The transport of a species in complex flow fields is an important phenomenon related to many areas in science and engineering. There has been significant progress theoretically and experimentally in understanding active transport in steady, periodic flows such as a chain of vortices but many open questions remain for transport in complex and chaotic flows. This thesis investigates the active transport in a three-dimensional, time-dependent flow field characterized by a spatiotemporally chaotic state of Rayleigh-Be?nard convection. A nonlinear Fischer-Kolmogorov-Petrovskii-Piskunov reaction is selected to study the transport within these flows. A highly efficient, parallel spectral element approach is employed to solve the Boussinesq and the reaction-advection-diffusion equations in a spatially-extended cylindrical domain with experimentally relevant boundary conditions. The transport is quantified using statistics of spreading and in terms of active transport characteristics like front speed and geometry and are compared with those results for transport in steady flows found in the literature. The results of the simulations indicate an anomalous diffusion process with a power law 2 < ? < 5/2 a result that deviates from other superdiffusive processes in simpler flows, and reveals that the presence of spiral defect chaos induces strongly anomalous transport. Additionally, transport was found to most likely occur in a direction perpendicular to a convection roll in the flow field. The presence of the spiral defect chaos state of the fluid convection is found to enhance the front perimeter by t^3/2 and by a perimeter enhancement ratio r(p) = 2.3. / Master of Science

Local and global forms of inhibition control directionally selective ganglion cells (DSGCs) in the mammalian retina. Specifically, local inhibition arising from GABAergic starburst amacrine cells (SACs) strongly contributes to direction selectivity. In this thesis, I demonstrate that increasing ambient illumination leads to the recruitment of GABAergic wide-field amacrine cells (WACs) endowing the DS circuit with an additional feature: size selectivity. Using a combination of electrophysiology, pharmacology and light/electron microscopy, I demonstrate that WACs predominantly contact presynaptic bipolar cells, which drive direct excitation and feed-forward inhibition (through SACs) to DSGCs, therefore maintaining the appropriate balance of inhibition/excitation required for generating DS. This circuit arrangement permits high-fidelity direction coding over a range of ambient light levels, over which size selectivity is adjusted. Together, these results provide novel insights into the anatomical and functional arrangement of multiple inhibitory interneurons within a single computational module in the retina. / Graduate

