47 resultados para combinatorial optimisation


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The set covering problem is an NP-hard combinatorial optimization problemthat arises in applications ranging from crew scheduling in airlines todriver scheduling in public mass transport. In this paper we analyze searchspace characteristics of a widely used set of benchmark instances throughan analysis of the fitness-distance correlation. This analysis shows thatthere exist several classes of set covering instances that have a largelydifferent behavior. For instances with high fitness distance correlation,we propose new ways of generating core problems and analyze the performanceof algorithms exploiting these core problems.

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One of the main questions to solve when analysing geographically added information consists of the design of territorial units adjusted to the objectives of the study. This is related with the reduction of the effects of the Modificable Areal Unit Problem (MAUP). In this paper an optimisation model to solve regionalisation problems is proposed. This model seeks to reduce disadvantages found in previous works about automated regionalisation tools

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A systematic method to improve the quality (Q) factor of RF integrated inductors is presented in this paper. The proposed method is based on the layout optimization to minimize the series resistance of the inductor coil, taking into account both ohmic losses, due to conduction currents, and magnetically induced losses, due to eddy currents. The technique is particularly useful when applied to inductors in which the fabrication process includes integration substrate removal. However, it is also applicable to inductors on low-loss substrates. The method optimizes the width of the metal strip for each turn of the inductor coil, leading to a variable strip-width layout. The optimization procedure has been successfully applied to the design of square spiral inductors in a silicon-based multichip-module technology, complemented with silicon micromachining postprocessing. The obtained experimental results corroborate the validity of the proposed method. A Q factor of about 17 have been obtained for a 35-nH inductor at 1.5 GHz, with Q values higher than 40 predicted for a 20-nH inductor working at 3.5 GHz. The latter is up to a 60% better than the best results for a single strip-width inductor working at the same frequency.

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One of the main questions to solve when analysing geographically added information consists of the design of territorial units adjusted to the objectives of the study. This is related with the reduction of the effects of the Modificable Areal Unit Problem (MAUP). In this paper an optimisation model to solve regionalisation problems is proposed. This model seeks to reduce disadvantages found in previous works about automated regionalisation tools

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We describe the effect of guanidinylation of the aminoglycoside moiety on acridine-neamine-containing ligands for the stem-loop structure located at the exon 10-5′-intron junction of Tau pre-mRNA, an important regulatory element of tau gene alternative splicing. On the basis of dynamic combinatorial chemistry experiments, ligands that combine guanidinoneamine and two different acridines were synthesized and their RNA-binding properties were compared with those of their amino precursors. Fluorescence titration experiments and UV-monitored melting curves revealed that guanidinylation has a positive effect both on the binding affinity and specificity of the ligands for the stemloop RNA, as well as on the stabilization of all RNA sequences evaluated, particularly some mutated sequences associated with the development of FTDP-17 tauopathy. However, this correlation between binding affinity and stabilization due to guanidinylation was only found in ligands containing a longer spacer between the acridine and guanidinoneamine moieties, since a shorter spacer produced the opposite effect (e.g. lower binding affinity and lower stabilization). Furthermore, spectroscopic studies suggest that ligand binding does not significantly change the overall RNA structure upon binding (circular dichroism) and that the acridine moiety might intercalate near the bulged region of the stem->loop structure (UV-Vis and NMR spectroscopy).

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In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimization method to generate the network from the values of the betweenness centrality. We compare the performance of this technique when reconstructing different categories of networks –random, regular, small-world, scale-free and clustered–. We show that the method allows an exact reconstruction of small networks and leads to good topological approximations in the case of networks with larger orders. The method can be used to generate a quasi-optimal topology fora communication network from a list with the values of the maximum allowable traffic for each node.

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This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

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Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

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The inversion problem concerning the windowed Fourier transform is considered. It is shown that, out of the infinite solutions that the problem admits, the windowed Fourier transform is the "optimal" solution according to a maximum-entropy selection criterion.

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During the regeneration of freshwater planarians, polarity and patterning programs play essential roles in determining whether a head or a tail regenerates at anterior or posterior-facing wounds. This decision is made very soon after amputation. The pivotal role of the Wnt/β-catenin and Hh signaling pathways in re-establishing anterior-posterior (AP) polarity has been well documented. However, the mechanisms that control the growth and differentiation of the blastema in accordance with its AP identity are less well understood. Previous studies have described a role of Smed-egfr-3, a planarian epidermal growth factor receptor, in blastema growth and differentiation. Here, we identify Smed-egr-4, a zinc-finger transcription factor belonging to the early growth response gene family, as a putative downstream target of Smed-egfr-3. Smed-egr-4 is mainly expressed in the central nervous system and its silencing inhibits anterior regeneration without affecting the regeneration of posterior regions. Single and combinatorial RNA interference to target different elements of the Wnt/β-catenin pathway, together with expression analysis of brain- and anterior-specific markers, revealed that Smed-egr-4: (1) is expressed in two phases - an early Smed-egfr-3-independent phase and a late Smed-egfr-3-dependent phase; (2) is necessary for the differentiation of the brain primordia in the early stages of regeneration; and (3) that it appears to antagonize the activity of the Wnt/β-catenin pathway to allow head regeneration. These results suggest that a conserved EGFR/egr pathway plays an important role in cell differentiation during planarian regeneration and indicate an association between early brain differentiation and the proper progression of head regeneration.

