Identification of water-soluble selenium-containing proteins in selenized yeast by size-exclusion-reversed-phase HPLC/ICPMS followed by MALDI-TOF and electrospray Q-TOF mass spectrometry

An approach to speciation of selenium incorporated in yeast proteins was developed. The tryptic digest of a water-soluble protein fraction isolated by size-exclusion chromatography was analyzed by reversed-phase HPLC/ICPMS. The selenopeptides selected owing to the detector's elemental specificity were then analyzed by MALDI-TOFMS in order to select target ions for collision-induced dissociation MS. The latter, carried out with an electrospray Q-TOF spectrometer, enabled the sequencing of the selenopeptides detected by HPLC/ICPMS. The approach allowed for the first time the identification of a family of Se-containing proteins resulting from the replacement by selenomethionine of 2-9 methionine residues in a salt-stress-induced protein SIP18 (Mr 8874). The presence of these proteins was confirmed by MALDI-TOFMS of the original (nondigested) protein fraction. Another selenium protein identified was a heat-shock protein HSP12 (Mr 11693) in which the only methionine residue was replaced by selenomethionine. These two Se-containing proteins accounted for more than 95% of selenium in the water-soluble protein fraction.     

Pressure distribution in an assembly of wooden cylinders with various aspect ratios under uniaxial confined compression

Understanding how forces propagate in granular assemblages is important for equipment design and process control in many technologies. Yet, it remains poorly understood. In this study, a cuboidal assembly comprising cylinders of various lengths (aspect ratios AR ranging from 0.9 to 3.6) were subjected to uniaxial confined compression tests. Samples were vertically compressed until the top platen exerted a pressure of 50 kPa on the uppermost particles. This maximum pressure corresponds to the hydrostatic pressure of an approximately 15 m high column of chopped wood that may be encountered in real storage structures. The nonlinear loading curves were obtained depended on the aspect ratios of the cylinders. The modulus of elasticity, calculated from the linear elastic part of the stress–strain curve, monotonically decreased from 10.2 to 8.6 MPa as the aspect ratio increased from 1.2 to 3.6. The elastic modulus and volume fraction exhibited similar trends as functions of the aspect ratio. The horizontal-to-vertical pressure ratio was calculated as the horizontal pressure exerted on the wider walls to the vertical pressure exerted on the top lid during loading–unloading cycles. For ARs up to 3.6, the pressure ratio was approximately 0.31; for the longest cylinders (AR = 3.6), it decreased to approximately 0.27, probably because the assumption of the representative chamber volume was invalidated at this AR.     

A survey on resource allocation in high performance distributed computing systems

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.     

Potential effects in multi-resolution post-classification change detection

Change detection is one of the primary applications of remote-sensing data, and many techniques have been developed during the past three decades. Although frequently criticized and despite many alternatives, due to its simplicity and intuitive manner, post-classification change detection still remains one of the most applied techniques. Many studies in the field of change detection analysis acknowledge, for instance, the impact of misregistration, inconsistencies in classification schemes or differences in methods for image interpretation. However, there are additional, rarely studied influences that can cause large errors in change detection results, including integrating multi-resolution data, the adjacency effect and the minimum mapping units (MMUs) that are applied to the classification before change detection. This study demonstrates these effects for the complex land cover of the Alvarado mangrove area at the Mexican Gulf Coast, employing 10 m Système Pour l'Observation de la Terre 5 (SPOT-5) high geometric resolution (HRG)‐based and 57 m Landsat Multispectral Scanner (MSS) classifications. As a baseline, the proportion of the fine spatial resolution classes within the coarse spatial resolution cells were derived, from which proportional change matrices were computed. The analysis employs difference measures to compare change matrices and proportional maps. The impact of various tested resampling functions was negligible if coarse resolution data were refined. For coarsening fine spatial resolution data, change matrix comparison was comparatively small but yielded differences of approximately 20% in spatially explicit measures. Incorrect positional alignment indicated differences of up to 5% in the change matrix for a misregistration of 100 m and even higher spatially explicit differences (28%). The discrepancies due to the adjacency effect were rather low. MMUs of 25 ha resulted in differences of up to 36% in the change matrix. The magnitude of the discrepancies of all studied effects depends on the class diversity in the map, and some can also be related to the difference in spatial resolution.     

Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures

This paper studies a heavy-tailed stochastic volatility (SV) model with leverage effect, where a bivariate Student-t distribution is used to model the error innovations of the return and volatility equations. Choy et al. (2008) studied this model by expressing the bivariate Student-t distribution as a scale mixture of bivariate normal distributions. We propose an alternative formulation by first deriving a conditional Student-t distribution for the return and a marginal Student-t distribution for the log-volatility and then express these two Student-t distributions as a scale mixture of normal (SMN) distributions. Our approach separates the sources of outliers and allows for distinguishing between outliers generated by the return process or by the volatility process, and hence is an improvement over the approach of Choy et al. (2008). In addition, it allows an efficient model implementation using the WinBUGS software. A simulation study is conducted to assess the performance of the proposed approach and its comparison with the approach by Choy et al. (2008). In the empirical study, daily exchange rate returns of the Australian dollar to various currencies and daily stock market index returns of various international stock markets are analysed. Model comparison relies on the Deviance Information Criterion and convergence diagnostic is monitored by Geweke’s convergence test.     

Biparametric Models for Elastic Wedge Foundation

In this paper, some biparametric models for an elastic foundation are proposed. It is assumed that the foundation has the shape of the wedge. The modeling procedure starts from the linear elasticity equations into which we introduce some simplifying assumptions based on the conceptions of decay functions. The simplified models are described by the ordinary differential equations. Stationary and nonstationary Green’s functions for the foundation considered are obtained by applying the Hankel and Laplace transform methods. An example of the interaction between the rigid plate and the elastic wedge foundation is studied.     

Quantitative image analysis of polyurethane/carbon nanotube composite micostructures

Polyurethane/carbon nanotube (PUR/CNTs) composites are much more functional than pure polyurethanes. High intensity ultrasonic agitation was applied while preparing a mixture of multiwall carbon nanotubes and a monomer. The monomer/MWNT complexes were used to prepare PUR/CNTs nanocomposites. This paper describes the application of quantitative image analysis to characterise the microstructure of the monomer and segmented polyurethane with carbon nanotubes (CNTs). Stereological parameters chosen for analysis were used to evaluate the CNTs' dispersion in the monomer complex and the degree of matrix phase separation in the nanocomposites examined. The nanoparticles induced changes in the structure of the hard and soft domains in the polyurethane matrix and influenced thermal and mechanical properties of the material. Due to the introduction of the nanotubes in the polyurethane matrix, the physical size and glass transition temperature of hard domains increased while the tensile strength and storage modulus decreased.     

Photo‐induced Charge Transfer and Relaxation of Persistent Charge Carriers in Polymer/Nanocrystal Composites for Applications in Hybrid Solar Cells

The photo‐induced charge transfer and the dynamics of persistent charge carriers in blends of semiconducting polymers and nanocrystals are investigated. Regioregular poly(3‐hexylthiophene) (P3HT) is used as the electron donor material, while the acceptor moiety is established by CdSe nanocrystals (nc‐CdSe) prepared via colloidal synthesis. As a reference system, organic blends of P3HT and [6,6]‐phenyl C₆₁‐butyric acid methyl ester (PCBM) are studied as well. The light‐induced charge transfer between P3HT and the acceptor materials is studied by photoluminescence (PL), photo‐induced absorption (PIA) and light‐induced electron spin resonance spectroscopy (LESR). Compared to neat P3HT samples, both systems show an intensified formation of polarons in the polymer upon photo‐excitation, pointing out successful separation of photogenerated charge carriers. Additionally, relaxation of the persistent charge carriers is investigated, and significant differences are found between the hybrid composite and the purely organic system. While relaxation, reflected in the transient signal decay of the polaron signal, is fast in the organic system, the hybrid blends exhibit long‐term persistence. The appearance of a second, slow recombination channel indicates the existence of deep trap states in the hybrid system, which leads to the capture of a large fraction of charge carriers. A change of polymer conformation due to the presence of nc‐CdSe is revealed by low temperature LESR measurements and microwave saturation techniques. The impact of the different recombination behavior on the photovoltaic efficiency of both systems is discussed.     

Maternal mental health and integrated programs for mothers with substance abuse issues.

To examine the impact of integrated treatment programs (those with substance use treatment and pregnancy-, parenting-, or child-related services) on maternal mental health, we compiled a database of studies of integrated programs published between 1990 and 2007 with outcome data on maternal mental health. There were 18 cohort studies, 3 randomized trials, and 2 quasi-experimental studies. Of the five studies comparing integrated to nonintegrated programs, three studies provided enough information to allow for them to be combined in a meta-analysis. The average effect size was 0.23 (95% CI = 0.15 to 0.31, SE = 0.04), p Q = 5.66, p = .059. This meta-analysis is the first systematic quantitative review of studies evaluating the impact of integrated programs on maternal mental health. Findings suggest that integrated programs may be associated with a small advantage over nonintegrated programs in improving maternal mental health. This review highlights the need for further research with improved methodology, study quality, and reporting to improve our understanding of how best to meet the mental health needs of mothers with substance abuse issues. (PsycINFO Database Record (c) 2010 APA, all rights reserved)