Cash balance management: A comparison between genetic algorithms and particle swarm optimization

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 February 2012-31 March 2012

This article documents the addition of 171 microsatellite marker loci and 27 pairs of single nucleotide polymorphism (SNP) sequencing primers to the Molecular Ecology Resources Database. Loci were developed for the following species: Bombus pauloensis, Cephalorhynchus heavisidii, Cercospora sojina, Harpyhaliaetus coronatus, Hordeum vulgare, Lachnolaimus maximus, Oceanodroma monteiroi, Puccinia striiformis f. sp. tritici, Rhea americana, Salmo salar, Salmo trutta, Schistocephalus solidus, Sousa plumbea and Tursiops aduncus. These loci were cross-tested on the following species: Aquila heliaca, Bulweria bulwerii, Buteo buteo, Buteo swainsoni, Falco rusticolus, Haliaeetus albicilla, Halobaena caerulea, Hieraaetus fasciatus, Oceanodroma castro, Puccinia graminis f. sp. Tritici, Puccinia triticina, Rhea pennata and Schistocephalus pungitii. This article also documents the addition of 27 sequencing primer pairs for Puffinus baroli and Bulweria bulwerii and cross-testing of these loci in Oceanodroma castro, Pelagodroma marina, Pelecanoides georgicus, Pelecanoides urinatrix, Thalassarche chrysostoma and Thalassarche melanophrys.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Evaluation of the genetic diversity of Histoplasma capsulatum var. capsulatum isolates from north-eastern Brazil

Since the beginning of the HIV epidemic, there has been a significant increase in the number of histoplasmosis cases in Ceara, a state in north-east Brazil. The lack of epidemiological data on the genotypes circulating in the north-east region shows the importance of more detailed studies on the molecular epidemiology of Histoplasma capsulatum var. capsulatum in this region. Different molecular techniques have been used to better characterize the genetic profile of H. capsulatum var. capsulatum strains. The aim of this study was to analyse the genetic diversity of H. capsulatum var. capsulatum isolates in Fortaleza, the capital of Ceara, through the sequencing of the internal transcribed spacer (ITS)1-5.8S-ITS2 region, and establish the molecular profile of these isolates, along with strains from south-east Brazil, by RAPD analysis, featuring the different clusters in those regions. The isolates were grouped into two clusters. Cluster 1 included strains from the south-east and north-east regions with separation of isolates into three distinct subgroups (subgroups 1a, 1 b and 1 c). Cluster 2 included only samples from north-east Brazil. Sequencing of the ITS1 -5.8S-ITS2 region allowed the detection of two major clades, which showed geographical correlation between them and their subgroups. Therefore, it can be concluded that the H. capsulatum var. capsulatum isolates from Ceara have a high degree of genetic polymorphism. The molecular data also confirm that populations of this fungus are composed of different genotypes in Brazil and worldwide.

A new evolutionary clustering search for a no-wait flow shop problem with set-up times

This paper addresses the m-machine no-wait flow shop problem where the set-up time of a job is separated from its processing time. The performance measure considered is the total flowtime. A new hybrid metaheuristic Genetic Algorithm-Cluster Search is proposed to solve the scheduling problem. The performance of the proposed method is evaluated and the results are compared with the best method reported in the literature. Experimental tests show superiority of the new method for the test problems set, regarding the solution quality. (c) 2012 Elsevier Ltd. All rights reserved.

Phylogenetic relationship of dengue virus type 3 isolated in Brazil and Paraguay and global evolutionary divergence dynamics

Background: Dengue is the most important mosquito-borne viral disease worldwide. Dengue virus comprises four antigenically related viruses named dengue virus type 1 to 4 (DENV1-4). DENV-3 was re-introduced into the Americas in 1994 causing outbreaks in Nicaragua and Panama. DENV-3 was introduced in Brazil in 2000 and then spread to most of the Brazilian States, reaching the neighboring country, Paraguay in 2002. In this study, we have analyzed the phylogenetic relationship of DENV-3 isolated in Brazil and Paraguay with viruses isolated worldwide. We have also analyzed the evolutionary divergence dynamics of DENV-3 viruses. Results: The entire open reading frame (ORF) of thirteen DENV-3 isolated in Brazil (n = 9) and Paraguay (n = 4) were sequenced for phylogenetic analysis. DENV-3 grouped into three main genotypes (I, II and III). Several internal clades were found within each genotype that we called lineage and sub-lineage. Viruses included in this study belong to genotype III and grouped together with viruses isolated in the Americas within the lineage III. The Brazilian viruses were further segregated into two different sub-lineage, A and B, and the Paraguayan into the sub-lineage B. All three genotypes showed internal grouping. The nucleotide divergence was in average 6.7% for genotypes, 2.7% for lineages and 1.5% for sub-lineages. Phylogenetic trees constructed with any of the protein gene sequences showed the same segregation of the DENV-3 in three genotypes. Conclusion: Our results showed that two groups of DENV-3 genotypes III circulated in Brazil during 2002-2009, suggesting different events of introduction of the virus through different regions of the country. In Paraguay, only one group DENV-3 genotype III is circulating that is very closely related to the Brazilian viruses of sub-lineage B. Different degree of grouping can be observed for DENV-3 and each group showed a characteristic evolutionary divergence. Finally, we have observed that any protein gene sequence can be used to identify the virus genotype.

