5-hydroxytryptamine 3-receptor antagonist modulates gallbladder emptying and motilin release induced by erythromycin

In the present study we evaluated the effect of ondansetron (formerly indicated as GR38032F), a potent and selective type-3 5-hydroxytryptamine receptor antagonist, on erythromycin-induced gallbladder emptying and motilin release, as well as gallbladder emptying induced by a regular meal in healthy volunteers. Gallbladder emptying was evaluated by sonography. Ondansetron, at the dose of 0.05 mg/kg, significantly reduced (P < 0.001 by ANOVA) the gallbladder emptying induced by 2 mg/kg/hr erythromycin, but did not increase basal gallbladder volume or inhibit gallbladder emptying induced by a regular meal. Ondansetron also inhibited the motilin release induced by erythromycin (P < 0.001, by ANOVA). These results suggest that serotoninergic mechanisms modulate the effects of erythromycin on the gastrointestinal tract. The exact site of action of ondansetron remains to be identified.     

Automatic Control Valve–Induced Transients in Operative Pipe System

In most cases, the final configuration of complex pipe networks is attained simply by connecting subsystems initially designed to work separately. Thus, automatic control valves (ACV) are often installed in the confluence nodes where the subsystems meet. The present paper deals with the response and hydraulic behavior of ACVs, topics on which data are scarce. More precisely, attention is focused on transients, which occur in a water-distribution pipe system in operation due to the action of an ACV, both from an experimental and numerical point of view. The aim of the water-hammer field tests is to enlarge the amount of the experimental data concerning unsteady-state flow processes in operating pipe systems. The numerical model extends to field conditions and ACVs laboratory work on the hydraulic characterization of valves and the unsteady-state friction simulation.     

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline.     

Fatigue-crack advance mechanisms in polymers

The room-temperature fatigue-crack propagation behaviour of poly(butylene terephthalate) is strongly influenced by hysteretic heating near the crack tip since the glass transition temperature is just above room temperature. At low frequencies or stress intensities, the crack tip damage zone consists of several layers of crazes. At high frequencies or stress intensities, hysteretic heating causes a drop in yield stress and a large increase in the depth of the crack tip damage layer. At the same time, the increase in the plane stress plastic zones near the free surfaces produces large shear lips which flank the interior craze zone. This transformation results in a crack growth rate transition which appears as a crack deceleration followed by rapid crack acceleration. This thermal transition can be suppressed or delayed by immersion in water or silicone oil to reduce heat build-up in the sample during testing.     

Cloud broker proposal based on multicriteria decision-making and virtual infrastructure migration

The adoption of infrastructure as a Service (IaaS) is a reality for academic, industrial, and governmental institutions. Cloud tenants request dynamically provisioned virtual infrastructures (VIs) tailored to their application requirements, detailing not only the virtual compute/storage resources but also the network components, topology, and services. The creation of a large number of cloud providers came along with the widespread use of VIs. The selection of an appropriate provider is a challenging task due to the diversity of the IaaS market and formally is a multicriteria analysis (NP-hard). Notwithstanding the provider selection complexity, the mobility of VI-hosted applications is limited due to the optimization anchors introduced by providers. Although the existing IaaS cloud brokers can indicate a hosting provider, they lack on conceptual and technical skills to migrate a VI and all its internal components between providers. This work enhances the state-of-the-art on IaaS cloud brokerage by proposing virtual infrastructure multicriteria allocation and migration–based broker (VIMAM), which performs a multicriteria analysis of providers and VI migration. VIMAM is driven by an analytic hierarchy process (AHP) to select an IaaS provider, offering a set of predefined weighting schemas to represent distinct tenant perspectives. Moreover, to migrate a VI, VIMAM takes into account the virtual machines, containers, switches, and other topology elements. In addition to discussing the AHP ranking weights and frequency of providers selection, the experimental analysis details the implementation of an OpenStack and Docker–based prototype for VI migration.     

On discrete models and immunological algorithms for protein structure prediction

Discrete models for protein structure prediction embed the protein amino acid sequence into a discrete spatial structure, usually a lattice, where an optimal tertiary structure is predicted on the basis of simple assumptions relating to the hydrophobic–hydrophilic character of amino acids in the sequence and to relevant interactions for free energy minimization. While the prediction problem is known to be NP complete even in the simple setting of Dill’s model with a 2D-lattice, a variety of bio-inspired algorithms for this problem have been proposed in the literature. Immunological algorithms are inspired by the kind of optimization that immune systems perform when identifying and promoting the replication of the most effective antibodies against given antigens. A quick, state-of-the-art survey of discrete models and immunological algorithms for protein structure prediction is presented in this paper, and the main design and performance features of an immunological algorithm for this problem are illustrated in a tutorial fashion.     

Interpretability in symbolic regression: a benchmark of explanatory methods using the Feynman data set

Genetic Programming and Evolvable Machines - In some situations, the interpretability of the machine learning models plays a role as important as the model accuracy. Interpretability comes from the...     

