Fitness Landscape Analysis and Metaheuristics Efficiency

Landscape analysis has been identified as a promising way to develop efficient optimization methods. Nevertheless, the links between properties of the landscape and efficiency of methods is not easy to understand. In this article, we propose to give a contribution in this field using a vehicle routing problem as an illustration. Metaheuristics use a neighborhood operator that connects solutions of the search space. Thus, this operator acts on the dynamics of the search and impacts metaheuristics efficiency. Therefore, we characterize two landscapes differenciated by their neighborhood function and then, we analyze the performance of classical metaheuristics using one or the other neighborhood operator. Finally, a discussion provides insights on the relations between results of the landscape analysis and results of methods performance.     

The first three anisotropy constants of nickel

The technique of ferromagnetic resonance at 23 GHz has been used to determine the first three anisotropy constants of pure Ni down to 4.2K. A temperature and orientation dependent linewidth has also been observed.     

Ruthenium(III) readily abstracts NO from L-arginine,the physiological precursor to NO,in the presence of H2O2. A remarkably simple model system for NO synthases

Reaction of [Ru(Hedta)Cl]- with H2O2 in the presence of arginine, produces NO, in the form of an Ru(II)-(NO+) complex and citrulline which is a remarkably simple model system for the physiological NO synthase reaction.     

Monohydroxamic acids and bridging dihydroxamic acids as chelators to ruthenium(III) and as nitric oxide donors: syntheses, speciation studies and nitric oxide releasing investigations

The synthesis and spectroscopic characterisation of novel mononuclear Ru(III)(edta)(hydroxamato) complexes of general formula [Ru(H2edta)(monoha)] (where monoha = 3- or 4-NH2, 2-, 3- or 4-C1 and 3-Me-phenylhydroxamato), as well as the first example of a Ru(III)-N-aryl aromatic hydroxamate, [Ru(H2edta)(N-Me-bha)].H2O (N-Me-bha = N-methylbenzohydroxamato) are reported. Three dinuclear Ru(III) complexes with bridging dihydroxamato ligands of general formula [{Ru(H2edta)}2(mu-diha)] where diha = 2,6-pyridinedihydroxamato and 1,3- or 1,4-benzodihydroxamato, the first of their kind with Ru(III), are also described. The speciation of all of these systems (with the exception of the Ru-1,4-benzodihydroxamic acid and Ru-N-methylbenzohydroxamic systems) in aqueous solution was investigated. We previously proposed that nitrosyl abstraction from hydroxamic acids by Ru(III) involves initial formation of Ru(III)-hydroxamates. Yet, until now, no data on the rate of nitric oxide (NO) release from hydroxamic acids has been published. We now describe a UV-VIS spectroscopic study, where we monitored the decrease in the ligand-to-metal charge-transfer band of a series of Ru(III)-monohydroxamates with time, with a view to gaining an insight into the NO-releasing properties of hydroxamic acids.     

Novel platinum(II) ammine hydroxamate and hydroximate complexes and the platinum-assisted hydrolysis of hydroxamic acids

The 2-pyridinecarboxylate (2-pyca) platinum(IV) complex [2-pycaH2][PtCl4(2-pyca)].H2O, 1, has been synthesised from K2[PtCl4] following the hydrolysis of 2-pyridinehydroxamic acid (2-pyhaH) in the presence of H2O2, and directly from K2[PtCl6] and picolinic acid. Structural characterisation of 1 reveals octahedral geometry about platinum(IV) consisting of a (N,O)-bidentate pyridinecarboxylate ligand and four chloride ligands. A mechanism for the hydrolysis of 2-pyridinehydroxamic acid to 2-pyridinecarboxylic acid is proposed. Two novel coordination modes of hydroxamic acids to platinum(II) are also reported. The dinuclear platinum ammine hydroximato complex, [{cis-Pt(NH3)2}2(mu-2-pyhaH(-1))](ClO4)2.H2O, 3, has been synthesised where the two platinum(II) centres are bridged via(O,O) and (N,N) coordination. The latter coordination mode is via the hydroximate nitrogen and the pyridine nitrogen. The corresponding mononuclear platinum(II) pyridinehydroxamate complex, [cis-Pt(NH3)2(2-pyha)]ClO4, 4, has been synthesised. Spectroscopic studies indicate that the coordination mode is through the pyridine nitrogen and hydroxamate oxygen atoms (N,O).     

Manifold preprocessing for laser‐induced breakdown spectroscopy under Mars conditions

Laser‐induced breakdown spectroscopy (LIBS) is currently being used onboard the Mars Science Laboratory rover Curiosity to predict elemental abundances in dust, rocks, and soils using a partial least squares regression model developed by the ChemCam team. Accuracy of that model is constrained by the number of samples needed in the calibration, which grows exponentially with the dimensionality of the data, a phenomenon known as the curse of dimensionality. LIBS data are very high dimensional, and the number of ground‐truth samples (i.e., standards) recorded with the ChemCam before departing for Mars was small compared with the dimensionality, so strategies to optimize prediction accuracy are needed. In this study, we first use an existing machine learning algorithm, locally linear embedding (LLE), to combat the curse of dimensionality by embedding the data into a low‐dimensional manifold subspace before regressing. LLE constructs its embedding by maintaining local neighborhood distances and discarding large global geodesic distances between samples, in an attempt to preserve the underlying geometric structure of the data. We also introduce a novel supervised version, LLE for regression (LLER), which takes into account the known chemical composition of the training data when embedding. LLER is shown to outperform traditional LLE when predicting most major elements. We show the effectiveness of both algorithms using three different LIBS datasets recorded under Mars‐like conditions. Copyright © 2015 John Wiley & Sons, Ltd.