A-1 - Monthly Public Assistance Statistical Report Family Investment Program, September 2011

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, October 2011

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Entropy of a correlated system of nucleons

Realistic nucleon-nucleon interactions induce correlations to the nuclear many-body system, which lead to a fragmentation of the single-particle strength over a wide range of energies and momenta. We address the question of how this fragmentation affects the thermodynamical properties of nuclear matter. In particular, we show that the entropy can be computed with the help of a spectral function, which can be evaluated in terms of the self-energy obtained in the self-consistent Green's function approach. Results for the density and temperature dependences of the entropy per particle for symmetric nuclear matter are presented and compared to the results of lowest order finite-temperature Brueckner-Hartree-Fock calculations. The effects of correlations on the calculated entropy are small, if the appropriate quasiparticle approximation is used. The results demonstrate the thermodynamical consistency of the self-consistent T-matrix approximation for the evaluation of the Green's functions.

Statistical hadronization of supercooled quark-gluon plasma

The fast simultaneous hadronization and chemical freeze-out of supercooled quark-gluon plasma, created in relativistic heavy ion collisions, can lead to the reheating of the expanding matter and to the change in a collective flow profile. We use the assumption of statistical nature of the hadronization process, and study quantitatively the freeze-out in the framework of hydrodynamical Bjorken model with different simple quark-gluon plasma equations of state.

Distribution of single-particle strength due to short-range and tensor correlations

The distribution of single-particle strength in nuclear matter is calculated for a realistic nucleon-nucleon interaction. The influence of the short-range repulsion and the tensor component of the nuclear force on the spectral functions is to move approximately 13% of the total strength for all single-particle states beyond 100 MeV into the particle domain. This result is related to the abundantly observed quenching phenomena in nuclei which include the reduction of spectroscopic factors observed in (e,ep) reactions and the missing strength in low energy response functions.

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, November 2011

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, December 2011

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Familiality and SNP heritability of age at onset and episodicity in major depressive disorder.

BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Kinematic reduction of reaction-diffusion fronts with multiplicative noise. Derivation of stochastic sharp-interface equations

We study the dynamics of generic reaction-diffusion fronts, including pulses and chemical waves, in the presence of multiplicative noise. We discuss the connection between the reaction-diffusion Langevin-like field equations and the kinematic (eikonal) description in terms of a stochastic moving-boundary or sharp-interface approximation. We find that the effective noise is additive and we relate its strength to the noise parameters in the original field equations, to first order in noise strength, but including a partial resummation to all orders which captures the singular dependence on the microscopic cutoff associated with the spatial correlation of the noise. This dependence is essential for a quantitative and qualitative understanding of fluctuating fronts, affecting both scaling properties and nonuniversal quantities. Our results predict phenomena such as the shift of the transition point between the pushed and pulled regimes of front propagation, in terms of the noise parameters, and the corresponding transition to a non-Kardar-Parisi-Zhang universality class. We assess the quantitative validity of the results in several examples including equilibrium fluctuations and kinetic roughening. We also predict and observe a noise-induced pushed-pulled transition. The analytical predictions are successfully tested against rigorous results and show excellent agreement with numerical simulations of reaction-diffusion field equations with multiplicative noise.

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, January 2012

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Statistical mechanics in the extended Gaussian ensemble

The extended Gaussian ensemble (EGE) is introduced as a generalization of the canonical ensemble. This ensemble is a further extension of the Gaussian ensemble introduced by Hetherington [J. Low Temp. Phys. 66, 145 (1987)]. The statistical mechanical formalism is derived both from the analysis of the system attached to a finite reservoir and from the maximum statistical entropy principle. The probability of each microstate depends on two parameters ß and ¿ which allow one to fix, independently, the mean energy of the system and the energy fluctuations, respectively. We establish the Legendre transform structure for the generalized thermodynamic potential and propose a stability criterion. We also compare the EGE probability distribution with the q-exponential distribution. As an example, an application to a system with few independent spins is presented.

Influence of disorder strength on phase-field models of interfacial growth

We study the influence of disorder strength on the interface roughening process in a phase-field model with locally conserved dynamics. We consider two cases where the mobility coefficient multiplying the locally conserved current is either constant throughout the system (the two-sided model) or becomes zero in the phase into which the interface advances (one-sided model). In the limit of weak disorder, both models are completely equivalent and can reproduce the physical process of a fluid diffusively invading a porous media, where super-rough scaling of the interface fluctuations occurs. On the other hand, increasing disorder causes the scaling properties to change to intrinsic anomalous scaling. In the limit of strong disorder this behavior prevails for the one-sided model, whereas for the two-sided case, nucleation of domains in front of the invading front are observed.

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, February 2012

A-1 - Monthly Public Assistance Statistical Report Family Investment Program