No description available.

Thesis (M. S.)--Bioengineering, Georgia Institute of Technology, 2009. / Committee Chair: Kemp, Melissa; Committee Member: Brand, Oliver; Committee Member: Lu, Hang. Part of the SMARTech Electronic Thesis and Dissertation Collection.

No description available.

Thesis (M. S.)--Biomedical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Hang Lu; Committee Co-Chair: Rachel Chen; Committee Member: Johnna Temenoff; Committee Member: Yonathan Thio. Part of the SMARTech Electronic Thesis and Dissertation Collection.

No description available.

New approaches to the analysis of trace metal concentrations in seawater have the potential to advance the field of oceanography and provide a more comprehensive understanding of the marine biogeochemical cycles of trace metals and the processes regulating these cycles. Traditional oceanographic methods of trace metal analysis were developed several decades ago using benchtop liquid-liquid extraction (Danielson et al., 1978; Kinrade and Van Loon, 1974; Miller and Bruland, 1994; Moffett and Zika, 1987). More modern techniques utilize flow based solid phase extraction to eliminate the high ionic strength matrix to determine dissolved concentrations with great accuracy and precision but do not allow for the determination of metal speciation in solution (Wells and Bruland, 1998). The method developed here measures oceanographically relevant concentrations of copper (Cu) in seawater via chemiluminescence (Marshall et al., 2003 and Coale et al., 1992) and micro-molar levels of silver (Ag) colorimetrically after automated liquid-liquid extraction. The Zone Fluidics (Marshall et al., 2003) analyzer for trace Cu determined SAFe D2 standard seawater (www.geotraces.org) to be 1.77 nM Cu comparable to the expected consensus value. The method was used to determine dissolved Cu depth profiles for major stations along the Line P Time-series transect (48N 125W - 50N 145W) in the Pacific Ocean during February 2011. This method consumes less than 200 µL of sample and reagents and is performed in less than 3 minutes making it suitable for ship or lab based analysis. / Graduate / 0485 / 0425 / cschwang11@gmail.com

This thesis summarises research on the improved design, integration and expansion of past cortex-like computer vision models, following biologically-inspired methodologies. By adopting early theories and algorithms as a building block, particular interest has been shown for algorithmic parameterisation, feature extraction, invariance properties and classification. Overall, the major original contributions of this thesis have been: 1. The incorporation of a salient feature-based method for semantic feature extraction and refinement in object recognition. 2. The design and integration of colour features coupled with the existing morphological-based features for efficient and improved biologically-inspired object recognition. 3. The introduction of the illumination invariance property with colour constancy methods under a biologically-inspired framework. 4. The development and investigation of rotation invariance methods to improve robustness and compensate for the lack of such a mechanism in the original models. 5. Adaptive Gabor filter design that captures texture information, enhancing the morphological description of objects in a visual scene and improving the overall classification performance. 6. Instigation of pioneering research on Spiking Neural Network classification for biologically-inspired vision. Most of the above contributions have also been presented in two journal publications and five conference papers. The system has been fully developed and tested in computers using MATLAB under a variety of image datasets either created for the purposes of this work or obtained from the public domain. / © Cranfield University

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Molecular weight and concentration are two most important characteristics of polymers synthesized through chemical or microbial processes. However, current methods for characterizing polymer molecular weight such as Multi-Angle Laser Light Scattering (MALLS) or Gel Permeation Chromatography (GPC) require precise information on concentration as well as extensive sample preparation. Additionally, these current methods are also generally expensive, low throughput, and require large sample titers. These limitations prevent dynamic time-point studies of changes in molecular weight, which would be very useful for monitoring synthesis progress in microbes or in chemical synthesis. In this thesis, we designed, fabricated, and tested a rapid, low cost, high throughput, modular microfluidic system for determining polymer molecular weight in samples of unknown concentrations. To assess the accuracy of this system, we first constructed theoretical predictions for its accuracy, and then compared these to the experimental results from our microfluidic system. The system evaluated molecular weight by correlating the behavior of polymers in various solvent conditions to their molecular weights. The system consists of two modules for measuring fluid viscosity, and for controlling solvent conditions. Results of this study will show that this system is able to evaluate the differences in polymer viscosity for varying molecular weights and solvent conditions. For the solvent control module, we show that salt concentrations in small titers of polymer solutions can be rapidly added or subtracted and evaluated compared with current methods. Next, we will show the efficacy of the viscosity module at rapidly and accurately assessing fluid viscosity over a wide range of molecular weights. Finally, we will show the effects of solvent changes on molecular weight viscosity, and thus the efficacy of the system in determining molecular weight from fluid viscosity. This system will be applied to the evaluation of both the biologically produced polymer Hyaluronic Acid (HA) as well as the synthetically produced polymer Poly-ethylene Oxide (PEO).

Binding of the antigen receptor on T cells initiates a rapid series of signaling events leading to an immune response. To fully understand T cell mediated immunity, underlying regulatory properties of the receptor network must be understood. Monitoring dynamic protein signaling events allows for network analysis. Unfortunately, dynamic data acquisition is often extremely time-consuming and expensive with conventional methods; the number of proteins monitored at the same time on the same sample is limited. Furthermore, with conventional, multi-well plate assays it is difficult to achieve adequate resolution at sub-minute timescales. Microfluidics is a capable alternative, providing uniformity in sample handling to reduce error between experiments and precision in timing, an important factor in monitoring phosphorylation events that occur within minutes of stimulation. We used a two-module microfluidic platform for simultaneous multi-time point stimulation and lysis of T cells to investigate early signaling events with a resolution down to 20 seconds using only small amounts of cells and reagents. The device did not elicit adverse cellular stress in Jurkat cells. The activation of 6 important proteins in the signaling cascade upon stimulation with a soluble form of α-CD3 in the device was quantified and compared under a variety of conditions. First, in comparison to manual pipetting, the microdevice exhibits significantly less error between experiments. Secondly, a comparison between Jurkat cells and primary T cells shows similar dynamic trends across the 6 proteins. Finally, we have used the device to compare properties of long-term vs, short-term cultured primary T cells. As expected, older cells present a much weakened response to antigenic cues, as measured with TCR response markers. This modular microdevice provides a flexible format for investigating cell signaling properties through the use of soluble cue stimuli.