Ring‐opening polymerization of lactones initiated by diphenylzinc–coinitiator systems

Diphenylzinc, alone or in combination with water and butanone as coinitiators, was used as a polymerization initiator system for a variety of lactones at varying temperatures. The resulting data indicate that the course of the polymerization is greatly influenced by the lactone structure, as well as by the molar ratio of coinitiator to diphenylzinc. When used alone, diphenylzinc exhibited high activity as an initiator in δ‐valerolactone polymerizations, although it was less efficient when used in the β‐butyrolactone and the β‐propiolactone polymerizations. Activity in the polymerization of β‐lactones was increased by adding small amounts of butanone or water. It was also observed that the diphenylzinc–butanone combination was more effective than the diphenylzinc–water mixture in the polymerizations of β‐butyrolactone and β‐propiolactone. Copyright © 2003 Society of Chemical Industry     

Electrical Properties of GeO2–NiO Materials Containing Ni2GeO4

The GeO₂–NiO system is studied in the stability range of Ni₂GeO₄ by temperature-dependent resistivity measurements, in combination with x-ray diffraction, differential thermal analysis, and thermogravimetry. The resistivity of the starting mixtures and heat-treated samples is measured in the composition range 55–90 mol % NiO. The effect of air humidity on the resistivity of the samples is examined.     

A multigrid accelerated hybrid unstructured mesh method for 3D compressible turbulent flow

 A cell vertex finite volume method for the solution of steady compressible turbulent flow problems on unstructured hybrid meshes of tetrahedra, prisms, pyramids and hexahedra is described. These hybrid meshes are constructed by firstly discretising the computational domain using tetrahedral elements and then by merging certain tetrahedra. A one equation turbulence model is employed and the solution of the steady flow equations is obtained by explicit relaxation. The solution process is accelerated by the addition of a multigrid method, in which the coarse meshes are generated by agglomeration, and by parallelisation. The approach is shown to be effective for the simulation of a number of 3D flows of current practical interest. Sponsored by The Research Council of Norway, project number 125676/410 Dedicated to the memory of Prof. Mike Crisfield, a respected colleague     

Finding all hops shortest paths

In this letter, we introduce and investigate a new problem referred to as the All Hops Shortest Paths (AHSP) problem. The AHSP problem involves selecting, for all hop counts, the shortest paths from a given source to any other node in a network. We derive a tight lower bound on the worst-case computational complexities of the optimal comparison-based solutions to AHSP.     

High-efficiency LEDs of 1.6–2.4 µm spectral range for medical diagnostics and environment monitoring

High efficient LED structures covering the spectral range of 1.6–2.4 μm have been developed on the basis of GaSb and its solid solutions. The electroluminescent characteristics and their temperature and current dependences have been studied. The radiative and nonradiative recombination mechanisms and their effect on the quantum efficiency have been investigated. A quantum efficiency of 40–60% has been obtained in the quasi-steady mode at room temperature. A short-pulse optical power of 170 mW was reached. __________ Translated from Fizika i Tekhnika Poluprovodnikov, Vol. 37, No. 8, 2003, pp. 996–1009. Original Russian Text Copyright ? 2003 by Stoyanov, Zhurtanov, Astakhova, Imenkov, Yakovlev.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.     

Switched-Current Filters Revisited: Square-Root Domain Sampled-Data Filters

In this brief, the well-known switched-current (SI) filtering technique is revisited using the concept of the square-root domain (SRD) filtering. It is proved that SI filters are a subclass of the SRD filters, where sampled-data signal processing is performed. This is achieved by considering typical lossless and lossy SRD sampled-data integrator configurations, using a set of complementary SRD operators which are based on the quadratic I-V relationship of MOS transistor operated in the saturation. Circuit examples are given, where linear-domain integrator and third-order filter configurations were derived using appropriate SRD sampled-data building blocks