971 resultados para differential evolution algorithm
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We consider stochastic partial differential equations with multiplicative noise. We derive an algorithm for the computer simulation of these equations. The algorithm is applied to study domain growth of a model with a conserved order parameter. The numerical results corroborate previous analytical predictions obtained by linear analysis.
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We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow.
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We study nonstationary non-Markovian processes defined by Langevin-type stochastic differential equations with an OrnsteinUhlenbeck driving force. We concentrate on the long time limit of the dynamical evolution. We derive an approximate equation for the correlation function of a nonlinear nonstationary non-Markovian process, and we discuss its consequences. Non-Markovicity can introduce a dependence on noise parameters in the dynamics of the correlation function in cases in which it becomes independent of these parameters in the Markovian limit. Several examples are discussed in which the relaxation time increases with respect to the Markovian limit. For a Brownian harmonic oscillator with fluctuating frequency, the non-Markovicity of the process decreases the domain of stability of the system, and it can change an infradamped evolution into an overdamped one.
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Pyogenic liver abscess is a severe condition and a therapeutic challenge. Treatment failure may be due to an unrecognized ingested foreign body that migrated from the gastrointestinal tract. There has recently been a marked increase in the number of reported cases of this condition, but initial misdiagnosis as cryptogenic liver abscess still occurs in the majority of cases. We conducted the current study to characterize this entity and provide a diagnostic strategy applicable worldwide. To this end, data were collected from our case and from a systematic review that identified 59 well-described cases. Another systematic review identified series of cryptogenic-and Asian Klebsiella-liver abscess; these data were pooled and compared with the data from the cases of migrated foreign body liver abscess. The review points out the low diagnostic accuracy of history taking, modern imaging, and even surgical exploration. A fistula found through imaging procedures or endoscopy warrants surgical exploration. Findings suggestive of foreign body migration are symptoms of gastrointestinal perforation, computed tomography demonstration of a thickened gastrointestinal wall in continuity with the abscess, and adhesions seen during surgery. Treatment failure, left lobe location, unique location (that is, only 1 abscess location within the liver), and absence of underlying conditions also point to the diagnosis, as shown by comparison with the cryptogenic liver abscess series. This study demonstrates that migrated foreign body liver abscess is a specific entity, increasingly reported. It usually is not cured when unrecognized, and diagnosis is mainly delayed. This study provides what we consider the best available evidence for timely diagnosis with worldwide applicability. Increased awareness is required to treat this underestimated condition effectively, and further studies are needed.
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Context: Ovarian tumors (OT) typing is a competency expected from pathologists, with significant clinical implications. OT however come in numerous different types, some rather rare, with the consequence of few opportunities for practice in some departments. Aim: Our aim was to design a tool for pathologists to train in less common OT typing. Method and Results: Representative slides of 20 less common OT were scanned (Nano Zoomer Digital Hamamatsu®) and the diagnostic algorithm proposed by Young and Scully applied to each case (Young RH and Scully RE, Seminars in Diagnostic Pathology 2001, 18: 161-235) to include: recognition of morphological pattern(s); shortlisting of differential diagnosis; proposition of relevant immunohistochemical markers. The next steps of this project will be: evaluation of the tool in several post-graduate training centers in Europe and Québec; improvement of its design based on evaluation results; diffusion to a larger public. Discussion: In clinical medicine, solving many cases is recognized as of utmost importance for a novice to become an expert. This project relies on the virtual slides technology to provide pathologists with a learning tool aimed at increasing their skills in OT typing. After due evaluation, this model might be extended to other uncommon tumors.
