Adaptive and multi-mining versions of the DM-GRASP hybrid metaheuristic

Metaheuristics represent an important class of techniques to solve, approximately, hard combinatorial optimization problems for which the use of exact methods is impractical. Some researches have been combining machine learning techniques with metaheuristics to adaptively guide and improve the search for near optimal solutions. An example of such development is the DM-GRASP, a hybrid version of the Greedy Randomized Adaptative Search Procedures (GRASP) metaheuristic which incorporates a data mining process. In this hybrid proposal, after executing half of the total number of iterations, the data mining process extracts patterns from an elite set of sub-optimal solutions for the optimization problem. These patterns present characteristics of near optimal solutions and can be used to guide the following half GRASP iterations in the search through the solution space. In this work, we explore new versions of the DM-GRASP metaheuristic to experiment, not a single activation, but multiple and adaptive executions of the data mining process during the metaheuristic execution. We also applied the data mining technique into a reactive GRASP to show that a more sophisticated and not memoryless GRASP approach can also benefit from the use of this technique. In order to evaluate these new proposals, we adopted the server replication for reliable multicast problem since the best known results for this problem were obtained by GRASP and DM-GRASP implementations. The computational experiments, comparing traditional GRASP, DM-GRASP, and the new proposals, showed that multiple and adaptive executions of the data mining process can improve the results obtained by the DM-GRASP hybrid metaheuristic—the new proposals were able to find better results in less computational time for the reliable multicast problem.     

Interval Methods for Model Qualification: Methodology and Advanced Application

An actual model in simulation (e.g. in chemistry) or control (e.g. in robotics) is often too complex to use, and sometimes impossible to obtain. To handle a system in practice, a simplification of the real model is often necessary. This simplification goes through some hypotheses made on the system or the modeling approach. These hypotheses are rarely verified whereas they could lead to an inadmissible model, over approximated for its use. In this paper, we propose a method that qualifies the simplification validity for all models that can be expressed by real-valued variables involved in closed-form relations and depending on parameters. We based our approach on a verification of a quality threshold on the hypothesis relevance. This method, based on interval analysis, checks the acceptance of the hypothesis in a full range of the whole model space, and gives bounds on the quality threshold and on the model parameters. Our approach is experimentally validated on a robotic application.     

Bubble dynamics: Long-time behavior and interaction in viscous liquids

A mathematical two-phase model is used to numerically investigate physical and rheological effects on small, individual bubbles in high-viscosity liquids under pressure impact. It is found out that bubbles remain stable over time at high viscosity and surface tension. The steady case is considered and connected to the stability behavior of the bubble. An upper bound for the bubble radius is derived and the new equilibrium state of the bubble can be predicted by means of stability theorems of differential equations. Finally, the interaction of a limited number of well separated bubbles in an Hele-Shaw flow is mathematically analyzed to visualize and physically interpret their trajectories. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Multibody dynamics with unilateral constraints and friction

In the view of robotics or granular media mechanics, we ask for the statement of the dynamical evolution problem for multibody systems with contacts and friction. The “event driven” approach does not allow to state an evolution problem in a systematic way: it gives a peculiar status to the instants of impact and to the contact points although they are unknowns of the problem. This matter of fact has given rise to a new approach in the frictionless case [4, 6] we generalize to the case including friction. Following to the point of view of Lagrange on the equation of the dynamics, we emphasize the systematic use of virtual powers and duality. This bias suggests to put emphasis on generalized reaction forces in the statement of the evolution problem and not on local reaction forces of the real world. This point of view allows to escape from pathologies e.g. Painlevé paradox [5] and Kane Paradox [3]. The proposed evolution problem accounts for impacts and friction in case of multiple unilateral constraints. We prove the existence and uniqueness of the solution to the associated rate problem. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

