Influence of external factors in resistance of Corynebacterium urealyticum to antimicrobial agents

Corynebacterium urealyticum is usually resistant to multiple antibiotics. We analyzed whether previous hospitalization and/or the use of antibiotics was a factor associated with the appearance of resistance to different antibiotics in C. urealyticum. Our findings suggest that resistant strains of C. urealyticum are likely to be acquired directly from the hospital environment and that the use of antibiotics in the hospital setting could favor the appearance of multiresistant strains.     

A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams

This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings.     

Segmentation of the carotid intima-media region in B-mode ultrasound images

This paper proposes a new approach for the segmentation of both near-end and far-end intima-media regions of the common carotid artery in ultrasound images. The method requires minimal user interaction and is able to segment the near-end wall in arteries with large, hypoechogenic and irregular plaques, issues usually not considered previously due to the increased segmentation difficulty.     

A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands

The multi-compartment vehicle routing problem (MC-VRP) consists of designing transportation routes to satisfy the demands of a set of customers for several products that, because of incompatibility constraints, must be loaded in independent vehicle compartments. Despite its wide practical applicability the MC-VRP has not received much attention in the literature, and the few existing methods assume perfect knowledge of the customer demands, regardless of their stochastic nature. This paper extends the MC-VRP by introducing uncertainty on what it is known as the MC-VRP with stochastic demands (MC-VRPSD). The MC-VRPSD is modeled as a stochastic program with recourse and solved by means of a memetic algorithm. The proposed memetic algorithm couples genetic operators and local search procedures proven to be effective on deterministic routing problems with a novel individual evaluation and reparation strategy that accounts for the stochastic nature of the problem. The algorithm was tested on instances of up to 484 customers, and its results were compared to those obtained by a savings-based heuristic and a memetic algorithm (MA/SCS) for the MC-VRP that uses a spare capacity strategy to handle demand fluctuations. In addition to effectively solve the MC-VRPSD, the proposed MA/SCS also improved 14 best known solutions in a 40-problem testbed for the MC-VRP.     

A methodology for the generation of planar models for multibody chain drives

To overcome the difficulty on building manually complex models of chain drives, this work proposes a comprehensive methodology to build multibody models of any general chain drive automatically from a minimal set of data. The proposed procedure also evaluates the initial positions and velocities of all components of the drive that are consistent with the kinematic joints or with the contact pairs used in the model. In this methodology, all links and sprockets are represented by rigid bodies connected to each other either by ideal or by clearance revolute joints. The clearance revolute joint contact is further extended to handle the contact between the chain rollers and the sprocket teeth exact profiles. A suitable cylindrical continuous contact law is applied to describe the interaction on all contact pairs. One of the complexities of the computational study of roller chain drives is the large number of bodies in the system and the dynamics of the successive engagement and disengagement of the rollers with the sprockets. Each time a roller engages or disengages with a sprocket tooth, the number of rigid bodies in contact changes. The search for the contact pairs is recognized as one of the most time consuming task in contact analysis. This work proposes a procedure to specify the contact pairs and their update during the dynamic analysis optimizing the computational efficiency of the contact search. The methodologies adopted result in a general computer program that is applied and demonstrated in a generic chain drive that can be used in industrial machines, vehicle engines or any other type of mechanical system.     

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

Nowadays, the patients and physicians use the health-related websites as an important information source and, therefore, it is critical the quality evaluation of health- related websites. The quality assessment of health-related websites becomes especially relevant because their use imply the existence of a wide range of threats which can affect people’s health. Additionally, website quality evaluation can also contribute to maximize the exploitation of invested resources by organizations in the development of user-perceived quality websites. But there is not yet a clear and unambiguous definition of the concept of website quality and the debate about quality evaluation on the Web remains open. In this paper, we present a qualitative and user-oriented methodology for assessing quality of health-related websites based on a 2-tuple fuzzy linguistic approach. To identify the quality criteria set, a qualitative research has been carried out using the focus groups technique. The measurement method generates linguistic quality assessments considering the visitors’ judgements with respect to those quality criteria. The combination of the linguistic judgements is implemented without a loss of information by applying a 2-tuple linguistic weighted average operator. This methodology means an improvement on quality evaluation of health websites through the commitment to put users first.     

