Mechanical characterization and modeling stress relaxation behavior of acrylic–polyurethane-based graft-interpenetrating polymer networks

The stress relaxation behavior of acrylic–polyurethane (PU)-based graft-interpenetrating polymer networks (IPNs) was characterized via dynamic mechanical analysis (DMA) and modeled using finite element method (FEM) analysis. Stress relaxation of glassy IPN specimens was experimentally studied under flexural testing, while rubbery IPN specimens were tested in tension. The effects of varying the styrene content in the acrylic copolymer phase, compatibility of the two phases in IPNs, and changing the concentration of acrylic copolymer and PU were studied. A higher percentage of styrene content resulted in higher homogeneity of IPN specimens, and decrease in initial modulus for acrylic copolymer specimens. Additionally, glassy IPN specimens with 90% styrene shows resistance to relaxation as high as acrylic copolymer samples. Experimental results were used to develop a numerical model to study stress relaxation response of specimens. While polymer systems have been studied computationally, numerical modeling of IPN systems is still in its infancy. A three-dimensional FEM model was developed using the Generalized Maxwell model and four-term Prony series constants, which were extracted from the stress relaxation experiments. With four terms in the Prony series, a good match was observed between experimental observations and results from the FEM model.     

Recommending multimedia visiting paths in cultural heritage applications

The valorization and promotion of worldwide Cultural Heritage by the adoption of Information and Communication Technologies represent nowadays some of the most important research issues with a large variety of potential applications. This challenge is particularly perceived in the Italian scenario, where the artistic patrimony is one of the most diverse and rich of the world, able to attract millions of visitors every year to monuments, archaeological sites and museums. In this paper, we present a general recommendation framework able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context-aware recommendation techniques supporting intelligent multimedia services for the users—i.e. dynamic visiting paths for a given environment. Specific applications of our system within the cultural heritage domain are proposed by means of real case studies in the mobile environment related both to an outdoor and indoor scenario, together with some results on user’s satisfaction and system accuracy.     

Visual search tree profiling

Understanding how the search space is explored for a given constraint problem – and how it changes for different models, solvers or search strategies – is crucial for efficient solving. Yet programmers often have to rely on the crude aggregate measures of the search that are provided by solvers, or on visualisation tools that can show the search tree, but do not offer sophisticated ways to navigate and analyse it, particularly for large trees. We present an architecture for profiling a constraint programming search that is based on a lightweight instrumentation of the solver. The architecture combines a visualisation of the search tree with various tools for convenient navigation and analysis of the search. These include identifying repeated subtrees, high-level abstraction and navigation of the tree, and the comparison of two search trees. The resulting system is akin to a traditional program profiler, which helps the user to focus on the parts of the execution where an improvement to their program would have the greatest effect.     

Semantic weaving of configuration fragments into a consistent system configuration

Configuration fragments developed separately and focusing on different aspects, such as availability, security or performance of a system need to be integrated into a consistent system configuration to avoid system malfunctions. The main challenges of such integration are due to the overlapping entities and the integration relations between the entities of the different configuration fragments. In this paper we propose a model based approach for a consistent integration of configuration fragments into a system configuration. We use and extend the model weaving technique to capture the semantics of the relations between the entities of the configuration fragments. Moreover, we generate automatically the constraints corresponding to these semantic relations to complete the target system configuration profile. These constraints can be used to guard the configuration consistency during runtime modifications.     

Towards a smooth design process for static communicative node‐link diagrams

Node‐link infographics are visually very rich and can communicate messages effectively, but can be very difficult to create, often involving a painstaking and artisanal process. In this paper we present an investigation of node‐link visualizations for communication and how to better support their creation. We begin by breaking down these images into their basic elements and analyzing how they are created. We then present a set of techniques aimed at improving the creation workflow by bringing more flexibility and power to users, letting them manipulate all aspects of a node‐link diagram (layout, visual attributes, etc.) while taking into account the context in which it will appear. These techniques were implemented in a proof‐of‐concept prototype called GraphCoiffure, which was designed as an intermediary step between graph drawing/editing software and image authoring applications. We describe how GraphCoiffure improves the workflow and illustrate its benefits through practical examples.     

Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on bladder cancer

A major requirement in the application of proteins as clinical biomarkers is that they provide a highly sensitive and specific result in disease assessment. Since single biomarkers are generally of limited accuracy, a group or panel of well-characterized biomarkers appears appropriate, providing a more robust and sensitive MS-based analytical platform. CE coupled to MS has been successfully used in biomarker discovery and application, as it enables the selective detection of peptides and small proteins, combining the high separation capacity of CE with the advanced sensitivity of MS. CE-MS allows the characterization of highly complex samples (such as urine, plasma, and other biofluids) in a consistent and reproducible way. It has a range of applications, many focusing especially in studies on urinary peptide biomarkers in kidney and cardiovascular diseases. Another major field of interest has been malignancy of the genitourinary system. In the first part of this review, we cover technical aspects and performance characteristics of CE-MS, with special focus on the requirements for biomarker discovery and clinical application. In the second part, we review the potential and development of CE-MS in the management of genitourinary cancers, especially bladder cancer. CE-MS has been employed in several studies aimed at discovering biomarkers for bladder cancer that may be useful in diagnosis, monitoring for recurrence, and prediction of the risk for the muscle-invasive stage. In the last part of the review, we discuss current challenges and provide an outlook for ongoing and possible future developments.     

Query answering under probabilistic uncertainty in Datalog+ / − ontologies

The recently introduced Datalog+?/?? family of ontology languages is especially useful for representing and reasoning over lightweight ontologies, and is set to play a central role in the context of query answering and information extraction for the Semantic Web. Recently, it has become apparent that it is necessary to develop a principled way to handle uncertainty in this domain. In addition to uncertainty as an inherent aspect of the Web, one must also deal with forms of uncertainty due to inconsistency and incompleteness, uncertainty resulting from automatically processing Web data, as well as uncertainty stemming from the integration of multiple heterogeneous data sources. In this paper, we take an important step in this direction by developing a probabilistic extension of Datalog+?/??. This extension uses Markov logic networks as the underlying probabilistic semantics. Here, we focus especially on scalable algorithms for answering threshold queries, which correspond to the question “what is the set of all ground atoms that are inferred from a given probabilistic ontology with a probability of at least p?”. These queries are especially relevant to Web information extraction, since uncertain rules lead to uncertain facts, and only information with a certain minimum confidence is desired. We present several algorithms, namely a basic approach, an anytime one, and one based on heuristics, which is guaranteed to return sound results. Furthermore, we also study inconsistency in probabilistic Datalog+?/?? ontologies. We propose two approaches for computing preferred repairs based on two different notions of distance between repairs, namely symmetric and score-based distance. We also study the complexity of the decision problems corresponding to computing such repairs, which turn out to be polynomial and NP-complete in the data complexity, respectively.