A species conserving genetic algorithm for multimodal function optimization

This paper introduces a new technique called species conservation for evolving parallel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current generation are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimization problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.

Optimization of dynamic properties and link performance for directly-modulated gain-coupled DFB lasers

This paper demonstrates the respective roles that combined gain- and index-coupling play in the dynamic properties and overall link performance of DFB lasers. It is shown that for datacommunication applications, modest gain-coupling enables optimum transmission at 10Gbit/s.

Capacitive nanoelectromechanical switch based on suspended carbon nanotube array

We present the fabrication and high frequency characterization of a capacitive nanoelectromechanical system (NEMS) switch using a dense array of horizontally aligned single-wall carbon nanotubes (CNTs). The nanotubes are directly grown onto metal layers with prepatterned catalysts with horizontal alignment in the gas flow direction. Subsequent wetting-induced compaction by isopropanol increases the nanotube density by one order of magnitude. The actuation voltage of 6 V is low for a NEMS device, and corresponds to CNT arrays with an equivalent Young's modulus of 4.5-8.5 GPa, and resistivity of under 0.0077 Ω·cm. The high frequency characterization shows an isolation of -10 dB at 5 GHz. © 2010 American Institute of Physics.

Geometric optimization methods for the analysis of gene expression data

DNA microarrays provide such a huge amount of data that unsupervised methods are required to reduce the dimension of the data set and to extract meaningful biological information. This work shows that Independent Component Analysis (ICA) is a promising approach for the analysis of genome-wide transcriptomic data. The paper first presents an overview of the most popular algorithms to perform ICA. These algorithms are then applied on a microarray breast-cancer data set. Some issues about the application of ICA and the evaluation of biological relevance of the results are discussed. This study indicates that ICA significantly outperforms Principal Component Analysis (PCA).

A Label-Free Protein Microfluidic Array for Parallel Immunoassays

A label-free protein microfluidic array for immunoassays based on the combination of imaging ellipsometry and an integrated microfluidic system is presented. Proteins can be patterned homogeneously on substrate in array format by the microfluidic system simultaneously. After preparation, the protein array can be packed in the microfluidic system which is full of buffer so that proteins are not exposed to denaturing conditions. With simple microfluidic channel junction, the protein microfluidic array can be used in serial or parallel format to analyze single or multiple samples simultaneously. Imaging ellipsometry is used for the protein array reading with a label-free format. The biological and medical applications of the label-free protein microfluidic array are demonstrated by screening for antibody–antigen interactions, measuring the concentration of the protein solution and detecting five markers of hepatitis B.

Optimization Of Off-Null Ellipsometry For Air/Solid Interfaces

The optimization of off-null ellipsometry is described with emphasis on the improvement of sample thickness sensitivity. Optimal conditions are dependent on azimuth angle settings of the polarizer, compensator, and analyzer in a polarizer-compensator-sample-analyzer ellipsometer arrangement. Numerical simulation utilized offers an approach to present the dependence of the sensitivity on the azimuth angle settings, from which optimal settings corresponding to the best sensitivity are derived. For a series of samples of SiO2 layer (thickness in the range of 1.8-6.5 nm) on silicon substrate, the theory analysis proves that sensitivity at the optimal settings is increased 20 times compared to that at null settings used in most works, and the relationship between intensity and thickness is simplified as a linear type instead of the original nonlinear type, with the relative error reduced to similar to 1/100 at the optimal settings. Furthermore the discussion has been extended toward other factors affecting the sensitivity of the practical system, such as the linear dynamic range of the detector, the signal-to-noise ratio and the intensity from the light source, etc. Experimental results from the investigation Of SiO2 layer on silicon substrate are chosen to verify the optimization. (c) 2007 Optical Society of America.