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Impressive developments in X-ray imaging are associated with X-ray phase contrast computed tomography based on grating interferometry, a technique that provides increased contrast compared with conventional absorption-based imaging. A new "single-step" method capable of separating phase information from other contributions has been recently proposed. This approach not only simplifies data-acquisition procedures, but, compared with the existing phase step approach, significantly reduces the dose delivered to a sample. However, the image reconstruction procedure is more demanding than for traditional methods and new algorithms have to be developed to take advantage of the "single-step" method. In the work discussed in this paper, a fast iterative image reconstruction method named OSEM (ordered subsets expectation maximization) was applied to experimental data to evaluate its performance and range of applicability. The OSEM algorithm with different subsets was also characterized by comparison of reconstruction image quality and convergence speed. Computer simulations and experimental results confirm the reliability of this new algorithm for phase-contrast computed tomography applications. Compared with the traditional filtered back projection algorithm, in particular in the presence of a noisy acquisition, it furnishes better images at a higher spatial resolution and with lower noise. We emphasize that the method is highly compatible with future X-ray phase contrast imaging clinical applications.
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In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.
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BACKGROUND: Understanding how alternative phenotypes arise from the same genome is a major challenge in modern biology. Eusociality in insects requires the evolution of two alternative phenotypes - workers, who sacrifice personal reproduction, and queens, who realize that reproduction. Extensive work on honeybees and ants has revealed the molecular basis of derived queen and worker phenotypes in highly eusocial lineages, but we lack equivalent deep-level analyses of wasps and of primitively eusocial species, the latter of which can reveal how phenotypic decoupling first occurs in the early stages of eusocial evolution. RESULTS: We sequenced 20 Gbp of transcriptomes derived from brains of different behavioral castes of the primitively eusocial tropical paper wasp Polistes canadensis. Surprisingly, 75% of the 2,442 genes differentially expressed between phenotypes were novel, having no significant homology with described sequences. Moreover, 90% of these novel genes were significantly upregulated in workers relative to queens. Differential expression of novel genes in the early stages of sociality may be important in facilitating the evolution of worker behavioral complexity in eusocial evolution. We also found surprisingly low correlation in the identity and direction of expression of differentially expressed genes across similar phenotypes in different social lineages, supporting the idea that social evolution in different lineages requires substantial de novo rewiring of molecular pathways. CONCLUSIONS: These genomic resources for aculeate wasps and first transcriptome-wide insights into the origin of castes bring us closer to a more general understanding of eusocial evolution and how phenotypic diversity arises from the same genome.
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A simple non-targeted differential HPLC-APCI/MS approach has been developed in order to survey metabolome modifications that occur in the leaves of Arabidopsis thaliana following wound-induced stress. The wound-induced accumulation of metabolites, particularly oxylipins, was evaluated by HPLC-MS analysis of crude leaf extracts. A generic, rapid and reproducible pressure liquid extraction procedure was developed for the analysis of restricted leaf samples without the need for specific sample preparation. The presence of various oxylipins was determined by head-to-head comparison of the HPLC-MS data, filtered with a component detection algorithm, and automatically compared with the aid of software searching for small differences in similar HPLC-MS profiles. Repeatability was verified in several specimens belonging to different series. Wound-inducible jasmonates were efficiently highlighted by this non-targeted approach without the need for complex sample preparation as is the case for the 'oxylipin signature' procedure based on GC-MS. Furthermore this HPLC-MS screening technique allowed the isolation of induced compounds for further characterisation by capillary-scale NMR (CapNMR) after HPLC scale-up. In this paper, the screening method is described and applied to illustrate its potential for monitoring polar and non-polar stress-induced constituents as well as its use in combination with CapNMR for the structural assignment of wound-induced compounds of interest
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Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.
