Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network

A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp., in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp., sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms.

De novo RNA synthesis and homology modeling of the classical swine fever virus RNA polymerase

Classical swine fever virus (CSFV) non-structural protein 5B (NS5B) encodes an RNA-dependent RNA polymerase (RdRp), a key enzyme which initiates RNA replication by a de novo mechanism without a primer and is a potential target for anti-virus therapy. We expressed the NS5B protein in Escherichia coli. The rGTP can stimulate de novo initiation of RNA synthesis and mutation of the GDD motif to Gly-Asp-Asp (GAA) abolishes the RNA synthesis. To better understand the mechanism of viral RNA synthesis in CSFV, a three-dimensional model was built by homology modeling based on the alignment with several virus RdRps. The model contains 605 residues folded in the characteristic fingers, palm and thumb domains. The fingers domain contains an N-terminal region that plays an important role in conformational change. We propose that the experimentally observed promotion of polymerase efficiency by rGTP is probably due to the conformational changes of the polymerase caused by binding the rGTP. Mutation of the GDD to GAA interferes with the interaction between the residues at the polymerase active site and metal ions, and thus renders the polymerase inactive. (c) 2005 Elsevier B.V. All rights reserved.

Modeling of cyanobacterial blooms in hypereutrophic Lake Dianchi, China

Compared with other approaches for modeling and predicting, artificial neural networks are more effective in describing complex and non-linear systems. The occurrence of cyanobacterial blooms has been a continuous and serious problem over the past decades in hypereutrophic Lake Dianchi. Yet, the main factor(s) initiating these blooms remain(s) unclear. During 2001-2002 at 40 sampling sites in Lake Dianchi, physicochemical parameters possibly relating to the blooms were measured. Parameters directly or indirectly relating to the cyanobacterial blooms were used as driving factors in a back-propagation network to model the concentration of chlorophyll a. According to sensitivity analysis, chemical oxygen demand was identified as a very significant environmental factor for algal growth in Lake Dianchi.

AMPS modeling of light J-V characteristics of a-Si based solar cells

AMPS (Analysis of microelectronic and photonic structures) mode,which was developed by Pennsylvania State University, has been used to module the light J-V characteristics of a-Si solar cells with a structure of TCO/p-a-SiC:H/i-a-Si:H/n-a-Si:H/ metal. The effects of valence band offset and contact barriers at p/i and TOC/p, n/metal interfaces on the light J-V characteristics have been examined. The modeling has qualitatively categorized and explained the non-ideal J-V behaviors (rollover, crossover, Voc shift,and rollunder) observed in a-Si based solar cells.

A highly efficient beam propagation method for modeling step-index waveguides with tilt interface

Based on a new finite-difference scheme and Runge-Kutta method together with transparent boundary conditions (TBCs), a novel beam propagation method to model step-index waveguides with tilt interfaces is presented. The modified scheme provides an precies description of the tilt interface of the nonrectangular waveguide structure, showing a much better efficiency and accuracy comparing with the previously presented formulas.

Optical constants of cubic GaN/GaAs(001): Experiment and modeling

The optical constants epsilon(E)=epsilon(1)(E)+iepsilon(2)(E) of unintentionally doped cubic GaN grown on GaAs(001) have been measured at 300 K using spectral ellipsometry in the range of 1.5-5.0 eV. The epsilon(E) spectra display a structure, associated with the critical point at E-0 (direct gap) and some contribution mainly coming from the E-1 critical point. The experimental data over the entire measured spectral range (after oxide removal) has been fit using the Holden-Munoz model dielectric function [M. Munoz et al., J. Appl. Phys. 92, 5878 (2002)]. This model is based on the electronic energy-band structure near critical points plus excitonic and band-to-band Coulomb-enhancement effects at E-0, E-0 + Delta(0) and the E-1, E-1 + Delta(1), doublet. In addition to evaluating the energy of the E-0 critical point, the binding energy (R-1) of the two-dimensional exciton related to the E-1 critical point was estimated using the effective mass/k.p theory. The line, shape of the imaginary part of the cubic-GaN dielectric function shows excitonic effects at room temperature not withstanding that the exciton was not resolved. (C) 2003 American Institute of Physics.

Modeling the dynamics of Si wafer bonding during annealing

The bonding behavior of silicon wafers depends on activation energy for the formation of siloxane bonds. In this article we developed a quantitative model on the dynamics of silicon wafer bonding during annealing. Based on this model, a significant difference in the bonding behaviors is compared quantitatively between the native oxide bonding interface and the thermal oxide bonding interface. The results indicate that the bonding strength of the native oxide interface increases with temperature much more rapidly than that of the thermal oxide interface. (C) 2000 American Institute of Physics. [S0021-8979(00)05520-1].

Kinetic modeling of N incorporation in GaInNAs growth by plasma-assisted molecular-beam epitaxy

We have studied the growth of GaInNAs by a plasma-assisted molecular-beam epitaxy (MBE). It was found that the N-radicals were incorporated into the epitaxial layer like dopant atoms. In the range of 400-500 degrees C, the growth temperature (T-g) mainly affected the crystal quality of GaInNAs rather than the N concentration. The N concentration dropped rapidly when T-g exceeded 500 degrees C. Considering N desorption alone is insufficient to account for the strong falloff of the N concentration with T-g over 500 degrees C, the effect of thermally-activated N surface segregation must be taken into account. The N concentration was independent of the arsenic pressure and the In concentration in GaInNAs layers, but inversely proportional to the growth rate. Based on the experimental results, a kinetic model including N desorption and surface segregation was developed to analyze quantitatively the N incorporation in MBE growth. (C) 2000 American Institute of Physics. [S0003-6951(00)00928-1].

Modeling and optimization of semiconductor manufacturing process with neural networks

A neural network-based process model is proposed to optimize the semiconductor manufacturing process. Being different from some works in several research groups which developed neural network-based models to predict process quality with a set of process variables of only single manufacturing step, we applied this model to wafer fabrication parameters control and wafer lot yield optimization. The original data are collected from a wafer fabrication line, including technological parameters and wafer test results. The wafer lot yield is taken as the optimization target. Learning from historical technological records and wafer test results, the model can predict the wafer yield. To eliminate the "bad" or noisy samples from the sample set, an experimental method was used to determine the number of hidden units so that both good learning ability and prediction capability can be obtained.

Generalized Viscoplastic Modeling of Debris Flow

Various concepts have been proposed or used in the development of rheological models for debris flow. The earliest model developed by Bagnold was based on the concept of the “dispersive” pressure generated by grain collisions. Bagnold’s concept appears to be theoretically sound, but his empirical model has been found to be inconsistent with most theoretical models developed from non-Newtonian fluid mechanics. Although the generality of Bagnold’s model is still at issue, debris-flow modelers in Japan have generally accepted Takahashi’s formulas derived from Bagnold’s model. Some efforts have recently been made by theoreticians in non-Newtonian fluid mechanics to modify or improve Bagnold’s concept or model. A viable rheological model should consist both of a rate-independent part and a rate-dependent part. A generalized viscoplastic fluid (GVF) model that has both parts as well as two major rheological properties (i.e., the normal stress effect and soil yield criterion) is shown to be sufficiently accurate, yet practical, for general use in debris-flow modeling. In fact, Bagnold’s model is found to be only a particular case of the GVF model. Analytical solutions for (steady) uniform debris flows in wide channels are obtained from the GVF model based on Bagnold’s simplified assumption of constant grain concentration.