Software quality model for the evaluation of semantic technologies

In order to obtain high-quality software products, the specification and evaluation of quality during the software development process is of crucial importance. One important component in software evaluation is the software quality model, since it provides the basis for software evaluation and gives a better insight of the software characteristics that influence its quality. Furthermore, quality models also ensure a consistent terminology for software product quality and provide guidance for its measurement. In recent years, semantic technologies have started to gain importance and, as the field becomes more and more popular, the number of these technologies is increasing exponentially. Just as with any other software product, the quality of semantic technologies is an important concern, and multiple evaluations of semantic technologies have been performed. However, the problem is that there is no consistent terminology for describing the quality of semantic technologies and it is difficult to compare them because of differences in the meaning of the evaluation characteristics used. Also, existing software quality models do not define those quality characteristics that are specific to semantic technologies. This thesis presents a quality model for semantic technologies which aims to provide a common ground in the field of semantic technology evaluation. It also presents a new method for extending software quality models, based on a bottom-up approach, that is used to define the quality model for semantic technologies. Finally, this thesis describes the use of the semantic technology quality model in a web application that visualizes semantic technology evaluation results and provides semantic technology recommendations

Extending Software Quality Models - A Sample In The Semantic Technologies Domain

In order to correctly evaluate semantic technologies,which have become widely adopted in recent years, we need to put evaluations under the scope of a unique software quality model.This paper presents a quality model for semantic technologies. First, some well-known software quality models are described,together with methods for extending them. Afterwards, a new method for extending quality models is proposed and it is then used to define a quality model for semantic technologies by extending the ISO 9126 quality model. Finally, the proposed model is validated by analyzing existing semantic technology evaluations

Semantic Technology Recommendation Based on the Analytic Network Process

Semantic technologies have become widely adopted in recent years, and choosing the right technologies for the problems that users face is often a difficult task. This paper presents an application of the Analytic Network Process for the recommendation of semantic technologies, which is based on a quality model for semantic technologies. Instead of relying on expert-based comparisons of alternatives, the comparisons in our framework depend on real evaluation results. Furthermore, the recommendations in our framework derive from user quality requirements, which leads to better recommendations tailored to users’ needs. This paper also presents an algorithm for pairwise comparisons, which is based on user quality requirements and evaluation results

A Recommendation Framework Based on the Analytic Network Process and its Application in the Semantic Technology Domain

When users face a certain problem needing a product, service, or action to solve it, selecting the best alternative among them can be a dicult task due to the uncertainty of their quality. This is especially the case in the domains where users do not have an expertise, like for example in Software Engineering. Multiple criteria decision making (MCDM) methods are methods that help making better decisions when facing the complex problem of selecting the best solution among a group of alternatives that can be compared according to different conflicting criteria. In MCDM problems, alternatives represent concrete products, services or actions that will help in achieving a goal, while criteria represent the characteristics of these alternatives that are important for making a decision

A Recommendation Framework Based on the Analytic Network Process and its Application in the Semantic Technology Domain

When users face a certain problem needing a product, service, or action to solve it, selecting the best alternative among them can be a dicult task due to the uncertainty of their quality. This is especially the case in the domains where users do not have an expertise, like for example in Software Engineering. Multiple criteria decision making (MCDM) methods are methods that help making better decisions when facing the complex problem of selecting the best solution among a group of alternatives that can be compared according to different conflicting criteria. In MCDM problems, alternatives represent concrete products, services or actions that will help in achieving a goal, while criteria represent the characteristics of these alternatives that are important for making a decision

Flea-borne rickettsioses: ecologic considerations.

Ecologic and economic factors, as well as changes in human behavior, have resulted in the emergence of new and the reemergence of existing but forgotten infectious diseases during the past 20 years. Flea-borne disease organisms (e.g., Yersinia pestis, Rickettsia typhi, R. felis, and Bartonella henselae) are widely distributed throughout the world in endemic-disease foci, where components of the enzootic cycle are present. However, flea-borne diseases could reemerge in epidemic form because of changes in vector-host ecology due to environmental and human behavior modification. The changing ecology of murine typhus in southern California and Texas over the past 30 years is a good example of urban and suburban expansion affecting infectious disease outbreaks. In these areas, the classic rat-flea-rat cycle of R. typhi has been replaced by a peridomestic animal cycle involving, e.g., free-ranging cats, dogs, and opossums and their fleas. In addition to the vector-host components of the murine typhus cycle, we have uncovered a second typhuslike rickettsia, R. felis. This agent was identified from the blood of a hospitalized febrile patient and from opossums and their fleas. We reviewed the ecology of R. typhi and R. felis and present recent data relevant to the vector biology, immunology, and molecular characterization and phylogeny of flea-borne rickettsioses