Genetic features and molecular epidemiology of Enterococcus faecium isolated in two university hospitals in Brazil

The global emergence of vancomycin-resistant Enterococcus faecium (VREfm) has been characterized by a clonal spread of strains belonging to clonal complex 17 (CC17). Genetic features and clonal relationships of 53 VREfm isolated from patients in 2 hospitals in Ribeirao Preto, Sao Paulo, Brazil, during 2005-2010 were determined as a contribution to the Brazilian evolutionary history of these nosocomial pathogens. All isolates were daptomycin susceptible, vancomycin-resistant, and had the vanA gene. The predominant virulence genes were acm and esp. Only 5 VREfm isolated in 2005-2006 had intact Tn1546, while 81% showed Tn1546 with deleted left extremity and insertion of IS1251 between the vanS and vanH genes. Multilocus sequence typing analysis permitted the identification of 9 different sequence types (STs), with 5 being new ones (656, 657, 658, 659, and 660). Predominant STs were ST412 and ST478, all belonging to CC17, except ST658. This is the first report of the ST78 in Brazil. (c) 2012 Elsevier Inc. All rights reserved.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

Abstract Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks.

Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.

Influence of pollination and seed dispersal on the genetic population structure of two Commiphora species in Madagascar and South Africa

Pollination and seed dispersal are important ecological processes for the regeneration of plant populations and both vectors for gene exchange between plant populations. For my thesis, I studied the pollination ecology of the South African tree Commiphora harveyi (Burseraceae) and compared it with C. guillauminii from Madagascar. Both species have low visitation rates and a low number of pollinating insect species, resulting in a low fruit set. While their pollination ecology is very similar, they differ in their seed dispersal with a low seed dispersal rate in the Malagasy and a high seed dispersal rate in the South African species. This should be reflected in a stronger genetic differentiation among populations in the Malagasy than in the South African species. My results, based on AFLP markers, contradict these expectations, the overall differentiation was lower in the Malagasy (FST = 0.05) than in the South African species (FST = 0.16). However, at a smaller spatial scale (below 3 km), the Malagasy species was genetically more strongly differentiated than the South African species, which was reflected by the high inter-population variance within the sample site (C. guillauminii: 72.2 - 85.5 %; C. harveyi: 8.4 - 14.5 %). This strong differentiation could arise from limited gene flow, which was confirmed by spatial autocorrelation analyses. The shape of the autocorrelogram suggested that gene exchange between individuals occurred only up to 3 km in the Malagasy species, whereas up to 30 km in the South African species. These results on the genetic structure correspond to the expectations based on seed dispersal data. Thus, seed dispersal seems to be a key factor for the genetic structure in plant populations on a local scale.

Theoretical and implementation aspects in the mechanization of the metatheory of programming languages

Interactive theorem provers are tools designed for the certification of formal proofs developed by means of man-machine collaboration. Formal proofs obtained in this way cover a large variety of logical theories, ranging from the branches of mainstream mathematics, to the field of software verification. The border between these two worlds is marked by results in theoretical computer science and proofs related to the metatheory of programming languages. This last field, which is an obvious application of interactive theorem proving, poses nonetheless a serious challenge to the users of such tools, due both to the particularly structured way in which these proofs are constructed, and to difficulties related to the management of notions typical of programming languages like variable binding. This thesis is composed of two parts, discussing our experience in the development of the Matita interactive theorem prover and its use in the mechanization of the metatheory of programming languages. More specifically, part I covers: - the results of our effort in providing a better framework for the development of tactics for Matita, in order to make their implementation and debugging easier, also resulting in a much clearer code; - a discussion of the implementation of two tactics, providing infrastructure for the unification of constructor forms and the inversion of inductive predicates; we point out interactions between induction and inversion and provide an advancement over the state of the art. In the second part of the thesis, we focus on aspects related to the formalization of programming languages. We describe two works of ours: - a discussion of basic issues we encountered in our formalizations of part 1A of the Poplmark challenge, where we apply the extended inversion principles we implemented for Matita; - a formalization of an algebraic logical framework, posing more complex challenges, including multiple binding and a form of hereditary substitution; this work adopts, for the encoding of binding, an extension of Masahiko Sato's canonical locally named representation we designed during our visit to the Laboratory for Foundations of Computer Science at the University of Edinburgh, under the supervision of Randy Pollack.

