Speakers and abstracts are listed below:

Role of Self-Heating in the Nonlinear Transport in Metallic Carbon Nanotubes
Marcelo Kuroda (CE)

Carbon nanotubes are promising candidates for nano-electronics due to their natural small scales as well as their mechanical, thermal, and electrical properties. In this context, recent series of experiments have unveiled the potential of metallic carbon nanotubes as a substitute for copper for interconnects in integrated circuits. These experiments also showed that metallic carbon nanotubes exhibit nonlinear electrical characteristics similar to semiconductor materials (ranging from saturation to negative differential resistance), which strongly depend on the device configuration. Our work introduces a new model based on the Boltzmann transport equation to account for the transport nonlinearities. Our results show that Joule heating and heat dissipation play a crucial role in the features observed in the IV characteristics. Our model provides a coherent picture of electrical and thermal transport in metallic carbon nanotubes, in good agreement with experiments.

Predicting Prosodic Phrasing Through Grammatical Interface
Tae-Jin Yoon (CS)

The prosodic structure of speech is based on complex interaction within and between several different levels of linguistic, and paralinguistic organization, and is expressed in the modulation of F0, intensity, duration, and voice quality, as well as the occurrence of pauses. Even though leading theories of prosody maintain that prosody is shaped through the interaction of grammatical factors from phonology, syntax, semantics, and pragmatics, there is no consensus on how to model their interaction. I provide a new probabilistic model of the mapping between prosody and phonology, syntax, and argument structure. The model encodes phonological features, shallow syntactic constituent structure, and basic argument structure. A machine learning experiment using these features to predict prosodic phrase boundaries achieves more than 92% accuracy in predicting prosodic boundary location. An experiment for predicting the strength of prosodic boundaries achieve 88.06% accuracy. This study sheds light on the relationship between prosodic phrase structure and other grammatical structures.

Three-Dimensional Microelectrode Array for Recording Dissociated Neuronal Cultures
Katherine Musick (NT)

Presently, in vitro studies of neural networks are done with two-dimensional monolayers of cells even though three-dimensional cultures are more like in vivo correlates in both structure and response to stimuli. This research project aims to advance knowledge of neural networks through the development of a device that permits in-depth study of three-dimensional neural cultures in vitro. The device, a three-dimensional microelectrode array (3D MEA), is designed as a stack of individually-patterned thin films. Electrodes and microfluidic channels are created on these thin films prior to stacking. The purpose of the microfluidics is to provide an artificial vasculature for nutrient supply and aeration, as well as to permit loading of dissociated neurons into the structure. Once the neurons grow and establish electrical activity, the embedded electrodes will allow for both recording and stimulation. The resulting system should allow the collective properties of 3D neural networks to be observed and manipulated with a level of control not possible in living animals. Progress to date includes fabrication of a two-layer device and short-term neural culturing within the device.