953 resultados para adaptive algorithm


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Root system architecture is a trait that displays considerable plasticity because of its sensitivity to environmental stimuli. Nevertheless, to a significant degree it is genetically constrained as suggested by surveys of its natural genetic variation. A few regulators of root system architecture have been isolated as quantitative trait loci through the natural variation approach in the dicotyledon model, Arabidopsis. This provides proof of principle that allelic variation for root system architecture traits exists, is genetically tractable, and might be exploited for crop breeding. Beyond Arabidopsis, Brachypodium could serve as both a credible and experimentally accessible model for root system architecture variation in monocotyledons, as suggested by first glimpses of the different root morphologies of Brachypodium accessions. Whether a direct knowledge transfer gained from molecular model system studies will work in practice remains unclear however, because of a lack of comprehensive understanding of root system physiology in the native context. For instance, apart from a few notable exceptions, the adaptive value of genetic variation in root system modulators is unknown. Future studies should thus aim at comprehensive characterization of the role of genetic players in root system architecture variation by taking into account the native environmental conditions, in particular soil characteristics.

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This paper presents a first approach of Evaluation Engine Architecture (EEA) as proposal to support adaptive integral assessment, in the context of a virtual learning environment. The goal of our research is design an evaluation engine tool to assist in the whole assessment process within the A2UN@ project, linking that tool with the other key elements of a learning design (learning task, learning resources and learning support). The teachers would define the relation between knowledge, competencies, activities, resources and type of assessment. Providing this relation is possible obtain more accurate estimations of student's knowledge for adaptive evaluations and future recommendations. The process is supported by usage of educational standards and specifications and for an integral user modelling

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In this paper, we are proposing a methodology to determine the most efficient and least costly way of crew pairing optimization. We are developing a methodology based on algorithm optimization on Eclipse opensource IDE using the Java programming language to solve the crew scheduling problems.

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Gene duplication and neofunctionalization are known to be important processes in the evolution of phenotypic complexity. They account for important evolutionary novelties that confer ecological adaptation, such as the major histocompatibility complex (MHC), a multigene family crucial to the vertebrate immune system. In birds, two MHC class II β (MHCIIβ) exon 3 lineages have been recently characterized, and two hypotheses for the evolutionary history of MHCIIβ lineages were proposed. These lineages could have arisen either by 1) an ancient duplication and subsequent divergence of one paralog or by 2) recent parallel duplications followed by functional convergence. Here, we compiled a data set consisting of 63 MHCIIβ exon 3 sequences from six avian orders to distinguish between these hypotheses and to understand the role of selection in the divergent evolution of the two avian MHCIIβ lineages. Based on phylogenetic reconstructions and simulations, we show that a unique duplication event preceding the major avian radiations gave rise to two ancestral MHCIIβ lineages that were each likely lost once later during avian evolution. Maximum likelihood estimation shows that following the ancestral duplication, positive selection drove a radical shift from basic to acidic amino acid composition of a protein domain facing the α-chain in the MHCII α β-heterodimer. Structural analyses of the MHCII α β-heterodimer highlight that three of these residues are potentially involved in direct interactions with the α-chain, suggesting that the shift following duplication may have been accompanied by coevolution of the interacting α- and β-chains. These results provide new insights into the long-term evolutionary relationships among avian MHC genes and open interesting perspectives for comparative and population genomic studies of avian MHC evolution.

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ABSTRACT: Ultramarathons comprise any sporting event involving running longer than the traditional marathon length of 42.195 km (26.2 miles). Studies on ultramarathon participants can investigate the acute consequences of ultra-endurance exercise on inflammation and cardiovascular or renal consequences, as well as endocrine/energetic aspects, and examine the tissue recovery process over several days of extreme physical load. In a study published in BMC Medicine, Schütz et al. followed 44 ultramarathon runners over 4,487 km from South Italy to North Cape, Norway (the Trans Europe Foot Race 2009) and recorded daily sets of data from magnetic resonance imaging, psychometric, body composition and biological measurements. The findings will allow us to better understand the timecourse of degeneration/regeneration of some lower leg tissues such as knee joint cartilage, to differentiate running-induced from age-induced pathologies (for example, retropatelar arthritis) and finally to assess the interindividual susceptibility to injuries. Moreover, it will also provide new information about the complex interplay between cerebral adaptations/alterations and hormonal influences resulting from endurance exercise and provide data on the dose-response relationship between exercise and brain structure/function. Overall, this study represents a unique attempt to investigate the limits of the adaptive response of human bodies.Please see related article: http://www.biomedcentral.com/1741-7015/10/78.