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Sudoku problems are some of the most known and enjoyed pastimes, with a never diminishing popularity, but, for the last few years those problems have gone from an entertainment to an interesting research area, a twofold interesting area, in fact. On the one side Sudoku problems, being a variant of Gerechte Designs and Latin Squares, are being actively used for experimental design, as in [8, 44, 39, 9]. On the other hand, Sudoku problems, as simple as they seem, are really hard structured combinatorial search problems, and thanks to their characteristics and behavior, they can be used as benchmark problems for refining and testing solving algorithms and approaches. Also, thanks to their high inner structure, their study can contribute more than studies of random problems to our goal of solving real-world problems and applications and understanding problem characteristics that make them hard to solve. In this work we use two techniques for solving and modeling Sudoku problems, namely, Constraint Satisfaction Problem (CSP) and Satisfiability Problem (SAT) approaches. To this effect we define the Generalized Sudoku Problem (GSP), where regions can be of rectangular shape, problems can be of any order, and solution existence is not guaranteed. With respect to the worst-case complexity, we prove that GSP with block regions of m rows and n columns with m = n is NP-complete. For studying the empirical hardness of GSP, we define a series of instance generators, that differ in the balancing level they guarantee between the constraints of the problem, by finely controlling how the holes are distributed in the cells of the GSP. Experimentally, we show that the more balanced are the constraints, the higher the complexity of solving the GSP instances, and that GSP is harder than the Quasigroup Completion Problem (QCP), a problem generalized by GSP. Finally, we provide a study of the correlation between backbone variables – variables with the same value in all the solutions of an instance– and hardness of GSP.

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Growth factors seem to be part of a complex cellular signalling language, in which individual growth factors are the equivalents of the letters that compose words. According to this analogy, informational content lies, not in an individual growth factor, but in the entire set of growth factors and others signals to which a cell is exposed. The ways in which growth factors exert their combinatorial effects are becoming clearer as the molecular mechanisms of growth factors actions are being investigated. A number of related extracellular signalling molecules that play widespread roles in regulating development in both invertebrates and vertebrates constitute the Fibroblast Growth Factor (FGF) and type beta Transforming Growth Factor ((TGF beta). The latest research literature about the role and fate of these Growth factors and their influence in the craniofacial bone growth ad development is reviewed

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Growth factors seem to be part of a complex cellular signalling language, in which individual growth factors are the equivalents of the letters that compose words. According to this analogy, informational content lies, not in an individual growth factor, but in the entire set of growth factors and others signals to which a cell is exposed. The ways in which growth factors exert their combinatorial effects are becoming clearer as the molecular mechanisms of growth factors actions are being investigated. A number of related extracellular signalling molecules that play widespread roles in regulating development in both invertebrates and vertebrates constitute the Fibroblast Growth Factor (FGF) and type beta Transforming Growth Factor ((TGF beta). The latest research literature about the role and fate of these Growth factors and their influence in the craniofacial bone growth ad development is reviewed

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The analysis of the shape of excitation-emission matrices (EEMs) is a relevant tool for exploring the origin, transport and fate of dissolved organic matter (DOM) in aquatic ecosystems. Within this context, the decomposition of EEMs is acquiring a notable relevance. A simple mathematical algorithm that automatically deconvolves individual EEMs is described, creating new possibilities for the comparison of DOM fluorescence properties and EEMs that are very different from each other. A mixture model approach is adopted to decompose complex surfaces into sub-peaks. The laplacian operator and the Nelder-Mead optimisation algorithm are implemented to individuate and automatically locate potential peaks in the EEM landscape. The EEMs of a simple artificial mixture of fluorophores and DOM samples collected in a Mediterranean river are used to describe the model application and to illustrate a strategy that optimises the search for the optimal output.

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Animal olfactory systems have a critical role for the survival and reproduction of individuals. In insects, the odorant-binding proteins (OBPs) are encoded by a moderately sized gene family, and mediate the first steps of the olfactory processing. Most OBPs are organized in clusters of a few paralogs, which are conserved over time. Currently, the biological mechanism explaining the close physical proximity among OBPs is not yet established. Here, we conducted a comprehensive study aiming to gain insights into the mechanisms underlying the OBP genomic organization. We found that the OBP clusters are embedded within large conserved arrangements. These organizations also include other non-OBP genes, which often encode proteins integral to plasma membrane. Moreover, the conservation degree of such large clusters is related to the following: 1) the promoter architecture of the confined genes, 2) a characteristic transcriptional environment, and 3) the chromatin conformation of the chromosomal region. Our results suggest that chromatin domains may restrict the location of OBP genes to regions having the appropriate transcriptional environment, leading to the OBP cluster structure. However, the appropriate transcriptional environment for OBP and the other neighbor genes is not dominated by reduced levels of expression noise. Indeed, the stochastic fluctuations in the OBP transcript abundance may have a critical role in the combinatorial nature of the olfactory coding process.