Submillimeter satellite radiometer first semiannual engineering progress report

Development of 560 GHz fourth harmonic mixer and 140 GHz third harmonic generator for use in radiomete

Submillimeter satellite radiometer Final engineering report

All solid-state superheterodyne Dicke radiometer for submillimeter wavelength

Free energy landscapes, dynamics and the edge of chaos in mean-field models of spin glasses

Metastable states in Ising spin-glass models are studied by finding iterative solutions of mean-field equations for the local magnetizations. Two different equations are studied: the TAP equations which are exact for the SK model, and the simpler `naive-mean-field' (NMF) equations. The free-energy landscapes that emerge are very different. For the TAP equations, the numerical studies confirm the analytical results of Aspelmeier et al., which predict that TAP states consist of close pairs of minima and index-one (one unstable direction) saddle points, while for the NMF equations saddle points with large indices are found. For TAP the barrier height between a minimum and its nearby saddle point scales as (f-f_0)^{-1/3} where f is the free energy per spin of the solution and f_0 is the equilibrium free energy per spin. This means that for `pure states', for which f-f_0 is of order 1/N, the barriers scale as N^{1/3}, but between states for which f-f_0 is of order one the barriers are finite and also small so such metastable states will be of limited physical significance. For the NMF equations there are saddles of index K and we can demonstrate that their complexity Sigma_K scales as a function of K/N. We have also employed an iterative scheme with a free parameter that can be adjusted to bring the system of equations close to the `edge of chaos'. Both for the TAP and NME equations it is possible with this approach to find metastable states whose free energy per spin is close to f_0. As N increases, it becomes harder and harder to find solutions near the edge of chaos, but nevertheless the results which can be obtained are competitive with those achieved by more time-consuming computing methods and suggest that this method may be of general utility.Comment: 13 page

Forecasting time series by means of evolutionary algorithms

Proceeding of: 8th International Conference in Parallel Problem Solving from Nature - PPSN VIII , Birmingham, UK, September 18-22, 2004.The time series forecast is a very complex problem, consisting in predicting the behaviour of a data series with only the information of the previous sequence. There is many physical and artificial phenomenon that can be described by time series. The prediction of such phenomenon could be very complex. For instance, in the case of tide forecast, unusually high tides, or sea surges, result from a combination of chaotic climatic elements in conjunction with the more normal, periodic, tidal systems associated with a particular area. Too much variables influence the behaviour of the water level. Our problem is not only to find prediction rules, we also need to discard the noise and select the representative data. Our objective is to generate a set of prediction rules. There are many methods tying to achieve good predictions. In most of the cases this methods look for general rules that are able to predict the whole series. The problem is that usually the time series has local behaviours that dont allow a good level of prediction when using general rules. In this work we present a method for finding local rules able to predict only some zones of the series but achieving better level prediction. This method is based on the evolution of set of rules genetically codified, and following the Michigan approach. For evaluating the proposal, two different domains have been used: an artificial domain widely use in the bibliography (Mackey-Glass series) and a time series corresponding to a natural phenomenon, the water level in Venice Lagoon.Investigation supported by the Spanish Ministry of Science and Technology through the TRACER project under contract TIC2002-04498-C05-

Effects of diabetes family history and exercise training on the expression of adiponectin and leptin and their receptors

The daughters of patients with diabetes have reduced insulin sensitivity index (ISI) scores compared with women with no family history of diabetes, but their ISI increase more in response to exercise training(1). The present study aimed to determine whether differences between these groups in exercise-induced changes in circulating adiponectin and leptin concentrations and expression of their genes and receptors in subcutaneous adipose tissue (SAT), could explain differences in the exercise-induced changes in ISI between women with and without a family history of diabetes

Long-term impact on healthcare resource utilization of statin treatment, and its cost effectiveness in the primary prevention of cardiovascular disease: a record linkage study

Aims: To assess the impact on healthcare resource utilization, costs, and quality of life over 15 years from 5 years of statin use in men without a history of myocardial infarction in the West of Scotland Coronary Prevention Study (WOSCOPS).<p></p> Methods: Six thousand five hundred and ninety-five participants aged 45–54 years were randomized to 5 years treatment with pravastatin (40 mg) or placebo. Linkage to routinely collected health records extended follow-up for secondary healthcare resource utilization to 15 years. The following new results are reported: cause-specific first and recurrent cardiovascular hospital admissions including myocardial infarction, heart failure, stroke, coronary revascularization and angiography; non-cardiovascular hospitalization; days in hospital; quality-adjusted life years (QALYs); costs of pravastatin treatment, treatment safety monitoring, and hospital admissions.<p></p> Results: Five years treatment of 1000 patients with pravastatin (40 mg/day) saved the NHS £710 000 (P < 0.001), including the cost of pravastatin and lipid and safety monitoring, and gained 136 QALYs (P = 0.017) over the 15-year period. Benefits per 1000 subjects, attributable to prevention of cardiovascular events, included 163 fewer admissions and a saving of 1836 days in hospital, with fewer admissions for myocardial infarction, stroke, heart failure and coronary revascularization. There was no excess in non-cardiovascular admissions or costs (or in admissions associated with diabetes or its complications) and no evidence of heterogeneity of effect over sub-groups defined by baseline cardiovascular risk.<p></p> Conclusion: Five years' primary prevention treatment of middle-aged men with a statin significantly reduces healthcare resource utilization, is cost saving, and increases QALYs. Treatment of even younger, lower risk individuals is likely to be cost-effective.<p></p&gt

An analysis of the production-regeneration system in the coastal upwelling area off N.W. Africa based on oxygen, nitrate and ammonium distributions

Using the hydrographic and nutrient data from the R/V Jean Charcot CINECA-V cruise and Broenkow\u27s (1965) mixing model, we have calculated the biologically induced changes in the oxygen, nitrate and ammonium distribution patterns of the upwelling system off Cape Blanc, N .W. Africa...

On the importance of nonlinear modeling in computer performance prediction

Computers are nonlinear dynamical systems that exhibit complex and sometimes even chaotic behavior. The models used in the computer systems community, however, are linear. This paper is an exploration of that disconnect: when linear models are adequate for predicting computer performance and when they are not. Specifically, we build linear and nonlinear models of the processor load of an Intel i7-based computer as it executes a range of different programs. We then use those models to predict the processor loads forward in time and compare those forecasts to the true continuations of the time seriesComment: Appeared in "Proceedings of the 12th International Symposium on Intelligent Data Analysis