New results and applications for multi-secret sharing schemes

In a multi-secret sharing scheme (MSSS), \(\ell \) different secrets are distributed among the players in some set \(\mathcal{P }=\{P_1,\ldots ,P_n\}\) , each one according to an access structure. The trivial solution to this problem is to run \(\ell \) independent instances of a standard secret sharing scheme, one for each secret. In this solution, the length of the secret share to be stored by each player grows linearly with \(\ell \) (when keeping all other parameters fixed). Multi-secret sharing schemes have been studied by the cryptographic community mostly from a theoretical perspective: different models and definitions have been proposed, for both unconditional (information-theoretic) and computational security. In the case of unconditional security, there are two different definitions. It has been proved that, for some particular cases of access structures that include the threshold case, a MSSS with the strongest level of unconditional security must have shares with length linear in \(\ell \) . Therefore, the optimal solution in this case is equivalent to the trivial one. In this work we prove that, even for a more relaxed notion of unconditional security, and for some kinds of access structures (in particular, threshold ones), we have the same efficiency problem: the length of each secret share must grow linearly with \(\ell \) . Since we want more efficient solutions, we move to the scenario of MSSSs with computational security. We propose a new MSSS, where each secret share has constant length (just one element), and we formally prove its computational security in the random oracle model. To the best of our knowledge, this is the first formal analysis on the computational security of a MSSS. We show the utility of the new MSSS by using it as a key ingredient in the design of two schemes for two new functionalities: multi-policy signatures and multi-policy decryption. We prove the security of these two new multi-policy cryptosystems in a formal security model. The two new primitives provide similar functionalities as attribute-based cryptosystems, with some advantages and some drawbacks that we discuss at the end of this work.     

Rinneite,K3Na[FeCl6], at 293, 84 and 9.5 K

The crystal structure of tripotassium sodium hexa­chloro­ferrate(II) has been determined by X‐ray diffraction at 293, 84 and 9.5 K. The accurate and extensive data sets collected should be suitable for charge–density analysis studies.     

Microwave-assisted synthesis of α-ethoxycarbamates

An efficient and reproducible synthesis of various α-ethoxycarbamates is described via a microwave heating mode. Compared to the thermal process, the microwave dielectric heating induces a dramatic reduction of the reaction time and the improvement of the yields. The reaction is general since applicable to aromatic and aliphatic aldehydes with various primary amines. Several examples involving chiral aldehydes have also been considered.     

Concentration-Dependent Interactions of Amphiphilic PiB Derivative Metal Complexes with Amyloid Peptides Aβ and Amylin**

Metal chelates targeted to amyloid peptides are widely explored as diagnostic tools or therapeutic agents. The attachment of a metal complex to amyloid recognition units typically leads to a decrease in peptide affinity. We show here that by separating a macrocyclic GdL chelate and a PiB targeting unit with a long hydrophobic C10 linker, it is possible to attain nanomolar affinities for both Aβ_1-40 (K_d=4.4 nm ) and amylin (K_d=4.5 nm ), implicated, respectively in Alzheimer's disease and diabetes. The Scatchard analysis of surface plasmon resonance data obtained for a series of amphiphilic, PiB derivative GdL complexes indicate that their Aβ_1-40 or amylin binding affinity varies with their concentration, thus micellar aggregation state. The GdL chelates also affect peptide aggregation kinetics, as probed by thioflavin-T fluorescence assays. A 2D NMR study allowed identifying that the hydrophilic region of Aβ_1-40 is involved in the interaction between the monomer peptide and the Gd³⁺ complex. Finally, ex vivo biodistribution experiments were conducted in healthy mice by using ¹¹¹In labeled analogues. Their pancreatic uptake, ∼3 %ID g⁻¹, is promising to envisage amylin imaging in diabetic animals.     

Experimental and Computational Study on the Anti-Markovnikov Hydrofunctionalization of Olefins Using Glycine-Extended AQ-Auxiliaries

Two similar tridentate directing groups derived from glycine and 8-aminoquinoline were shown to enable the palladium-catalyzed anti-Markovnikov hydrofunctionalization of 4-pentenylamine with drastically different efficiencies. A computational investigation into the origin of the reactivity difference between these isomeric, carbonyl-transposed auxiliaries suggests that protonation state, thus charge of the substrate-metal complex prior to nucleopalladation is key. These investigations have culminated in a directing group design that can undergo Pd-catalyzed hydrofunctionalization under relatively mild conditions, as low as room temperature.