Mass determination of the fatty acids released from tannin-stimulated rabbit alveolar macrophages

Previous studies with macrophages that had been prelabeled with [¹⁴C]arachidonic acid (20∶4) have shown that condensed tannin is a potent agonist for the release of arachidonic acid. However, it has not been demonstrated that the percentage release of [¹⁴C]20∶4 accurately reflects the metabolic activity of the endogenous 20∶4 pool. In order to measure the 20∶4 mass release relative to the total cellular 20∶4 pool, the free fatty acids of freshly isolated alveolar macrophages were derivatized with a fluorescent reagent, and then separated and quantified by high-performance liquid chromatography. The amounts of esterified fatty acids were measured by gas chromatography of the methyl esters. Free fatty acid levels were compared to those of the total esterified plus unesterified fatty acids to determine the actual percentage released of each fatty acid. Tannin-stimulated release of 20∶4 mass reflected that previously reported for the release of [¹⁴C]20∶4 label but at a slower rate and at a much lower percentage indicating that [¹⁴C]20∶4 had been incorporated into part of a more reactive pool. The specificity of the fatty acid release induced by tannin and β-1,3-glucan, a known agonist for 20∶4 release, was also examined. Both agonists promoted an increase in the levels of free 20∶4 and of other fatty acids. A comparison of the absolute increases of each of the fatty acids indicated that tannin caused a preferential increase in the mass of free 20∶4, whereas β-1,3-glucan evoked a selective increase in the mass of 16∶0. Deceased.     

Effects of solid solution alloying on creep deformation of aluminum

The effects of solid solution alloying on the creep-rupture properties, deformation characteristics, ductility, and fracture of pure aluminum were studied by means of creep-rupture tests on polished specimens of three alloys each of Al-Cu (0.24, 0.79, and 2.05 pct Cu), Al-Zn (4.93, 9.89, and 19.78 pct Zn), and Al-Mg (0.94, 1.92, and 5.10 pct Mg) at 500°, 700°, and 900°F.     

Chromium distribution between liquid iron and molten basic slags

An equilibrium study was made of the distribution of chromium and oxygen between liquid iron, containing less than 1 pct Cr, and simple slags of the CaO(MgO)-SiO₂-FeO-Cr₂O₃ type in the temperature range 1526° to 1734°C The effects of slag oxidation, temperature, and basicity were observed.     

A note about the complexity of minimizing Nesterov's smooth Chebyshev–Rosenbrock function

This short note considers and resolves the apparent contradiction between known worst-case complexity results for first- and second-order methods for solving unconstrained smooth nonconvex optimization problems and a recent note by Jarre [On Nesterov's smooth Chebyshev–Rosenbrock function, Optim. Methods Softw. (2011)] implying a very large lower bound on the number of iterations required to reach the solution's neighbourhood for a specific problem with variable dimension.     

Mutual information for Lucas-Kanade Tracking (MILK): an inverse compositional formulation

Mutual Information (MI) is popular for registration via function optimisation. This work proposes an inverse compositional formulation of MI for Levenberg-Marquardt optimisation. This yields a constant Hessian, which may be pre-computed. Speed improvements of 15% were obtained, with convergence accuracies similar to those of the standard formulation.     

Hierarchical classification of protein function with ensembles of rules and particle swarm optimisation

This paper focuses on hierarchical classification problems where the classes to be predicted are organized in the form of a tree. The standard top-down divide and conquer approach for hierarchical classification consists of building a hierarchy of classifiers where a classifier is built for each internal (non-leaf) node in the class tree. Each classifier discriminates only between its child classes. After the tree of classifiers is built, the system uses them to classify test examples one class level at a time, so that when the example is assigned a class at a given level, only the child classes need to be considered at the next level. This approach has the drawback that, if a test example is misclassified at a certain class level, it will be misclassified at deeper levels too. In this paper we propose hierarchical classification methods to mitigate this drawback. More precisely, we propose a method called hierarchical ensemble of hierarchical rule sets (HEHRS), where different ensembles are built at different levels in the class tree and each ensemble consists of different rule sets built from training examples at different levels of the class tree. We also use a particle swarm optimisation (PSO) algorithm to optimise the rule weights used by HEHRS to combine the predictions of different rules into a class to be assigned to a given test example. In addition, we propose a variant of a method to mitigate the aforementioned drawback of top-down classification. These three types of methods are compared against the standard top-down hierarchical classification method in six challenging bioinformatics datasets, involving the prediction of protein function. Overall HEHRS with the rule weights optimised by the PSO algorithm obtains the best predictive accuracy out of the four types of hierarchical classification method.     

Rational wavelet decompositions of transfer functions in hardy-sobolev classes

The model approximation of transfer functions using rational wavelets (or molecular decompositions) is considered. By using techniques from Hardy-Sobolev spaces it is shown that Hilbert space methods such as a modified matching-pursuit algorithm and least-squares technique can be employed to obtain good approximations in bothH ² andH norms. Several theoretical results are given on rates of convergence when the methods are applied to delay systems and fractional filters.The research of the first author was supported by E.P.S.R.C.