Spatio-temporal Modelling of Remote-sensing Lake Surface Water Temperature Data

Remote-sensing technology is widely used in environmental monitoring. The coverage and resolution of satellite based data provide scientists with great opportunities to study and understand environmental change. However, the large volume and the missing observations in the remote-sensing data present challenges to statistical analysis. This paper investigates two approaches to the spatio-temporal modelling of remote-sensing lake surface water temperature data. Both methods use the state space framework, but with different parameterizations to reflect different aspects of the problem. The appropriateness of the methods for identifying spatial/temporal patterns in the data is discussed

Functional PCA for Remotely Sensed Lake Surface Water Temperature Data

Functional principal component analysis is used to investigate a high-dimensional surface water temperature data set of Lake Victoria, which has been produced in the ARC-Lake project. Two different perspectives are adopted in the analysis: modelling temperature curves (univariate functions) and temperature surfaces (bivariate functions). The latter proves to be a better approach in the sense of both dimension reduction and pattern detection. Computational details and some results from an application to Lake Victoria data are presented

Within Lake Clustering of High Resolution Satellite Retrievals: A Functional Data and Clustering Approach

No abstract available

Understanding higher education in further education colleges

This summary presents the main findings from research undertaken for the Department for Business, Innovation and Skills (BIS) to understand the current nature of higher education (HE) in further education colleges (FECs) in England. The study was carried out between March 2011 and March 2012 by a team from the University of Sheffield and the Institute of Education, University of London. The research involved a range of qualitative and quantitative approaches, including: a review of the relevant literature; an analysis of administrative data on provision and participation; fieldwork in case-study FECs; interviews with managers in colleges and their partner higher education institutions (HEIs); a questionnaire survey of students coupled with in-class discussion groups; and interviews with employers. An overview of the design and conduct of the study is given in Chapter 1, including its aims, sources, methods and timetable. Methods of data collection and analysis are also described in relevant chapters and appendices

Functional Principal Component Analysis for Non-stationary Dynamic Time Series

Motivated by a highly dynamic hydrological high-frequency time series, we propose time-varying Functional Principal Component Analysis (FPCA) as a novel approach for the analysis of non-stationary Functional Time Series (FTS) in the frequency domain. Traditional FPCA does not take into account (i) the temporal dependence between the functional observations and (ii) the changes in the covariance/variability structure over time, which could result in inadequate dimension reduction. The novel time-varying FPCA proposed adapts to the changes in the auto-covariance structure and varies smoothly over frequency and time to allow investigation of whether and how the variability structure in an FTS changes over time. Based on the (smooth) time-varying dynamic FPCs, a bootstrap inference procedure is proposed to detect significant changes in the covariance structure over time. Although this time-varying dynamic FPCA can be applied to any dynamic FTS, it has been applied here to study the daily processes of partial pressure of CO2 in a small river catchment in Scotland

Unsaturated fatty acid regulation of cytochrome P450 expression via a CAR-dependent pathway.

The liver is responsible for key metabolic functions, including control of normal homoeostasis in response to diet and xenobiotic metabolism/detoxification. We have shown previously that inactivation of the hepatic cytochrome P450 system through conditional deletion of POR (P450 oxidoreductase) induces hepatic steatosis, liver growth and P450 expression. We have exploited a new conditional model of POR deletion to investigate the mechanism underlying these changes. We demonstrate that P450 induction, liver growth and hepatic triacylglycerol (triglyceride) homoeostasis are intimately linked and provide evidence that the observed phenotypes result from hepatic accumulation of unsaturated fatty acids, which mediate these phenotypes by activation of the nuclear receptor CAR (constitutive androstane receptor) and, to a lesser degree, PXR (pregnane X receptor). To our knowledge this is the first direct evidence that P450s play a major role in controlling unsaturated fatty acid homoeostasis via CAR. The regulation of P450s involved in xenobiotic metabolism by this mechanism has potentially significant implications for individual responses to drugs and environmental chemicals

The Gods We Choose

Pages 140-14

Ode To Beetles

Pages 138-13