Molecular phylogeography of the Woodland Ringlet (Erebia medusa [Denis and Schiffermüller] 1775) in Europe

Phylogeography is a recent field of biological research that links phylogenetics to biogeography through deciphering the imprint that evolutionary history has left on the genetic structure of extant populations. During the cold phases of the successive ice ages, which drastically shaped species’ distributions since the Pliocene, populations of numerous species were isolated in refugia where many of them evolved into different genetic lineages. My dissertation deals with the phylogeography of the Woodland Ringlet (Erebia medusa [Denis and Schiffermüller] 1775) in Central and Eastern Europe. This Palaearctic butterfly species is currently distributed from central France and south eastern Belgium over large parts of Central Europe and southern Siberia to the Pacific. It is absent from those parts of Europe with mediterranean, oceanic and boreal climates. It was supposed to be a Siberian faunal element with a rather homogeneous population structure in Central Europe due to its postglacial expansion out of a single eastern refugium. An already existing evolutionary scenario for the Woodland Ringlet in Central and Eastern Europe is based on nuclear data (allozymes). To know if this is corroborated by organelle evolutionary history, I sequenced two mitochondrial markers (part of the cytochrome oxydase subunit one and the control region) for populations sampled over the same area. Phylogeography largely relies on the construction of networks of uniparentally inherited haplotypes that are compared to geographic haplotype distribution thanks to recent developed methods such as nested clade phylogeographic analysis (NCPA). Several ring-shaped ambiguities (loops) emerged from both haplotype networks in E. medusa. They can be attributed to recombination and homoplasy. Such loops usually avert the straightforward extraction of the phylogeographic signal contained in a gene tree. I developed several new approaches to extract phylogeographic information in the presence of loops, considering either homoplasy or recombination. This allowed me to deduce a consistent evolutionary history for the species from the mitochondrial data and also adds plausibility for the occurrence of recombination in E. medusa mitochondria. Despite the fact that the control region is assumed to have a lack of resolving power in other species, I found a considerable genetic variation of this marker in E. medusa which makes it a useful tool for phylogeographic studies. In combination with the allozyme data, the mitochondrial genome supports the following phylogeographic scenario for E. medusa in Europe: (i) a first vicariance, due to the onset of the Würm glaciation, led to the formation of several major lineages, and is mirrored in the NCPA by restricted gene flow, (ii) later on further vicariances led to the formation of two sub-lineages in the Western lineage and two sub-lineages in the Eastern lineage during the Last Glacial Maximum or Older Dryas; additionally the NCPA supports a restriction of gene flow with isolation by distance, (iii) finally, vicariance resulted in two secondary sub-lineages in the area of Germany and, maybe, to two other secondary sub-lineages in the Czech Republic. The last postglacial warming was accompanied by strong range expansions in most of the genetic lineages. The scenario expected for a presumably Siberian faunal element such as E. medusa is a continuous loss of genetic diversity during postglacial westward expansion. Hence, the pattern found in this thesis contradicts a typical Siberian origin of E. medusa. In contrast, it corroboratess the importance of multiple extra-Mediterranean refugia for European fauna as it was recently assumed for other continental species.

Modeling and simulation of a synthetic genetic circuit that implements a multicelled behavior in a growing microcolony of E. coli

