559 resultados para Delineation
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Contractile proteins are encoded by multigene families, most of whose members are differentially expressed in fast- versus slow-twitch myofibers. This fiber-type-specific gene regulation occurs by unknown mechanisms and does not occur within cultured myocytes. We have developed a transient, whole-animal assay using somatic gene transfer to study this phenomenon and have identified a fiber-type-specific regulatory element within the promoter region of a slow myofiber-specific gene. A plasmid-borne luciferase reporter gene fused to various muscle-specific contractile gene promoters was differentially expressed when injected into slow- versus fast-twitch rat muscle: the luciferase gene was preferentially expressed in slow muscle when fused to a slow troponin I promoter, and conversely, was preferentially expressed in fast muscle when fused to a fast troponin C promoter. In contrast, the luciferase gene was equally well expressed by both muscle types when fused to a nonfiber-type-specific skeletal actin promoter. Deletion analysis of the troponin I promoter region revealed that a 157-bp enhancer conferred slow-muscle-preferential activity upon a minimal thymidine kinase promoter. Transgenic analysis confirmed the role of this enhancer in restricting gene expression to slow-twitch myofibers. Hence, somatic gene transfer may be used to rapidly define elements that direct myofiber-type-specific gene expression prior to the generation of transgenic mice.
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This paper presents a new approach to the delineation of local labour markets based on evolutionary computation. The main objective is the regionalisation of a given territory into functional regions based on commuting flows. According to the relevant literature, such regions are defined so that (a) their boundaries are rarely crossed in daily journeys to work, and (b) a high degree of intra-area movement exists. This proposal merges municipalities into functional regions by maximizing a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. Real results are presented based on the latest database from the Census of Population in the Region of Valencia. Comparison between the results obtained through the official method which currently is most widely used (that of British Travel-to-Work Areas) and those from our approach is also presented, showing important improvements in terms of both the number of different market areas identified that meet the statistical criteria and the degree of aggregate intra-market interaction.
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This paper presents a new approach to the delineation of local labor markets based on evolutionary computation. The aim of the exercise is the division of a given territory into functional regions based on travel-to-work flows. Such regions are defined so that a high degree of inter-regional separation and of intra-regional integration in both cases in terms of commuting flows is guaranteed. Additional requirements include the absence of overlap between delineated regions and the exhaustive coverage of the whole territory. The procedure is based on the maximization of a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. In the experimentation stage, two variations of the fitness function are used, and the process is also applied as a final stage for the optimization of the results from one of the most successful existing methods, which are used by the British authorities for the delineation of travel-to-work areas (TTWAs). The empirical exercise is conducted using real data for a sufficiently large territory that is considered to be representative given the density and variety of travel-to-work patterns that it embraces. The paper includes the quantitative comparison with alternative traditional methods, the assessment of the performance of the set of operators which has been specifically designed to handle the regionalization problem and the evaluation of the convergence process. The robustness of the solutions, something crucial in a research and policy-making context, is also discussed in the paper.
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Given a territory composed of basic geographical units, the delineation of local labour market areas (LLMAs) can be seen as a problem in which those units are grouped subject to multiple constraints. In previous research, standard genetic algorithms were not able to find valid solutions, and a specific evolutionary algorithm was developed. The inclusion of multiple ad hoc operators allowed the algorithm to find better solutions than those of a widely-used greedy method. However, the percentage of invalid solutions was still very high. In this paper we improve that evolutionary algorithm through the inclusion of (i) a reparation process, that allows every invalid individual to fulfil the constraints and contribute to the evolution, and (ii) a hillclimbing optimisation procedure for each generated individual by means of an appropriate reassignment of some of its constituent units. We compare the results of both techniques against the previous results and a greedy method.
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The delineation of functional economic areas, or market areas, is a problem of high practical relevance, since the delineation of functional sets such as economic areas in the US, Travel-to-Work Areas in the United Kingdom, and their counterparts in other OECD countries are the basis of many statistical operations and policy making decisions at local level. This is a combinatorial optimisation problem defined as the partition of a given set of indivisible spatial units (covering a territory) into regions characterised by being (a) self-contained and (b) cohesive, in terms of spatial interaction data (flows, relationships). Usually, each region must reach a minimum size and self-containment level, and must be continuous. Although these optimisation problems have been typically solved through greedy methods, a recent strand of the literature in this field has been concerned with the use of evolutionary algorithms with ad hoc operators. Although these algorithms have proved to be successful in improving the results of some of the more widely applied official procedures, they are so time consuming that cannot be applied directly to solve real-world problems. In this paper we propose a new set of group-based mutation operators, featuring general operations over disjoint groups, tailored to ensure that all the constraints are respected during the operation to improve efficiency. A comparative analysis of our results with those from previous approaches shows that the proposed algorithm systematically improves them in terms of both quality and processing time, something of crucial relevance since it allows dealing with most large, real-world problems in reasonable time.
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Federal Highway Administration, Washington, D.C.
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Federal Highway Administration, Washington, D.C.
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Federal Highway Administration, Washington, D.C.
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Federal Highway Administration, Office of Research and Development, Washington, D.C.
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Federal Highway Administration, Office of Research and Development, Washington, D.C.
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Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin
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Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin
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Federal Highway Administration, Washington, D.C.
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Federal Highway Administration, Washington, D.C.