130,388 research outputs found
Semantic subtyping for objects and classes
No full textThere are two approaches for defining subtyping relations: the syntactic and the semantic one. In the semantic approach one starts from a model of the language of interest and an interpretation of types as subsets of the model. The subtyping relation is then defined as inclusion of sets denoting types. An orthogonal issue, typical of object-oriented languages, is the issue of nominal vs. structural subtyping. We aim to integrate structural subtyping with boolean connectives and semantic subtyping for a object-oriented core language and define a Java-like programming platform that exploits the benefits of both approaches, expressible in terms of code reuse and of compactness of program writing
Compositional event structure semantics for the internal pi-calculus
No full textWe propose the first compositional event structure semantics for a very expressive pi-calculus, generalising Winskel’s event structures for CCS. The pi-calculus we model is the piI-calculus with recursive definitions and summations. First we model the synchronous calculus, introducing a notion of dynamic renaming to the standard operators on event structures. Then we model the asynchronous calculus, for which a new additional operator, called rooting, is necessary for representing causality due to new name binding. The semantics are shown to be operationally adequate and sound with respect to bisimulation
Nutriscore's impact on purchase intention for products with geographical indications: a Bayesian causal mediation analysis
No full textThis study investigated how (NS) and geographical indication (GI) labels interact to influence consumers' purchase intention for hard cheese products in Italy and the Netherlands. Using a Bayesian causal mediation analysis framework, we conducted an online randomised experiment with a between-subjects design. The analysis focused on the effect of an NS grade D label on purchase intention, comparing generic cheeses to those with PDO label. Furthermore, we explored whether perceived healthiness mediates the relationship between an NS grade D label and purchase intention for these products. The results revealed that although an NS grade D label can reduce perceived healthiness, particularly in countries with low familiarity with GIs, its total effect on purchase intention is limited. In the Netherlands, PDO label mitigates the negative effect of NS grade D on perceived healthiness, demonstrating its ability to offset unfavourable nutritional signals. We identified a dual effect of an NS grade D label: a negative effect on purchase intention due to its impact on perceived healthiness and a direct positive effect likely to result from consumers appreciating the transparency it provides. This suggests that consumers can appreciate the information value of NS, even if the label conveys unfavourable nutritional information. These insights are valuable to policymakers and industry stakeholders when managing the implementation of packaging labels in various European markets
Impatto del modello C3S su alcuni indicatori di sviluppo rurale nella regione indiana di Meghalaya
No full textImpatto del modello C3S su alcuni indicatori di sviluppo rurale nella regione indiana di Meghalay
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Respicell(TM): An innovative dissolution apparatus for inhaled products
No full textTo overcome some of the shortfalls of the types of dissolution testing currently used for pulmonary products, a new custom-built dissolution apparatus has been developed. For inhalation products, the main in vitro characterisation required by pharmacopoeias is the deposition of the active pharmaceutical ingredient in an impactor to estimate the dose delivered to the target site, i.e., the lung. Hence, the collection of the respirable dose (<5 μm) also appears to be an essential requirement for the study of the dissolution rate of particles, because it results as being a relevant parameter for the pharmacological action of the powder. In this sense, dissolution studies could become a complementary test to the routine testing of inhaled formulation delivered dose and aerodynamic performance, providing a set of data significant for product quality, efficacy and/or equivalence. In order to achieve the above-mentioned objectives, an innovative dissolution apparatus (RespiCellTM) suitable for the dissolution of the respirable fraction of API deposited on the filter of a fast screening impactor (FSI) (but also of the entire formulation if desirable) was designed at the University of Parma and tested. The purpose of the present work was to use the RespiCell dissolution apparatus to compare and discriminate the dissolution behaviour after aerosolisation of various APIs characterised by different physico-chemical properties (hydrophilic/lipophilic) and formulation strategies (excipients, mixing technology)
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