Synthetic Biology is a relatively new discipline, born at the beginning of the New Millennium, that brings the typical engineering approach (abstraction, modularity and standardization) to biotechnology. These principles aim to tame the extreme complexity of the various components and aid the construction of artificial biological systems with specific functions, usually by means of synthetic genetic circuits implemented in bacteria or simple eukaryotes like yeast. The cell becomes a programmable machine and its low-level programming language is made of strings of DNA. This work was performed in collaboration with researchers of the Department of Electrical Engineering of the University of Washington in Seattle and also with a student of the Corso di Laurea Magistrale in Ingegneria Biomedica at the University of Bologna: Marilisa Cortesi. During the collaboration I contributed to a Synthetic Biology project already started in the Klavins Laboratory. In particular, I modeled and subsequently simulated a synthetic genetic circuit that was ideated for the implementation of a multicelled behavior in a growing bacterial microcolony. In the first chapter the foundations of molecular biology are introduced: structure of the nucleic acids, transcription, translation and methods to regulate gene expression. An introduction to Synthetic Biology completes the section. In the second chapter is described the synthetic genetic circuit that was conceived to make spontaneously emerge, from an isogenic microcolony of bacteria, two different groups of cells, termed leaders and followers. The circuit exploits the intrinsic stochasticity of gene expression and intercellular communication via small molecules to break the symmetry in the phenotype of the microcolony. The four modules of the circuit (coin flipper, sender, receiver and follower) and their interactions are then illustrated. In the third chapter is derived the mathematical representation of the various components of the circuit and the several simplifying assumptions are made explicit. Transcription and translation are modeled as a single step and gene expression is function of the intracellular concentration of the various transcription factors that act on the different promoters of the circuit. A list of the various parameters and a justification for their value closes the chapter. In the fourth chapter are described the main characteristics of the gro simulation environment, developed by the Self Organizing Systems Laboratory of the University of Washington. Then, a sensitivity analysis performed to pinpoint the desirable characteristics of the various genetic components is detailed. The sensitivity analysis makes use of a cost function that is based on the fraction of cells in each one of the different possible states at the end of the simulation and the wanted outcome. Thanks to a particular kind of scatter plot, the parameters are ranked. Starting from an initial condition in which all the parameters assume their nominal value, the ranking suggest which parameter to tune in order to reach the goal. Obtaining a microcolony in which almost all the cells are in the follower state and only a few in the leader state seems to be the most difficult task. A small number of leader cells struggle to produce enough signal to turn the rest of the microcolony in the follower state. It is possible to obtain a microcolony in which the majority of cells are followers by increasing as much as possible the production of signal. Reaching the goal of a microcolony that is split in half between leaders and followers is comparatively easy. The best strategy seems to be increasing slightly the production of the enzyme. To end up with a majority of leaders, instead, it is advisable to increase the basal expression of the coin flipper module. At the end of the chapter, a possible future application of the leader election circuit, the spontaneous formation of spatial patterns in a microcolony, is modeled with the finite state machine formalism. The gro simulations provide insights into the genetic components that are needed to implement the behavior. In particular, since both the examples of pattern formation rely on a local version of Leader Election, a short-range communication system is essential. Moreover, new synthetic components that allow to reliably downregulate the growth rate in specific cells without side effects need to be developed. In the appendix are listed the gro code utilized to simulate the model of the circuit, a script in the Python programming language that was used to split the simulations on a Linux cluster and the Matlab code developed to analyze the data.

Genetic characterisation and global comparison of ancient Mediterranean Great White Sharks population (Carcharodon carcharias, L.1758)

This study poses as its objective the genetic characterization of the ancient population of the Great White shark, Carcharodon carcharias, L.1758, present in the Mediterranean Sea. Using historical evidence, for the most part buccal arches but also whole, stuffed examples from various national museums, research institutes and private collections, a dataset of 18 examples coming from the Mediterranean Sea has been created, in order to increase the informations regarding this species in the Mediterranean. The importance of the Mediterranean provenance derives from the fact that a genetic characterization of this species' population does not exist, and this creates gaps in the knowledge of this species in the Mediterranean. The genetic characterization of the individuals will initially take place by the extraction of the ancient DNA and the analysis of the variations in the sequence markers of the mitochondrial DNA. This approach has allowed the genetic comparison between ancient populations of the Mediterranean and contemporary populations of the same geographical area. In addition, the genetic characterization of the population of white sharks of the Mediterranean, has allowed a genetic comparison with populations from global "hot spots", using published sequences in online databases (NCBI, GenBank). Analyzing the variability of the dataset, both in terms space and time, I assessed the evolutionary relationships of the Mediterranean population of Great Whites with the global populations (Australia/New Zealand, South Africa, Pacific USA, West Atlantic), and the temporal trend of the Mediterranean population variability. This method based on the sequencing of two portions of mitochondrial DNA genes, markers showed us how the population of Great White Sharks in the Mediterranean, is genetically more similar to the populations of the Australia Pacific ocean, American Pacific Ocean, rather than the population of South Africa, and showing also how the population of South Africa is abnormally distant from all other clusters. Interestingly, these results are inconsistent with the results from tagging of this species. In addition, there is evidence of differences between the ancient population of the Mediterranean with the modern one. This differentiation between the ancient and modern population of white shark can be the result of events impacting on this species occurred over the last two centuries.

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.