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Abstract The main objective of this work is to show how the choice of the temporal dimension and of the spatial structure of the population influences an artificial evolutionary process. In the field of Artificial Evolution we can observe a common trend in synchronously evolv¬ing panmictic populations, i.e., populations in which any individual can be recombined with any other individual. Already in the '90s, the works of Spiessens and Manderick, Sarma and De Jong, and Gorges-Schleuter have pointed out that, if a population is struc¬tured according to a mono- or bi-dimensional regular lattice, the evolutionary process shows a different dynamic with respect to the panmictic case. In particular, Sarma and De Jong have studied the selection pressure (i.e., the diffusion of a best individual when the only selection operator is active) induced by a regular bi-dimensional structure of the population, proposing a logistic modeling of the selection pressure curves. This model supposes that the diffusion of a best individual in a population follows an exponential law. We show that such a model is inadequate to describe the process, since the growth speed must be quadratic or sub-quadratic in the case of a bi-dimensional regular lattice. New linear and sub-quadratic models are proposed for modeling the selection pressure curves in, respectively, mono- and bi-dimensional regu¬lar structures. These models are extended to describe the process when asynchronous evolutions are employed. Different dynamics of the populations imply different search strategies of the resulting algorithm, when the evolutionary process is used to solve optimisation problems. A benchmark of both discrete and continuous test problems is used to study the search characteristics of the different topologies and updates of the populations. In the last decade, the pioneering studies of Watts and Strogatz have shown that most real networks, both in the biological and sociological worlds as well as in man-made structures, have mathematical properties that set them apart from regular and random structures. In particular, they introduced the concepts of small-world graphs, and they showed that this new family of structures has interesting computing capabilities. Populations structured according to these new topologies are proposed, and their evolutionary dynamics are studied and modeled. We also propose asynchronous evolutions for these structures, and the resulting evolutionary behaviors are investigated. Many man-made networks have grown, and are still growing incrementally, and explanations have been proposed for their actual shape, such as Albert and Barabasi's preferential attachment growth rule. However, many actual networks seem to have undergone some kind of Darwinian variation and selection. Thus, how these networks might have come to be selected is an interesting yet unanswered question. In the last part of this work, we show how a simple evolutionary algorithm can enable the emrgence o these kinds of structures for two prototypical problems of the automata networks world, the majority classification and the synchronisation problems. Synopsis L'objectif principal de ce travail est de montrer l'influence du choix de la dimension temporelle et de la structure spatiale d'une population sur un processus évolutionnaire artificiel. Dans le domaine de l'Evolution Artificielle on peut observer une tendence à évoluer d'une façon synchrone des populations panmictiques, où chaque individu peut être récombiné avec tout autre individu dans la population. Déjà dans les année '90, Spiessens et Manderick, Sarma et De Jong, et Gorges-Schleuter ont observé que, si une population possède une structure régulière mono- ou bi-dimensionnelle, le processus évolutionnaire montre une dynamique différente de celle d'une population panmictique. En particulier, Sarma et De Jong ont étudié la pression de sélection (c-à-d la diffusion d'un individu optimal quand seul l'opérateur de sélection est actif) induite par une structure régulière bi-dimensionnelle de la population, proposant une modélisation logistique des courbes de pression de sélection. Ce modèle suppose que la diffusion d'un individu optimal suit une loi exponentielle. On montre que ce modèle est inadéquat pour décrire ce phénomène, étant donné que la vitesse de croissance doit obéir à une loi quadratique ou sous-quadratique dans le cas d'une structure régulière bi-dimensionnelle. De nouveaux modèles linéaires et sous-quadratique sont proposés pour des structures mono- et bi-dimensionnelles. Ces modèles sont étendus pour décrire des processus évolutionnaires asynchrones. Différentes dynamiques de la population impliquent strategies différentes de recherche de l'algorithme résultant lorsque le processus évolutionnaire est utilisé pour résoudre des problèmes d'optimisation. Un ensemble de problèmes discrets et continus est utilisé pour étudier les charactéristiques de recherche des différentes topologies et mises à jour des populations. Ces dernières années, les études de Watts et Strogatz ont montré que beaucoup de réseaux, aussi bien dans les mondes biologiques et sociologiques que dans les structures produites par l'homme, ont des propriétés mathématiques qui les séparent à la fois des structures régulières et des structures aléatoires. En particulier, ils ont introduit la notion de graphe sm,all-world et ont montré que cette nouvelle famille de structures possède des intéressantes propriétés dynamiques. Des populations ayant ces nouvelles topologies sont proposés, et leurs dynamiques évolutionnaires sont étudiées et modélisées. Pour des populations ayant ces structures, des méthodes d'évolution asynchrone sont proposées, et la dynamique résultante est étudiée. Beaucoup de réseaux produits par l'homme se sont formés d'une façon incrémentale, et des explications pour leur forme actuelle ont été proposées, comme le preferential attachment de Albert et Barabàsi. Toutefois, beaucoup de réseaux existants doivent être le produit d'un processus de variation et sélection darwiniennes. Ainsi, la façon dont ces structures ont pu être sélectionnées est une question intéressante restée sans réponse. Dans la dernière partie de ce travail, on montre comment un simple processus évolutif artificiel permet à ce type de topologies d'émerger dans le cas de deux problèmes prototypiques des réseaux d'automates, les tâches de densité et de synchronisation.