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In vivo dosimetry is a way to verify the radiation dose delivered to the patient in measuring the dose generally during the first fraction of the treatment. It is the only dose delivery control based on a measurement performed during the treatment. In today's radiotherapy practice, the dose delivered to the patient is planned using 3D dose calculation algorithms and volumetric images representing the patient. Due to the high accuracy and precision necessary in radiation treatments, national and international organisations like ICRU and AAPM recommend the use of in vivo dosimetry. It is also mandatory in some countries like France. Various in vivo dosimetry methods have been developed during the past years. These methods are point-, line-, plane- or 3D dose controls. A 3D in vivo dosimetry provides the most information about the dose delivered to the patient, with respect to ID and 2D methods. However, to our knowledge, it is generally not routinely applied to patient treatments yet. The aim of this PhD thesis was to determine whether it is possible to reconstruct the 3D delivered dose using transmitted beam measurements in the context of narrow beams. An iterative dose reconstruction method has been described and implemented. The iterative algorithm includes a simple 3D dose calculation algorithm based on the convolution/superposition principle. The methodology was applied to narrow beams produced by a conventional 6 MV linac. The transmitted dose was measured using an array of ion chambers, as to simulate the linear nature of a tomotherapy detector. We showed that the iterative algorithm converges quickly and reconstructs the dose within a good agreement (at least 3% / 3 mm locally), which is inside the 5% recommended by the ICRU. Moreover it was demonstrated on phantom measurements that the proposed method allows us detecting some set-up errors and interfraction geometry modifications. We also have discussed the limitations of the 3D dose reconstruction for dose delivery error detection. Afterwards, stability tests of the tomotherapy MVCT built-in onboard detector was performed in order to evaluate if such a detector is suitable for 3D in-vivo dosimetry. The detector showed stability on short and long terms comparable to other imaging devices as the EPIDs, also used for in vivo dosimetry. Subsequently, a methodology for the dose reconstruction using the tomotherapy MVCT detector is proposed in the context of static irradiations. This manuscript is composed of two articles and a script providing further information related to this work. In the latter, the first chapter introduces the state-of-the-art of in vivo dosimetry and adaptive radiotherapy, and explains why we are interested in performing 3D dose reconstructions. In chapter 2 a dose calculation algorithm implemented for this work is reviewed with a detailed description of the physical parameters needed for calculating 3D absorbed dose distributions. The tomotherapy MVCT detector used for transit measurements and its characteristics are described in chapter 3. Chapter 4 contains a first article entitled '3D dose reconstruction for narrow beams using ion chamber array measurements', which describes the dose reconstruction method and presents tests of the methodology on phantoms irradiated with 6 MV narrow photon beams. Chapter 5 contains a second article 'Stability of the Helical TomoTherapy HiArt II detector for treatment beam irradiations. A dose reconstruction process specific to the use of the tomotherapy MVCT detector is presented in chapter 6. A discussion and perspectives of the PhD thesis are presented in chapter 7, followed by a conclusion in chapter 8. The tomotherapy treatment device is described in appendix 1 and an overview of 3D conformai- and intensity modulated radiotherapy is presented in appendix 2. - La dosimétrie in vivo est une technique utilisée pour vérifier