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

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

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

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

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

Preliminary design for Arctic atmospheric radiative transfer experiments

If current plans are realized, within the next few years, an extraordinary set of coordinated research efforts focusing on energy flows in the Arctic will be implemented. All are motivated by the prospect of global climate change. SHEBA (Surface Energy Budget of the Arctic Ocean), led by the National Science Foundation (NSF) and the Office of Naval Research (ONR), involves instrumenting an ice camp in the perennial Arctic ice pack, and taking data for 12-18 months. The ARM (Atmospheric Radiation Measurement) North Slope of Alaska and Adjacent Arctic Ocean (NSA/AAO) Cloud and Radiation Testbed (CART) focuses on atmospheric radiative transport, especially in the presence of clouds. The NSA/AAO CART involves instrumenting a sizeable area on the North Slope of Alaska and adjacent waters in the vicinity of Barrow, and acquiring data over a period of about 10 years. FIRE (First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment) Phase 3 is a program led by the National Aeronautics and Space Administration (NASA) which focuses on Arctic clouds, and which is coordinated with SHEBA and ARM. FIRE has historically emphasized data from airborne and satellite platforms. All three program anticipate initiating Arctic data acquisition during spring, 1997. In light of his historic opportunity, the authors discuss a strawman atmospheric radiative transfer experimental plan that identifies which features of the radiative transport models they think should be tested, what experimental data are required for each type of test, the platforms and instrumentation necessary to acquire those data, and in general terms, how the experiments could be conducted. Aspects of the plan are applicable to all three programs

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

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

The Distance To The Hyades Cluster Based On Hubble Space Telescope Fine Guidance Sensor Parallaxes

Trigonometric parallax observations made with the Hubble Space Telescope (HST) Fine Guidance Sensor (FGS) 3 of seven Hyades members in six fields of view have been analyzed along with their proper motions to determine the distance to the cluster. Knowledge of the convergent point and mean proper motion of the Hyades is critical to the derivation of the distance to the center of the cluster. Depending on the choice of the proper-motion system, the derived cluster center distance varies by 9%. Adopting a reference distance of 46.1 pc or m - M = 3.32, which is derived from the ground-based parallaxes in the General Catalogue of Trigonometric Stellar Parallaxes (1995 edition), the FK5/PPM proper-motion system yields a distance 4% larger, while the Hanson system yields a distance 2% smaller. The HST FGS parallaxes reported here yield either a 14% or 5% larger distance, depending on the choice of the proper-motion system. Orbital parallaxes (Torres et al.) yield an average distance 4% larger than the reference distance. The variation in the distance derived from the HST data illustrates the importance of the proper-motion system and the individual proper motions to the derivation of the distance to the Hyades center; therefore, a full utilization of the HST FGS parallaxes awaits the establishment of an accurate and consistent proper-motion system.NASA HST GTO, HF-1042.01-93A, HF-1046.01-93A, NAS526555Astronom

Tracing the temporal evolution of clusters in a financial stock market

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

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