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The objective of research was to analyse the potential of Normalized Difference Vegetation Index (NDVI) maps from satellite images, yield maps and grapevine fertility and load variables to delineate zones with different wine grape properties for selective harvesting. Two vineyard blocks located in NE Spain (Cabernet Sauvignon and Syrah) were analysed. The NDVI was computed from a Quickbird-2 multi-spectral image at veraison (July 2005). Yield data was acquired by means of a yield monitor during September 2005. Other variables, such as the number of buds, number of shoots, number of wine grape clusters and weight of 100 berries were sampled in a 10 rows × 5 vines pattern and used as input variables, in combination with the NDVI, to define the clusters as alternative to yield maps. Two days prior to the harvesting, grape samples were taken. The analysed variables were probable alcoholic degree, pH of the juice, total acidity, total phenolics, colour, anthocyanins and tannins. The input variables, alone or in combination, were clustered (2 and 3 Clusters) by using the ISODATA algorithm, and an analysis of variance and a multiple rang test were performed. The results show that the zones derived from the NDVI maps are more effective to differentiate grape maturity and quality variables than the zones derived from the yield maps. The inclusion of other grapevine fertility and load variables did not improve the results.
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A number of bacterial species, mostly proteobacteria, possess monothiol glutaredoxins homologous to the Saccharomyces cerevisiae mitochondrial protein Grx5, which is involved in iron–sulphur cluster synthesis. Phylogenetic profiling is used to predict that bacterial monothiol glutaredoxins also participate in the iron–sulphur cluster (ISC) assembly machinery, because their phylogenetic profiles are similar to the profiles of the bacterial homologues of yeast ISC proteins. High evolutionary cooccurrence is observed between the Grx5 homologues and the homologues of the Yah1 ferredoxin, the scaffold proteins Isa1 and Isa2, the frataxin protein Yfh1 and the Nfu1 protein. This suggests that a specific functional interaction exists between these ISC machinery proteins. Physical interaction analyses using low-definition protein docking predict the formation of strong and specific complexes between Grx5 and several components of the yeast ISC machinery. Two-hybrid analysis has confirmed the in vivo interaction between Grx5 and Isa1. Sequence comparison techniques and cladistics indicate that the other two monothiol glutaredoxins of S. cerevisiae, Grx3 and Grx4, have evolved from the fusion of a thioredoxin gene with a monothiol glutaredoxin gene early in the eukaryotic lineage, leading to differential functional specialization. While bacteria do not contain these chimaeric glutaredoxins, in many eukaryotic species Grx5 and Grx3/4-type monothiol glutaredoxins coexist in the cell.
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Most metazoans rely on aerobic energy production, which is dependent on adequate oxygen supply. In the case of reduced oxygen supply (hypoxia), the most profound changes in gene expression are mediated by transcription factors named hypoxia-inducible factors (HIF alpha). These proteins are post-translationally regulated by prolyl-4-hydroxylase (PHD) enzymes that are direct “sensors” of cellular oxygen levels. This thesis examines the molecular evolution of metazoan HIF systems. In early metazoans the HIF system emerged from pre-existing PHD oxygen sensors and early bHLH-PAS transcription factors. In invertebrates our analysis revealed an unexpected diversity of PHD genes and HIF alpha sequence characteristics. An early branching vertebrate, the epaulette shark (Hemiscyllium ocellatum) was chosen for sequencing and hypoxia preconditioning studies of HIF alpha and PHD genes. As no quantitative PCR reference genes were available, this thesis includes the first study of reference genes in cartilaginous fish species. Applying multiple statistical analysis we also discoveredthat commonly used reference gene software may perform poorly with some data sets. Novel reference genes allowed accurate measurements of the mRNAlevels of the studied target genes. Cartilaginous fishes have three genomic duplicates of both HIF alpha and PHD genes like mammals and teleost fishes. Combining functional divergence and selection analyses it was possible to describe how sequence changes in both HIF alpha and PHD duplicates may have contributed to the differential oxygen sensitivityof HIF alphas. Additionally, novel teleost HIF-1 alpha sequences were produced and used to reveal the molecular evolution of HIF-1 alpha in this lineage rich with hypoxia tolerant species.
