Forecasting Responses of Seagrass Distributions to Changing Water Quality Using Monitoring Data

Extensive data sets on water quality and seagrass distributions in Florida Bay have been assembled under complementary, but independent, monitoring programs. This paper presents the landscape-scale results from these monitoring programs and outlines a method for exploring the relationships between two such data sets. Seagrass species occurrence and abundance data were used to define eight benthic habitat classes from 677 sampling locations in Florida Bay. Water quality data from 28 monitoring stations spread across the Bay were used to construct a discriminant function model that assigned a probability of a given benthic habitat class occurring for a given combination of water quality variables. Mean salinity, salinity variability, the amount of light reaching the benthos, sediment depth, and mean nutrient concentrations were important predictor variables in the discriminant function model. Using a cross-validated classification scheme, this discriminant function identified the most likely benthic habitat type as the actual habitat type in most cases. The model predicted that the distribution of benthic habitat types in Florida Bay would likely change if water quality and water delivery were changed by human engineering of freshwater discharge from the Everglades. Specifically, an increase in the seasonal delivery of freshwater to Florida Bay should cause an expansion of seagrass beds dominated by Ruppia maritima and Halodule wrightii at the expense of the Thalassia testudinum-dominated community that now occurs in northeast Florida Bay. These statistical techniques should prove useful for predicting landscape-scale changes in community composition in diverse systems where communities are in quasi-equilibrium with environmental drivers.

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Responsiveness of voltage-gated calcium channels in SH-SY5Y human neuroblastoma cells on quasi-three-dimensional micropatterns formed with poly (l-lactic acid)

Introduction: In this study, quasi-three-dimensional (3D) microwell patterns were fabricated with poly (l-lactic acid) for the development of cell-based assays, targeting voltage-gated calcium channels (VGCCs). Methods and materials: SH-SY5Y human neuroblastoma cells were interfaced with the microwell patterns and found to grow as two dimensional (2D), 3D, and near two dimensional (N2D), categorized on the basis of the cells’ location in the pattern. The capability of the microwell patterns to support 3D cell growth was evaluated in terms of the percentage of the cells in each growth category. Cell spreading was analyzed in terms of projection areas under light microscopy. SH-SY5Y cells’ VGCC responsiveness was evaluated with confocal microscopy and a calcium fluorescent indicator, Calcium GreenTM-1. The expression of L-type calcium channels was evaluated using immunofluorescence staining with DM-BODIPY. Results: It was found that cells within the microwells, either N2D or 3D, showed more rounded shapes and less projection areas than 2D cells on flat poly (l-lactic acid) substrates. Also, cells in microwells showed a significantly lower VGCC responsiveness than cells on flat substrates, in terms of both response magnitudes and percentages of responsive cells, upon depolarization with 50 mM K+. This lower VGCC responsiveness could not be explained by the difference in L-type calcium channel expression. For the two patterns addressed in this study, N2D cells consistently exhibited an intermediate value of either projection areas or VGCC responsiveness between those for 2D and 3D cells, suggesting a correlative relation between cell morphology and VGCC responsiveness. Conclusion: These results suggest that the pattern structure and therefore the cell growth characteristics were critical factors in determining cell VGCC responsiveness and thus provide an approach for engineering cell functionality in cell-based assay systems and tissue engineering scaffolds.

A multimodal and adaptive real-time human -computer interface for peoples with severe motor disability

This dissertation introduces the design of a multimodal, adaptive real-time assistive system as an alternate human computer interface that can be used by individuals with severe motor disabilities. The proposed design is based on the integration of a remote eye-gaze tracking system, voice recognition software, and a virtual keyboard. The methodology relies on a user profile that customizes eye gaze tracking using neural networks. The user profiling feature facilitates the notion of universal access to computing resources for a wide range of applications such as web browsing, email, word processing and editing. ^ The study is significant in terms of the integration of key algorithms to yield an adaptable and multimodal interface. The contributions of this dissertation stem from the following accomplishments: (a) establishment of the data transport mechanism between the eye-gaze system and the host computer yielding to a significantly low failure rate of 0.9%; (b) accurate translation of eye data into cursor movement through congregate steps which conclude with calibrated cursor coordinates using an improved conversion function; resulting in an average reduction of 70% of the disparity between the point of gaze and the actual position of the mouse cursor, compared with initial findings; (c) use of both a moving average and a trained neural network in order to minimize the jitter of the mouse cursor, which yield an average jittering reduction of 35%; (d) introduction of a new mathematical methodology to measure the degree of jittering of the mouse trajectory; (e) embedding an onscreen keyboard to facilitate text entry, and a graphical interface that is used to generate user profiles for system adaptability. ^ The adaptability nature of the interface is achieved through the establishment of user profiles, which may contain the jittering and voice characteristics of a particular user as well as a customized list of the most commonly used words ordered according to the user's preferences: in alphabetical or statistical order. This allows the system to successfully provide the capability of interacting with a computer. Every time any of the sub-system is retrained, the accuracy of the interface response improves even more. ^

Regulation of Bone Marrow Stem Cells through Oscillatory Shear Stresses - A Heart Valve Tissue Engineering Perspective

