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Math 661-103: Applied Statistics, J. M. Loh

Mathematical Sciences Syllabi

No abstract provided.

Math 661-851: Applied Statistics, A. Pole

Mathematical Sciences Syllabi

No abstract provided.

Math 663-101: Introduction To Biostatistics, G. Kariuki

Mathematical Sciences Syllabi

No abstract provided.

Math 680-101: Advanced Statistical Learning, W. Guo

Mathematical Sciences Syllabi

No abstract provided.

Math 690-001: Advanced Applied Mathematics Iii - Partial Differential Equations, A. Oza

Mathematical Sciences Syllabi

No abstract provided.

Math 691-101: Stochastic Processes With Applications, J. Maclaurin

Mathematical Sciences Syllabi

No abstract provided.

Hist 345-001: Communication Through The Ages, Florencia Pierri

History Syllabi

No abstract provided.

Frsc 359-003: Physical Methods Of Forensics, David Fisher

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Developmental And Sex Modulated Neurological Alterations In Autism Spectrum Disorder, Azeezat Azeez

Dissertations

Autism Spectrum Disorder (ASD) was first described in 1943 by Dr. Leo Kranner in a case study published in The Nervous Child. It is a neurodevelopment disorder, with a range of clinical symptoms. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), used by clinicians to diagnose mental disorders, a child needs to have persistent social deficits, language impairments, and repetitive behaviors, that cannot be explained by neurological damage or intellectual disability. It is known that children diagnosed with ASD are often are developmentally delayed therefore alterations in the typical developmental trajectory should be a major factor in …

Modelling In Vitro Dissolution And Release Of Sumatriptan Succinate From Polyvinylpyrrolidone-Based Microneedles Aided By Iontophoresis, James Paul Ronnander

Dissertations

A novel dissolving microneedle array system is developed to investigate permeation of a sumatriptan succinate formulations through the skin aided by iontophoresis. Three formulations consisting of hydrophilic, positively charged drug molecules encapsulated in a water-soluble biologically suitable polymer, polyvinylpyrrolidone (PVP), have been accepted by the U.S. Food and Drug Administration (FDA). The microneedle systems are fabricated with 600 pyramid-shaped needles, each 500 µm tall, on a 0.785-cm² circular array. In vitro transdermal studies with minipig skin and vertical Franz diffusion cells show > 68% permeation of sumatriptan over a 24-hour period. A combination of microneedle and electrical current density ranging …

Effects Of Electro-Osmotic Consolidation Of Clays And Its Improvement Using Ion Exchange Membranes, Lucas Martin

Dissertations

Electro-osmosis is an established method of expediting consolidation of soft, saturated clayey soils compared to commonly used methods, such as preloading with wick drains. In electro-osmotic consolidation a direct current (DC) is applied via inserted electrodes. This causes hydrated ions in the interstitial fluid to migrate to oppositely charged electrodes. Because the clay particles have a negative surface charge, the majority of ions in the interstitial fluid are positively charged. Therefore, the net flow will be towards the negatively charged electrode (cathode), where the water can be removed and thus consolidation is achieved. Certain problems, such as pH changes in …

Engineering Of Escherichia Coli 2-Oxoglutarate Dehydrogenase Complex With Mechanistic And Synthetic Goals, Joydeep Chakraborty

Dissertations

The Escherichia coli 2-oxoglutarate dehydrogenase complex (OGDHc) compromises multiple copies of three enzymes - 2-oxoglutarate dehydrogenase (E1o), dihydrolipoyl succinyltransferase (E2o), and dihydrolipoyl dehydrogenase (E3). OGDHc is found in the Krebs cycle and catalyzes the formation of the all-important succinyl-Coenzyme A (succinyl-CoA). OGDHc was engineered to understand the catalytic mechanism and optimized for chemical synthetic goals.

Succinyl-CoA formation takes place within the catalytic domain of E2o via a transesterification reaction. The succinyl group from the thiol ester of S8-succinyldihydrolipoyl-E2o is transferred to the thiol group of CoA. Mechanistic studies were designed to investigate enzymatic transthioesterification. His375 and Asp374 was shown to …

Analyzing Evolution Of Rare Events Through Social Media Data, Xiaoyu Lu

Dissertations

Recently, some researchers have attempted to find a relationship between the evolution of rare events and temporal-spatial patterns of social media activities. Their studies verify that the relationship exists in both time and spatial domains. However, few of those studies can accurately deduce a time point when social media activities are most highly affected by a rare event because producing an accurate temporal pattern of social media during the evolution of a rare event is very difficult. This work expands the current studies along three directions. Firstly, we focus on the intensity of information volume and propose an innovative clustering …

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan

Dissertations

Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The …

Applied Deep Learning In Intelligent Transportation Systems And Embedding Exploration, Xiaoyuan Liang

Dissertations

Deep learning techniques have achieved tremendous success in many real applications in recent years and show their great potential in many areas including transportation. Even though transportation becomes increasingly indispensable in people’s daily life, its related problems, such as traffic congestion and energy waste, have not been completely solved, yet some problems have become even more critical. This dissertation focuses on solving the following fundamental problems: (1) passenger demand prediction, (2) transportation mode detection, (3) traffic light control, in the transportation field using deep learning. The dissertation also extends the application of deep learning to an embedding system for visualization …

Data Multiplexing In Vector Acoustic Communication: System Design And Experiments, Erjian Zhang

Dissertations

Acoustic particle velocity channels, which are vector components of the acoustic field, have been recently explored to achieve communication purposes underwater. Vector sensors and transducers that can utilize acoustic particle velocity channels have compact multichannel designs, which are perfect for compact size underwater platforms. In this dissertation, an underwater acoustic multiple-input multiple-output (MIMO) communication system featuring orthogonal frequency division multiplexing (OFDM) and frequency shift keying (FSK) modulation is discussed. By transmitting multiple independent data streams simultaneously over several channels within the same bandwidth, the proposed MIMO system increases the transmission rate. A variety of components of the system such as …

