Fixed-range optimum trajectories for short-haul aircraft

An algorithm, based on the energy-state method, is derived for calculating optimum trajectories with a range constraint. The basis of the algorithm is the assumption that optimum trajectories consist of, at most, three segments: an increasing energy segment (climb); a constant energy segment (cruise); and a decreasing energy segment (descent). This assumption allows energy to be used as the independent variable in the increasing and decreasing energy segments, thereby eliminating the integration of a separate adjoint differential equation and simplifying the calculus of variations problem to one requiring only pointwise extremization of algebraic functions. The algorithm is used to compute minimum fuel, minimum time, and minimum direct-operating-cost trajectories, with range as a parameter, for an in-service CTOL aircraft and for an advanced STOL aircraft. For the CTOL aircraft and the minimum-fuel performance function, the optimum controls, consisting of air-speed and engine power setting, are continuous functions of the energy in both climb and descent as well as near the maximum or cruise energy. This is also true for the STOL aircraft except in the descent where at one energy level a nearly constant energy dive segment occurs, yielding a discontinuity in the airspeed at that energy. The reason for this segment appears to be the relatively high fuel flow at idle power of the engines used by this STOL aircraft. Use of a simplified trajectory which eliminates the dive increases the fuel consumption of the total descent trajectory by about 10 percent and the time to fly the descent by about 19 percent compared to the optimum

Challenges and implications of routine depression screening for depression in chronic disease and multimorbidity: a cross sectional study

<b>Background</b> Depression screening in chronic disease is advocated but its impact on routine practice is uncertain. We examine the effects of a programme of incentivised depression screening in chronic disease within a UK primary care setting.<p></p> <b>Methods and Findings</b> Cross sectional analysis of anonymised, routinely collected data (for 2008-9) from family practices in Scotland serving a population of circa 1.8 million. Patients registered in primary care with at least one of three chronic diseases, coronary heart disease, diabetes and stroke, underwent incentivised depression screening using the Hospital Anxiety and Depression Score (HADS). <p></p> 125143 patients were identified with at least one chronic disease. 10670 (8.5%) were under treatment for depression and exempt from screening. Of the remaining, HADS were recorded for 35537 (31.1%) patients. 7080 (19.9% of screened) had raised HADS (≥8); the majority had indications of mild depression with a HADS between 8 and 10. Over 6 months, 572 (8%) of those with a raised HADS (≥8) were initiated on antidepressants, while 696 (2.4%) patients with a normal HADS (<8) were also initiated on antidepressants (relative risk of antidepressant initiation with raised HADS 3.3 (CI 2.97-3.67), p value <0.0001). Of those with multimorbidity who were screened, 24.3% had a raised HADS (≥8). A raised HADS was more likely in females, socioeconomically deprived, multimorbid or younger (18-44) individuals. Females and 45-64 years old were more likely to receive antidepressants.<p></p> <b>Limitations</b> – retrospective study of routinely collected data.<p></p> <b>Conclusions </b> Despite incentivisation, only minority of patients underwent depression screening, suggesting that systematic depression screening in chronic disease can be difficult to achieve in routine practice. Targeting those at greatest risk such as the multimorbid or using simpler screening methods may be more effective. Raised HADS was associated with a higher number of new antidepressant prescriptions which has significant resource implications. The clinical benefits of such screening remain uncertain and merit investigation

Supersonic aircraft Patent

Design of supersonic aircraft with novel fixed, swept wing planfor

Biological Records Centre Annual Report 2005-2006

The period covered by this report is the first year of a new six-year partnership between CEH and JNCC. For this period, there is increased emphasis on targeted survey, on analysis and interpretation and on communications and outreach. These activities were always part of BRC’s work, but they have been given greater prominence as a result of rapid developments in information technology. Data are increasingly reaching BRC in electronic form, so that the effort of data entry and collation is reduced. The data, collected by many volunteers and then collated and analysed at BRC, document the changing status and distribution of plants and animals in Britain. Distribution maps are published in atlases and are available via the internet through the NBN Gateway. The effects of change or loss of habitats, the influence of climate change and the consequences of changing water quality are all examples of the environmental factors that affect our biodiversity and which BRC aims to document and understand. The results are vital for developing environmental policies, to support conservation, and for fundamental ecological research. BRC is funded jointly by JNCC and NERC through a partnership based on a Memorandum of Agreement (MoA). The partnership started in 1973 when the Nature Conservancy was divided to form the successor bodies Nature Conservancy Council (NCC) and Institute of Terrestrial Ecology (ITE). NCC was in turn divided further to form JNCC and three Country Agencies, while ITE was merged with other NERC units to form CEH. Through all these changes, the partnership has been maintained. A six-year memorandum of agreement ended on 31 January 2005 (Hill et al. 2005). The present report covers the first full year, 2005-6, of the new agreement for 2005-2010. Rapid progress in information technology continues to be highly beneficial for BRC, whose data are increasingly used by the UK country conservation agencies, environmental consultants, NGOs, research workers, policy makers and volunteers. It is gratifying to know that, through our ability to display data on the National Biodiversity Network (NBN) Gateway, some of our data suppliers now have immediate access to their own data in a convenient form. The year 2005-6 has been one of steady progress, with new datasets added to BRC, substantial additions to existing data, and improved communication with the NBN Gateway. The most high profile activity of the year has been the Harlequin Ladybird Survey, which has enabled us to observe the early stages of colonization by a mobile insect in greater detail than has been possible in any previous case

Functional generalized additive models

We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·, ·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as by Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·, ·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. The FGAM is implemented in R in the refund package. There are additional supplementary materials available online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America

Large-Eddy Simulation of Waked Turbines in a Scaled Wind Farm Facility

The aim of this paper is to present the numerical simulation of waked scaled wind turbines operating in a boundary layer wind tunnel. The simulation uses a LES-lifting-line numerical model. An immersed boundary method in conjunction with an adequate wall model is used to represent the effects of both the wind turbine nacelle and tower, which are shown to have a considerable effect on the wake behavior. Multi-airfoil data calibrated at different Reynolds numbers are used to account for the lift and drag characteristics at the low and varying Reynolds conditions encountered in the experiments. The present study focuses on low turbulence inflow conditions and inflow non-uniformity due to wind tunnel characteristics, while higher turbulence conditions are considered in a separate study. The numerical model is validated by using experimental data obtained during test campaigns conducted with the scaled wind farm facility. The simulation and experimental results are compared in terms of power capture, rotor thrust, downstream velocity profiles and turbulence intensity

Analysis and design of on-grade reinforced concrete track support structures

For the improvement of rail service, the Department of Transportation, Federal Rail Administration, is sponsoring a test track on the Atchison, Topeka, and Santa Fe Railway. The test track will contain nine separate rail support structures, including one conventional section for control and three reinforced concrete structures on grade, one slab and two beam sections. The analysis and design of these latter structures was accomplished by means of the finite element method, NASTRAN, and is presented