Abstract
One of the classical problems in the structural optimization field is to find the stiffest truss, under a given load and with a bound on the total volume. This is a well-studied problem for continuous cross sectional areas. Generally, the optimal solutions obtained for this problem contain bars with many different cross sectional areas. However, in real life, only a finite set of possible values for those cross sectional areas can be considered. We propose a Semidefinite Programming with discrete variables for this problem. In order to solve the problem we derive and compare two exact algorithms. The first one is a branch and bound algorithm where the branching is done only on the bar-areas. The second algorithm has two stages. In the first stage a branch and bound on the nodes of the structure is performed. In the second stage, considering the nodes in the structure from the first stage, a branch and bound algorithm on the bar-areas is performed.

Abstract
We report on the development of a Genetic Algorithm (GA), which has been integrated into a Decision Support System to plan the best assignment of the weekly self-promotion space for a TV station. The problem addressed consists on deciding which shows to advertise and when such that the number of viewers, of an intended group or target, is maximized. The GA proposed incorporates a greedy heuristic to find good initial solutions. These solutions, as well as the solutions later obtained through the use of the GA, go then through a repair procedure. This is used with two objectives, which are addressed in turn. Firstly, it checks the solution feasibility and if unfeasible it is fixed by removing some shows. Secondly, it tries to improve the solution by adding some extra shows. Since the problem faced by the commercial TV station is too big and has too many features it cannot be solved exactly. Therefore, in order to test the quality of the solutions provided by the proposed GA we have randomly generated some smaller problem instances. For these problems we have obtained solutions on average within 1% of the optimal solution value.

Abstract
Power flow calculations are one of the most important computational tools for planning and operating electric power systems. After the stabilization of the deterministic power flow calculation methods, the need to capture uncertainty in load definition lead first to the development of probabilistic models, and later to fuzzy approaches able to deal with qualitative declarations and other non-probabilistic information about the value of the loads. Present fuzzy power flow (FPF) calculations use typically incremental techniques, in order to obtain a good approximation of the fuzzy state variables. However, these models and procedures are not entirely satisfactory for the evaluation of the adequacy of the electric transmission system, since they are not completely symmetric. In this paper, we show how to perform the detailed calculation of the state variables of the FPF problem in an exact and symmetrical way, by means of solving multiple optimization problems. The procedure is illustrated using the IEEE 118 test system.

Abstract
It has been suggested that dark matter particles which scatter inelastically from detector target nuclei could explain the apparent incompatibility of the DAMA modulation signal (interpreted as evidence for particle dark matter) with the null results from CDMS-II and XENON10. Among the predictions of inelastically interacting dark matter are a suppression of low-energy events, and a population of nuclear recoil events at higher nuclear recoil equivalent energies. This is in stark contrast to the well-known expectation of a falling exponential spectrum for the case of elastic interactions. We present a new analysis of XENON10 dark matter search data extending to E(nr)=75 keV nuclear recoil equivalent energy. Our results exclude a significant region of previously allowed parameter space in the model of inelastically interacting dark matter. In particular, it is found that dark matter particle masses m(chi)greater than or similar to 150 GeV are disfavored.

Abstract
Background: Comparative studies using hundreds of sequences can give a detailed picture of the evolution of a given gene family. Nevertheless, retrieving only the sequences of interest from public databases can be difficult, in particular, when working with highly divergent sequences. The difficulty increases substantially when one wants to include in the study sequences from many (or less well studied) species whose genomes are non-annotated or incompletely annotated. Methodology/Principal Findings: In this work we evaluate the usefulness of different approaches of gene retrieval and classification, using the distal-less (DLX) gene family as a test case. Furthermore, we evaluate whether the use of a large number of gene sequences from a wide range of animal species, the use of multiple alternative alignments, and the use of amino acids aligned with high confidence only, is enough to recover the accepted DLX evolutionary history. Conclusions/Significance: The canonical DLX homeobox gene sequence here derived, together with the characteristic amino acid variants here identified in the DLX homeodomain region, can be used to retrieve and classify DLX genes in a simple and efficient way. A program is made available that allows the easy retrieval of synteny information that can be used to classify gene sequences. Maximum likelihood trees using hundreds of sequences can be used for gene identification. Nevertheless, for the DLX case, the proposed DLX evolutionary is not recovered even when multiple alignment algorithms are used.

Abstract
Marginal prices have been recognized as the core approach to the economic evaluation of generation and transmission services in an electricity market environment. In this context, this paper presents the New Fuzzy Optimal Power Flow algorithm as a model to addresses the impact of load and generation cost uncertainties in nodal marginal prices. Since loads and generation costs are represented by fuzzy numbers, nodal marginal prices will no longer be represented by deterministic values, but rather by fuzzy membership functions reflecting the specified uncertainties. The paper also presents the algorithm used for the integration of the transmission losses effect on the results. Since the proposed algorithm uses multiparametric programming techniques, it contributes to characterize in a better way the system behavior. Finally, it includes results based on the IEEE 24 bus/38 branch test system to illustrate the proposed approach.