The human brain consists of billions of neurons and these neurons pool together in groups at different scales. On one hand, these neural entities tend to behave as single units and on the other hand show collective macroscopic patterns of activity. The neural units communicate with each other and process information over time. This communication is through small electrical impulses which at the macroscopic scale are measurable as brain waves. The electric field that is produced collectively by macroscopic groups of neurons within the brain can be measured on the surface of the skull via a brain imaging modality called Electroencephalography (EEG). The brain as a neural system has variant connection topology, in which an area might not only be connected to its adjacent neighbors homogeneously but also distant areas can directly transfer brain activity [16]. Timing of these brain activity communications between different neural units bring up overall emerging spatiotemporal patterns. The dynamics of these patterns and formation of neural activities in cortical surface is influenced by the presence of long-range connections between heterogeneous neural units. Brain activity at large-scale is thought to be involved in the information processing and the implementation of cognitive functions of the brain. This research aims to determine how the spatiotemporal pattern formation phenomena in the brain depend on its connection topology. This connection topology consists of homogeneous connections in local cortical areas alongside the couplings between distant functional units as heterogeneous connections. Homogeneous connectivity or synaptic weight distribution representing the large-scale anatomy of cortex is assumed to depend on the Euclidean distance between interacting neural units. Altering characteristics of inhomogeneous pathways as control parameters guide the brain pattern formation through phase transitions at critical points. In this research, linear stability analysis is applied to a macroscopic neural field in a one-dimensional circular and a twodimensional spherical model of the brain in order to find destabilization mechanism and subsequently emerging patterns. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Tout positionnement global précis nécessite un repère de référence tel le repère international de référence terrestre (ITRF). La détermination de l’ITRF s’appuie sur des séries temporelles de positions d’instruments géodésiques, en particulier des stations GNSS permanentes. Les séries temporelles de positions de stations GNSS sont corrélées temporellement et spatialement. De nombreuses études ont caractérisé la dépendance temporelle de ces séries et son impact sur la détermination de repères de référence. En revanche, les corrélations spatiales (entre stations proches) des séries GNSS n’ont jusqu’à présent jamais été prises en compte dans le calcul de repères de référence. L’objectif de cette thèse est donc de proposer une méthodologie pour la prise en compte de ces corrélations spatiales et d’évaluer son apport.Les dépendances spatiales entre les séries de 195 stations GNSS sont tout d’abord évaluées à l’aide de variogrammes empiriques confirmant l’existence de corrélations jusqu’à des distances d’environ 5000 km. Des modèles de covariance exponentielle ne dépendant que de la distance inter-stations sont ajustés sur ces variogrammes empiriques.Une méthodologie basée sur un filtre de Kalman est ensuite développée pour prendre en compte les dépendances spatiales des séries GNSS dans le calcul d’un repère de référence. Trois modèles de dépendance spatiale sont proposés : un modèle ne tenant pas compte de la dépendance spatiale (cas actuel du calcul de l’ITRF), un modèle basé sur les covariances empiriques entre séries de différentes stations, et un modèle basé sur les fonctions de covariance exponentielle mentionnées ci-dessus. Ces différents modèles sont appliqués à trois jeux tests d’une dizaine de stations chacun situés en Europe, aux Caraïbes et sur la côte est des États-Unis. Les trois modèles sont évalués à l’aune d’un critère de validation croisée, c’est-à-dire sur leur capacité à prédire les positions des stations en l’absence de données. Les résultats sur les jeux tests d’Europe et des États-Unis montrent une amélioration considérable de cette capacité prédictive lorsque la dépendance spatiale des séries est prise en compte. Cette amélioration est maximale lorsque le modèle de covariance exponentielle est utilisé. L’amélioration est nettement moindre, mais toujours présente sur le jeu test des Caraïbes.Les trois modèles sont également évalués sur leur capacité à déterminer des vitesses de déplacement exactes à partir de séries temporelles de positions courtes. L’impact de la prise en compte de la dépendance spatiale des séries sur l’exactitude des vitesses estimées est significatif. Comme précédemment, l’amélioration est maximale lorsque le modèle de covariance exponentielle est utilisé.Cette thèse démontre ainsi l’intérêt de la prise en compte des dépendances spatiales entre séries GNSS pour la détermination de repères de référence. La méthodologie développée pourra être utilisée pour le calcul de futures versions de l’ITRF. / Any global and precise positioning requires a reference frame such as the International Terrestrial Reference Frame (ITRF). The determination of the ITRF relies on the position time series of various geodetic instruments, including in particular permanent GNSS stations. GNSS station position time series are known to be temporally and spatially correlated. Many authors have studied the temporal dependency of GNSS time series and its impact on the determination of terrestrial reference frames. On the other hand, the spatial correlations (i.e., between nearby stations) of GNSS time series have so far never been taken into account in the computation of terrestrial reference frames. The objective of this thesis is therefore to develop a methodology to account for the spatial correlations of GNSS time series, and evaluate its benefits.The spatial dependencies between the position time series of 195 GNSS stations are first evaluated by means of empirical variograms, which confirm the existence of correlations up to distances of about 5000 km. Exponential covariance models, depending only on the distance between stations, are adjusted to these empirical variograms.A methodology based on a Kalman filter is then developed to take into account the spatial dependencies of GNSS time series in the computation of a terrestrial reference frame. Three models of spatial dependency are proposed: a model which does not account for the spatial dependency between GNSS time series (current case of the ITRF computation), a model based on the empirical covariances between the time series of different stations, and a model based on the exponential covariance functions mentioned above.These different models are applied to three test cases of ten stations each, located in Europe, in the Caribbean, and along the east coast of the US. The three models are evaluated with regard to a cross-validation criterion, i.e., on their capacity to predict station positions in the absence of observations. The results obtained with the Europe and US test cases demonstrate a significant improvement of this predictive capacity when the spatial dependency of the series is taken into account. This improvement is highest when the exponential covariance model is used. The improvement is much lower, but still present with the Caribbean test case.The three models are also evaluated with regard to their capacity to determine accurate station velocities from short position time series. The impact of accounting for the spatial dependency between series on the accuracy of the estimated velocities is again significant. Like previously, the improvement is highest when the exponential covariance model is used.This thesis thus demonstrates the interest of accounting for the spatial dependency of GNSS station position time series in the determination of terrestrial reference frames. The developed methodology could be used in the computation of future ITRF versions.