la dose délivrée au patient en faisant une mesure, généralement pendant la première séance du traitement. Il s'agit de la seule technique de contrôle de la dose délivrée basée sur une mesure réalisée durant l'irradiation du patient. La dose au patient est calculée au moyen d'algorithmes 3D utilisant des images volumétriques du patient. En raison de la haute précision nécessaire lors des traitements de radiothérapie, des organismes nationaux et internationaux tels que l'ICRU et l'AAPM recommandent l'utilisation de la dosimétrie in vivo, qui est devenue obligatoire dans certains pays dont la France. Diverses méthodes de dosimétrie in vivo existent. Elles peuvent être classées en dosimétrie ponctuelle, planaire ou tridimensionnelle. La dosimétrie 3D est celle qui fournit le plus d'information sur la dose délivrée. Cependant, à notre connaissance, elle n'est généralement pas appliquée dans la routine clinique. Le but de cette recherche était de déterminer s'il est possible de reconstruire la dose 3D délivrée en se basant sur des mesures de la dose transmise, dans le contexte des faisceaux étroits. Une méthode itérative de reconstruction de la dose a été décrite et implémentée. L'algorithme itératif contient un algorithme simple basé sur le principe de convolution/superposition pour le calcul de la dose. La dose transmise a été mesurée à l'aide d'une série de chambres à ionisations alignées afin de simuler la nature linéaire du détecteur de la tomothérapie. Nous avons montré que l'algorithme itératif converge rapidement et qu'il permet de reconstruire la dose délivrée avec une bonne précision (au moins 3 % localement / 3 mm). De plus, nous avons démontré que cette méthode permet de détecter certaines erreurs de positionnement du patient, ainsi que des modifications géométriques qui peuvent subvenir entre les séances de traitement. Nous avons discuté les limites de cette méthode pour la détection de certaines erreurs d'irradiation. Par la suite, des tests de stabilité du détecteur MVCT intégré à la tomothérapie ont été effectués, dans le but de déterminer si ce dernier peut être utilisé pour la dosimétrie in vivo. Ce détecteur a démontré une stabilité à court et à long terme comparable à d'autres détecteurs tels que les EPIDs également utilisés pour l'imagerie et la dosimétrie in vivo. Pour finir, une adaptation de la méthode de reconstruction de la dose a été proposée afin de pouvoir l'implémenter sur une installation de tomothérapie. Ce manuscrit est composé de deux articles et d'un script contenant des informations supplémentaires sur ce travail. Dans ce dernier, le premier chapitre introduit l'état de l'art de la dosimétrie in vivo et de la radiothérapie adaptative, et explique pourquoi nous nous intéressons à la reconstruction 3D de la dose délivrée. Dans le chapitre 2, l'algorithme 3D de calcul de dose implémenté pour ce travail est décrit, ainsi que les paramètres physiques principaux nécessaires pour le calcul de dose. Les caractéristiques du détecteur MVCT de la tomothérapie utilisé pour les mesures de transit sont décrites dans le chapitre 3. Le chapitre 4 contient un premier article intitulé '3D dose reconstruction for narrow beams using ion chamber array measurements', qui décrit la méthode de reconstruction et présente des tests de la méthodologie sur des fantômes irradiés avec des faisceaux étroits. Le chapitre 5 contient un second article intitulé 'Stability of the Helical TomoTherapy HiArt II detector for treatment beam irradiations'. Un procédé de reconstruction de la dose spécifique pour l'utilisation du détecteur MVCT de la tomothérapie est présenté au chapitre 6. Une discussion et les perspectives de la thèse de doctorat sont présentées au chapitre 7, suivies par une conclusion au chapitre 8. Le concept de la tomothérapie est exposé dans l'annexe 1. Pour finir, la radiothérapie «informationnelle 3D et la radiothérapie par modulation d'intensité sont présentées dans l'annexe 2.