Heart valve disease occurs in adults as well as in pediatric population due to age-related changes, rheumatic fever, infection or congenital condition. Current treatment options are limited to mechanical heart valve (MHV) or bio-prosthetic heart valve (BHV) replacements. Lifelong anti-coagulant medication in case of MHV and calcification, durability in case of BHV are major setbacks for both treatments. Lack of somatic growth of these implants require multiple surgical interventions in case of pediatric patients. Advent of stem cell research and regenerative therapy propose an alternative and potential tissue engineered heart valves (TEHV) treatment approach to treat this life threatening condition. TEHV has the potential to promote tissue growth by replacing and regenerating a functional native valve. Hemodynamics play a crucial role in heart valve tissue formation and sustained performance. The focus of this study was to understand the role of physiological shear stress and flexure effects on de novo HV tissue formation as well as resulting gene and protein expression. A bioreactor system was used to generate physiological shear stress and cyclic flexure. Human bone marrow mesenchymal stem cell derived tissue constructs were exposed to native valve-like physiological condition. Responses of these tissue constructs to the valve-relevant stress states along with gene and protein expression were investigated after 22 days of tissue culture. We conclude that the combination of steady flow and cyclic flexure helps support engineered tissue formation by the co-existence of both OSS and appreciable shear stress magnitudes, and potentially augment valvular gene and protein expression when both parameters are in the physiological range.

On-screen pre-deblurring of digital images using the wavefront aberration function of the human eye to improve computer access for the visually impaired

Traditional Optics has provided ways to compensate some common visual limitations (up to second order visual impairments) through spectacles or contact lenses. Recent developments in wavefront science make it possible to obtain an accurate model of the Point Spread Function (PSF) of the human eye. Through what is known as the "Wavefront Aberration Function" of the human eye, exact knowledge of the optical aberration of the human eye is possible, allowing a mathematical model of the PSF to be obtained. This model could be used to pre-compensate (inverse-filter) the images displayed on computer screens in order to counter the distortion in the user's eye. This project takes advantage of the fact that the wavefront aberration function, commonly expressed as a Zernike polynomial, can be generated from the ophthalmic prescription used to fit spectacles to a person. This allows the pre-compensation, or onscreen deblurring, to be done for various visual impairments, up to second order (commonly known as myopia, hyperopia, or astigmatism). The technique proposed towards that goal and results obtained using a lens, for which the PSF is known, that is introduced into the visual path of subjects without visual impairment will be presented. In addition to substituting the effect of spectacles or contact lenses in correcting the loworder visual limitations of the viewer, the significance of this approach is that it has the potential to address higher-order abnormalities in the eye, currently not correctable by simple means.

Characterization of engineered human lung tissue

Characterizing engineered human lung tissue is an important step in developing a functional tissue replacement for lung tissue repair and in vitro analysis. Small tissue constructs were grown by seeding IMR-90 fetal lung fibroblasts and adult microvascular endothelial cells onto a Polyglycolic acid (PGA) polymer template. Introducing the constructs to dynamic culture conditions inside a bioreactor facilitated three-dimensional growth seen in scanning electron microscopy images (SEM). Characterization of the resultant tissue samples was done using SEM imagery, tensile tests, and biochemical assays to quantify extra-cellular matrix (ECM) composition. Tensile tests of the engineered samples indicated an increase in the mechanical properties when compared with blank constructs. Elastin and collagen content was found to average 3.19% and 15.49% respectively in relation to total mass of the tissue samples. The presence of elastin and collagen within the constructs most likely explains the mechanical differences that we noted. These findings suggest that the necessary ECM can be established in engineered tissue constructs and that optimization of this procedure has the capacity to generate the load bearing elements required for construction of a functional lung tissue equivalent.

Regulation of bone marrow stem cells through oscillatory shear stresses - A heart valve tissue engineering perspective

Heart valve disease occurs in adults as well as in pediatric population due to age-related changes, rheumatic fever, infection or congenital condition. Current treatment options are limited to mechanical heart valve (MHV) or bio-prosthetic heart valve (BHV) replacements. Lifelong anti-coagulant medication in case of MHV and calcification, durability in case of BHV are major setbacks for both treatments. Lack of somatic growth of these implants require multiple surgical interventions in case of pediatric patients. Advent of stem cell research and regenerative therapy propose an alternative and potential tissue engineered heart valves (TEHV) treatment approach to treat this life threatening condition. TEHV has the potential to promote tissue growth by replacing and regenerating a functional native valve. Hemodynamics play a crucial role in heart valve tissue formation and sustained performance. The focus of this study was to understand the role of physiological shear stress and flexure effects on de novo HV tissue formation as well as resulting gene and protein expression. A bioreactor system was used to generate physiological shear stress and cyclic flexure. Human bone marrow mesenchymal stem cell derived tissue constructs were exposed to native valve-like physiological condition. Responses of these tissue constructs to the valve-relevant stress states along with gene and protein expression were investigated after 22 days of tissue culture. We conclude that the combination of steady flow and cyclic flexure helps support engineered tissue formation by the co-existence of both OSS and appreciable shear stress magnitudes, and potentially augment valvular gene and protein expression when both parameters are in the physiological range. ^