SINGULARLY PERTURBED DISCOUNTED MARKOV CONTROL PROCESSES IN A GENERAL STATE SPACE

This paper studies the asymptotic optimality of discrete-time Markov decision processes (MDPs) with general state space and action space and having weak and strong interactions. By using a similar approach as developed by Liu, Zhang, and Yin [Appl. Math. Optim., 44 (2001), pp. 105-129], the idea in this paper is to consider an MDP with general state and action spaces and to reduce the dimension of the state space by considering an averaged model. This formulation is often described by introducing a small parameter epsilon > 0 in the definition of the transition kernel, leading to a singularly perturbed Markov model with two time scales. Our objective is twofold. First it is shown that the value function of the control problem for the perturbed system converges to the value function of a limit averaged control problem as epsilon goes to zero. In the second part of the paper, it is proved that a feedback control policy for the original control problem defined by using an optimal feedback policy for the limit problem is asymptotically optimal. Our work extends existing results of the literature in the following two directions: the underlying MDP is defined on general state and action spaces and we do not impose strong conditions on the recurrence structure of the MDP such as Doeblin's condition.

Materials prepared from biopolyethylene and curaua fibers: Composites from biomass

Composites of high-density biopolyethylene (HDBPE) obtained from ethylene derived from sugarcane ethanol and curaua fibers were formed by first mixing in an internal mixer followed by thermopressing. Additionally, hydroxyl-terminated polybutadiene (LHPB), which is usually used as an impact modifier, was mainly used in this study as a compatibilizer agent. The fibers, HDBPE and LHPB were also compounded using an inter-meshing twin-screw extruder and, subsequently, injection molded. The presence of the curaua fibers enhanced some of the properties of the HDBPE, such as its flexural strength and storage modulus. SEM images showed that the addition of LHPB improved the adhesion of the fiber/matrix at the interface, which increased the impact strength of the composite. The higher shear experienced during processing probably led to a more homogeneous distribution of fibers, making the composite that was prepared through extruder/injection molding more resistant to impact than the composite processed by the internal mixer/thermopressing. (c) 2012 Elsevier Ltd. All rights reserved.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

A novel HLA-E allele, E*01:03:05, identified in two Brazilian individuals

Brazilian National Research Council (CNPq/Brazil)

Effect of the Type of Emulsifying Salt on Microstructure and Rheological Properties of "Requeijao Cremoso" Processed Cheese Spreads

The role of different types of emulsifying saltssodium citrate (TSC), sodium hexametaphosphate (SHMP), sodium tripolyphosphate (STPP) and tetrasodium pyrophosphate (TSPP)on microstructure and rheology of requeijao cremoso processed cheese was determined. The cheeses manufactured with TSC, TSPP, and STPP behaved like concentrated solutions, while the cheese manufactured with SHMP exhibited weak gel behavior and the lowest values for the phase angle (G/G). This means that SHMP cheese had the protein network with the largest amount of molecular interactions, which can be explained by its highest degree of fat emulsification. Rotational viscometry indicated that all the spreadable cheeses behaved like pseudoplastic fluids. The cheeses made with SHMP and TSPP presented low values for the flow behavior index, meaning that viscosity was more dependent on shear rate. Regarding the consistency index, TSPP cheese showed the highest value, which could be attributed to the combined effect of its high pH and homogeneous fat particle size distribution.