BMP Signaling Mediates Effects of Exercise on Hippocampal Neurogenesis and Cognition in Mice

Exposure to exercise or to environmental enrichment increases the generation of new neurons in the adult hippocampus and promotes certain kinds of learning and memory. While the precise role of neurogenesis in cognition has been debated intensely, comparatively few studies have addressed the mechanisms linking environmental exposures to cellular and behavioral outcomes. Here we show that bone morphogenetic protein (BMP) signaling mediates the effects of exercise on neurogenesis and cognition in the adult hippocampus. Elective exercise reduces levels of hippocampal BMP signaling before and during its promotion of neurogenesis and learning. Transgenic mice with decreased BMP signaling or wild type mice infused with a BMP inhibitor both exhibit remarkable gains in hippocampal cognitive performance and neurogenesis, mirroring the effects of exercise. Conversely, transgenic mice with increased BMP signaling have diminished hippocampal neurogenesis and impaired cognition. Exercise exposure does not rescue these deficits, suggesting that reduced BMP signaling is required for environmental effects on neurogenesis and learning. Together, these observations show that BMP signaling is a fundamental mechanism linking environmental exposure with changes in cognitive function and cellular properties in the hippocampus

Reverse transcriptase PCR amplification of Rickettsia typhi from infected mammalian cells and insect vectors

We developed a reverse transcriptase PCR assay to detect expression of 120- and 17-kDa antigen genes in Rickettsia typhi. Infected Vero cell and flea RNAs were reverse transcribed by using random hexamers. The cDNA was amplified by using high concentrations of primer and template in an inexpensive, nonradioactive assay.Peer reviewedEntomology and Plant Patholog

Superspreading: Mechanisms and Molecular Design

The intriguing ability of certain surfactant molecules to drive the superspreading of liquids to complete wetting on hydrophobic substrates is central to numerous applications that range from coating flow technology to enhanced oil recovery. Despite significant experimental efforts, the precise mechanisms underlying superspreading remain unknown to date. Here, we isolate these mechanisms by analyzing coarse-grained molecular dynamics simulations of surfactant molecules of varying molecular architecture and substrate affinity. We observe that for superspreading to occur, two key conditions must be simultaneously satisfied: the adsorption of surfactants from the liquid–vapor surface onto the three-phase contact line augmented by local bilayer formation. Crucially, this must be coordinated with the rapid replenishment of liquid–vapor and solid–liquid interfaces with surfactants from the interior of the droplet. This article also highlights and explores the differences between superspreading and conventional surfactants, paving the way for the design of molecular architectures tailored specifically for applications that rely on the control of wetting

Biomarkers of severity and threshold of allergic reactions during oral peanut challenges

Background: oral food challenge (OFC) is the criterion standard to assess peanut allergy (PA), but it involves a risk of allergic reactions of unpredictable severity.Objective: our aim was to identify biomarkers for risk of severe reactions or low dose threshold during OFC to peanut.Methods: we assessed Learning Early about Peanut Allergy study, Persistance of Oral Tolerance to Peanut study, and Peanut Allergy Sensitization study participants by administering the basophil activation test (BAT) and the skin prick test (SPT) and measuring the levels of peanut-specific IgE, Arachis hypogaea 2–specific IgE, and peanut-specific IgG4, and we analyzed the utility of the different biomarkers in relation to PA status, severity, and threshold dose of allergic reactions to peanut during OFC.Results: when a previously defined optimal cutoff was used, the BAT diagnosed PA with 98% specificity and 75% sensitivity. The BAT identified severe reactions with 97% specificity and 100% sensitivity. The SPT, level of Arachis hypogaea 2–specific IgE, level of peanut-specific IgE, and IgG4/IgE ratio also had 100% sensitivity but slightly lower specificity (92%, 93%, 90%, and 88%, respectively) to predict severity. Participants with lower thresholds of reactivity had higher basophil activation to peanut in vitro. The SPT and the BAT were the best individual predictors of threshold. Multivariate models were superior to individual biomarkers and were used to generate nomograms to calculate the probability of serious adverse events during OFC for individual patients.Conclusions: the BAT diagnosed PA with high specificity and identified severe reactors and low threshold with high specificity and high sensitivity. The BAT was the best biomarker for severity, surpassed only by the SPT in predicting threshold. Nomograms can help estimate the likelihood of severe reactions and reactions to a low dose of allergen in individual patients with PA