Experimental Design Applied for Cost and Efficiency of Antioxidants in Biodiesel

Oxidation stability is a parameter of great importance for biodiesel quality control to both producers and subsequent consumers. To maintain the quality of biodiesel, currently the most effective and economical method is the addition of antioxidants that prevent or retard the biofuel oxidation reaction. In this study, efficiency and cost of synthetic antioxidants added to B100 biodiesel from soybean oil and pork fat were evaluated, using butylhydroxyanisole (BHA), butylhydroxytoluene (BHT) and tert-butylhydroquinone (TBHQ), in pure form or in mixtures, according to a simplex-centroid mixture experimental design. Results demonstrate an increased induction period (IP) in all trials when compared to the control sample, and TBHQ was the only antioxidant alone that met all the specification standards, while BHT and BHA alone met only the American standard specifications. The antioxidant mixture that presented the highest synergistic effect was that of TBHQ and BHA. Multi-response optimization indicated an optimum formulation containing 75 % TBHQ and 25 % BHA with an IP of 7.27 h at 110 °C and the antioxidant mixture cost of 31.31 USD, to be added for a ton of biodiesel. This simplex-centroid mixture experimental design shows an ability to be applied in the biodiesel, oils and fats industry to evaluate the oxidation stability and the occurrence of synergism between different mixtures of synthetic or natural antioxidants and their costs.     

Photoactivable Elimination of Tumorigenic Human Induced Pluripotent Stem Cells by Using a Lectin–Doxorubicin Prodrug Conjugate

Human pluripotent stem cells (hPSCs) are attractive resources for regenerative medicine, but medical applications are hindered by their tumorigenic potential. Previously, a hPSC-specific lectin probe, rBC2LCN, was identified through comprehensive glycome analysis by using high-density lectin microarrays. Herein, a lectin–doxorubicin (DOX) prodrug conjugate, with controllable photolysis activation for the elimination of tumorigenic human induced pluripotent stem cells, has been developed. rBC2LCN was fused with a biotin-binding protein, tamavidin (BC2Tama), and the fusion protein was expressed in Escherichia coli and purified by means of affinity chromatography. BC2Tama was then conjugated with doxorubicin-photocleavable biotin (DOXPCB). The BC2Tama–DOXPCB conjugates were observed to bind to hPSCs followed by internalization. Upon exposure to ultraviolet light, DOX was released inside the cells, which allowed specific killing of the hPSCs. Thus, BC2Tama–DOXPCB should be useful for the targeted elimination of hPSCs contained in hPSC-derived cell therapy products. This is the first report of the generation of lectin–prodrug conjugates. BC2Tama should be applicable for the targeted delivery of various types of biotinylated compounds into hPSCs.     

Mixing of a self-assembled supramolecular polymer and a covalent polymer in organic solutions

We report on a neutron scattering study of the molecular structure of a self-assembled supramolecular polymer composed of a bicopper complex within a solution of a covalent polymer (atactic polystyrene/trans-decalin). The study is achieved by putting two binary phases in contact and allowing for diffusion of both components in either phase. It is shown that the one-dimensional bicopper filaments are compatible to a high extent with the atactic polymer. These results are discussed in the light of a recently devised encapsulation process of the bicopper filaments within the fibrils of a physical network of isotactic polystyrene.     

Rapid Synthesis and Antiproliferative Properties of Polyazamacrocycle-Based Bi- and Tetra-Gold(I) Phosphine Dithiocarbamate Complexes

A family of bi- and tetrametallic gold(I) phosphine dithiocarbamate complexes were synthesized, starting from cyclam and dimethylcyclam polyazamacrocycles, respectively, along with their monometallic gold(I) chloridophosphine precursors. Their antiproliferative properties were evaluated on two cancer cell lines (A549 and NSCLC-N6-L16). Most of the mono- and bimetallic complexes displayed strong activities and, in particular, one bimetallic derivative showed antiproliferative properties in the low micromolar range. Insights into the structure–activity relationships are given, along with determination of the thioredoxin reductase inhibition potential, two-photon imaging of the fluorescent derivatives, and evaluation of gold uptake.     

On the use of models for high-performance scientific computing applications: an experience report

This paper reports on a four-year project that aims to raise the abstraction level through the use of model-driven engineering (MDE) techniques in the development of scientific applications relying on high-performance computing. The development and maintenance of high-performance scientific computing software is reputedly a complex task. This complexity results from the frequent evolutions of supercomputers and the tight coupling between software and hardware aspects. Moreover, current parallel programming approaches result in a mixing of concerns within the source code. Our approach relies on the use of MDE and consists in defining domain-specific modeling languages targeting various domain experts involved in the development of HPC applications, allowing each of them to handle their dedicated model in a both user-friendly and hardware-independent way. The different concerns are separated thanks to the use of several models as well as several modeling viewpoints on these models. Depending on the targeted execution platforms, these abstract models are translated into executable implementations by means of model transformations. To make all of these effective, we have developed a tool chain that is also presented in this paper. The approach is assessed through a multi-dimensional validation that focuses on its applicability, its expressiveness and its efficiency. To capitalize on the gained experience, we analyze some lessons learned during this project.     

An A Contrario Decision Method for Shape Element Recognition

Shape recognition is the field of computer vision which addresses the problem of finding out whether a query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simply sort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is the decision stage, which should aim at giving a clear-cut answer to the question: “do these two shapes look alike?” In this article, the proposed solution consists in bounding the number of false correspondences of the query shape among the database shapes, ensuring that the obtained matches are not likely to occur “by chance”. As an application, one can decide with a parameterless method whether any two digital images share some shapes or not.     

Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation

This paper describes a multi-agent coordination mechanism applied to intersection simulation situations. In a goal of urban traffic simulation, we must consider the dynamic interactions between autonomous vehicles. The field of multi-agent systems provides us some studies for such systems, in particular on the coordination mechanisms. Conflicts between vehicles (i.e. agents) are very frequent in such applications, and they may cause deadlocks, particularly at intersections such as crossroads. Our approach is based on the solving of two player games/decision matrices which characterize three basic situations. An aggregation method generalizes to n-player games for complex crossroads. The objective of this approach consists in searching basic two-player matrices for solving n-agent problems. To explain the principle, we describe our approach for a particular case of crossroad with three agents. Finally, the obtained results have been examined via a tool of road traffic simulation, ARCHISIM. We assume also that the global traffic replicates the behavior of agents in different situations.     

A new tangible user interface for machine learning document review

This paper describes a tool for assisting lawyers and paralegal teams during document review in eDiscovery. The tool combines a machine learning technology (CategoriX) and advanced multi-touch interface capable of not only addressing the usual cost, time and accuracy issues in document review, but also of facilitating the work of the review teams by capitalizing on the intelligence of the reviewers and enabling collaborative work.     

Zero Orders and Dimensions of Some Invariant Subspaces in Linear Structured Systems

In this paper we consider linear structured systems which represent a large class of parameter-dependent linear systems and we study invariants for such systems under a large group of transformations including state feedback. In this context we consider the dimension of the maximal output-nulling invariant subspace of a linear structured system, the number and structure of its invariant zeros and its structure at infinity. We give generic characterizations of the invariants in terms of properties of the directed graph that can be naturally associated with a linear structured system. Date received: March 1, 2002. Date revised: April 1, 2003. The first authors stay at the Laboratoire dAutomatique de Grenoble was supported by grants of the Netherlands Organization for Scientific Research (NWO), the Institut National Polytechnique de Grenoble (INPG) and the French Ministry of Research.