Earticle

The catalytic dehydrocoupling of bis(1-sila-3-butyl)benzene 1 and 2-phenyl-1,3-disilapropane 2 by Cp2ZrCl2/Red-Al and Cp2ZrCl2/n-BuLi was reported to compare their catalytic efficiency. The dehydrocoupling of monomeric silanes 1 with the Cp2ZrC12/Red-Al and Cp2ZrCl2/n-BuLi combination catalysts produced two phases of polymers: one is a highly crosslinked insoluble solid, and the other is noncross-linked or slightly cross-linked soluble oil and could be a precursor for the solid polymer. The dehydrocoupling of 2 with the Cp2ZrCl2/n-BuLi combination catalyst similarly produced two phases of polymers. By contrast, the catalytic reaction of 2 with the Cp2ZrCl2/Red-Al combination catalyst produced a soluble polymer via redistribution/dehydrocoupling process.

Chemical modification of porous silicon surface has been investigated to have different physical surface properties. Porous silicon modified with dodecyl functionality exhibits hydrophobic feature, however the oxidation of porous silicon to modify with hydroxyl group displays hydrophilic properties. Surface characterization for both dodecyl and hydroxyl derivatized porous silicon was investigated by FT-IR spectroscopy. To determine the surface coverage, the amine functionalized surface was reduced by dithiothreitol (DTT) and the released 2-thiopyridone was quantified by UV/vis spectroscopy.

The differences of properties for both single-layered and multi-layered porous silicon were investigated. Multistructured porous silicons such as DBR or rugate porous silicon exhibit strong reflection resonances providing the reflection of a specific wavelength in the optical reflectivity spectrum. DBR PSi displays a square varying porosity gradient in the direction perpendicular to the plane of the filter but a sinusoidally varying porosity gradient was obtained for rugate PSi.

New method to encode multiple photonic features of Bragg type reflector on silicon wafer has been investigated. Multiple bit encodes of distributed Bragg reflector features have been prepared by electrochemical etching of crystalline silicon by using various square wave current densities. Optical characterization of multi-encoding of distributed Bragg reflectors on porous silicon was achieved by Ocean optics 2000 spectrometer for the search of possible applications of multiple bit encoding of distributed Bragg reflectors such as multiplexed assays and chemical sensors. The morphology and cross-sectional structure of multi-encoded distributed Bragg reflectors was investigated by field emission scanning electron micrograph.

Tuberculosis is a major health problem in humans because of its multidrug resistance and discovering new treatments for this disease is urgently required. The synthesis of isoprenoids in Mycobacterium tuberculosis has been reported as an interesting pathway to target. In this context, 2C-methyl-D-erythritol 4-phosphate (MEP) pathway of M. tuberculosis has drawn attention. The MEP pathway begins with the condensation of glyceraldehyde 3-phosphate and pyruvate forming 1-deoxy-D-xylulose 5-phosphate (DXP) which is catalyzed by 1-deoxy-D-xylulose 5-phosphate synthase (DXS). As there is no X-ray structure was reported for this target, comparative modeling was used to generate the three dimensional structure. The structure was further validated by PROCHECK, VERIFY-3D, PROSA, ERRAT and WHATIF. Molecular docking studies was performed with the substrate (Thiamine pyrophosphate) and the reported inhibitor 2-methyl-3-(4-fluorophenyl)-5-(4-methoxy-phenyl)-4H-pyrazolol[1,5-a]pyrimidin-7-one) against the developed model to identify the crucial residues in the active site. This study may further be useful to provide structure based drug design.

Holographic quantitative structure-activity relationships (HQSAR) is a useful tool to correlates structures with their biological activities. HQSAR is a two dimensional (2D) QSAR methodology, which generates QSAR equations through 2D fingerprint and correlates it with biological activity. Here, we report a 2D-QSAR model for a series of fifty-one 3,4-dihydroxychalcones derivatives utilizing HQSAR methodology. We developed HQSAR model with 6 optimum numbers of components (ONC), which resulted in cross-validated correlation coefficient (q2) of 0.855 with 0.283 standard error of estimate (SEE). The non-cross-validated correlation coefficient (r2) with 0.966 indicates the model is predictive enough for analysis. Developed HQSAR model was binned in to a hologram length of 257. Atomic contribution map revealed the importance of dihydroxy substitution on phenyl ring.

c-Jun N-terminal kinase-3 (JNK-3) has been shown to mediate neuronal apoptosis and make the promising therapeutic target for neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and other CNS disorders. In order to better understand the structural and chemical features of JNK-3, comparative molecular field analysis (CoMFA) was performed on a series of 3,5-disubstituted quinolines derivatives. The best predictions were obtained CoMFA model (q2=0.707, r2=0.972) and the statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The resulting contour map from 3D-QSAR models might be helpful to design novel and more potent JNK3 derivatives.

Cyclic AMP receptor protein(CRP) is involved in the activation of many genes corresponding to catabolite enzymes in Escherichia coli. In this study, mutant CRP(S128A) was used to elucidate the effect of Ser 128 on the cAMP-induced structural change. Based on the protease digestion and thermal analysis, serine 128 in CRP affects the cAMP binding capability and then structural change of CRP protein. In addition, CD spectra in near UV region revealed that S128A CRP retained the sensitive conformation to thermal effect relative to that of wild-type CRP, in spite of identical Tm values in the absence of cAMP.

Bae and Kim displayed a sequence of 4th degree self-reciprocal polynomials whose maximal zeros are related in a very nice and far from obvious way. The auxiliary polynomials in their results that parametrize their coefficients are of significant independent interest. In this note we show that such auxiliary polynomials are related to Chebyshev polynomials.

Today they use a weather radar with spatially high resolution in predicting rainfall intensity and utilizing the information for super short-range forecast in order to make predictions of such severe meteorological phenomena as heavy rainfall and snow. For a weather radar, they use the Z-R relation between the reflectivity factor(Z) and rainfall intensity(R) by rainfall particles in the atmosphere in order to estimate intensity. Most used among the various Z-R relation is Z=200R1.6 applied to stratiform rain. It's also used to estimate basic rainfall intensity of a weather radar run by the weather center. This study set out to compare rainfall intensity between the reflectivity of a weather radar and the ground rainfall of ASOS(Automatic Surface Observation System) by analyzing many different cases of heavy rain, analyze the errors of different weather radars and identify their problems, and investigate their applicability to nowcasting in case of severe weather.

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. The system that uses the artificial neural network(ANN) falls in a local minima when it learns many nonlinear data, and its classification accuracy ratio becomes low. To make up for this risk, the SVM/ANN hybrid algorithm is proposed in this paper. The proposed algorithm is the method that ANN learns selectively after clustering the SNR data by SVM, then more improved performance estimation can be obtained than using ANN only and The proposed algorithm can make the higher classification accuracy by decreasing the nonlinearity of the massive data during the training procedure. Experimental results indicate that the proposed SVM/ANN hybrid algorithm generally outperforms ANN algorithm.