Co-metabolic models of Streptococcus thermophilus in co-culture with Lactobacillus bulgaricus or Lactobacillus acidophilus

To shed light on the interactions occurring in fermented milks when using co-cultures of Streptococcus thermophilus with Lactobacillus bulgaricus (StLb) or Lactobacillus acidophilus (StLa), a new co-metabolic model was proposed and checked either in the presence of Inulin as a prebiotic or not. For this purpose, the experimental data of concentrations of substrates and fermented products were utilized in balances of carbon, reduction degree and ATP. S. thermophilus exhibited always quicker growth compared to the other two microorganisms, while the percentage of lactose fermented to lactic acid, that of galactose metabolized, and the levels of diacetyl and acetoin formed strongly depended on the type of co-culture and the presence of inulin. The StLb co-culture led to higher acetoin and lower diacetyl levels compared to StLa, probably because of more reducing conditions or limited acetoin dehydrogenation. Inulin addition to StLa suppressed acetoin accumulation and hindered that of diacetyl, suggesting catabolite repression of alpha-acetolactate synthase expression in S. thermophilus. Both co-cultures showed the highest ATP requirements for biomass growth and maintenance at the beginning of fermentation, consistently with the high energy demand of enzyme induction during lag phase. Inulin reduced these requirements making biomass synthesis and maintenance less energy-consuming. Only a fraction of galactose was released from lactose, consistently with the galactose-positive phenotype of most dairy strains. The galactose fraction metabolized without inulin was about twice that in its presence, which suggests inhibition of the galactose transport system of S. thermophilus by fructose released from partial inulin hydrolysis. (C) 2012 Elsevier B.V. All rights reserved.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

BPIFB1 (LPLUNC1) is upregulated in cystic fibrosis lung disease

Although the biology the PLUNC (recently renamed BPI fold, BPIF) family of secreted proteins is poorly understood, multiple array based studies have suggested that some are differentially expressed in lung diseases. We have examined the expression of BPIFB1 (LPLUNC1), the prototypic two-domain containing family member, in lungs from CF patients and in mouse models of CF lung disease. BPIFB1 was localized in CF lung samples along with BPIFA1, MUC5AC, CD68 and NE and directly compared to histologically normal lung tissues and that of bacterial pneumonia. We generated novel antibodies to mouse BPIF proteins to conduct similar studies on ENaC transgenic (ENaC-Tg) mice, a model for CF-like lung disease. Small airways in CF demonstrated marked epithelial staining of BPIFB1 in goblet cells but staining was absent from alveolar regions. BPIFA1 and BPIFB1 were not co-localised in the diseased lungs. In ENaC-Tg mice there was strong staining of both proteins in the airways and luminal contents. This was most marked for BPIFB1 and was noted within 2 weeks of birth. The two proteins were present in distinct cells within epithelium. BPIFB1 was readily detected in BAL from ENaC-Tg mice but was absent from wild-type mice. Alterations in the expression of BPIF proteins is associated with CF lung disease in humans and mice. It is unclear if this elevation of protein production, which results from phenotypic alteration of the cells within the diseased epithelium, plays a role in the pathogenesis of the disease.

The In Vitro and In Vivo Antitumour Activities of Nitrosyl Ruthenium Amine Complexes

Ruthenium compounds of the type trans-[Ru(NO)(NH3)(4)(L)] X-3, L = N-heterocyclic ligands, P(OEt)(3), SO32-, X BF4- or PF6-, or [Ru(NO)Hedta], were tested for antitumour activity in vitro against murine melanoma and human tumour cells. The ruthenium complexes induced DNA fragmentation and morphological alterations suggestive of necrotic tumour cell death. The calculated IC50 values were lower than 100 mu M. Complexes for which L = isn or imN were partially effective in vivo in a syngeneic model of murine melanoma B16F10, increasing animal survival. In addition, the same ruthenium complexes effectively inhibited angiogenesis of HUVEC cells in vitro. The results suggest that these nitrosyl complexes are a promising platform to be explored for the development of novel antitumour agents.

