both historic and ethnographic evidence to validate the image analysis protocol, differences in spatial and temporal distribution are examined for the practices of manuring with both fuel residues and with turf. The validation of the hypotheses expected from ethnographic and historical data that quantitative soils-based evidence allows the definition of variations in manuring strategies and provides a more secure basis from which to interpret manuring management strategies in archaeological landscapes

Human responses, resilience and vulnerability : an interdisciplinary approach to understanding past farm success and failure in Mývatnssveit, northern Iceland

This thesis presents a new perspective on the study of past farm success and failure; it builds on the concepts of resilience and vulnerability to construct a theoretical framework which integrates environmental, historical and ethnographical data. The basic framework establishes that the resilience or vulnerability of a social-ecological system is a function of three factors: i) the exposure of the system to external (environmental) stresses, ii) the sensitivity of the system to these stresses and iii) the ability of the human component of the system to respond to them. The research focused on the component of human capacity of response (the sum of coping and adaptive capacity) within this framework. The temporal scale of the study was the 18th century, although reference is made to earlier periods for comparison. The location of the study area was Mývatnssveit, a livestock-based farming community in northern Iceland, while the spatial scale of the study is that of individual farms in the area. The results showed that successful farms had a higher capacity of response than failed farms, and that this was conferred by a greater availability and quality of resources, including human resources, natural resources and productive resources (those directly involved in agriculture). Human resources were assessed by records of number of servants per farm and by evidence of learning/knowledge transfer obtained via micromorphological analyses of home-field soils. Natural resources considered to be of particular importance were fish and eggs. Indicators of productive resources included tax value, land rent, livestock numbers and phosphorus content in home-fields. The latter revealed that the soil condition pre-settlement was linked to its post-settlement quality. An analysis of present day perceptions of historical farm abandonment in the area corresponds with the conclusions reached through the data integration in placing the human factor above the environmental one in influencing success and failure. The thesis concludes by highlighting the individuality of the study farms and the historical resilience of the livestock-based farming system. Additionally, areas of potential for future research are identified.EThOS - Electronic Theses Online ServiceGBUnited Kingdo