1,461 research outputs found

    A New Model for Family Resource Allocation Among Siblings: Competition, Forbearance, and Support

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    Previous research analyzing within-family education resource allocation usually employs the sibship and birth order of a child as explanatory variables. We argue in this paper that to correctly characterize the resource competition and support scenario within a family, one should identify the Sex, Seniority, and most importantly Age Difference of a child’s sibling structure, and hence we call our analysis a SSAD model of family resource allocation. We show that siblings with different combinations of SSAD may play distinct roles in family resource allocation. Ignoring such facts may distort the significance and/or direction of the prediction. We support our analysis with empirical evidence using data from Taiwan.

    A Sensitivity Study on the Effects of Particle Chemistry, Asphericity and Size on the Mass Extinction Efficiency of Mineral Dust in the Earth's Atmosphere: From the Near to Thermal IR

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    To determine a plausible range of mass extinction efficiencies (MEE) of terrestrial atmospheric dust from the near to thermal IR, sensitivity analyses are performed over an extended range of dust microphysical and chemistry perturbations. The IR values are subsequently compared to those in the near-IR, to evaluate spectral relationships in their optical properties. Synthesized size distributions consistent with measurements, model particle size, while composition is defined by the refractive indices of minerals routinely observed in dust, including the widely used OPAC/Hess parameterization. Single-scattering properties of representative dust particle shapes are calculated using the T-matrix, Discrete Dipole Approximation and Lorenz-Mie light-scattering codes. For the parameterizations examined, MEE ranges from nearly zero to 1.2 square meters per gram, with the higher values associated with non-spheres composed of quartz and gypsum. At near-IR wavelengths, MEE for non-spheres generally exceeds those for spheres, while in the thermal IR, shape-induced changes in MEE strongly depend on volume median diameter (VMD) and wavelength, particularly for MEE evaluated at the mineral resonant frequencies. MEE spectral distributions appear to follow particle geometry and are evidence for shape dependency in the optical properties. It is also shown that non-spheres best reproduce the positions of prominent absorption peaks found in silicates. Generally, angular particles exhibit wider and more symmetric MEE spectral distribution patterns from 8-10 micrometers than those with smooth surfaces, likely due to their edge-effects. Lastly, MEE ratios allow for inferring dust optical properties across the visible-IR spectrum. We conclude the MEE of dust aerosol are significant for the parameter space investigated, and are a key component for remote sensing applications and the study of direct aerosol radiative effects

    Don't bleach chaotic data

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    A common first step in time series signal analysis involves digitally filtering the data to remove linear correlations. The residual data is spectrally white (it is ``bleached''), but in principle retains the nonlinear structure of the original time series. It is well known that simple linear autocorrelation can give rise to spurious results in algorithms for estimating nonlinear invariants, such as fractal dimension and Lyapunov exponents. In theory, bleached data avoids these pitfalls. But in practice, bleaching obscures the underlying deterministic structure of a low-dimensional chaotic process. This appears to be a property of the chaos itself, since nonchaotic data are not similarly affected. The adverse effects of bleaching are demonstrated in a series of numerical experiments on known chaotic data. Some theoretical aspects are also discussed.Comment: 12 dense pages (82K) of ordinary LaTeX; uses macro psfig.tex for inclusion of figures in text; figures are uufile'd into a single file of size 306K; the final dvips'd postscript file is about 1.3mb Replaced 9/30/93 to incorporate final changes in the proofs and to make the LaTeX more portable; the paper will appear in CHAOS 4 (Dec, 1993

    Inferring hidden states in Langevin dynamics on large networks: Average case performance

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    We present average performance results for dynamical inference problems in large networks, where a set of nodes is hidden while the time trajectories of the others are observed. Examples of this scenario can occur in signal transduction and gene regulation networks. We focus on the linear stochastic dynamics of continuous variables interacting via random Gaussian couplings of generic symmetry. We analyze the inference error, given by the variance of the posterior distribution over hidden paths, in the thermodynamic limit and as a function of the system parameters and the ratio {\alpha} between the number of hidden and observed nodes. By applying Kalman filter recursions we find that the posterior dynamics is governed by an "effective" drift that incorporates the effect of the observations. We present two approaches for characterizing the posterior variance that allow us to tackle, respectively, equilibrium and nonequilibrium dynamics. The first appeals to Random Matrix Theory and reveals average spectral properties of the inference error and typical posterior relaxation times, the second is based on dynamical functionals and yields the inference error as the solution of an algebraic equation.Comment: 20 pages, 5 figure

    The effect of cross rolling on the microstructure of ferrous and non-ferrous metals and alloys

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    The cross rolling is the one of most perspective method of refinement microstructure metals by severe plastic deformation method. This method gives ability to get the long length billets. However, deformation and trajectories of the metal is very heterogeneous across the section of the rolled piece. This paper presents the finite element method (FEM) simulation of hot cross rolling and experimental study of the effect of the cross rolling on a different threeroll mills on the microstructure of ordinary structural alloy steel, stainless steel and technical copper in different zones of the bar. Analysis showed significant structure refinement in all cases. The best result was achieved on the stainless steel, and shown the formation of equal-axis ultra-fine-grain structure on the bar periphery

    Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

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    The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas

    Tracing the temporal evolution of clusters in a financial stock market

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    We propose a methodology for clustering financial time series of stocks' returns, and a graphical set-up to quantify and visualise the evolution of these clusters through time. The proposed graphical representation allows for the application of well known algorithms for solving classical combinatorial graph problems, which can be interpreted as problems relevant to portfolio design and investment strategies. We illustrate this graph representation of the evolution of clusters in time and its use on real data from the Madrid Stock Exchange market.Comment: 22 pages, 3 figures (submitted for publication

    Wurtzite Effects on Spin Splitting of GaN/AlN Quantum Wells

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    A new mechanism (DeltaC1-DeltaC3 coupling) is accounted for the spin splitting of wurtzite GaN, which is originated from the intrinsic wurtzite effects (band folding and structure inversion asymmetry). The band-folding effect generates two conduction bands (DeltaC1 and DeltaC3), in which p-wave probability has tremendous change when kz approaches anti-crossing zone. The spin-splitting energy induced by the DeltaC1-DeltaC3 coupling and wurtzite structure inversion asymmetry is much larger than that evaluated by traditional Rashba or Dresselhaus effects. When we apply the coupling to GaN/AlN quantum wells, we find that the spin-splitting energy is sensitively controllable by an electric field. Based on the mechanism, we proposed a p-wave-enhanced spin-polarized field effect transistor, made of InxGa1-xN/InyAl1-yN, for spintronics application.Comment: 12 pages, 4 figures (total 16 pages

    Improving numerical reasoning capabilities of inductive logic programming systems

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    Inductive Logic Programming (ILP) systems have been largely applied to classification problems with a considerable success. The use of ILP systems in problems requiring numerical reasoning capabilities has been far less successful. Current systems have very limited numerical reasoning capabilities, which limits the range of domains where the ILP paradigm may be applied. This paper proposes improvements in numerical reasoning capabilities of ILP systems. It proposes the use of statistical-based techniques like Model Validation and Model Selection to improve noise handling and it introduces a new search stopping criterium based on the PAG method to evaluate learning performance. We have found these extensions essential to improve on results mer statistical-based algorithms for time series forecasting used in the empirical evaluation study
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