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Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

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To date, state-of-the-art seismic material parameter estimates from multi-component sea-bed seismic data are based on the assumption that the sea-bed consists of a fully elastic half-space. In reality, however, the shallow sea-bed generally consists of soft, unconsolidated sediments that are characterized by strong to very strong seismic attenuation. To explore the potential implications, we apply a state-of-the-art elastic decomposition algorithm to synthetic data for a range of canonical sea-bed models consisting of a viscoelastic half-space of varying attenuation. We find that in the presence of strong seismic attenuation, as quantified by Q-values of 10 or less, significant errors arise in the conventional elastic estimation of seismic properties. Tests on synthetic data indicate that these errors can be largely avoided by accounting for the inherent attenuation of the seafloor when estimating the seismic parameters. This can be achieved by replacing the real-valued expressions for the elastic moduli in the governing equations in the parameter estimation by their complex-valued viscoelastic equivalents. The practical application of our parameter procedure yields realistic estimates of the elastic seismic material properties of the shallow sea-bed, while the corresponding Q-estimates seem to be biased towards too low values, particularly for S-waves. Given that the estimation of inelastic material parameters is notoriously difficult, particularly in the immediate vicinity of the sea-bed, this is expected to be of interest and importance for civil and ocean engineering purposes.

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A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

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We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

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From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

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Genome-wide scans of genetic differentiation between hybridizing taxa can identify genome regions with unusual rates of introgression. Regions of high differentiation might represent barriers to gene flow, while regions of low differentiation might indicate adaptive introgression-the spread of selectively beneficial alleles between reproductively isolated genetic backgrounds. Here we conduct a scan for unusual patterns of differentiation in a mosaic hybrid zone between two mussel species, Mytilus edulis and M. galloprovincialis. One outlying locus, mac-1, showed a characteristic footprint of local introgression, with abnormally high frequency of edulis-derived alleles in a patch of M. galloprovincialis enclosed within the mosaic zone, but low frequencies outside of the zone. Further analysis of DNA sequences showed that almost all of the edulis allelic diversity had introgressed into the M. galloprovincialis background in this patch. We then used a variety of approaches to test the hypothesis that there had been adaptive introgression at mac-1. Simulations and model fitting with maximum-likelihood and approximate Bayesian computation approaches suggested that adaptive introgression could generate a "soft sweep," which was qualitatively consistent with our data. Although the migration rate required was high, it was compatible with the functioning of an effective barrier to gene flow as revealed by demographic inferences. As such, adaptive introgression could explain both the reduced intraspecific differentiation around mac-1 and the high diversity of introgressed alleles, although a localized change in barrier strength may also be invoked. Together, our results emphasize the need to account for the complex history of secondary contacts in interpreting outlier loci.

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1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole (Microtus arvalis) as study organism, we tested how exposure to flea parasitism during the juvenile stage affects the physiology (haematocrit, resistance to oxidative stress, resting metabolism, spleen mass, and testosterone), morphology (body mass, testis mass) and motor performance (open field activity and swimming speed) of the same individuals when infested with fleas in adulthood. According to the 'predictive adaptive response' hypothesis, we predicted that voles parasitized at the adult stage would perform better if they had already been parasitized with fleas at the juvenile stage. 3. We found that voles exposed to fleas in adulthood had a higher metabolic rate if already exposed to fleas when juvenile, compared to voles free of fleas when juvenile and voles free of fleas in adulthood. Independently of juvenile parasitism, adult parasitism impaired adult haematocrit and motor performances. Independently of adult parasitism, juvenile parasitism slowed down crawling speed in adult female voles. 4. Our results suggest that juvenile parasitism has long-term effects that do not protect from the detrimental effects of adult parasitism. On the contrary, experiencing parasitism in early-life incurs additional costs upon adult parasitism measured in terms of higher energy expenditure, rather than inducing an adaptive shift in the developmental trajectory. 5. Hence, our study provides experimental evidence for long term costs of parasitism. We found no support for a predictive adaptive response in this host-parasite system.

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We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid (whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then the problem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

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To compete over limited parental resources, young animals communicate with their parents and siblings by producing honest vocal signals of need. Components of begging calls that are sensitive to food deprivation may honestly signal need, whereas other components may be associated with individual-specific attributes that do not change with time such as identity, sex, absolute age and hierarchy. In a sib-sib communication system where barn owl (Tyto alba) nestlings vocally negotiate priority access to food resources, we show that calls have individual signatures that are used by nestlings to recognize which siblings are motivated to compete, even if most vocalization features vary with hunger level. Nestlings were more identifiable when food-deprived than food-satiated, suggesting that vocal identity is emphasized when the benefit of winning a vocal contest is higher. In broods where siblings interact iteratively, we speculate that individual-specific signature permits siblings to verify that the most vocal individual in the absence of parents is the one that indeed perceived the food brought by parents. Individual recognition may also allow nestlings to associate identity with individual-specific characteristics such as position in the within-brood dominance hierarchy. Calls indeed revealed age hierarchy and to a lower extent sex and absolute age. Using a cross-fostering experimental design, we show that most acoustic features were related to the nest of origin (but not the nest of rearing), suggesting a genetic or an early developmental effect on the ontogeny of vocal signatures. To conclude, our study suggests that sibling competition has promoted the evolution of vocal behaviours that signal not only hunger level but also intrinsic individual characteristics such as identity, family, sex and age.