Mechanical and Thermal Properties of Thermoplastic Random Copolyesters Made from Lipid- Derived Medium and Long Chain Poly (x-hydroxyfatty acid) s

The physical properties of novel thermoplastic random copolyesters [-(CH2)(n)-COO-/-(CH2)(n)-COO-](x) made of long (n=12) and medium (n=8) chain length -hydroxyfatty esters [HO-(CH2)(n)-COOCH3] derived from bio-based vegetable oil feedstock are described. Poly(-hydroxy tridecanoate/-hydroxy nonanoate) P(-Me13-/-Me9-) random copolyesters (M-n=11,000-18,500 g/mol) with varying molar ratios were examined by TGA, DSC, DMA and tensile analysis, and WAXD. For the whole range of P(-Me13-/-Me9-) compositions, the WAXD data indicated an orthorhombic polyethylene-like crystal packing. Their melting characteristics, determined by DSC, varied with composition suggesting an isomorphic cocrystallization behavior. TGA of the P(-Me13-/-Me9-)s indicated improved thermal stability determined by their molar compositions. The glass transition temperature, investigated by DMA, was also found to vary with composition. The crystallinities of P(-Me13-/-Me9-)s however, were unaffected by the composition. The stiffness (Young's modulus) of these materials was found to be related to their degrees of crystallinity. (c) 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40492.

Genetic parameters for production traits of dairy Gyr (Bos indicus) x Holstein cattle estimated with a random regression model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Random regression models using different functions to model milk flow in dairy cows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Coherence characteristics of random lasing in a dye doped hybrid powder

The photon statistics of the random laser emission of a Rhodamine B doped di-ureasil hybrid powder is investigated to evaluate its degree of coherence above threshold. Although the random laser emission is a weighted average of spatially uncorrelated radiation emitted at different positions in the sample, a spatial coherence control was achieved due to an improved detection configuration based on spatial filtering. By using this experimental approach, which also allows for fine mode discrimination and timeresolved analysis of uncoupled modes from mode competition, an area not larger than the expected coherence size of the random laser is probed. Once the spectral and temporal behavior of nonoverlapping modes is characterized, an assessment of the photon-number probability distribution and the resulting second-order correlation coefficient as a function of time delay and wavelength was performed. The outcome of our single photon counting measurements revealed a high degree of temporal coherence at the time of maximum pump intensity and at wavelengths around the Rhodamine B gain maximum.

Effect of random/aligned nylon-6/MWCNT fibers on dental resin composite reinforcement

The aims of this study were (1) to synthesize and characterize random and aligned nanocomposite fibers of multi-walled carbon nanotubes (MWCNT)/nylon-6 and (2) to determine their reinforcing effects on the flexural strength of a dental resin composite.Nylon-6 was dissolved in hexafluoropropanol (10 wt%), followed by the addition of MWCNT (hereafter referred to as nanotubes) at two distinct concentrations (i.e., 0.5 or 1.5 wt%). Neat nylon-6 fibers (without nanotubes) were also prepared. The solutions were electrospun using parameters under low- (120 rpm) or high-speed (6000 rpm) mandrel rotation to collect random and aligned fibers, respectively. The processed fiber mats were characterized by scanning (SEM) and transmission (TEM) electron microscopies, as well as by uni-axial tensile testing. To determine the reinforcing effects on the flexural strength of a dental resin composite, bar-shaped (20 x 2 x 2 mm(3)) resin composite specimens were prepared by first placing one increment of the composite, followed by one strip of the mat, and one last increment of composite. Non-reinforced composite specimens were used as the control. The specimens were then evaluated using flexural strength testing. SEM was done on the fractured surfaces. The data were analyzed using ANOVA and the Tukey's test (alpha=5%).Nanotubes were successfully incorporated into the nylon-6 fibers. Aligned and random fibers were obtained using high- and low-speed electrospinning, respectively, where the former were significantly (p<0.001) stronger than the latter, regardless of the nanotubes'presence. Indeed, the dental resin composite tested was significantly reinforced when combined with nylon-6 fibrous mats composed of aligned fibers (with or without nanotubes) or random fibers incorporated with nanotubes at 0.5 wt%. (C) 2015 Elsevier Ltd. All rights reserved.

Random regression models for milk, fat and protein in Colombian Buffaloes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Processing and structural properties of random oriented lead lanthanum zirconate titanate thin films

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Diffusive random laser modes under a spatiotemporal scope

At present the prediction and characterization of the emission output of a diffusive random laser remains a challenge, despite the variety of investigated materials and theoretical interpretations given up to now. Here, a new mode selection method, based on spatial filtering and ultrafast detection, which allows to separate individual lasing modes and follow their temporal evolution is presented. In particular, the work explores the random laser behavior of a ground powder of an organic-inorganic hybrid compound based on Rhodamine B incorporated into a di-ureasil host. The experimental approach gives direct access to the mode structure and dynamics, shows clear modal relaxation oscillations, and illustrates the lasing modes stochastic behavior of this diffusive scattering system. The effect of the excitation energy on its modal density is also investigated. Finally, imaging measurements reveal the dominant role of diffusion over amplification processes in this kind of unconventional lasers. (C) 2015 Optical Society of America

Genotype x environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Molecular characterization of Pleurotus ostreatus commercial strains by random amplified polymorphic DNA (RAPD)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Electroluminescence of phenylene-vinylene random copolymers with different conjugation lengths

PPV random derivates were synthesized and characterized. Polymer light emitting diodes (PLEDs) were assembled using the random copolymers as emissive layer and showed EL in the blue-green region in function of the method of preparation. The increase in the average conjugation degree in the polymer chain led to the reduction of the turn-on voltage of the device. The addition of Alq3 as ETL increased tenfold the luminescence efficiency. (C) 2009 Elsevier B.V. All rights reserved.

Partially Observed Markov Random Fields Are Variable Neighborhood Random Fields

The present paper has two goals. First to present a natural example of a new class of random fields which are the variable neighborhood random fields. The example we consider is a partially observed nearest neighbor binary Markov random field. The second goal is to establish sufficient conditions ensuring that the variable neighborhoods are almost surely finite. We discuss the relationship between the almost sure finiteness of the interaction neighborhoods and the presence/absence of phase transition of the underlying Markov random field. In the case where the underlying random field has no phase transition we show that the finiteness of neighborhoods depends on a specific relation between the noise level and the minimum values of the one-point specification of the Markov random field. The case in which there is phase transition is addressed in the frame of the ferromagnetic Ising model. We prove that the existence of infinite interaction neighborhoods depends on the phase.