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This study provides an empirical test of a previously proposed assertion that intelligence as adaptation has an attitudinal as well as an ability component. The ability component deals with what the basic knowledge and skills are that underlie intelligence, and how much of each one an individual has. The attitudinal component deals with how an individual chooses to deploy the abilities they have. In other words, to what use are the abilities put? It is argued that it is impossible fully to separate the measurement of the ability component from the attitudinal one. In a diverse population, even taking an intelligence test will show itself to involve an attitude toward the test, which may enhance or detract from performance, as when one sees the test as irrelevant or harmful to one’s life, or as a sociocultural misfit to one’s life experience. To succeed, people need not only to have abilities, but attitudes that put those abilities to effective use to accomplish individuals’ life goals. In the study, we found that intelligent attitudes are related, but non-identical, to germane constructs, such as wisdom, the need for cognition, creativity, and openness to experience. Scores on the attitudinal measure were not related to scores on tests of fluid intelligence and academic abilities/achievement. Thus, the range of attitudes regarding how to deploy intelligence can vary over ability levels.

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues.

The ocean component of current coupled atmosphere-ocean climate models cannot resolve meso-scales below about 100km whereas much of ocean's turbulent energy lies in this range of scales inducing uxes that affect all aspects of ocean circulation and hence the associated climate models. In this thesis, we focus on the study of the problem of investigating and parameterizing the effective large-scale transport properties of vortex dominated sub-grid scale flow structures in meso-scale oceanic turbulence. We develop a methodology based on homogenization theory toward representing the effects of meso-scale coherent structures on large-scale transport in the ocean. Our systematic parametrization strategy relies on constructing a hierarchy of deterministic and random flow models and on coupling the results from numerical simulations of these models and the asymptotic analysis with respect to key non-dimensional physical parameters such as Péclet and Strouhal numbers of the cell problems arising from homogenization theory and of the model equations. In our hierarchy of flow models, we first construct the prototype compactly supported smoothly decaying vortex, the modified Rankine vortex, used in constructing the kinematic vortex dominated deterministic and random flows designed in this thesis. Next, in increasing order of complexity, we investigate the transport properties of first a simple deterministic flow, a Rankine vortex flow, in which a periodic array of compactly supported smoothly decaying vortices is superposed with a constant mean flow, second of a steady non-Gaussian random flow, a Poisson blob velocity model consisting of a superposition of randomly distributed compactly supported smoothly decaying vortices, and third of two time-dependent non-Gaussian random flows, the stochastically advected Poisson blob flow, in which a random number of uniformly randomly distributed modified Rankine vortices move around the domain according to independent Brownian motions, and the stochastic blinking vortex flow in which at any time a random number of uniformly randomly distributed modified Rankine vortices having exponential lifetimes exist in the domain. In the sequel, we derive analytically the second order covariance structures of the time-dependent random velocity fields using probabilistic formulations of these velocity fields, and the universal defining properties such as the Eulerian root-mean-squared velocity, the Eulerian correlation length, and the Eulerian correlation time of these time-dependent random velocity fields using their covariance structures. We show that in all our kinematic models, it is possible to parametrize the large-scale effective transport properties of the investigated idealized vortex dominated flows by simple functions of key universal non-dimensional flow parameters after identifying the data collapses in the parameter spaces. In all our models, in the asymptotic regimes of high and low Péclet number, we establish the relationships between the effective transport properties of our models and the underlying model specific parameters, such as the vortex radius, the vortex velocity and the amount of vortex overlap in the domain, as well as the relationships between the effective transport properties of our models and the universal defining flow characteristics such as the Eulerian root-mean-squared velocity, the Eulerian correlation length, and the Eulerian correlation time of the random velocity fields used in these models. Using arguments based on the mixing length theory and the Taylor's formula, we derive the underlying intrinsic Lagrangian correlation length and time scales of our random models in these asymptotic regimes. In our time-dependent random models, we show that at moderate to high Péclet numbers and for large enough Strouhal number, the effective transport properties are sensitive to the changes in Strouhal number. We account for this behaviour by proving formally through a stochastic averaging principle that in the limit of high Strouhal number the effective transport properties of our time-dependent random models can be described by Kubo's formula. At present, we find a substantial discrepancy between the results of our numerical computations for the enhancement of diffusivity and low Péclet number asymptotic calculations for the stochastic blinking vortex model and aim to resolve this in future work. After extraction of spatial and temporal vortex statistics from a vortex dominated quasi-geostrophic simulation and calibration of our time-dependent models in accordance with these statistics, we compare the results of our calibrated models with the results obtained from the vortex dominated quasi-geostrophic simulation of the meso-scale oceanic turbulence.