This study of the spatiotemporal patterns of colorectal cancer (CRC) in Iowa introduced the importance of examining the geographic patterns of four epidemiological measures (incidence, late-stage incidence, mortality, and survival) as inter-related phases in the natural history of the disease rather than as independent measures. To conduct such an analysis required the development of a framework for conducting spatiotemporal correlation analysis involving two or more measures across two or more periods. This framework is based on geographic units called spatially adaptive filter areas.which effectively address the small number problem. This common spatial epidemiology problem occurs when the population in a unit of geography is too small to calculate a reliable disease rate. The spatially adaptive filter areas are created by aggregating smaller geographic units which, by themselves, do not have sufficiently large populations to calculate statistically reliable disease rates. Conducting spatiotemporal analysis magnifies the small number problem because stratifying disease data by time further reduces the sample sizes in each period, thus increasing the potential for unreliable disease rates. This spatiotemporal framework satisfies two conditions: 1) the rates of each measure in all small areas in the study region meet a minimum level of statistical reliability in all periods, and 2) the disease outcomes measured for one period relies on the same geographic units as the rates calculated for all other periods and measures. We applied the spatiotemporal framework to colorectal cancer data collected in the state of Iowa between 1999 and 2010. Using rates calculated in spatial filter areas, we found that the proportion of cases diagnosed at a late-stage among the population at risk for CRC is more correlated with CRC mortality than when late-stage is measured as the proportion of late-stage cases among the CRC cases diagnosed at any stage. We also found that, when measured in the context of the statewide change, an observed decline in the rate of CRC mortality in a small area does not necessarily mean that its level of mortality is improving. We also found that the correlation between rates of CRC mortality and the survival time among patients diagnosed with CRC varied across Iowa. The results described in this dissertation could potentially reduce the burden of colorectal cancer and improve the health of communities by providing public health professionals and cancer control specialists with evidence to enhance their decision-making processes.

This dissertation focused on examining murder-suicide in the United States through descriptive, time-series and spatiotemporal analyses using a self-created and herein verified national database that spanned the years 1999 through 2009. Chapter 2, "Establishment and validation of a national database for murder-suicide in the United States: 1999-2009," describes the methods and sources used in the creation of a national database of murder-suicide. The database was validated using less geographically and/or temporally expansive databases through the use of capture-recapture methods in two ways: the number of events identified in specified space and time was compared and cases were matched using the perpetrator's name. Victim and perpetrator characteristics were then described as compared to previous studies. Chapter 3, "A time-series analysis of murder, suicide and murder-suicide in the United States, 1999-2007" utilized time-series analysis techniques to investigate the impact of time varying covariates on murder, suicide and murder-suicide. Analyses were conducted in the United States at the national level from January 1999 to December 2007. Johansen's multivariable cointegration analysis showed that two-month time lagged murder was positively associated with murder, suicide and murder-suicide. Two-month time lagged suicide was negatively associated with murder, suicide and murder-suicide. Two-month time lagged murder-suicide was not related to any of the three events. Chapter 4, "Spatiotemporal relationships among murder, suicide and murder-suicide in the United States: 1999-2008" examined space, time, and spatiotemporal relationships among murder, suicide and murder-suicide using a spatiotemporal scan statistic from SaTScanTM. Thirty-five temporal and spatiotemporal clusters of murder, suicide, murder/murder-suicide, suicide/murder-suicide and murder/suicide/murder-suicide were identified. No purely spatial clusters, clusters of murder/suicide without murder-suicide, or purely murder-suicide were identified. The murder-suicide database, that will be made public in 2012, will be a novel source of information for investigators interested in studying murder-suicides with the inclusion of date, place, perpetrator and victim characteristics. Its validation along with the time-series and spatiotemporal analyses provides greater understanding of murder-suicide by itself and compared to murder and suicide.

A public domain code "Object Oriented Finite element analysis for materials science" (OOF) has been extended to include tools for analysis of viscoelastic materials. Utility of these tools has been discussed along with possible applications in this publication. Added features in OOF include means to quantitatively analyze the spatiotemporal response of a composite polymeric material in dynamic as well as in static deformation conditions. These coupled with the existing features of OOF, in particular, the complete analysis of mechanical characteristics of materials provide a comprehensive tool for the studies of time dependent behavior of variety of materials including polymeric solid composites, polymer nanocomposites, polymer blends, block copolymers, and so on. The viscoelastic module draws its strength from the underlying OOF architecture to provide a macroscopic evaluation of mechanical properties using microstructural details. An application of this module for deformation analysis is the characterization of mechanical behavior a polymer nanocomposites. The deformation behaviour of polymer composite depends on the combined characteristic relaxation times of its constituents as well as its microstructural details. Results of analysis are expected to provide better insight into the role of microstructure as well as the role of interphase on the average mechanical / Singapore-MIT Alliance (SMA)

Objective: To describe the walking characteristics of a sample of ambulatory subjects with sub-acute incomplete spinal cord injury (iSCI). Methods: 52 subjects were included in a secondary analysis of clinical and spatiotemporal measures of walking. The study sample was described as a whole and subsequently divided into subgroups on the basis of 3 clinical factors (etiology, severity, and neurological level of injury) and 4 gait factors (gait aid, velocity, symmetry, and variability). Results: Clinical and spatiotemporal parameters were highly variable across the study population. Sub–groups with unique gait features were best identified by velocity and variability. Conclusions: Spatiotemporal measures of walking provide augmented description of walking in the sub-acute iSCI population. Sub-grouping by gait factors warrants further investigation with respect to their ability to act as predictors and modifiers of treatment effect.

