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E. coli promoter recognition is an area of great interest in bioinformatics. In this paper, we describe the implementation of a feed forward neural network to predict the E. coli promoter. According to the sequence conservation, some sequences with 60 bases are selected as positive samples and some corresponding non-promoters from E. coli coding areas are selected as negative samples, and a classifier based on feed forward neural network is trained. Results show that feed forward neural networks can extract the statistical characteristics of promoters more effectively, and that coding with four dimensions for nucleic acid data is superior to two dimensions. Another result demonstrated here is that the number of hidden layers seems to have no significant effect on E. coli promoter prediction precision. The research results in this paper can provide reference for promoter recognition research.

In this study, we decomposed 12 fMRI data sets from six subjects each 101 times using the infomax algorithm. The first decomposition was taken as a reference decomposition; the others were used to form a component matrix of 100 by 100 components. Equivalence relations between components in this matrix, defined as maximum spatial correlations to the components of the reference decomposition, were found by the Hungarian sorting method and used to form 100 equivalence classes for each data set. We then tested the reproducibility of the matched components in the equivalence classes using uncertainty measures based on component distributions, time courses, and ROC curves. Infomax ICA rarely failed to derive nearly the same components in different decompositions. Very few components per data set were poorly reproduced, even using vector angle uncertainty measures stricter than correlation and detection theory measures.

A technique of detecting the rolling and spinning of half-coated nanoparticles using interference ring patterns of the fluorescence has been applied to the measurement of torsional spring modulus of a double-stranded DNA. Using the unique ability to measure nanoparticle rotations in multiple degrees of freedom, we were able to determine the spinning of a nanoparticle tethered on the DNA and thereby the twisting of the DNA in real time. The detailed knowledge of the spinning as well as rolling behaviors of half-coated nanoparticles provides information about torsional elastic properties of the DNA under investigation.

Current optical coherence tomography (OCT) relies on patient cooperation to maintain fixation. For patients with eye complications, it is extremely difficult to achieve fixation on the eye. Most eye trackers are external and track only the pupils. Such method is not useful for the OCT. The only existing fundus image based tracker is a hardware-based system that is composed of a confocal reflectometer, dither scanner, and tracking galvanometers. The integration of such hardware based system with the OCT is not as desirable nor as portable. Therefore, we want an eye tracking system that can be installed in the computer connected to the OCT. In this paper, a real time internal eye tracking software based system is proposed. By combining intensity based object tracking adaptive mean shift algorithm with Kalman filtering techniques together, a robust real time eye tracking algorithm is proposed. The system is robust in terms of its acceptance to low resolution, coarsely quantized, or extremely noisy images and still able to produce desirable results with no pre-processing of images.

We have developed an integrated dynamic lens system for in vivo optical imaging. Bioinspired dynamic microfluidic lenses allow for real-time dynamic manipulation of the lens focal length via microfluidic injection into a PDMS membrane-capped chamber. A piezoelectrically actuated micropump is integrated with with the lens to provide highspeed, accurate lens tunability. The 5mm dynamic lens has demonstrated focal length tunability from 8.5mm to 23mm, numerical aperture values from 0.39 to 0.77, and resolution of 40 linepairs/mm. The micropump operates at 5 kHz and achieved a flow rate of approximately 2.4 mL/min. This system can be applied to optical probe techniques to improve diagnosis with real-time depth resolution and variable numerical aperture.