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The bedrock of old crystalline cratons is characteristically saturated with brittle structures formed during successive superimposed episodes of deformation and under varying stress regimes. As a result, the crust effectively deforms through the reactivation of pre-existing structures rather than by through the activation, or generation, of new ones, and is said to be in a state of 'structural maturity'. By combining data from Olkiluoto Island, southwestern Finland, which has been investigated as the potential site of a deep geological repository for high-level nuclear waste, with observations from southern Sweden, it can be concluded that the southern part of the Svecofennian shield had already attained structural maturity during the Mesoproterozoic era. This indicates that the phase of activation of the crust, i.e. the time interval during which new fractures were generated, was brief in comparison to the subsequent reactivation phase. Structural maturity of the bedrock was also attained relatively rapidly in Namaqualand, western South Africa, after the formation of first brittle structures during Neoproterozoic time. Subsequent brittle deformation in Namaqualand was controlled by the reactivation of pre-existing strike-slip faults.In such settings, seismic events are likely to occur through reactivation of pre-existing zones that are favourably oriented with respect to prevailing stresses. In Namaqualand, this is shown for present day seismicity by slip tendency analysis, and at Olkiluoto, for a Neoproterozoic earthquake reactivating a Mesoproterozoic fault. By combining detailed field observations with the results of paleostress inversions and relative and absolute time constraints, seven distinctm superimposed paleostress regimes have been recognized in the Olkiluoto region. From oldest to youngest these are: (1) NW-SE to NNW-SSE transpression, which prevailed soon after 1.75 Ga, when the crust had sufficiently cooled down to allow brittle deformation to occur. During this phase conjugate NNW-SSE and NE-SW striking strike-slip faults were active simultaneous with reactivation of SE-dipping low-angle shear zones and foliation planes. This was followed by (2) N-S to NE-SW transpression, which caused partial reactivation of structures formed in the first event; (3) NW-SE extension during the Gothian orogeny and at the time of rapakivi magmatism and intrusion of diabase dikes; (4) NE-SW transtension that occurred between 1.60 and 1.30 Ga and which also formed the NW-SE-trending Satakunta graben located some 20 km north of Olkiluoto. Greisen-type veins also formed during this phase. (5) NE-SW compression that postdates both the formation of the 1.56 Ga rapakivi granites and 1.27 Ga olivine diabases of the region; (6) E-W transpression during the early stages of the Mesoproterozoic Sveconorwegian orogeny and which also predated (7) almost coaxial E-W extension attributed to the collapse of the Sveconorwegian orogeny. The kinematic analysis of fracture systems in crystalline bedrock also provides a robust framework for evaluating fluid-rock interaction in the brittle regime; this is essential in assessment of bedrock integrity for numerous geo-engineering applications, including groundwater management, transient or permanent CO2 storage and site investigations for permanent waste disposal. Investigations at Olkiluoto revealed that fluid flow along fractures is coupled with low normal tractions due to in-situ stresses and thus deviates from the generally accepted critically stressed fracture concept, where fluid flow is concentrated on fractures on the verge of failure. The difference is linked to the shallow conditions of Olkiluoto - due to the low differential stresses inherent at shallow depths, fracture activation and fluid flow is controlled by dilation due to low normal tractions. At deeper settings, however, fluid flow is controlled by fracture criticality caused by large differential stress, which drives shear deformation instead of dilation.