A feasible direction algorithm for general nonlinear semidefinite programming

This paper deals with nonlinear smooth optimization problems with equality and inequality constraints, as well as semidefinite constraints on nonlinear symmetric matrix-valued functions. A new semidefinite programming algorithm that takes advantage of the structure of the matrix constraints is presented. This one is relevant in applications where the matrices have a favorable structure, as in the case when finite element models are employed. FDIPA_GSDP is then obtained by integration of this new method with the well known Feasible Direction Interior Point Algorithm for nonlinear smooth optimization, FDIPA. FDIPA_GSDP makes iterations in the primal and dual variables to solve the first order optimality conditions. Given an initial feasible point with respect to the inequality constraints, FDIPA_GSDP generates a feasible descent sequence, converging to a local solution of the problem. At each iteration a feasible descent direction is computed by merely solving two linear systems with the same matrix. A line search along this direction looks for a new feasible point with a lower objective. Global convergence to stationary points is proved. Some structural optimization test problems were solved very efficiently, without need of parameters tuning.     

Surface Lagrangian Remeshing: A new tool for studying long term evolution of continental lithosphere from 2D numerical modelling

In this paper we present a new local remeshing algorithm that is dedicated to the problem of erosion in finite element models whose grid follows the movement of the free surface. The method, which we name Surface Lagrangian Remeshing (SLR), is adapted to 2D Lagrangian models which couple surface erosion with deformation of Earth materials. The remeshing procedure preserves nodes defining the surface submitted to erosion and removes nodes belonging to surface elements whose internal angles or area is critically low. This algorithm is ideally suited to track long term surface evolution. To validate the method we perform a set of numerical tests, using triangular finite elements, which compare the results obtained with the SLR algorithm with global remeshing and with analytical results. The results show good agreements with analytical solutions. Interpolation errors associated with remeshing are generated locally and numerical diffusion is restricted to the remeshed domain itself. In addition this method is computationally costless compared to classical global remeshing algorithm. We propose to couple the SLR method with the Dynamical Lagrangian Remeshing (DLR) algorithm to enable local remeshing only of Lagrangian models coupling large deformation of Earth materials with large erosion.     

SIMUL 3.2: An Econometric Tool for Multidimensional Modelling

Initially developed in the context of ${\tt REGILINK}$ project, ${\tt SIMUL 3.2}$ econometric software is able to estimate and to run large-scale dynamic multi-regional, multi-sectoral models. The package includes a data bank management module, ${\tt GEBANK}$ which performs the usual data import/export functions, and transformations (especially the RAS and the aggregation one), a graphic module, ${\tt GRAPHE}$ , a cartographic module, ${\tt GEOGRA}$ for a “typical use”. For an “atypical use” the package includes ${\tt CHRONO}$ to help for the WDC (Working Days Correction) estimation and ${\tt GNOMBR}$ to replace the floating point arithmetic by a multi-precision one in a program. Although the current package includes a basic estimation’s (OLS) and solving’s (Gauss–Seidel) algorithms, it allows user to implement the equations in their reduced form ${Y_{r,b}=X_{r,b} + \varepsilon}$ and to use alternative econometric equations. ${\tt SIMUL}$ provides results and reports documentation in ASCII and ${\hbox{\LaTeX}}$ formats. The next releases of ${\tt SIMUL}$ should improve the OLS procedure according to the Wilkinson’s criteria, include Hildreth–Lu’s algorithm and comparative statics option. Later, the package should allow other models implementations (Input–Output, VAR etc.). Even if it’s probably outclassed by the major softwares in terms of design and statistic tests sets, ${\tt SIMUL}$ provides freely basic evolutive tools to estimate and run easily and safety some large scale multi-sectoral, multi-regional, econometric models.     

An Extended Empirical Valence Bond Model for Describing Proton Mobility in Water

In order to study the microscopic nature of the hydrated proton and its transport mechanism, we have introduced a multistate empirical valence bond model, fitted to ab initio results. This model was applied to the study, at low computational cost, of the structure and dynamics of an excess proton in liquid water. The quantum character of the proton is included by means of an effective parametrization of the model using preliminary path-integral calculations. The mechanism of proton transfer is interpreted as the translocation of a special O–H⁺–O bond along the hydrogen network, i.e., a series of reactions of the form H₅O₂⁺ + H₂O ⇌ H₂O + H₅O₂⁺, rather than H₃O⁺ + H₂O → H₂O + H₃O⁺ as usually described. The translocation of the special bond can be described as a diffusion process with a jump time of 1 ps. A time-dependent correlation function analysis of the special pair relaxation yields two timescales, 0.3 and 3.5 ps. The first time is attributed to the interconversion between a delocalized (H₅O₂⁺-like) and a localized (H₉O₄⁺-like) form of the hydrated proton within a given special pair. The second one is the relaxation time of the special pair, including return trajectories. The computed diffusion constant, as well as the isotopic substitution effect, are in good agreement with experiment. The hydration structure around the excess proton is discussed in terms of various radial distribution functions around the water molecules involved in the special pair and those in the first solvation shell. The hydrogen-bond-dynamics which accompanies the translocation process is studied statistically. The “Moses mechanism” proposed by Noam Agmon for proton mobility in water is partially verified by our simulations.     

