16,165 research outputs found
Prediction of thermal radiation from a rocket's exhaust plume
Data from absorption coefficients and fine-structure parameters measured for water vapor have been incorporated in an analytic program useful in evaluating heating by radiation from the exhaust plume of a large rocket
Analyzing Child Mortality in Nigeria with Geoadditive Survival Models
Child mortality reflects a country's level of socio-economic development and quality of life. In developing countries, mortality rates are not only influenced by socio-economic, demographic and health variables but they also vary considerably across regions and districts. In this paper, we analyze child mortality in Nigeria with flexible geoadditive survival models. This class of models allows to measure small-area district-specific spatial effects simultaneously with possibly nonlinear or time-varying effects of other factors. Inference is fully Bayesian and uses recent Markov chain Monte Carlo (MCMC) simulation. The application is based on the 1999 Nigeria Demographic and Health Survey. Our method assesses effects at a high level of temporal and spatial resolution not available with traditional parametric models
Geoadditive Latent Variable Modelling of Count Data on Multiple Sexual Partnering in Nigeria
The 2005 National HIV/AIDS and Reproductive Health Survey in Nigeria provides evidence that multiple sexual partnering increases the risk of contracting HIV and other sexually transmitted diseases. Therefore, partner reduction is one of the prevention strategies to accomplish the Millenium development goal of halting and reversing the spread of HIV/AIDS. In order to explore possible association between sexual partnering and some risk factors, this paper utilizes a novel Bayesian geoadditive latent variable model for count outcomes. This allows us to simultaneously analyze linear and nonlinear effects of covariates as well as spatial variations of one or more latent variables, such as attitude towards multiple partnering, which in turn directly influences the multivariate observable outcomes or indicators. Influence of demographic factors such as age, gender, locality, state of residence, educational attainment, etc., and knowledge about HIV/AIDS on attitude towards multiple partnering is also investigated. Results can provide insights to policy makers with the aim of reducing the spread of HIV and AIDS among the Nigerian populace through partner reduction
3D Simulation of Convection and Spectral Line Formation in A-type Stars
We present first realistic numerical simulations of 3D radiative convection
in the surface layers of main sequence A-type stars with Teff = 8000 K and 8500
K, log g = 4.4 and 4.0, recently performed with the CO5BOLD radiation
hydrodynamics code. The resulting models are used to investigate the structure
of the H+HeI and the HeII convection zones in comparison with the predictions
of local and non-local convection theories, and to determine the amount of
"overshoot" into the stable layers below the HeII convection zone. The
simulations also predict how the topology of the photospheric granulation
pattern changes from solar to A-type star convection. The influence of the
photospheric temperature fluctuations and velocity fields on the shape of
spectral lines is demonstrated by computing synthetic line profiles and line
bisectors for some representative examples, allowing us to confront the 3D
model results with observations.Comment: 5 pages, 6 figures (17 figure files), 1 Tabl
Using different groups of technological progress as input for sector modeling
This poster aims at describing different groups of technology use within a farm population and at delivering realistic prognoses of their future status as input for sector modeling. This because sector models are in many cases not based on reasonable technological progress estimations or too simplified as normative estimation or seen as mere extrapolation of past evolutions. The classification and utilization of technology groups is done for livestock activities, but illustrated hereafter for the finishing pigs activities. The research is worked out in three phases: • Organizational aspects of tuning information demand and supply; • Identification of technology groups; • Evolution of technology groups. Following techniques are used to identify the technology groups: Stochastic frontier analysis, cluster analysis and others. The results can be used in sector models to measure the impact of induced innovation on different technology groups.technology, sector modeling, induced innovation, Resource /Energy Economics and Policy,
Prediction of total emissivity of nitrogen- broadened and self-broadened hot water vapor
Total emissivity predicted for nitrogen-broadened and self-broadened hot water vapo
Analysis of the time to sustained progression in Multiple Sclerosis using generalised linear and additive models
The course of multiple sclerosis (MS) is generally difficult to predict. This is due to the great inter-individual variability with respect to symptoms and disability status. An important prognostic endpoint for MS is the expected time to sustained disease progression. Using the Expanded Disability Status Scale (EDSS) this endpoint is here defined as a rise of 1.0 or 0.5 compared to baseline EDSS (5.5) which is confirmed for at least six months. The goal of this paper was threefold. It aimed at identifying covariates which significantly influence sustained progression, determining size and form of the effect of these covariates and estimating the survival curves for given predictors. To this end a piecewise exponential model utilizing piecewise constant hazard rates and a Poisson model were devised. In order to improve and simplify these models a method for piecewise linear parameterization of non-parametric generalized additive models (GAMs) was applied. The models included fixed and random effects, the posterior distribution was estimated using Markov Chain Monte Carlo methods (MCMC) as well as a penalized likelihood approach and variables were selected using Akaikes information criterium (AIC). The models were applied to data of placebo patients from worldwide clinical trials that are pooled in the database of the Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR). Only with a pure exponential model and fixed effects, baseline EDSS and the number of relapses in the last 12 month before study entry had an effect on the hazard rate. For the piecewise exponential model with random study effects there was no effect of covariates on the hazard rate other than a slightly decreasing effect of time. This reflects the fact that unstable patients reach the event early and are therefore eliminated from the analysis (selection effect)
Riding the Yield Curve: Diversification of Strategies
Riding the yield curve, the fixed-income strategy of purchasing a longer-dated security and selling before maturity, has long been a popular means to achieve excess returns compared to buying-and-holding, despite its implicit violations of market efficiency and the pure expectations hypothesis of the term structure. This paper looks at the historic excess returns of different strategies across three countries and proposes several statistical and macro-based trading rules which seem to enhance returns even more. While riding based on the Taylor Rule works well even for longer investment horizons, our empirical results indicate that, using expectations implied by Fed funds futures, excess returns can only be increased over short horizons. Furthermore, we demonstrate that duration-neutral strategies are superior to standard riding on a risk- adjusted basis. Overall, our evidence stands in contrast to the pure expectations hypothesis and points to the existence of risk premia which may be exploited consistently.Term Structure, Interest Rates, Market Efficiency, Taylor Rule
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