Control of morphology and nanostructure of copper and cobalt oxalates: effect of complexing ions, polymeric additives and molecular weight

Precipitated oxalates are often nanostructured and can be used as precursors for nanostructured oxides for different applications. The modification of the particle shape and nanostructures of both copper and cobalt oxalates has been demonstrated using polymeric additives or complexing counter-ions. In the case of cobalt oxalate the characteristic elongated rod particle shape (axial ratio of 10) can be modified by using polymethymethacrylate (PMMA) to produce particles with lower axial ratios of 2, through cubes all the way to platelets (axial ratio 0.2). The PMMA inhibits the growth of the particles along the [101] direction more and more strongly as the concentration of the polymer increases. The crystallite size from XRD line broadening is not modified by the PMMA indicating that the PMMA does not influence the nucleation and growth but modifies the aggregation kinetics. Copper oxalates precipitated in the presence of different cellulose derived polymers with different molecular weights and functional groups (methyl and propyl) showed sensitivity to both molecular weight and functional group. Higher molecular weights did not influence the copper oxalate particle shape, whereas methyl cellulose gave elongated particles and propyl celluloses gave platelet like particles. Copper oxalate precipitated in the presence of acetate counter ions gave platelets with an axial ratio of 0.15 compared to the cushion-like morphology (axial ratio 0.5). The primary crystallites were more elongated along the [001] direction in the presence of acetate, modifying the proportion of the hydrophobic and hydrophilic surfaces and hence influencing the aggregation kinetics and particle shape. The copper and cobalt oxalate particle formation seems to be dominated by the primary particle aggregation with the different additives interacting specifically with different crystallographic faces of the primary particles. By tuning this interaction particles with different shapes and substructures can be formed.     

A survey of models and algorithms for winter road maintenance. Part IV: Vehicle routing and fleet sizing for plowing and snow disposal

This is the last part of a four-part survey of optimization models and solution algorithms for winter road maintenance planning. The two first parts of the survey address system design problems for winter road maintenance. The third part concentrates mainly on vehicle routing problems for spreading operations. The aim of this paper is to provide a comprehensive survey of optimization models and solution methodologies for the routing of vehicles for plowing and snow disposal operations. We also review models for the fleet sizing and fleet replacement problems.     

EM procedures using mean field-like approximations for Markov model-based image segmentation

Image segmentation using Markov random fields involves parameter estimation in hidden Markov models for which the EM algorithm is widely used. In practice, difficulties arise due to the dependence structure in the models and approximations are required. Using ideas from the mean field approximation principle, we propose a class of EM-like algorithms in which the computation reduces to dealing with systems of independent variables. Within this class, the simulated field algorithm is a new stochastic algorithm which appears to be the most promising for its good performance and speed, on synthetic and real image experiments.     

Boosting support vector machines for imbalanced data sets

Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed vector spaces or lack of information. Common approaches for dealing with the class imbalance problem involve modifying the data distribution or modifying the classifier. In this work, we choose to use a combination of both approaches. We use support vector machines with soft margins as the base classifier to solve the skewed vector spaces problem. We then counter the excessive bias introduced by this approach with a boosting algorithm. We found that this ensemble of SVMs makes an impressive improvement in prediction performance, not only for the majority class, but also for the minority class.     

Tetrahydroindoles as Multipurpose Screening Compounds and Novel Sirtuin Inhibitors

Indoles are privileged structures in medicinal and bioorganic chemistry that are particularly well suited to serve as platforms for diversity. Among many other therapeutic areas, the indole scaffold has been used to design aromatic compounds useful to interfere with enzymes engaged in the regulation of substrate acylation status, such as sirtuins. However, the planarity of the indole ring is not necessarily optimal for all target enzymes, especially when functionalization with aromatic side chains is required. Replacement of flat scaffolds by nonplanar molecular cores dominated by sp³ hybridization is a common strategy to avoid the disadvantages associated with poor solubility and high promiscuity, while covering less-well-explored areas of chemical space. Thus, we synthesized fragment-like tetrahydroindoles suitable for fragment-based drug discovery as well as a well-characterized small library intended as multipurpose screening compounds. For proof of principle, these compounds were screened against sirtuins 1–3, enzymes known to be addressable by indoles. We found that 2,6,6-trimethyl-4-oxo-4,5,6,7-tetrahydro-1H-indole-3-carboxamides are potent and selective SIRT2 inhibitors. Compound 16 t displayed an IC₅₀ value of 0.98 μm and could serve as exquisite starting point for hit-to-lead profiling.     

Near-Field Electron Energy Loss Spectroscopy in Porous Silicon

First results of an Electron Energy Loss Spectroscopy in the Near Field (NFEELS) mode of n⁺ porous silicon are described here. Sequences of EELS spectra in the low loss energy range (0–30 eV) were recorded, using a scanning transmission electron microscope, as the e-beam was scanned across a nano-hole surrounded by Si platelets. This technique is shown to be very sensitive to spectral and spatial changes in the electromagnetic field distribution outside the surface of nanoparticles, governed by their local nature and shape.     

Variable energy positron beam study of Xe-implanted uranium oxide

Doppler broadening of annihilation gamma-line combined with a slow positron beam was used to measure the momentum density distribution of annihilating pair in a set of sintered UO₂ samples. The influence of surface polishing, of implantation with 800-keV ¹³⁶Xe²⁺ at fluences of 1 × 10¹⁵ and 1 × 10¹⁶ Xe cm^?2, and of annealing were studied by following the changes of the momentum distribution shape by means of S and W parameters. The program used for this purpose was VEPFIT. At the two fluences in the stoichiometric as-implanted UO₂, formation of Xe bubbles was not detected. The post-implantation annealing and over-stoichiometry in the as-implanted sample caused Xe precipitation and formation of Xe bubbles.