Building a Open Source Framework for Virtual Medical Training

This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

Probabilistic logic with independence

This paper investigates probabilistic logics endowed with independence relations. We review propositional probabilistic languages without and with independence. We then consider graph-theoretic representations for propositional probabilistic logic with independence; complexity is analyzed, algorithms are derived, and examples are discussed. Finally, we examine a restricted first-order probabilistic logic that generalizes relational Bayesian networks. (c) 2007 Elsevier Inc. All rights reserved.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

The frontal assessment battery (FAB) reveals neurocognitive dysfunction in substance-dependent individuals in distinct executive domains: Abstract reasoning, motor programming, and cognitive flexibility

Substance-dependence is highly associated with executive cognitive function (ECF) impairments. However. considering that it is difficult to assess ECF clinically, the aim of the present study was to examine the feasibility of a brief neuropsychological tool (the Frontal Assessment Battery FAB) to detect specific ECF impairments in a sample of substance-dependent individuals (SDI). Sixty-two subjects participated in this study. Thirty DSM-IV-diagnosed SDI, after 2 weeks of abstinence, and 32 healthy individuals (control group) were evaluated with FAD and other ECF-related tasks: digits forward (DF), digits backward (DB), Stroop Color Word Test (SCWT), and Wisconsin Card Sorting Test (WCST). SDI did not differ from the control group on sociodemographic variables or IQ. However, SDI performed below the controls in OF, DB, and FAB. The SDI were cognitively impaired in 3 of the 6 cognitive domains assessed by the FAB: abstract reasoning, motor programming, and cognitive flexibility. The FAB correlated with DF, SCWT, and WCST. In addition, some neuropsychological measures were correlated with the amount of alcohol, cannabis, and cocaine use. In conclusion, SDI performed more poorly than the comparison group on the FAB and the FAB`s results were associated with other ECF-related tasks. The results suggested a negative impact of alcohol, cannabis, and cocaine use on the ECF. The FAB may be useful in assisting professionals as an instrument to screen for ECF-related deficits in SDI. (C) 2010 Elsevier Ltd. All rights reserved.

Predictors of word-level literacy amongst Grade 3 children in five diverse languages

Groups of Grade 3 children were tested on measures of word-level literacy and undertook tasks that required the ability to associate sounds with letter sequences and that involved visual, auditory and phonological-processing skills. These groups came from different language backgrounds in which the language of instruction was Arabic, Chinese, English, Hungarian or Portuguese. Similar measures were used across the groups, with tests being adapted to be appropriate for the language of the children. Findings indicated that measures of decoding and phonological-processing skills were good predictors of word reading and spelling among Arabic- and English-speaking children, but were less able to predict variability in these same early literacy skills among Chinese- and Hungarian-speaking children, and were better at predicting variability in Portuguese word reading than spelling. Results were discussed with reference to the relative transparency of the script and issues of dyslexia assessment across languages. Overall, the findings argue for the need to take account of features of the orthography used to represent a language when developing assessment procedures for a particular language and that assessment of word-level literacy skills and a phonological perspective of dyslexia may not be universally applicable across all language contexts. Copyright (C) 2008 John Wiley & Sons, Ltd.

Recognition by toll-like receptor 2 induces antigen-presenting cell activation and Th1 programming during infection by Neospora caninum

Neospora caninum is an apicomplexan parasite responsible for major economic losses due to abortions in cattle. Toll-like receptors (TLRs) sense specific microbial products and direct downstream signaling pathways in immune cells, linking innate, and adaptive immunity. Here, we analyze the role of TLR2 on innate and adaptive immune responses during N. caninum infection. Inflammatory peritoneal macrophages and bone marrow-derived dendritic cells exposed to N. caninum-soluble antigens presented an upregulated expression of TLR2. Increased receptor expression was correlated to TLR2/MyD88-dependent antigen-presenting cell maturation and pro-inflammatory cytokine production after stimulation by antigens. Impaired innate responses observed after infection of mice genetically deficient for TLR2((-/-)) was followed by downregulation of adaptive T helper 1 (Th1) immunity, represented by diminished parasite-specific CD4(+) and CD8(+) T-cell proliferation, IFN-gamma:interleukin (IL)-10 ratio, and IgG subclass synthesis. In parallel, TLR2(-/-) mice presented higher parasite burden than wild-type (WT) mice at acute and chronic stages of infection. These results show that initial recognition of N. caninum by TLR2 participates in the generation of effector immune responses against N. caninum and imply that the receptor may be a target for future prophylactic strategies against neosporosis. Immunology and Cell Biology (2010) 88, 825-833; doi:10.1038/icb.2010.52; published online 20 April 2010

Perinatal salt restriction: A new pathway to programming adiposity indices in adult female Wistar rats

Low birth weight has been associated with increased obesity in adulthood. It has been shown that dietary salt restriction during intrauterine life induces low birth weight and insulin resistance in adult Wistar rats. The present study had a two-fold objective: to evaluate the effects that low salt intake during pregnancy and lactation has on the amount and distribution of adipose tissue; and to determine whether the phenotypic changes in fat mass in this model are associated with alterations in the activity of the renin-angiotensin system. Maternal salt restriction was found to reduce birth weight in male and female offspring. In adulthood, the female offspring of dams fed the low-salt diet presented higher adiposity indices than those seen in the offspring of dams fed a normal-salt diet. This was attributed to the fact that adipose tissue mass (retroperitoneal but not gonadal, mesenteric or inguinal) was greater in those rats than in the offspring of dams fed a normal diet. The adult offspring of dams fed the low-salt diet, compared to those dams fed a normal-salt diet, presented the following: plasma leptin levels higher in males and lower in females; plasma renin activity higher in males but not in females; and no differences in body weight, mean arterial blood pressure or serum angiotensin-converting enzyme activity. Therefore, low salt intake during pregnancy might lead to the programming of obesity in adult female offspring. (c) 2009 Elsevier Inc. All rights reserved.

An integer linear programming approach for approximate string comparison

We introduce a problem called maximum common characters in blocks (MCCB), which arises in applications of approximate string comparison, particularly in the unification of possibly erroneous textual data coming from different sources. We show that this problem is NP-complete, but can nevertheless be solved satisfactorily using integer linear programming for instances of practical interest. Two integer linear formulations are proposed and compared in terms of their linear relaxations. We also compare the results of the approximate matching with other known measures such as the Levenshtein (edit) distance. (C) 2008 Elsevier B.V. All rights reserved.

A transformational language for mutant description

Mutation testing has been used to assess the quality of test case suites by analyzing the ability in distinguishing the artifact under testing from a set of alternative artifacts, the so-called mutants. The mutants are generated from the artifact under testing by applying a set of mutant operators, which produce artifacts with simple syntactical differences. The mutant operators are usually based on typical errors that occur during the software development and can be related to a fault model. In this paper, we propose a language-named MuDeL (MUtant DEfinition Language)-for the definition of mutant operators, aiming not only at automating the mutant generation, but also at providing precision and formality to the operator definition. The proposed language is based on concepts from transformational and logical programming paradigms, as well as from context-free grammar theory. Denotational semantics formal framework is employed to define the semantics of the MuDeL language. We also describe a system-named mudelgen-developed to support the use of this language. An executable representation of the denotational semantics of the language is used to check the correctness of the implementation of mudelgen. At the very end, a mutant generator module is produced, which can be incorporated into a specific mutant tool/environment. (C) 2008 Elsevier Ltd. All rights reserved.

Proximal methods for nonlinear programming: double regularization and inexact subproblems

This paper describes the first phase of a project attempting to construct an efficient general-purpose nonlinear optimizer using an augmented Lagrangian outer loop with a relative error criterion, and an inner loop employing a state-of-the art conjugate gradient solver. The outer loop can also employ double regularized proximal kernels, a fairly recent theoretical development that leads to fully smooth subproblems. We first enhance the existing theory to show that our approach is globally convergent in both the primal and dual spaces when applied to convex problems. We then present an extensive computational evaluation using the CUTE test set, showing that some aspects of our approach are promising, but some are not. These conclusions in turn lead to additional computational experiments suggesting where to next focus our theoretical and computational efforts.

Algorithms for two-dimensional cutting stock and strip packing problems using dynamic programming and column generation

We investigate several two-dimensional guillotine cutting stock problems and their variants in which orthogonal rotations are allowed. We first present two dynamic programming based algorithms for the Rectangular Knapsack (RK) problem and its variants in which the patterns must be staged. The first algorithm solves the recurrence formula proposed by Beasley; the second algorithm - for staged patterns - also uses a recurrence formula. We show that if the items are not so small compared to the dimensions of the bin, then these algorithms require polynomial time. Using these algorithms we solved all instances of the RK problem found at the OR-LIBRARY, including one for which no optimal solution was known. We also consider the Two-dimensional Cutting Stock problem. We present a column generation based algorithm for this problem that uses the first algorithm above mentioned to generate the columns. We propose two strategies to tackle the residual instances. We also investigate a variant of this problem where the bins have different sizes. At last, we study the Two-dimensional Strip Packing problem. We also present a column generation based algorithm for this problem that uses the second algorithm above mentioned where staged patterns are imposed. In this case we solve instances for two-, three- and four-staged patterns. We report on some computational experiments with the various algorithms we propose in this paper. The results indicate that these algorithms seem to be suitable for solving real-world instances. We give a detailed description (a pseudo-code) of all the algorithms presented here, so that the reader may easily implement these algorithms. (c) 2007 Elsevier B.V. All rights reserved.