Lexically scoped distribution: what you see is what you get

We define a lexically scoped, asynchronous and distributed π-calculus, with local communication and process migration. This calculus adopts the network-awareness principle for distributed programming and follows a simple model of distribution for mobile calculi: a lexical scope discipline combines static scoping with dynamic linking, associating channels to a fixed site throughout computation. This discipline provides for both remote invocation and process migration. A simple type system is a straightforward extension of that of the π-calculus, adapted to take into account the lexical scope of channels. An equivalence law captures the essence of this model: a process behavior depends on the channels it uses, not on where it runs.     

Off-line optimization and control for real time integration of a three-phase hydrogenation catalytic reactor

In order to develop and test the integration procedure, in this paper a real time process integration involving the optimization and control of the process is presented, in this case, with the two-layer approach. The used optimization algorithms were Levenberg–Marquardt and SQP that solve a non-linear least square problem subject to bounds on the variables. The two-layer approach is a hierarchical control structure where an optimization layer calculates the set points and manipulated variables to the advanced controller, which is based on the dynamic matrix control with constraints (QDMC). The non-isothermal dynamic model of the three-phase slurry catalytic reactor with appropriate solution procedure was utilized in this work (Vasco de Toledo, E. C., Santana, P. L., Maciel, M. R. W., & Maciel Filho, R. (2001). Dynamic modeling of a three-phase catalytic slurry reactor. Chemical Engineering Science, 56, 6055–6061). The model consists on mass and heat balance equations for the catalyst particles as well as for the bulk phases of gas and liquid. The model was used to describe the dynamic behavior of hydrogenation reaction of o-cresol to obtain 2-methil-cyclohexanol, in the presence of a catalyst Ni/SiO₂.     

The tetrahedral finite cell method: Higher‐order immersogeometric analysis on adaptive non‐boundary‐fitted meshes

The finite cell method (FCM) is an immersed domain finite element method that combines higher‐order non‐boundary‐fitted meshes, weak enforcement of Dirichlet boundary conditions, and adaptive quadrature based on recursive subdivision. Because of its ability to improve the geometric resolution of intersected elements, it can be characterized as an immersogeometric method. In this paper, we extend the FCM, so far only used with Cartesian hexahedral elements, to higher‐order non‐boundary‐fitted tetrahedral meshes, based on a reformulation of the octree‐based subdivision algorithm for tetrahedral elements. We show that the resulting TetFCM scheme is fully accurate in an immersogeometric sense, that is, the solution fields achieve optimal and exponential rates of convergence for h‐refinement and p‐refinement, if the immersed geometry is resolved with sufficient accuracy. TetFCM can leverage the natural ability of tetrahedral elements for local mesh refinement in three dimensions. Its suitability for problems with sharp gradients and highly localized features is illustrated by the immersogeometric phase‐field fracture analysis of a human femur bone. Copyright © 2016 John Wiley & Sons, Ltd.     

Plumes of discolored water of volcanic origin and possible implications for algal communities. The case of the Home Reef eruption of 2006 (Tonga, Southwest Pacific Ocean)

The Home Reef volcano (Tonga, Southwest Pacific Ocean) erupted in August 2006. Initially a submarine eruption it quickly evolved into a subaerial event upon the formation of an ephemeral island.Remote sensing data from different sensors including MODIS, ASTER, EO-1 ALI and Landsat-7 ETM+ were used to analyze the event, focusing on the plumes of discolored water, ocean chlorophyll-a concentration (OCC) and sea surface temperature.An early classification system for the plumes was devised based on spectral properties and point of origin. Plumes originated at the volcano were named Type-I and those associated to the pumice rafts Type-II.Anomalies in ocean chlorophyll-a concentration, measured using MODIS data, were analyzed and a large bloom, presumably dominated by Trichodesmium sp. was identified. The bloom, which contributed to OCC values 17 times higher than the background, was spatially and temporally coincident with a Type-I plume of discolored water. The OCC increase appears to have been caused by a combined effect of both ocean fertilizations by the subsurface volcanic plume and rising sea surface temperatures.The Home Reef event offers a good candidate for a case of ocean enrichment by a submarine volcano and highlights the need for continuous monitoring of the eruptions even after the end of the explosive, more spectacular stages.     

Analysis of the particle swarm algorithm in the optimization of a three-phase slurry catalytic reactor

The Particle Swarm Optimization (PSO) method was employed to optimize an industrial chemical process characterized by being difficult to be optimized by conventional deterministic methods. The chemical process is a three phase catalytic slurry reactor (tubular geometry) in which the reaction of the hydrogenation of o-cresol producing 2-methyl-cyclohexanol is carried out. The optimization problem was formulated considering as input variables the operating conditions of the reactor and as objective function the maximization of productivity, subject to the environmental constraint of conversion. The process was represented by a multivariable non-linear rigorous mathematical model and in order to solve the optimization problem, the performance of the PSO algorithm was evaluated considering four sets of parameters values suggested by the literature. PSO demonstrated to be efficient and robust to solve the constrained optimization problem, independently of the values of the PSO parameters. The solution of the rigorous mathematical model of the reactor was associated with a high computational burden, and although the PSO algorithm presented high rate of convergence, the attempt to make possible the optimization in a timeframe suitable to real time applications failed because the algorithm lost robustness (fraction of the number of runs the algorithm reached the optimization goal) when run with a reduced number of function evaluations. Therefore, if this type of application is desired, simplified mathematical models with fast and simple numerical methods must be preferred.     

Lamb Meat Quality Assessment by Support Vector Machines

The correct assessment of meat quality (i.e., to fulfill the consumer’s needs) is crucial element within the meat industry. Although there are several factors that affect the perception of taste, tenderness is considered the most important characteristic. In this paper, a Feature Selection procedure, based on a Sensitivity Analysis, is combined with a Support Vector Machine, in order to predict lamb meat tenderness. This real-world problem is defined in terms of two difficult regression tasks, by modeling objective (e.g. Warner–Bratzler Shear force) and subjective (e.g. human taste panel) measurements. In both cases, the proposed solution is competitive when compared with other neural (e.g. Multilayer Perceptron) and Multiple Regression approaches.     

A Reaction Attack on a Public Key Cryptosystem Based on the Word Problem

Wagner and Magyarik outlined a conceptual public key cryptosystem based on the hardness of the word problem for finitely presented groups. At the same time, they gave a specific example of such a system. We prove that in the present form their approach is vulnerable to so-called reaction attacks. In particular, for the proposed instance it is possible to retrieve the private key just by watching the performance of a legitimate recipient. Keywords:Finitely presented groups, Word problem, Public key encryption, Cryptanalysis.Work partially supported by the projects BFM2001-3239-C03-01, GE-EXP01-08     

The importance of landscape in wine quality perception: An integrated approach using choice-based conjoint analysis and combination-based permutation tests

This work’s aim is to evaluate the importance of landscape in wine quality perception using a novel integrated approach based on two statistical techniques, i.e. choice-based conjoint analysis (Gustafsson et al., 2001) and combination-based permutation tests (Corain and Salmaso, 2004, Pesarin and Salmaso, 2009a). To this end we developed a preference choice experiment which was submitted to a sample of respondents during blind wine tasting meetings. The obtained results allow us to weigh up and emphasise the importance of an attractive landscape to the perception of a finer quality of wine. Indeed, we noticed that associating wine to an image of greater visual impact, i.e. an evocative landscape, induces a significantly higher preference for the tasted wine. Moreover, the integrated application of choice-based conjoint analysis and combination-based permutation tests allows us to identify the specific relationship each market segment has with landscape, price and wine quality.