DALICA: Agent-Based Ambient Intelligence for Cultural-Heritage Scenarios

Villa Adriana is an enormous archaeological area where ancient artifacts and modern technology have found an unexpected equilibrium. The old artifacts are huge stone monuments; the modern technology includes PDAs and signals from the Galileo satellite combined with intelligent software agents. As part of the European CUSPIS project (Cultural Heritage Space Identification System, www. cuspis-project.info), we exploited intelligent agents for two ambient-intelligence scenarios applicable to Villa Adriana. One scenario involves cultural assets fruition-the possibility of accessing and enjoying cultural assets. This scenario concerns the dissemination of information about cultural assets; for example, users can visit a museum or archaeological site and receive on their mobile devices appropriate, personalized information about that place. The other scenario involves cultural assets monitoring, which concerns securely transporting cultural assets from the owner organization to a renter organization and back.     

Shadow attacks on users’ anonymity in pervasive computing environments

Privacy preserving technologies are likely to become an essential component of adaptive services in pervasive and mobile computing. Although privacy issues have been studied for a long time in computer science as well as in other fields, most studies are focused on the release of data from large repositories. Mobile and pervasive computing pose new challenges, requiring specific formal models for attacks and new privacy preserving techniques. This paper considers a specific pervasive computing scenario, and shows that the application of state-of-the-art techniques for the anonymization of service requests is insufficient to protect the privacy of users. A specific class of attacks, called shadow attacks, is formally defined and a defense technique is proposed. This defense is formally proved to be correct, and its effectiveness is validated by extensive experiments in a simulated environment.     

Querying and creating visualizations by analogy

While there have been advances in visualization systems, particularly in multi-view visualizations and visual exploration, the process of building visualizations remains a major bottleneck in data exploration. We show that provenance metadata collected during the creation of pipelines can be reused to suggest similar content in related visualizations and guide semi-automated changes. We introduce the idea of query-by-example in the context of an ensemble of visualizations, and the use of analogies as first-class operations in a system to guide scalable interactions. We describe an implementation of these techniques in VisTrails, a publicly-available, open-source system.     

Ambient occlusion and edge cueing to enhance real time molecular visualization

The paper presents a set of combined techniques to enhance the real-time visualization of simple or complex molecules (up to order of 106 atoms) space fill mode. The proposed approach includes an innovative technique for efficient computation and storage of ambient occlusion terms, a small set of GPU accelerated procedural impostors for space-fill and ball-and-stick rendering, and novel edge-cueing techniques. As a result, the user's understanding of the three-dimensional structure under inspection is strongly increased (even for still images), while the rendering still occurs in real time.     

Lower and upper bounds for the two-echelon capacitated location-routing problem

In this paper, we introduce two algorithms to address the two-echelon capacitated location-routing problem (2E-CLRP). We introduce a branch-and-cut algorithm based on the solution of a new two-index vehicle-flow formulation, which is strengthened with several families of valid inequalities. We also propose an adaptive large-neighbourhood search (ALNS) meta-heuristic with the objective of finding good-quality solutions quickly. The computational results on a large set of instances from the literature show that the ALNS outperforms existing heuristics. Furthermore, the branch-and-cut method provides tight lower bounds and is able to solve small- and medium-size instances to optimality within reasonable computing times.     

D-Index: Distance Searching Index for Metric Data Sets

In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.     

Hierarchies of parallel rewriting P systems — A survey

The paper is about some families of rewriting P systems, where the application of evolution rules is extended from the classical sequential rewriting to the parallel one (as, for instance, in Lindenmayer systems). As a result, consistency problems for the communication of strings may arise. Three variants of parallel rewriting P systems (already present in the literature) are considered here, together with the strategies they use to face the communication problem, and some parallelism methods for string rewriting are defined. We give a survey of all known results about each variant and we state some relations among the three variants, thus establishing hierarchies of parallel rewriting P systems. Various open problems related to the subject are also presented. Danicla Besozzi: She is assistant professor at the University of Milano. She received her M.S. in Mathematics (2000) from the University of Como and Ph.D. in Computer Science (2004) from the University of Milano. Her research interests cover topics in Formal Language Theory, Molecular Computing, Systems Biology. She is member of EATCS (European Association for Theoretical Computer Science) and EMCC (European Molecular Computing Consortium). Giancarlo Mauri: He is full professor of Computer Science at the University of Milano-Bicocca. His research interests are mainly in the area of theoretical computer science, and include: formal languages and automata, computational complexity, computational learning theory, soft computing techniques, cellular automata, bioinformatics and molecular computing. On these subjects, he published more than 150 scientific papers in international journals, contributed volumes and conference proceedings. Claudio Zandron: He received Ph.D. in Computer Science at the University of Milan, Italy, in 2001. Since 2002 he is assistant professor at the University of Milano-Bicocca, Italy. He is member of the EATCS (European Association for Theoretical Computer Science) and of EMCC (European Molecular Computing Consortium). His research interests are Molecular Computing (DNA and Membrane Computing) and Formal Languages.     

Distinct Tomato Cultivars Are Characterized by a Differential Pattern of Biochemical Responses to Drought Stress

Future climate scenarios suggest that crop plants will experience environmental changes capable of affecting their productivity. Among the most harmful environmental stresses is drought, defined as a total or partial lack of water availability. It is essential to study and understand both the damage caused by drought on crop plants and the mechanisms implemented to tolerate the stress. In this study, we focused on four cultivars of tomato, an economically important crop in the Mediterranean basin. We investigated the biochemical mechanisms of plant defense against drought by focusing on proteins specifically involved in this stress, such as osmotin, dehydrin, and aquaporin, and on proteins involved in the general stress response, such as HSP70 and cyclophilins. Since sugars are also known to act as osmoprotectants in plant cells, proteins involved in sugar metabolism (such as RuBisCO and sucrose synthase) were also analyzed. The results show crucial differences in biochemical behavior among the selected cultivars and highlight that the most tolerant tomato cultivars adopt quite specific biochemical strategies such as different accumulations of aquaporins and osmotins. The data set also suggests that RuBisCO isoforms and aquaporins can be used as markers of tolerance/susceptibility to drought stress and be used to select tomato cultivars within breeding programs.