This dissertation is motivated by the practical problem of highway traffic estimation using velocity measurements from GPS enabled mobile devices such as cell phones. In order to simplify the estimation procedure, a velocity model for highway traffic is constructed, which results in a dynamical system in which the observation operator is linear. It presents a new scalar hyperbolic partial differential equation (PDE) model for traffic velocity evolution on highways, based on the seminal Lighthill-Whitham-Richards (LWR) PDE for density. Equivalence of the solution of the new velocity PDE and the solution of the LWR PDE is shown for quadratic flux functions. Because this equivalence does not hold for general flux functions, a discretized model of velocity evolution based on the Godunov scheme applied to the LWR PDE is proposed. Using an explicit instantiation of the weak boundary conditions of the PDE, the discrete velocity evolution model is generalized to a network, thus making the model applicable to arbitrary highway networks. The resulting velocity model is a nonlinear and nondifferentiable discrete time dynamical system with a linear observation operator, for which a Monte Carlo based ensemble Kalman filtering data assimilation algorithm is applied.

The model and estimation technique is evaluated with experimental data obtained from a large-scale field experiment known as Mobile Century. The velocity estimates using GPS data from cellphones is compared to velocity estimates using inductive loop detector data from the PeMS system. More than 900 estimation simulations are performed using various volumes of GPS data and inductive loop detector data collected during the experiment, which show travel times can be reconstructed to less than 10% error with sufficient GPS data, loop data, or a combination of both. All data collected during the field experiment and used in the simulations are available for download at http://traffic.berkeley.edu.

Inkjet printing has been actively pursued as a means of realizing integrated electronic devices. To date, the vast majority of work on this topic has centered on the development of inks and process integration, while little research has focused on the details of pattern generation.

In this work, we first examine inkjet-printed conductive lines. We show several different printed-line morphologies and explain the causes of these forms of varying utility. More generally, we develop and demonstrate a methodology to optimize the raster-scan printing of patterned, two-dimensional films. We show that any fixed line spacing can not maintain the constant perimeter contact angle necessary for arbitrary patterned footprints. We propose and demonstrate a printing algorithm that adjusts line spacing to print optimal features.

Our work analyzing patterned drops reveals that drop contact angle is a function of position and shape. Numerical solutions to the Young-Laplace equation enable us to predict the sharpest corners possible in a rectangular bead with a given wetting behavior. We verify our computational results with printed rectangles on substrates with variable wetting. Finally, we motivate future research directions including general solutions to a patterned drop's surface in any corner and the behavior of line junctions and other concave corners of printed lines.

The integration of multimodal sensory information into a common neural code is a critical function of all complex nervous systems. This process is required for adaptive responding to incoming stimuli as well as the formation of a cognitive map of the external sensory environment. The underlying neural mechanisms of multimodal integration are poorly understood due, in part, to the technical difficulties of manipulating multimodal sensory information in combination with simultaneous in-vivo electrophysiological recording in awake behaving animals. We therefore developed a non-invasive multimodal virtual reality system that is conducive to wired electrophysiological recording techniques. This system allows for the dynamic presentation of highly immersive audiovisual virtual environments to rats maintained in a body fixed position on top of a quiet spherical treadmill. Notably, this allows the rats to remain at the same spatial location in the real world without the need for head fixation. This method opens the door for a wide array of future studies aimed at elucidating the underlying neural mechanisms of multimodal integration.