Witches : inaugural lecture delivered at Rhodes University

Inaugural lecture delivered at Rhodes UniversityRhodes University Libraries (Digitisation

Local Dosing in a 3-Mercaptopropionic Acid Chemically-Induced Epileptic Seizure Model with Microdialysis Sampling

The focus of this research was the development of an animal model for local administration of 3-mercaptopropionic acid (3-MPA) in a chemically-induced epileptic seizure model using microdialysis sampling with simultaneous electrocorticography recording (ECoG). Local administration of 3-MPA through the microdialysis probe was employed to elicit seizures in a localized brain region. Delivery of 3-MPA to the brain and changes in amino acid and catecholamine neurotransmitters were monitored. Simultaneous ECoG recordings were made using a microdialysis probe with an internal Ag/AgCl electrode. Local administration of a convulsant is important, as many clinical cases present with focal seizures. Neurochemical and electrical activity were monitored in three separate brain regions: the striatum, hippocampus, and locus coeruleus. 3-MPA was administered through the microdialysis probe in one region, while control samples were collected in the other two. These results demonstrated that unless two brain regions were connected via efferent or afferent pathways, administration of 3-MPA in one region had no neurochemical effect in the others. In the region where 3-MPA was administered, an increase in both glutamate, the main excitatory amino acid, and GABA, the main inhibitory amino acid, was seen. In addition, an increase in both dopamine and norepinephrine was seen. A multiple dosing regimen of 3-MPA was developed where 3-MPA was administered twice. These results showed that there was an attenuation in the increase of glutamate and GABA during the second administration of 3-MPA, indicating a neuronal protective mechanism taking place to decrease the effect of the second 3-MPA administration. Seizures were not detected using during local administration of 3-MPA using the microdialysis probes with an internal Ag/AgCl electrode. This was not due to the ineffectiveness of the electrodes, as they detected seizures during systemic dosing of 3-MPA. It is possible that the number of neurons excited from the local administration of 3-MPA were so limited that the signal was too small to be detected

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

Recent work has shown that optical flow estimation can be formulated as a supervised learning task and can be successfully solved with convolutional networks. Training of the so-called FlowNet was enabled by a large synthetically generated dataset. The present paper extends the concept of optical flow estimation via convolutional networks to disparity and scene flow estimation. To this end, we propose three synthetic stereo video datasets with sufficient realism, variation, and size to successfully train large networks. Our datasets are the first large-scale datasets to enable training and evaluating scene flow methods. Besides the datasets, we present a convolutional network for real-time disparity estimation that provides state-of-the-art results. By combining a flow and disparity estimation network and training it jointly, we demonstrate the first scene flow estimation with a convolutional network.Comment: Includes supplementary materia

Inclusion of an Introduction to Infrastructure Course in a Civil and Environmental Engineering Curriculum

Civil infrastructure refers to the built environment (sometimes referred to as public works) and consists of roads, bridges, buildings, dams, levees, drinking water treatment facilities, wastewater treatment facilities, power generation and transmission facilities, communications, solid waste facilities, hazardous waste facilities, and other sectors. Although there is a need to train engineers who have a holistic view of infrastructure, there is evidence that civil and environmental engineering (CEE) programs have not fully addressed this increasingly recognized need. One effective approach to address this educational gap is to incorporate a course related to infrastructure into the curriculum for first-year or second-year civil and environmental engineering students. Therefore, this study assesses the current status of teaching such courses in the United States and identifies the incentives for, and the barriers against, incorporating an introduction to infrastructure course into schools’ current CEE curricula. Two distinct activities enabled these objectives. First, a questionnaire was distributed to CEE programs across the United States, to which 33 responses were received. The results indicated that although the majority of participants believe that offering such a course will benefit students by increasing the breadth of the curriculum and by providing a holistic view of CEE, barriers such as the maximum allowable credits for graduation, the lack of motivation within a department—either because such a course did not have a champion or because the department had no plans to revise their curriculum—and a lack of expertise among faculty members inhibited inclusion of the course in curricula. Second, three case studies demonstrating successful inclusion of an introduction to infrastructure course into the CEE curriculum were evaluated. Cases were collected from Marquette University, University of Wisconsin-Platteville, and West Point CEE programs, and it was found that the key to success in including such a course is a motivated team of faculty members who are committed to educating students about different aspects of infrastructure. The results of the study can be used as a road map to help universities successfully incorporate an introduction to infrastructure course in their CEE programs