998 resultados para local contractive affine transformations


Relevância:

20.00% 20.00%

Publicador:

Relevância:

20.00% 20.00%

Publicador:

Resumo:

OBJECTIVE: This study was undertaken to investigate how aging affects dermal microvascular reactivity in skin areas differentially exposed to sunlight, and therefore to different degrees of photoaging. METHODS: We assessed, in young (18-30 years, n = 13) and aged males (≥60 years, n = 13), the thigh, forearm, and forehead's skin vasodilatory response to local heating (LTH) with a LDI. In each subject and at each location, local Tskin was brought from 34°C (baseline) to 39 or 41°C for 30 minutes, to effect submaximal vasodilation, with maximal vasodilation then elicited by further heating to 44°C. RESULTS: The CVCs evaluated at baseline and after maximal vasodilation (CVCmax ) were higher in the forehead than in the two other anatomical locations. On all locations, CVCmax decreased with age but less markedly in the forehead compared to the two other locations. When expressed in % of CVCmax , the plateau increase of CVCs in response to submaximal temperatures (39 and 41°C) did not vary with age, and minimally so with location. CONCLUSION: Skin aging, whether intrinsic or combined with photoaging, reduces the maximal vasodilatory capacity of the dermal microcirculation, but not its reactivity to local heating.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Abstract: To understand the processes of evolution, biologists are interested in the ability of a population to respond to natural or artificial selection. The amount of genetic variation is often viewed as the main factor allowing a species to answer to selection. Many theories have thus focused on the maintenance of genetic variability. Ecologists and population geneticists have long-suspected that the structure of the environment is connected to the maintenance of diversity. Theorists have shown that diversity can be permanently and stably maintained in temporal and spatial varying environment in certain conditions. Moreover, varying environments have been also theoretically demonstrated to cause the evolution of divergent life history strategies in the different niches constituting the environment. Although there is a huge number of theoretical studies selection and on life history evolution in heterogeneous environments, there is a clear lack of empirical studies. The purpose of this thesis was to. empirically study the evolutionary consequences of a heterogeneous environment in a freshwater snail Galba truncatula. Indeed, G. truncatula lives in two habitat types according the water availability. First, it can be found in streams or ponds which never completely dry out: a permanent habitat. Second, G. truncatula can be found in pools that freeze during winter and dry during summer: a temporary habitat. Using a common garden approach, we empirically demonstrated local adaptation of G. truncatula to temporary and permanent habitats. We used at first a comparison of molecular (FST) vs. quantitative (QST) genetic differentiation between temporary and permanent habitats. To confirm the pattern QST> FST between habitats suggesting local adaptation, we then tested the desiccation resistance of individuals from temporary and permanent habitats. This study confirmed that drought resistance seemed to be the main factor selected between habitats, and life history traits linked to the desiccation resistance were thus found divergent between habitats. However, despite this evidence of selection acting on mean values of traits between habitats, drift was suggested to be the main factor responsible of variation in variances-covariances between populations. At last, we found life history traits variation of individuals in a heterogeneous environment varying in parasite prevalence. This thesis empirically demonstrated the importance of heterogeneous environments in local adaptation and life history evolution and suggested that more experimental studies are needed to investigate this topic. Résumé: Les biologistes se sont depuis toujours intéressés en l'aptitude d'une population à répondre à la sélection naturelle. Cette réponse dépend de la quantité de variabilité génétique présente dans cette population. Plus particulièrement, les théoriciens se sont penchés sur la question du maintient de la variabilité génétique au sein d'environnements hétérogènes. Ils ont alors démontré que, sous certaines conditions, la diversité génétique peut se maintenir de manière stable et permanente dans des environnements variant au niveau spatial et temporel. De plus, ces environments variables ont été démontrés comme responsable de divergence de traits d'histoire de vie au sein des différentes niches constituant l'environnement. Cependant, malgré ce nombre important d'études théoriques portant sur la sélection et l'évolution des traits d'histoire de vie en environnement hétérogène, les études empiriques sont plus rares. Le but de cette thèse était donc d'étudier les conséquences évolutives d'un environnement hétérogène chez un esgarcot d'eau douce Galba truncatula. En effet, G. truncatula est trouvé dans deux types d'habitats qui diffèrent par leur niveau d'eau. Le premier, l'habitat temporaire, est constitué de flaques d'eau qui peuvent s'assécher pendant l'été et geler pendant l'hiver. Le second, l'habitat permanent, correspond à des marres ou à des ruisseaux qui ont un niveau d'eau constant durant toute l'année. Utilisant une approche expérimentale de type "jardin commun", nous avons démontré l'adaptation locale des individus à leur type d'habitat, permanent ou temporaire. Nous avons utilisé l'approche Fsr/QsT qui compare la différentiation génétique moléculaire avec la différentiation génétique quantitative entre les 2 habitats. Le phénomène d'adapation locale démontré par QsT > FsT, a été testé experimentalement en mesurant la résistance à la dessiccation d'individus d'habitat temporaire et permanent. Cette étude confirma que la résistance à la sécheresse a été sélectionné entre habitats et que les traits responsables de cette resistance sont différents entre habitats. Cependant si la sélection agit sur la valeur moyenne des traits entre habitats, la dérive génétique semble être le responsable majeur de la différence de variances-covariances entre populations. Pour finir, une variation de traits d'histoire de vie a été trouvée au sein d'un environnement hétérogène constitué de populations variants au niveau de leur taux de parasitisme. Pour conclure, cette thèse a donc démontré l'importance d'un environnement hétérogène sur l'adaptation locale et l'évolution des traits d'histoire de vie et suggère que plus d'études empiriques sur le sujet sont nécessaires.

Relevância:

20.00% 20.00%

Publicador: