Catalytic mechanisms of triphenyl bismuth, dibutyltin dilaurate, and their combination in polyurethane-forming reaction

The catalytic mechanisms of triphenyl bismuth (TPB), dibutyltin dilaurate (DBTDL) and their combination have been studied in a model polyurethane reaction system consisting of copolyether (tetrahydrofuran-ethyleneoxide) and N-100; NMR spectroscopy was used to detect the associations between reactants and catalysts. A relatively stable complex was shown to be formed between hydroxyl and isocyanate; the catalysts showed different effects on the isocyanate-hydroxyl complex, therefore resulting in different curing characteristics. The formation of hydrogen bonding between the complexed hydroxyl and other hydroxyl or the resulting urethane provided an ''auto-catalysis'' to urethane formation. DBTDL destroyed the isocyanate-hydroxyl complex before catalyzing the reaction through the formation of a ternary complex, whereas TPB was able to activate the isocyanate-hydroxyl complex directly to form urethane. The reaction catalyzed by the combination of TPB and DBTDL gained advantages from the multiple catalytic entities, i.e., TPB, DBTDL, and a TPB-DBTDL complex. (C) 1997 John Wiley & Sons, Inc.

ON THE SIGNIFICANCE OF WAVELENGTH POSITIONING ACCURACY IN MULTICOMPONENT ANALYSIS TECHNIQUES FOR THE CORRECTION OF LINE INTERFERENCES IN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION-SPECTROMETRY

The present paper reports some definite evidence for the significance of wavelength positioning accuracy in multicomponent analysis techniques for the correction of line interferences in inductively coupled plasma atomic emission spectrometry (ICP-AES). Using scanning spectrometers commercially available today, a large relative error, DELTA(A) may occur in the estimated analyte concentration, owing to wavelength positioning errors, unless a procedure for data processing can eliminate the problem of optical instability. The emphasis is on the effect of the positioning error (deltalambda) in a model scan, which is evaluated theoretically and determined experimentally. A quantitative relation between DELTA(A) and deltalambda, the peak distance, and the effective widths of the analysis and interfering lines is established under the assumption of Gaussian line profiles. The agreement between calculated and experimental DELTA(A) is also illustrated. The DELTA(A) originating from deltalambda is independent of the net analyte/interferent signal ratio; this contrasts with the situation for the positioning error (dlambda) in a sample scan, where DELTA(A) decreases with an increase in the ratio. Compared with dlambda, the effect of deltalambda is generally less significant.

Self-organized Criticality Model for Ocean Internal Waves

In this paper, we present a simple spring-block model for ocean internal waves based on the self-organized criticality (SOC). The oscillations of the water blocks in the model display power-law behavior with an exponent of -2 in the frequency domain, which is similar to the current and sea water temperature spectra in the actual ocean and the universal Garrett and Munk deep ocean internal wave model [Geophysical Fluid Dynamics 2(1972) 225; J. Geophys. REs. 80 (1975) 291]. The influence of the ratio of the driving force to the spring coefficient to SOC behaviors in the model is also discussed.

A microwave emissivity model of sea surface under wave breaking

With the effective medium approximation theory of composites, a remedial model is proposed for estimating the microwave emissivity of sea surface under wave breaking driven by strong wind on the basis of an empirical model given by Pandey and Kakar. In our model, the effects of the shapes of seawater droplets and the thickness of whitecap layer (i.e. a composite layer of air and sea water droplets) over the sea surface on the microwave emissivity are investigated by calculating the effective dielectric constant of whitecaps layer. The wind speed is included in our model, and the responses of water droplets shapes, such as sphere and ellipsoid, to the emissivity are also discussed at different microwave frequencies. The model is in good agreement with the experimental data of microwave emissivity of sea surface at microwave frequencies of 6.6, 10.7 and 37GHz.

A hybrid coupled ocean-atmosphere model and ENSO prediction study

A hybrid coupled ocean-atmosphere model is designed, which consists of a global AGCM and a simple anomaly ocean model in the tropical Pacific. Retroactive experimental predictions initiated in each season from 1979 to 1994 are performed. Analyses indicate that: (1) The overall predictive capability of this model for SSTA over the central-eastern tropical Pacific can reach one year, and the error is not larger than 0.8 degrees C. (2) The prediction skill depends greatly on the season when forecasts start. However, the phenomenon of SPB (spring prediction barrier) is not found in the model. (3) The ensemble forecast method can effectively improve prediction results. A new initialization scheme is discussed.

Fucoidan protects against dopaminergic neuron death in vivo and in vitro

Parkinson's disease is a neurodegenerative disorder of uncertain pathogenesis characterized by a loss of dopaminergic neurons in substantia nigra pars compacta, and can be modeled by the neurotoxin 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP). Oxidative stress may contribute to MPTP- and Parkinson's disease-related neurodegeneration. Fucoidan is a sulfated polysaccharide extracted from brown seaweeds which possesses a wide variety of biological activities including potent antioxidative effects. Here we investigated the effect of fucoidan treatment on locomoter activities of animals, striatal dopamine and its metabolites and survival of nigral dopaminergic neurons in MPTP-induced animal model of Parkinsonism in C57/BL mice in vivo and on the neuronal damage induced by 1-methyl-4-phenylpyridinium (MPP+) in vitro, and to study the possible mechanisms. When administered prior to MPTP, fucoidan reduced behavioral deficits, increased striatal dopamine and its metabolites levels, reduced cell death, and led to a marked increase in tyrosine hydroxylase expression relative to mice treated with MPTP alone. Furthermore, we found that fucoidan inhibited MPTP-induced lipid peroxidation and reduction of antioxidant enzyme activity. In addition, pre-treatment with fucoidan significantly protected against MPP+-induced damage in MN9D cells. Taken together, these findings suggest that fucoidan has protective effect in MPTP-induced neurotoxicity in this model of Parkinson's disease via its antioxidative activity. (C) 2009 Elsevier B.V. All rights reserved.

Analysis of high wheat yields in Northwest China

Grain yields of over 14 Mg ha(-1) were reported in 1978 for spring wheat (Triticum aestivum L.) grown in Northwest China. Understanding the circumstances under which this record yield was achieved may be useful in defining the key factors that lead to high grain yields and in determining the limits to wheat yield. A relatively simple, mechanistic model was used in an effort to simulate the record yield. The model was used as a framework in which various crop traits could be adjusted to match the observed crop growth. The weather that was characterized by cool temperatures and high levels of solar radiation, proved to be especially important in allowing a full-season crop to achieve record yields. Variables defining plant development in the model also had to be set to describe the high yielding cultivar grown in China. Leaf development was defined by the length of a phyllochron, which was set equal to 78 TU (thermal units, base temperature equal to 0 degrees C) based on independent data. The description of grain fill had to be defined to match simulation results with the observations. Two variables, length of the grain-fill period and the grain growth rate, were set in response to the unique traits of this cultivar and the low temperatures during grain development. These simulations led to important suggestions for examining the interaction between cool temperature regimes and developmental traits of wheat cultivars. (C) 1997 Published by Elsevier Science Ltd.

An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure-activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 +/- 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.