nSPARQL: A navigational language for RDF

Navigational features have been largely recognized as fundamental for graph database query languages. This fact has motivated several authors to propose RDF query languages with navigational capabilities. In this paper, we propose the query language nSPARQL that uses nested regular expressions to navigate RDF data. We study some of the fundamental properties of nSPARQL and nested regular expressions concerning expressiveness and complexity of evaluation. Regarding expressiveness, we show that nSPARQL is expressive enough to answer queries considering the semantics of the RDFS vocabulary by directly traversing the input graph. We also show that nesting is necessary in nSPARQL to obtain this last result, and we study the expressiveness of the combination of nested regular expressions and SPARQL operators. Regarding complexity of evaluation, we prove that given an RDF graph G and a nested regular expression E, this problem can be solved in time O(|G||E|).     

EXAM: a comprehensive environment for the analysis of access control policies

Policy integration and inter-operation is often a crucial requirement when parties with different access control policies need to participate in collaborative applications and coalitions. Such requirement is even more difficult to address for dynamic large-scale collaborations, in which the number of access control policies to analyze and compare can be quite large. An important step in policy integration and inter-operation is to analyze the similarity of policies. Policy similarity can sometimes also be a pre-condition for establishing a collaboration, in that a party may enter a collaboration with another party only if the policies enforced by the other party match or are very close to its own policies. Existing approaches to the problem of analyzing and comparing access control policies are very limited, in that they only deal with some special cases. By recognizing that a suitable approach to the policy analysis and comparison requires combining different approaches, we propose in this paper a comprehensive environment—EXAM. The environment supports various types of analysis query, which we categorize in the paper. A key component of such environment, on which we focus in the paper, is the policy analyzer able to perform several types of analysis. Specifically, our policy analyzer combines the advantages of existing MTBDD-based and SAT-solver-based techniques. Our experimental results, also reported in the paper, demonstrate the efficiency of our analyzer.     

An haptic-based immersive environment for shape analysis and modelling

Currently, the design of aesthetic products is a process that requires a set of activities where digital models and physical mockups play a key role. Typically, these are modified (and built) several times before reaching the desired design, increasing the development time and, consequently, the final product cost. In this paper, we present an innovative design environment for computer-aided design (CAD) surface analysis. Our system relies on a direct visuo-haptic display system, which enables users to visualize models using a stereoscopic view, and allows the evaluation of sectional curves using touch. Profile curves are rendered using an haptic device that deforms a plastic strip, thanks to a set of actuators, to reproduce the curvature of the shape co-located with the virtual model. By touching the strip, users are able to evaluate shape characteristics, such as curvature or discontinuities (rendered using sound), and to assess the surface quality. We believe that future computer-aided systems (CAS)/CAD systems based on our approach will contribute in improving the design process at industrial level. Moreover, these will allow companies to reduce the product development time by reducing the number of physical mockups necessary for the product design evaluation and by increasing the quality of the final product, allowing a wider exploration and comparative evaluation of alternatives in the given time.     

Global and robust formation-shape stabilization of relative sensing networks

This paper proposes a simple, distributed algorithm that achieves global stabilization of formations for relative sensing networks in arbitrary dimensions with fixed topology. Assuming the network runs an initialization procedure to equally orient all agent reference frames, convergence to the desired formation shape is guaranteed even in partially asynchronous settings. We characterize the algorithm robustness against several sources of errors: link failures, measurement errors, and frame initialization errors. The technical approach combines algebraic graph theory, multidimensional scaling, and distributed linear iterations.