Biotransformation of l‐menthol by twelve isolates of soil‐borne plant pathogenic fungi (Rhizoctonia solani) and classification of fungi

The microbial transformation of l‐menthol ( 1 ) was investigated by using 12 isolates of soil‐borne plant pathogenic fungi, Rhizoctonia solani (AG‐1‐IA Rs24, Joichi‐2, RRG97‐1; AG‐1‐IB TR22, R147, 110.4; AG‐1‐IC F‐1, F‐4, P‐1; AG‐1‐ID RCP‐1, RCP‐3, and RCP‐7) as a biocatalyst. Rhizoctonia solani F‐1, F‐4 and P‐1 showed 89.7–99.9% yields of converted product from 1 , RCP‐1, RCP‐3, and RCP‐7 26.0–26.9% and the other isolates 0.1–12.0%. In the cases of F‐1, F‐4 and P‐1, substrate 1 was converted to (?)‐(1S,3R,4S,6S)‐6‐hydroxymenthol ( 2 ), (?)‐(1S,3R,4S)‐1‐hydroxymenthol ( 3 ) and (+)‐(1S,3R,4R,6S)‐6,8‐dihydroxymenthol ( 4 ), which was a new compound. Substrate 1 was converted to 2 and/or 3 by RRG97‐1, 110.4, RCP‐1, RCP‐3 and RCP‐7. The structures of the metabolic products were elucidated on the basis of their spectral data. In addition, metabolic pathways of the biotransformation of 1 by Rhizoctonia solani are discussed. Finally, from the main component analysis and the differences in the yields of converted product from 1 , the 12 isolates of Rhizoctonia solani were divided into three groups based on an analysis of the metabolites. Copyright © 2003 Society of Chemical Industry     

Electronic properties of magnetically doped nanotubes

Effect of doping of carbon nanotubes by magnetic transition metal atoms has been considered in this paper. In the case of semiconducting tubes, it was found that the system has zero magnetization, whereas in metallic tubes the valence electrons of the tube screen the magnetization of the dopants: the coupling to the tube is usually antiferromagnetic (except for Cr).     

New fault locating system for air-insulated substations usingoptical current detector

The authors present the basic philosophy, construction, design features, and test results of a new fault locating system. This fault locating system helps to shorten the time required for restoration of service after the occurrence of a busbar fault in an air-insulated distribution substation. Recent optical and electronic technologies allow the design of a highly accurate and compact fault locating system which consists of optical current detectors using the Faraday effect and a fault locating processor using a digital data processing technique. The fault location is carried out by discriminating between the directions of zero-sequence currents. Through various tests and field operations, it has been confirmed that the system has sufficient performance for practical applications     

Ligand density-dependent influence of arginine–glycine–aspartate functionalized gold nanoparticles on osteogenic and adipogenic differentiation of mesenchymal stem cells

Extracellular matrix (ECM) plays a very important role in regulating cell function and fate. It is highly desirable to fabricate biomimetic models to investigate the role of ECM in stem cell differentiation. In this study, arginine–glycine–aspartate (RGD)-modified gold nanoparticles (Au NPs) with tunable surface ligand density were prepared to mimic the ECM microenvironment. Their effect on osteogenic and adipogenic differentiation of human mesenchymal stem cells (MSCs) was investigated. The biomimetic Au NPs were taken up by MSCs in a ligand density-dependent manner. The biomimetic NPs with a high RGD density had an inhibitive effect on the alkaline phosphatase (ALP) activity, calcium deposition, and osteogenic marker gene expression of MSCs. Their effect on oil droplet formation and adipogenic marker gene expression was negative when RGD density was low, while their effect was promotive when RGD density was high. The biomimetic Au NPs regulated the osteogenic and adipogenic differentiation of MSCs mainly through affecting the focal adhesion and cytoskeleton. This study highlights the roles of biomimetic NPs on stem cell differentiation that could provide a meaningful strategy in fabricating functional biomaterials for tissue engineering and biomedical applications.

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Prediction and analysis of flow behavior of a polymer melt through nanochannels using artificial neural network and statistical methods

A new methodology, namely, artificial neural network (ANN) approach was proposed for modeling and predicting flow behavior of the polyethylene melt through nanochannels of nanoporous alumina templates. Wetting length of the nanochannels was determined to be a function of time, temperature, diameter of nanochannels, and surface properties of the inner wall of the nanochannels. An ANN was designed to forecast the relationship between the length of wetting as output parameter and other aforementioned parameters as input variables. It was demonstrated that the ANN method is capable of modeling this phenomenon with high accuracy. The designed ANN was then employed to obtain the wetting length of the nanochannels for those cases, which were not reported by the wetting experiments. The results were then analyzed statistically to identify the effect of each independent variable, namely, time, temperature, diameter of nanochannels, and surface properties of the inner wall of nanochannels as well as their combinations on the wetting length of the nanochannels. Interesting results were attained and discussed.     

Failure detection and consensus in the crash-recovery model

Summary. We study the problems of failure detection and consensus in asynchronous systems in which processes may crash and recover, and links may lose messages. We first propose new failure detectors that are particularly suitable to the crash-recovery model. We next determine under what conditions stable storage is necessary to solve consensus in this model. Using the new failure detectors, we give two consensus algorithms that match these conditions: one requires stable storage and the other does not. Both algorithms tolerate link failures and are particularly efficient in the runs that are most likely in practice – those with no failures or failure detector mistakes. In such runs, consensus is achieved within time and with 4 n messages, where is the maximum message delay and n is the number of processes in the system. Received: May 1998 / Accepted: November 1999