Preparation of glucosamine hydrochloride from the chitin of Penaeus monodon

The present work gives some information on use of shrimp wastes of processing industries of Bangladesh in preparation of valuable chitin products such as glucosamine hydrochloride.

Survey of shark fisheries and preparation of a National Plan of Action (NPOA) for conservation and management of shark resources in Bangladesh

The report presents; terms of reference; work progress; surveys of shark fishers and traders; shark biodiversity survey; and a National Plan of Action (NPOA) for conservation and management of shark resources in Bangladesh.

Preparation and characterization of a novel pyrrole-benzophenone copolymerized silica nanocomposite as a reagent in a visual immunologic-agglutination test.

Biological sensing is explored through novel stable colloidal dispersions of pyrrole-benzophenone and pyrrole copolymerized silica (PPy-SiO(2)-PPyBPh) nanocomposites, which allow covalent linking of biological molecules through light mediation. The mechanism of nanocomposite attachment to a model protein is studied by gold labeled cholera toxin B (CTB) to enhance the contrast in electron microscopy imaging. The biological test itself is carried out without gold labeling, i.e., using CTB only. The protein is shown to be covalently bound through the benzophenone groups. When the reactive PPy-SiO(2)-PPyBPh-CTB nanocomposite is exposed to specific recognition anti-CTB immunoglobulins, a qualitative visual agglutination assay occurs spontaneously, producing as a positive test, PPy-SiO(2)-PPyBPh-CTB-anti-CTB, in less than 1 h, while the control solution of the PPy-SiO(2)-PPyBPh-CTB alone remained well-dispersed during the same period. These dispersions were characterized by cryogenic transmission microscopy (cryo-TEM), scanning electron microscopy (SEM), FTIR and X-ray photoelectron spectroscopy (XPS).

BarraCUDA – a Fast Sequence Mapping Software using Graphics Processing Units

High-throughput DNA sequencing (HTS) instruments today are capable of generating millions of sequencing reads in a short period of time, and this represents a serious challenge to current bioinformatics pipeline in processing such an enormous amount of data in a fast and economical fashion. Modern graphics cards are powerful processing units that consist of hundreds of scalar processors in parallel in order to handle the rendering of high-definition graphics in real-time. It is this computational capability that we propose to harness in order to accelerate some of the time-consuming steps in analyzing data generated by the HTS instruments. We have developed BarraCUDA, a novel sequence mapping software that utilizes the parallelism of NVIDIA CUDA graphics cards to map sequencing reads to a particular location on a reference genome. While delivering a similar mapping fidelity as other mainstream programs , BarraCUDA is a magnitude faster in mapping throughput compared to its CPU counterparts. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the mapping throughput. BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the mapping of millions of sequencing reads generated by HTS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available at http://seqbarracuda.sf.net

Fast-switching phase gratings using in-plane addressed short-pitch polymer stabilized chiral nematic liquid crystals

We demonstrate a fast-switching (sub-millisecond) phase grating based upon a polymer stabilized short-pitch chiral nematic liquid crystal that is electrically addressed using in-plane electric fields. The combination of the short-pitch and the polymer stabilization enables the diffraction pattern to be switched “on” and “off” reversibly in 600 µs. Results are presented on the far-field diffraction pattern along with the intensity of the diffraction orders as a function of the applied electric field and the response times.

Fast L0-based sparse signal recovery

This paper develops an algorithm for finding sparse signals from limited observations of a linear system. We assume an adaptive Gaussian model for sparse signals. This model results in a least square problem with an iteratively reweighted L2 penalty that approximates the L0-norm. We propose a fast algorithm to solve the problem within a continuation framework. In our examples, we show that the correct sparsity map and sparsity level are gradually learnt during the iterations even when the number of observations is reduced, or when observation noise is present. In addition, with the help of sophisticated interscale signal models, the algorithm is able to recover signals to a better accuracy and with reduced number of observations than typical L1-norm and reweighted L1 norm methods. ©2010 IEEE.