Development and application of an in vitro methodology to determine the transit tolerance of potentially probiotic Lactobacillus and Bifidobacterium species in the upper human gastrointestinal tract

An in vitro methodology which mimics in vivo human upper gastrointestinal transit was developed. The transit tolerance of potentially probiotic Lactobacillus and Bifidobacterium species was determined by exposing washed cell suspensions at 37 degrees C to a simulated gastric juice (pH 2.0), containing pepsin (0.3% w/v) and sodium chloride (0.5% w/v), and a simulated small intestinal juice (pH 8.0), containing pancreatin USP (1 g l-1) and sodium chloride (5 g l-1), and monitoring changes in total viable count periodically. The methodology was also employed to determine the effect of adding milk proteins (1 g l-1), hog gastric mucin (1 g l-1) and soyabean trypsinchymotrypsin inhibitor [SBTCI] (1 g l-1) on transit tolerance. The majority (14 of 15) of isolates lost > 90% viability during simulated gastric transit. Only one isolate, Lactobacillus fermentum KLD, was considered intrinsically resistant. The addition of milk proteins, singly and in combination, generally improved gastric transit tolerance. In this regard, two isolates, Lact. casei 212.3 and Bifidobacterium infantis 25962, exhibited 100% gastric transit tolerance in the presence of milk proteins. In general, the addition of hog gastric mucin did not influence simulated gastric transit tolerance of lactobacilli but tended to increase that of bifidobacteria. However, it increased that of Lact. casei 242 and Lact. salivarius 43338 but diminished that of B. bifidum 2715 and B. animalis Bo. Selected bile salts-resistant isolates were intrinsically tolerant to simulated small intestinal transit. Only Lact. casei F19 and B. adolescentis 15703T showed significant reduction in viability after 240 min. In general, the addition of milk proteins and SBTCI did not affect simulated small intestinal transit tolerance. However, they significantly improved the intrinsic resistance of Lact. casei F19 but diminished that of B. breve 15700T. It is concluded that, whereas the majority of bile salts-resistant lactobacilli and bifidobacteria may be intrinsically sensitive to gastric transit, they are intrinsically resistant to small intestinal transit. In addition, it is postulated that milk proteins and mucin may function as both buffering agents and inhibitors of digestive protease activity in vivo, thereby protecting ingested bacterial strains during upper gastrointestinal transit.     

ChangeLedge: Change design and planning in networked systems based on reuse of knowledge and automation

Proper management of Information Technology (IT) resources and services has become imperative for the success of modern organizations. The IT Infrastructure Library (ITIL) represents, in this context, the most widely accepted framework to help achieve this end. Among the processes that compose ITIL, change management has an important role in defining best practices and processes for the efficient and prompt handling of IT changes. In practice, however, such changes are usually described and documented in an ad hoc fashion, due to the lack of proper support to assist the design process. This hampers knowledge acquired when specifying, planning, and carrying out previous changes to be reused in subsequent requests, even though such reuse may result in fewer incidents and faster specification of change plans. To address this problem, in this paper we present a conceptual solution to support the design and planning of IT changes and explore the concept of change templates as a mechanism to formalize, preserve, and (re)use knowledge in the specification of (recurrent and similar) IT changes. To prove concept and technical feasibility of the proposed solution, we have developed a prototypical implementation of a change management system called ChangeLedge and used it to carry out a set of experiments, considering typical IT changes. The results obtained indicate the effectiveness and efficiency of the system, which is able to generate accurate and actionable change plans in substantially less time than would be spent by a skilled human operator.     

Improved similarity trees and their application to visual data classification

An alternative form to multidimensional projections for the visual analysis of data represented in multidimensional spaces is the deployment of similarity trees, such as Neighbor Joining trees. They organize data objects on the visual plane emphasizing their levels of similarity with high capability of detecting and separating groups and subgroups of objects. Besides this similarity-based hierarchical data organization, some of their advantages include the ability to decrease point clutter; high precision; and a consistent view of the data set during focusing, offering a very intuitive way to view the general structure of the data set as well as to drill down to groups and subgroups of interest. Disadvantages of similarity trees based on neighbor joining strategies include their computational cost and the presence of virtual nodes that utilize too much of the visual space. This paper presents a highly improved version of the similarity tree technique. The improvements in the technique are given by two procedures. The first is a strategy that replaces virtual nodes by promoting real leaf nodes to their place, saving large portions of space in the display and maintaining the expressiveness and precision of the technique. The second improvement is an implementation that significantly accelerates the algorithm, impacting its use for larger data sets. We also illustrate the applicability of the technique in visual data mining, showing its advantages to support visual classification of data sets, with special attention to the case of image classification. We demonstrate the capabilities of the tree for analysis and iterative manipulation and employ those capabilities to support evolving to a satisfactory data organization and classification.