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.     

New insights on multi-state component criticality and importance

In this paper, new importance measures for multi-state systems with multi-state components are introduced and evaluated. These new measures complement and enhance current work done in the area of multi-state reliability. In general, importance measures are used to evaluate and rank the criticality of component or component states with respect to system reliability. The focus of the study is to provide intuitive and clear importance measures that can be used to enhance system reliability from two perspectives: (1) how a specific component affects multi-state system reliability and (2) how a particular component state or set of states affects multi-state system reliability. The first measure unsatisfied demand index, provides insight regarding a component or component state contribution to unsatisfied demand. The second measure multi-state failure frequency index, elaborates on an approach that quantifies the contribution of a particular component or component state to system failure. Finally, the multi-state redundancy importance identifies where to allocate component redundancy as to improve system reliability. The findings of this study indicate that both perspectives can be used to complement each other and as an effective tool to assess component criticality. Examples illustrate and compare the proposed measures with previous multi-state importance measures.     

Functionalized Cluster‐Assembled Magnetic Nanostructures for Applications to high Integration‐Density Devices

This paper presents recent results on the preparation and characterization of original magnetic nanostructures from nanoclusters preformed in the gas phase. Magnetic binary‐clusters (i.e. Co‐Sm, Co‐Pt, Co‐Ag) with rather well controlled sizes, structures and compositions, are prepared in the gas phase using a combined laser vaporization‐rare gas condensation source and subsequently deposited at low energy (LECBD : Low Energy Cluster Beam Deposition) on various functionalized substrates to grow cluster‐assembled magnetic nanostructures exhibiting specific magnetic properties. Especially a high magnetic anisotropy and consequently a high magnetic blocking temperature compatible with future applications to high density memory devices and spin electronics are expected. In this context of applications, 2D‐organized arrays of functionalized binary‐cluster assembled dots are prepared by LECBD on FIB‐functionalized substrates (FIB: Focussed Ion Beam) with the ultimate objective to reach areal densities in the range of the Tbits/in².     

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.     

Experimental and Numerical Analysis of Soil–Pipe Interaction

Cases of pipeline damage caused by landslides are common in coastal or mountainous regions, where a continuous monitoring/repair activity is planned in order to maintain their serviceability. The analysis of the soil–structure interaction phenomenon can be invoked to improve the planning and design of buried pipelines, to guide monitoring, and to reduce the risk of damage or failure. Two different approaches are considered in this paper: small scale laboratory tests and numerical simulations using the distinct element method (DEM). The experimental setup consists of a box filled with sand and water. Several experiments were performed, in which the diameter and the depth of the tube varied. The numerical simulations are divided in two separate series: in the first, the numerical model is calibrated and its reliability in reproducing the experimental tests is checked; in the second series, the direction of the relative displacement between the tube and the surrounding “numerical soil” varies over the range ±90° with respect to the horizontal. In the latter, both vertical and horizontal components of the drag force are measured and the corresponding interaction diagrams are constructed. The DEM simulations provide useful information about the shape of the failure mechanisms and the force transfer within the soil.     

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.     

Implicit fault-tolerant control: application to induction motors

In this paper we propose an innovative way of dealing with the design of fault-tolerant control systems. We show how the nonlinear output regulation theory can be successfully adopted in order to design a regulator able to offset the effect of all possible faults which can occur and, in doing so, also to detect and isolate the occurred fault. The regulator is designed by embedding the (possible nonlinear) internal model of the fault. This idea is applied to the design of a fault-tolerant controller for induction motors in presence of both rotor and stator mechanical faults.