Objective: To describe the walking characteristics of a sample of ambulatory subjects with sub-acute incomplete spinal cord injury (iSCI). Methods: 52 subjects were included in a secondary analysis of clinical and spatiotemporal measures of walking. The study sample was described as a whole and subsequently divided into subgroups on the basis of 3 clinical factors (etiology, severity, and neurological level of injury) and 4 gait factors (gait aid, velocity, symmetry, and variability). Results: Clinical and spatiotemporal parameters were highly variable across the study population. Sub–groups with unique gait features were best identified by velocity and variability. Conclusions: Spatiotemporal measures of walking provide augmented description of walking in the sub-acute iSCI population. Sub-grouping by gait factors warrants further investigation with respect to their ability to act as predictors and modifiers of treatment effect.

This study investigated the spatiotemporal distribution of abundances of the fish eggs and Engraulid eggs in relation to environmental factors along the coastal waters off southwestern Taiwan. Moreover, the key to fish eggs under an optical microscope in winter(January) was revised. Samplings were carried out on a bimonthly basis. In total, 38 tows were conducted from January to November 2003.The samplings of eggs were collected by horizontal hauls with NORPAC and cyclindricalconic net at the water surface along Jiading, Linyuan and Fangliao. Sea surface temperature, sea surface salinity, dissolve oxygen, chlorophyll a concentration and density were measured simultaneously with a seabird CTD. The spatiotemporal distribution of the total eggs abundances of two kinds of nets were very similar, and more the abundance of cyclindricalconic net than the NORPAC net. Therefore, the total eggs abundance and species of cyclindricalconic net were adopted to investigate the spatiotemporal distribution of the eggs along the coastal waters off southwestern Taiwan. The total abundances of fish eggs demonstrated significant seasonal variations highest in July and lowest in November. The geographical difference was also observed that the highest abundances were recorded at Jiading, and followed by Linyuan and Fangliao. Based on the results of correlation analyses, it was revealed that the spatiotemporal fluctuations in the total abundances of fish eggs were significant positive correlated to the monthly variation of precipitation. 2,110 fish eggs were obtained from six samples in January, 2003, including Ophichthidae, Clupeidae, Synodontidae, Scaridae, Callionymidae, Soleidae , Cynoglossidae and Engraulidae. The fish eggs that couldn¡¦t be identified were firstly sorted into 28 groups by the egg shape, size, and membrane pattern. Furthermore, they were stored into 64 species based on the presence or absence, and the pattern of pigmentation. The group BIII, Engraulids eggs and unknown dead eggs were the top three dominant species. Due to the different composition of the dominant species, there were significant differences in the spatial distribution. The species composition of dominant group were the Callionymids eggs and unknown dead eggs in Jiading. The species composition of dominance group were group BIII , Engraulids eggs and unknown dead eggs in Linyuan, and Fangliao. In 2003, Engraulids eggs were very abundant in the coastal waters off southwestern Taiwan, representing 14% of the total fish egg abundances. Two peaks of Engraulids eggs abundances were found. One in the July to September 2003, and other one in January 2003. Spatial distribution in the abundances were also observed that the highest abundances were recorded at Fangliao, and followed by Linyuan and Jiading. The mortality rate of the Engraulids eggs was the reverse trends and spatial distribution of the Engraulids eggs abundances. The abundances of eggs were increased when precipitation was high and abundance of Amphipoda was low. The shape of Engraulids eggs was displayed regional differences. Engraulids eggs in Jiading and Fangliao were elongated shape, and oval shape in Linyuan. Seasonal variation in the egg shape was observed and also segregated into two groups representing elongated eggs group in May, July and September and oval eggs group in January, March and November, respectively. Engraulids eggs longitudinal diameter was significantly positive correlated with the SST and monthly precipitation, and were negatively correlated with sea surface salinity, dissolve oxygen and density. Maybe the group BIII was Mugilids eggs. Their spawning ground occurred in Linyuan. Furthermore, the spawning ground of both Callionymids eggs and Synodontids eggs were at Linyuan and Fangliao. The main spawning grounds of Engraulids eggs were at Linyuan and Fangliao along the coastal waters off southwestern Taiwan. The peak spawning season were in summer and winter 2003. The spawning time of Engraulids eggs was approximately at 00:00 to 01:00. The spatiotemporal variations of Engraulids eggs size were influenced by the alternation of the spawning grounds of Engraulids fish along the coastal waters off southwestern Taiwan.