Engineering Liganded Gold Nanoclusters as Efficient Theranostic Agents for Cancer Applications

Luminescent gold nanoclusters are rapidly gaining attention as efficient theranostic targets for imaging and therapeutics. Indeed, their ease of synthesis, their tunable optical properties and tumor targeting make them potential candidates for sensitive diagnosis and efficacious therapeutic applications. This concept highlights the key components for designing gold nanoclusters as efficient theranostics focusing on application in the field of oncology.     

A comparison tool between two ASN.1 specifications

ASN.1 (Abstract Syntax Notation number One) is a standardized formal notation used to describe data exchanged between heterogeneous systems. An ASN.1 specification consists of modules which break down into formal definitions. When a protocol is updated, a new version of its ASN. 1 specification is produced. To keep interoperability between applications which support different versions of the same protocol, the specifier has to ensure that the new modules are compatible with the old ones. Our comparator, based on a complete formalization of comparison rules, can indicate the potential incompatibilities between ASN. 1:1997 specifications.     

Learning–testing process in classroom: An empirical simulation model

This paper presents an empirical micro-simulation model of the teaching and the testing process in the classroom (Programs and sample data are available – the actual names of pupils have been hidden). It is a non-econometric micro-simulation model describing informational behaviors of the pupils, based on the observation of the pupils’ communication behavior during lessons and tests. The representation of the knowledge process is very simplified. However, we tried to study the involvements of individual motivation, capability and relationship with other pupils of each pupil, to compare them to the new-classical (and keynesian) and Austrian information and knowledge theoretical results. It is a first step and future development should concern expectation behaviors and dynamics. This paper aims too to give, we hope so, some criteria of pupils’ rationality in the classroom.     

Comparative analysis of CRISPR loci in lactic acid bacteria genomes

Clustered regularly interspaced short palindromic repeats (CRISPR) are hypervariable loci widely distributed in bacteria and archaea, that provide acquired immunity against foreign genetic elements. Here, we investigate the occurrence of CRISPR loci in the genomes of lactic acid bacteria (LAB), including members of the Firmicutes and Actinobacteria phyla. A total of 102 complete and draft genomes across 11 genera were studied and 66 CRISPR loci were identified in 26 species. We provide a comparative analysis of the CRISPR/cas content and diversity across LAB genera and species for 37 sets of CRISPR loci. We analyzed CRISPR repeats, CRISPR spacers, leader sequences, and cas gene content, sequences and architecture. Interestingly, multiple CRISPR families were identified within Bifidobacterium, Lactobacillus and Streptococcus, and similar CRISPR loci were found in distant organisms. Overall, eight distinct CRISPR families were identified consistently across CRISPR repeats, cas gene content and architecture, and sequences of the universal cas1 gene. Since the clustering of the CRISPR families does not correlate with the classical phylogenetic tree, we hypothesize that CRISPR loci have been subjected to horizontal gene transfer and further evolved independently in select lineages, in part due to selective pressure resulting from phage predation. Globally, we provide additional insights into the origin and evolution of CRISPR loci and discuss their contribution to microbial adaptation.     

Choosing the optimal hidden Markov model for secondary-structure prediction

Proteins are major constituents of living cells, forming many cellular components and most enzymes. So, knowledge of 3D protein structures is essential to understand biological mechanisms. Researchers often use neural networks to predict secondary structure in proteins, but the networks can be hard to interpret. This alternative method uses an optimal and interpretable hidden Markov model to classify protein residues. These HMM models account for the transitions observed in 3D structures and allow a predictive approach. We've developed a method for finding an optimal HMM to classify residues into secondary-structure classes. HMMs both provide a probabilistic framework for sequence treatment and produce interpretable models.     

Feedback mechanisms for global oscillations in Lure systems

The paper presents two mechanisms for global oscillations in feedback systems, based on bifurcations in absolutely stable systems. The external characterization of the oscillators provides the basis for a (energy-based) dissipativity theory for oscillators, thereby opening new possibilities for rigorous stability analysis of high-dimensional systems and interconnected oscillators.