Bax-induced cell death in Candida albicans

Bax is a pro-apoptotic member of the Bcl-2 family of proteins involved in the regulation of genetically programmed cell death in mammalian cells. It has been shown that heterologous expression of Bax in several yeast species, such as Saccharomyces cerevisiae, Schizosaccharomyces pombe and Pichia pastoris, also induces cell death. In this study we investigated the effects of Bax expression in the pathogenic yeast Candida albicans. Cell death inducing expression of Bax required a synthetic BAX gene that was codon-optimized for expression in Candida albicans. Expression of this BAX gene resulted in growth inhibition and cell death. By fusing Bax with the yeast enhanced green fluorescent protein of Aequoria victoria, the cell death-inducing effect of Bax was increased due to reduced proteolytic degradation of Bax. Using this fusion protein we showed that, upon expression in C. albicans, Bax co-localizes with the mitochondria. Furthermore, we showed for the first time that expression of Bax in yeast causes the mitochondria, which are normally distributed throughout the cell, to cluster in the perinuclear region.     

A comparative study of three BEM for transient dynamic crack analysis of 2-D anisotropic solids

Three different boundary element methods (BEM) for transient dynamic crack analysis in two-dimensional (2-D), homogeneous, anisotropic and linear elastic solids are presented. Hypersingular traction boundary integral equations (BIEs) in frequency- domain, Laplace-domain and time-domain with the corresponding elastodynamic fundamental solutions are applied for this purpose. In the frequency-domain and the Laplace-domain BEM, numerical solutions are first obtained in the transformed domain for discrete frequency or Laplace-transform parameters. Time-dependent results are subsequently obtained by means of the inverse Fourier-transform and the inverse Laplace-transform algorithm of Stehfest. In the time-domain BEM, the quadrature formula of Lubich is adopted to approximate the arising convolution integrals in the time-domain BIEs. Hypersingular integrals involved in the traction BIEs are computed through a regularization process that converts the hypersingular integrals to regular integrals, which can be computed numerically, and singular integrals which can be integrated analytically. Numerical results for the dynamic stress intensity factors are presented and discussed for a finite crack in an infinite domain subjected to an impact crack-face loading.     

Modeling microwave power structures based on k-furcated waveguides arbitrarily filled with materials by modal techniques.

Waveguide structures are very popular in the microwave power industry due to their power handling capabilities. Modal expansion of the waveguide fields and application of the circuit theory allow for the division of a complex device into several simpler sections which can be analyzed separately with the best suited method. The modal techniques can be divided into two groups--those which analyze junctions or discontinuities and those which examine propagation characteristics. In this paper, a review of modal techniques for high power applications is given. Modal expansion of the fields in the waveguides is then performed and applied to modeling of k-furcated waveguides. The modal analysis based on the Coupled Mode Method is described for the waveguides partially filled with isotropic materials. A hybrid modal analysis coupled with Finite Element Method suitable for more complex waveguide structures is also described. Computational results obtained for some real-life microwave devices are presented. Excellent agreement was found when comparing the results with those generated with a commercial FDTD simulator demonstrates the validity and reliability of the proposed method.     

DOCUMENT TRANSLATION RETRIEVAL BASED ON STATISTICAL MACHINE TRANSLATION TECHNIQUES

We compare different strategies to apply statistical machine translation techniques in order to retrieve documents that are a plausible translation of a given source document. Finding the translated version of a document is a relevant task; for example, when building a corpus of parallel texts that can help to create and evaluate new machine translation systems.

In contrast to the traditional settings in cross-language information retrieval tasks, in this case both the source and the target text are long and, thus, the procedure used to select which words or phrases will be included in the query has a key effect on the retrieval performance. In the statistical approach explored here, both the probability of the translation and the relevance of the terms are taken into account in order to build an effective query.     