Measurement of prompt J/psi and beauty hadron production cross sections at mid-rapidity in pp collisions at root s=7 TeV

The ALICE experiment at the LHC has studied J/psi production at mid-rapidity in pp collisions at root s = 7 TeV through its electron pair decay on a data sample corresponding to an integrated luminosity L-int = 5.6 nb(-1). The fraction of J/psi from the decay of long-lived beauty hadrons was determined for J/psi candidates with transverse momentum p(t) > 1,3 GeV/c and rapidity vertical bar y vertical bar < 0.9. The cross section for prompt J/psi mesons, i.e. directly produced J/psi and prompt decays of heavier charmonium states such as the psi(2S) and chi(c) resonances, is sigma(prompt J/psi) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 8.3 +/- 0.8(stat.) +/- 1.1 (syst.)(-1.4)(+1.5) (syst. pol.) mu b. The cross section for the production of b-hadrons decaying to J/psi with p(t) > 1.3 GeV/c and vertical bar y vertical bar < 0.9 is a sigma(J/psi <- hB) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 1.46 +/- 0.38 (stat.)(-0.32)(+0.26) (syst.) mu b. The results are compared to QCD model predictions. The shape of the p(t) and y distributions of b-quarks predicted by perturbative QCD model calculations are used to extrapolate the measured cross section to derive the b (b) over bar pair total cross section and d sigma/dy at mid-rapidity.

1,3-Azoles from ortho-naphthoquinones: Synthesis of aryl substituted imidazoles and oxazoles and their potent activity against Mycobacterium tuberculosis

Twenty-three naphthoimidazoles and six naphthoxazoles were synthesised and evaluated against susceptible and rifampicin- and isoniazid-resistant strains of Mycobacterium tuberculosis. Among all the compounds evaluated, fourteen presented MIC values in the range of 0.78 to 6.25 mu g/mL against susceptible and resistant strains of M. tuberculosis, Five structures were solved by X-ray crystallographic analysis. These substances are promising antimycobacterial prototypes. (C) 2012 Elsevier Ltd. All rights reserved.

Prevalence of non-organ-specific autoantibodies in a rural community from northeastern Brazil: a population-based study

Non-organ-specific autoantibodies (NOSA) are well-recognized diagnostic markers of autoimmune hepatitis (All-l) and primary biliary cirrhosis (PBC), but can also be observed in patients with viral hepatitis as well as in healthy subjects. The aim of this study was to evaluate the prevalence of NOSA in subjects living in a rural community in Brazil and to correlate their occurrence with the presence of liver disease. Seven hundred twenty-five apparently healthy subjects were randomly selected for assessment of antinuclear (ANA), anti-smooth muscle (SMA), antimitochondrial (AMA), anti-liver/kidney microsome type 1, and anti-liver cytosol type 1 antibodies. Subjects with those NOSA were evaluated for the presence of AIH, PBC, and viral hepatitis. Reactivities for all NOSA, SMA, ANA, and AMA were detected, respectively, in 14, 10, 4, and 0.1% of subjects, with a mean titer of 1:40. NOSA-positive subjects were significantly older and more frequently females. No correlation was observed between the occurrence of NOSA and PBC. AIH, or viral hepatitis. The prevalence of NOSA in Brazilians was 14%. They were usually low titer. NOSA were more frequently observed in females and older subjects and their presence was not correlated with the presence of AIH, PBC, or viral hepatitis. (C) 2012 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Optimal mean-variance control for discrete-time linear systems with Markovian jumps and multiplicative noises

In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.

Influence of Alloying Elements Upon the Solidification Interval of CA6NM Cast Martensitic Stainless Steel

The influence of different Cr and C contents upon the solidification interval of ASTM A352M-06 Grade CA6NM cast martensitic stainless steel has been investigated using computational thermodynamics, and checked against DTA measurements in samples taken from 13 large cast parts, in order to identify potential sources for improvement on the part castability. Calculation results suggest, indeed, that this would be the case for C: when its content increases from 0.018 to 0.044 wt.% C (within the allowed range in the alloy specification), the solidification intervals increases from 25 to 43 K, which suggests improved castability with decreasing C contents. DTA results, however, do not support this prediction, showing a fairly constant solidification interval around 23 K for all investigated samples. The results are discussed both regarding the impact in alloy processing and the fitness of the existing databases to reproduce experimental results in these limiting cases.