Matrix molecular orientation in fiber-reinforced polypropylene composites

A distinctive crystalline morphology which develops in certain fiber-reinforced thermoplastics, termed "transcrystallinity", occurs as the result of dense nucleation of polymer crystals at the surface of reinforcing fibers. As these fiber-sponsored nuclei grow, they impinge upon one another, such that crystal growth occurs essentially perpendicular to the fiber axis. Previous studies concerning transcrystallized composites have generally focused on single-fiber composites or model systems. Our interest is in elucidating the crystal orientation in conventional fiber-reinforced composites, and in quantifying the fraction of transcrystallized matrix, where present. In the present work, we develop a wide-angle X-ray scattering (WAXS) technique to investigate composites formed from an isotactic polypropylene (PP) matrix with practical loading levels of unidirectional pitch-based carbon, polyacrylonitrile (PAN)-based carbon, or aramid fibers. The transcrystalline fraction of the crystalline matrix approaches 0.95 in pitch-based carbon composites and 0.50 in the aramid composites near fiber loadings of 30 vol %. In addition, a previously-unreported mode of matrix orientation is observed in composites containing the non-transcrystallizing PAN-based carbon fibers, arising from restrictions on the isotropic growth of PP crystallites by the unidirectional fibers. This "constrained growth" orientation can coexist with the transcrystallized matrix at lower fiber loadings.     

Contribution of various substrates to total citric acid cycle flux and ]anaplerosis as determined by13C isotopomer analysis and O2 consumption in the heart

A simple relationship between parameters derived from a¹³C NMR isotopomer analysis and O₂ consumption is presented that allows measurement of the absolute rate of acetyl-CoA oxidation and anaplerotic flux in tissues oxidizing a mixture of four substrates. The method was first applied in a study of the effects of work state and -adrenergic stimulation on net acetate oxidation and anaplerosis in the isolated working rat heart. The results demonstrate that the anticipated ratio of 2 between O₂ consumption and TCA cycle flux for hearts oxidizing only acetate holds at low workload when anaplerosis is low, but deviates toward a factor of 3 under high workload conditions when anaplerosis is increased. This analysis was also extended to hearts that oxidize a more physiological mixture of substrates including long-chain fatty acids, acetoacetate, lactate, pyruvate, and glucose. We show that the contribution each substrate makes to total TCA cycle flux can be determined by combined¹³C NMR and O₂ consumption measurements. The present study also demonstrates that stimulation of anaplerosis (by addition of propionate) can significantly alter the relative contribution each substrate makes to total TCA cycle flux. We conclude that if¹³C labeling patterns are selected appropriately, a comprehensive picture of flux through all major metabolic pathways feeding the cycle can be determined in a single experiment even when complex physiological mixtures of substrates are provided.     

Credible sets for risk ratios in over-reported two-sample binomial data using the double-sampling scheme

We consider point and interval estimation for risk ratios based on two independent samples of binomial data subject to false positive misclassification. For such data it is well known that the model is unidentifiable. We consider incorporating training data obtained by using a double-sampling scheme to make the model identifiable. In this identifiable model, we propose a Bayesian method to make statistical inferences. In particular, we derive an easy-to-implement closed-form algorithm for drawing from the posterior distributions. The algorithm is illustrated using a real data example and further examined via Monte Carlo simulation studies.     

The effects of misspecified marginals and copulas on computing the value at risk: A Monte Carlo study

The effect on the estimation of the Value at Risk when dealing with multivariate portfolios when there is a misspecification both in the marginals and in the copulas is investigated. It is first shown that, when there is skewness in the data and symmetric marginals are used, the estimated elliptical (normal or t) copula correlations are negatively biased, reaching values as high as 70% of the true values. Besides, the bias almost doubles if negative correlations are considered, compared to positive correlations. As for the t copula degrees of freedom parameter, the use of wrong marginals delivers large positive biases, instead. If the dependence structure is represented by a copula which is not elliptical, e.g. the Clayton copula, the effects of marginal misspecifications on the copula parameter estimation can be rather different, depending on the sign of marginal skewness. Extensive Monte Carlo studies then show that the misspecifications in the marginal volatility equation more than offset the biases in copula parameters when VaR forecasting is of concern, small samples are considered and the data are leptokurtic. The biases in the volatility parameters are much smaller, whereas those ones in the copula parameters remain almost unchanged or even increase when the sample dimension increases. In this case, copula misspecifications do play a role for VaR estimation. However, these effects depend heavily on the sign of the dependence.     

Preliminary evaluation of electroencephalographic entrainment using thalamocortical modelling

Abstract: The concept of linked oscillators in biological control systems has long been established. Frequency entrainment is a predominant explanation behind many biological rhythms. In this paper a preliminary examination of electroencephalographic entrainment is made to survey the possibility and methods of achieving signal entrainment at the highest level of neurological organization and function. A model of the thalamocortical system is employed to generate simulated electroencephalographic signals and is tested in various configurations in the search for entrainment under very simple conditions. Additionally, an analysis of the coupled Van der Pol model of the circadian rhythm controller is performed to identify the possibility of affecting that system with a drastically different coupling input signal. We were able to conclude that overall signal shape can have a significant impact on the entrainment characteristics of the system. Due to the nature of the underlying mathematical structure of the model, by examining the circadian rhythm controller, we found that it is unsuitable for entrainment to an incident entraining signal of much higher frequency.     

A study on the effects of using short utterance length development data in the design of GPLDA speaker verification systems

This paper studies the performance degradation of Gaussian probabilistic linear discriminant analysis (GPLDA) speaker verification system, when only short-utterance data is used for speaker verification system development. Subsequently, a number of techniques, including utterance partitioning and source-normalised weighted linear discriminant analysis (SN-WLDA) projections are introduced to improve the speaker verification performance in such conditions. Experimental studies have found that when short utterance data is available for speaker verification development, GPLDA system overall achieves best performance with a lower number of universal background model (UBM) components. As a lower number of UBM components significantly reduces the computational complexity of speaker verification system, that is a useful observation. In limited session data conditions, we propose a simple utterance-partitioning technique, which when applied to the LDA-projected GPLDA system shows over 8% relative improvement on EER values over baseline system on NIST 2008 truncated 10–10 s conditions. We conjecture that this improvement arises from the apparent increase in the number of sessions arising from our partitioning technique and this helps to better model the GPLDA parameters. Further, partitioning SN-WLDA-projected GPLDA shows over 16% and 6% relative improvement on EER values over LDA-projected GPLDA systems respectively on NIST 2008 truncated 10–10 s interview-interview, and NIST 2010 truncated 10–10 s interview-interview and telephone-telephone conditions.     

Bayesian sample-size determination for two independent Poisson rates

Because of the high cost and time constraints for clinical trials, researchers often need to determine the smallest sample size that provides accurate inferences for a parameter of interest. Although most experimenters have employed frequentist sample-size determination methods, the Bayesian paradigm offers a wide variety of sample-size determination methodologies. Bayesian sample-size determination methods are becoming increasingly more popular in clinical trials because of their flexibility and easy interpretation inferences. Recently, Bayesian approaches have been used to determine the sample size of a single Poisson rate parameter in a clinical trial setting. In this paper, we extend these results to the comparison of two Poisson rates and develop methods for sample-size determination for hypothesis testing in a Bayesian context. We have created functions in R to determine the parameters for the conjugate gamma prior and calculate the sample size for the average length criterion and average power methods. We also provide two examples that implement our sample-size determination methods using clinical data.