Life Sciences Commons^™

Towards Understanding The Role Of Central Processing In Release From Masking, Nima Alamatsaz

Dissertations

People with normal hearing have the ability to listen to a desired target sound while filtering out unwanted sounds in the background. However, most patients with hearing impairment struggle in noisy environments, a perceptual deficit which current hearing aids and cochlear implants cannot resolve. Even though peripheral dysfunction of the ears undoubtedly contribute to this deficit, surmounting evidence has implicated central processing in the inability to detect sounds in background noise. Therefore, it is essential to better understand the underlying neural mechanisms by which target sounds are dissociated from competing maskers. This research focuses on two phenomena that help suppress …

Exploring Fused Deposition Modeling (Fdm) Three-Dimensional Printing Tablet Design Options For Pharmaceutical Dosage Forms, Guluzar Gorkem Buyukgoz

Dissertations

This dissertation examines the use of Fused Deposition Modeling (FDM) based three-dimensional (3D) printing approach for developing patient-specific dosage forms and addressing related technical challenges in such drug delivery systems. The first main objective is to explore pharmaceutical tablet design options using novel FDM 3D printing technology as the drug delivery platform such that drug form and tablet properties are tailored by considering patient age-specific formulations and dissolution control. Of the five different design options, two proposed options meet the main objective of providing similar drug release, whereas the popular option of fixed drug concentration but differing tablet size could …

Alcohol As A Catalyst For Hiv-Associated Neuroinflammation And Tbi-Induced Iron Toxicity, Agnieszka Agas

Dissertations

Alcohol has long been considered an exacerbator of diseases, disorders, and injuries as well as many of the accompanying symptoms. As an alternative approach, this dissertation explores alcohol as a catalyst for two different human disease conditions, human immunodeficiency virus (HIV)-associated neuroinflammation and traumatic brain injury (TBI)-induced iron toxicity. In HIV-1 infection, this dissertation presents a novel anti-viral drug, called Drug-S, for a possible inhibition and treatment of HIV-1 disease progression.

The first aim explores the influence of alcohol with HIV-associated neuroinflammation on macrophage migration across an in vitro model of the blood brain barrier. There is a gap in …

Selective Neural Stimulation By Leveraging Electrophysiological Diversity And Using Alternative Stimulus Waveforms, Bemin Ghobreal

Dissertations

Efforts on finding the principle mechanism for selective neural stimulation have concentrated on segregating the neurons based on their size and other geometric factors. However, neuronal subtypes found in different parts of the nervous system also differ in their electrophysiological properties. The primary objective of this study is to investigate the feasibility of selective activation of neurons by leveraging the diversity seen in passive and active membrane properties.

Using both a local membrane model and an axon model based on the CRRSS, the diversity of electrophysiological properties is simulated by varying four model parameters (membrane leakage-Gleak and capacitance-Cm, temperature coefficient-Ktemp, …

Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu

Dissertations

Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …