Biomechanical behavior and histological organization of the three-layered passive esophagus as a function of topography

The zero-stress state of the mucosa-submucosa and two muscle esophageal layers has been delineated, but their multi-axial response has not, because muscle dissection may not leave tubular specimens intact for inflation/extension testing. The histomechanical behavior of the three-layered porcine esophagus was investigated in this study, through light microscopic examination and uniaxial tension, with two-dimensional strain measurement in pairs of orthogonally oriented specimens. The two-dimensional Fung-type strain-energy function described suitably the pseudo-elastic tissue response, affording faithful simulations to our data. Differences in the scleroprotein content and configuration were identified as a function of layer, topography, and orientation, substantiating the macromechanical differences found. In view of the failure and optimized material parameters, the mucosa-submucosa was stronger and stiffer than muscle, associating it with a higher collagen content. A notable topographical distribution was apparent, with data for the abdominal region differentiated from that for the cervical region, owing to the existence of inner muscle with a circumferential arrangement and of outer muscle with a longitudinal arrangement in the former region, and of both muscle layers with oblique arrangement in the latter region, with thoracic esophagus being a transition zone. Tissue from the mucosa-submucosa was stronger and stiffer longitudinally, relating with a preferential collagen reinforcement along that axis, but more extensible in the orthogonal axis.     

On exploiting static and dynamically mined metadata for exploratory web searching

Most Web Search Engines (WSEs) are appropriate for focalized search, i.e., they make the assumption that users can accurately describe their information need using a small sequence of terms. However, as several user studies have shown, a high percentage of search tasks are exploratory, and focalized search very commonly leads to inadequate interactions and poor results. This paper proposes exploiting static and dynamically mined metadata for enriching web searching with exploration services. Online results clustering, which is a mining task of dynamic nature since it is based on query-dependent snippets, is useful for providing users with overviews of the top results and thus allowing them to restrict their focus to the desired parts. On the other hand, the various static metadata that are available to a search engine (e.g., domain, language, date, and filetype) are commonly exploited only through the advanced (form-based) search facilities that some WSEs offer (and users rarely use). We propose an approach that combines both kinds of metadata by adopting the interaction paradigm of dynamic taxonomies and faceted exploration, which allows the users to restrict their focus gradually using both static and dynamically derived metadata. Special focus is given on the design and analysis of incremental algorithms for speeding up the exploration process. The experimental evaluation over a real WSE shows that this combination results to an effective, flexible, and efficient exploration experience. Finally, we report the results of a user study indicating that this direction is promising in terms of user preference, satisfaction, and effort.     

Direction relations and two-dimensional range queries: optimisation techniques

This paper defines direction relations (e.g., north, northeast) between two-dimensional objects and shows how they can be efficiently retrieved using B-, KDB- and R- tree-based data structures. Essentially, our work studies optimisation techniques for 2D range queries that arise during the processing of direction relations. We test the efficiency of alternative indexing methods through extensive experimentation and present analytical models that estimate their performance. The analytical estimates are shown to be very close to the actual results and can be used by spatial query optimizers in order to predict the retrieval cost. In addition, we implement modifications of the existing structures that yield better performance for certain queries. We conclude the paper by discussing the most suitable method depending on the type of the range and the properties of the data.     

PoweRGen: A power-law based generator of RDFS schemas

As the amount of RDF datasets available on the Web has grown significantly over the last years, scalability and performance of Semantic Web (SW) systems are gaining importance. Current RDF benchmarking efforts either consider schema-less RDF datasets or rely on fixed RDFS schemas. In this paper, we present the first RDFS schema generator, termed PoweRGen, which takes into account the features exhibited by real SW schemas. It considers the power-law functions involved in (a) the combined in- and out-degree distribution of the property graph (which captures the domains and ranges of the properties defined in a schema) and (b) the out-degree distribution of the transitive closure (TC) of the subsumption graph (which essentially captures the class hierarchy). The synthetic schemas generated by PoweRGen respect the power-law functions given as input with an accuracy ranging between 89 and 96%, as well as, various morphological characteristics regarding the subsumption hierarchy depth, structure, etc.     

Multiple Phase Neighborhood Search-GRASP for the Capacitated Vehicle Routing Problem

Greedy Randomized Adaptive Search Procedure (GRASP) has been proved to be a very efficient algorithm for the solution of the Traveling Salesman Problem. Also, it has been proved that expanding the local search with the use of two or more different local search strategies helps the algorithm to avoid trapping in a local optimum. In this paper, a new modified version of GRASP, called Multiple Phase Neighborhood Search-GRASP (MPNS-GRASP), for the solution of the Vehicle Routing Problem is proposed. In this method, a stopping criterion based on Lagrangean Relaxation and Subgradient Optimization is utilized. In addition, a different way for expanding the neighborhood search is used based on a new strategy, the Circle Restricted Local Search Moves strategy. The algorithm was tested on two sets of benchmark instances and gave very satisfactory results. In both sets of instances the results have solution qualities with average values near to the optimum values and in a number of them the algorithm finds the optimum. The computational time of the algorithm is decreased significantly compared to other heuristic and metaheuristic algorithms due to the fact that the new strategy, the Expanding Neighborhood Search Strategy, is used.     

Star-like auto-configurable layouts of variable radius for visualizing and exploring RDF/S ontologies

The visualization of ontologies is a challenging task especially if they are large. In this paper we propose a visualization approach which is based on star-like graphs of variable radius which enables users to gradually explore and navigate through the entire ontology without overloading them. The star-like graphs are visualized using a Force Directed Placement algorithm (FDP) specially suited for RDF schemas whose configuration parameters can be adjusted interactively by the end-user via an intuitive on-screen tool bar. In addition, and since each star-like graph exhibits different graph features, we propose a novel automatic configuration method for the FDP algorithm parameters that is based on a number of quality metrics (area density and verticality of subclass hierarchies) and corresponding corrective actions. The experimental evaluation showed the quality of the yielded layout is significantly improved and the proposed approach is acceptably fast for real-time exploration. The user study showed that users prefer these views and perform various very common tasks faster.