Prognostic normative reasoning

Human users planning for multiple objectives in complex environments are subjected to high levels of cognitive workload, which can severely impair the quality of the plans created. This paper describes a software agent that can proactively assist cognitively overloaded users by providing normative reasoning about prohibitions and obligations so that the user can focus on her primary objectives. In order to provide proactive assistance, we develop the notion of prognostic normative reasoning (PNR) that consists of the following steps: (1) recognizing the user's planned activities, (2) reasoning about norms to evaluate those predicted activities, and (3) providing necessary assistance so that the user's activities are consistent with norms. The idea of PNR integrates various AI techniques, namely, user intention recognition, normative reasoning over a user's intention, and planning, execution and replanning for assistive actions. In this paper, we describe an agent architecture for PNR and discuss practical applications.     

Declarative planning in procedural agent architectures

Practical agent languages and their corresponding architectures have often relied on a static plan library with more or less direct trigger-response activation mechanisms as a source for agent behaviours for the sake of runtime efficiency. Although efficient, such a language design choice severely limits an agent’s ability to reason about its goals and adapt to unforeseen circumstances after being deployed. This effectively delegates the task of planning to the designers themselves, who must design plan libraries able to cope with every foreseeable situation an agent might find itself in by designing plans to deal with any contingency. In this paper we develop a formal conversion process from traditional BDI agent languages into declarative planning. Using this conversion process, we show how to integrate domain independent planning algorithms into the BDI interpreter, allowing a designer to program an agent not only through the trigger-response mechanism used in traditional languages, but also in terms of declarative goals. Our contribution here is twofold: firstly we increase an agent’s ability to cope with unforeseen situations and secondly we unburden an agent designer from having to define multiple plan combinations that could be easily generated by a planner.     

Fault tolerant embedded systems design by multi-objective optimization

The design of fault tolerant systems is gaining importance in large domains of embedded applications where design constrains are as important as reliability. New software techniques, based on selective application of redundancy, have shown remarkable fault coverage with reduced costs and overheads. However, the large number of different solutions provided by these techniques, and the costly process to assess their reliability, make the design space exploration a very difficult and time-consuming task. This paper proposes the integration of a multi-objective optimization tool with a software hardening environment to perform an automatic design space exploration in the search for the best trade-offs between reliability, cost, and performance. The first tool is commanded by a genetic algorithm which can simultaneously fulfill many design goals thanks to the use of the NSGA-II multi-objective algorithm. The second is a compiler-based infrastructure that automatically produces selective protected (hardened) versions of the software and generates accurate overhead reports and fault coverage estimations. The advantages of our proposal are illustrated by means of a complex and detailed case study involving a typical embedded application, the AES (Advanced Encryption Standard).     

Reference spectra to classify Amazon water types

Reference spectra extracted from spectral libraries can distinguish different water types in images when associated with limnological information. In this study, we compiled available databases into a single spectral library, using field water reflectance spectra and limnological data collected by different researchers and campaigns in the Amazonian region. By using an iterative clustering procedure based on the combination of reflectance and optically active components (OACs), reference spectra representative of the major Amazonian water types were defined from this library. Differences between the resultant limnological classes were also evaluated by paired t-tests at significance level 0.05. Finally, reference spectra were tested for Spectral Angle Mapper (SAM) classification of waters in Hyperion/Earth Observing-One (EO-1) and Medium Resolution Imaging Spectrometer (MERIS)/Environment Satellite (Envisat) images acquired simultaneously as the field campaigns. Results showed highly variable concentrations of OACs due to the complexity of the Amazonian aquatic environments. Ten classes were defined to represent this complexity, broadly grouped into four limnological characteristics: clear waters with low concentrations of OACs (class 1); black waters rich in dissolved organic carbon (DOC) (class 2); waters with large concentrations of inorganic suspended solids (ISSs) (classes 3–7); and waters dominated by chlorophyll-a (chl-a) (classes 8–10). Using the ten reference spectra, SAM classification of the field water curves produced an overall accuracy of 86% with the highest values observed for classes 3, 4, 6 and 7 and the lowest accuracy for classes 1 and 2. The results of paired t-tests confirmed the class differences based on the concentrations of OACs. SAM classification of the Hyperion and MERIS images using ground truth information resulted in overall classification accuracies of 48% and 67%, respectively, with the highest errors associated with specific portions of the scenes that were not adequately represented in the spectral library.