Measurement Of Stresses And Their Effect On Transport In Thin Film Battery Electrodes, Subhajit Rakshit

Dissertations

At the moment, there is a significant push towards environmentally friendly energy production and gasoline-free transportation technologies. As a result, there is a renewed interest in energy storage devices such as lithium-ion batteries which will play a key role in providing energy storage capability for these applications. However, the current battery technology is reaching its limits and may not meet future energy storage demands. The increased demand and the limited lithium reserves in geographically remote areas of the earth will lead to higher cost of Li. The alternative battery technologies, such as sodium-ion batteries, are promising due to their low …

Memorias Del 4o. Coloquio De Estudios Sobre Juegos De Rol, Ricardo Morales-Carbajal, Carlos Villa Angulo, Miguel Ángel Bastarrachea Magnani, Christian Miguel Rudich De La Rosa, Julio César López Corolla, Luis Enrique González Bernal, Luis R. Miguez, Nicolás Carrillo Santarelli, Mauricio Rangel, Ruben Darío Hernández Mendo, Tomás Amans, Jesús Flores Romo, Maurizio Tazzer Dieterlen, Sandra Patricia Reyes Vega, Mario Nauzet García Hernández, Blanca Estela López Pérez, Cristo Leon, James Lipuma

STEM for Success Resources

Aquí se recopilan las ponencias recibidas para ser publicadas en el 4o. Coloquio de estudios sobre juegos de rol (2019), realizado en el Tec de Monterrey campus Puebla el 4 y 5 de julio de 2019. Únicamente se publican las ponencias cuyos autores dieron permiso explícito para ello y que facilitaron copia de su trabajo. Los resúmenes de las ponencias pasaron por un proceso de revisión doble ciego para ser admitidas en el coloquio.

Editor: Mauricio Rangel Jiménez

Chem 244-043: Organic Chemistry Ii, Andrew B. Naughton

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Chem 126-041: General Chemistry Ii, David Fisher

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Chem 339-011: Analytical Physical Chemistry For Chemical Engineers, Elena Avzianova

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Chem 126-141: General Chemistry Ii, David Fisher

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Model-Based Deep Autoencoders For Characterizing Discrete Data With Application To Genomic Data Analysis, Tian Tian

Dissertations

Deep learning techniques have achieved tremendous successes in a wide range of real applications in recent years. For dimension reduction, deep neural networks (DNNs) provide a natural choice to parameterize a non-linear transforming function that maps the original high dimensional data to a lower dimensional latent space. Autoencoder is a kind of DNNs used to learn efficient feature representation in an unsupervised manner. Deep autoencoder has been widely explored and applied to analysis of continuous data, while it is understudied for characterizing discrete data. This dissertation focuses on developing model-based deep autoencoders for modeling discrete data. A motivating example of …

Blind Separation For Intermittent Sources Via Sparse Dictionary Learning, Annan Dong

Dissertations

Radio frequency sources are observed at a fusion center via sensor measurements made over slow flat-fading channels. The number of sources may be larger than the number of sensors, but their activity is sparse and intermittent with bursty transmission patterns. To account for this, sources are modeled as hidden Markov models with known or unknown parameters. The problem of blind source estimation in the absence of channel state information is tackled via a novel algorithm, consisting of a dictionary learning (DL) stage and a per-source stochastic filtering (PSF) stage. The two stages work in tandem, with the latter operating on …

Probabilistic Spiking Neural Networks : Supervised, Unsupervised And Adversarial Trainings, Alireza Bagheri

Dissertations

Spiking Neural Networks (SNNs), or third-generation neural networks, are networks of computation units, called neurons, in which each neuron with internal analogue dynamics receives as input and produces as output spiking, that is, binary sparse, signals. In contrast, second-generation neural networks, termed as Artificial Neural Networks (ANNs), rely on simple static non-linear neurons that are known to be energy-intensive, hindering their implementations on energy-limited processors such as mobile devices. The sparse event-based characteristics of SNNs for information transmission and encoding have made them more feasible for highly energy-efficient neuromorphic computing architectures. The most existing training algorithms for SNNs are based …

Supercapacitors With Gate Electrodes, Tazima Selim Chowdhury

Dissertations

A new approach to improve the capacitance of supercapacitors (SC) is proposed in this study. A typical SC is composed of an anode and a cathode; a separator in between them assures an unintentional discharge of the capacitor. The study focuses on a family of structured separators, either electronically active or passive which are called gates. An active structured separator layer has been fabricated and analyzed. The structured separator has characteristics of electrical diode and is fabricated out of functionalized carbon nanotubes (CNT). Improvement of the overall capacitance of SC, equipped with either active or passive structured separators demonstrated a …

Multi-Wavelength Investigation Of Energy Release And Chromospheric Evaporation In Solar Flares, Viacheslav M. Sadykov

Dissertations

For a comprehensive understanding of the energy release and chromospheric evaporation processes in solar flares it is necessary to perform a combined multi-wavelength analysis using observations from space-based and ground-based observatories, and compare the results with predictions of the radiative hydrodynamic (RHD) flare models. Initially, the case study of spatially-resolved chromospheric evaporation properties for an M 1.0-class solar flare (SOL2014-06-12T21:12) using data form IRIS (Interface Region Imaging Spectrograph), HMI/SDO (Helioseismic and Magnetic Imager onboard Solar Dynamics Observatory), and VIS/GST (Visible Imaging Spectrometer at Goode Solar Telescope), demonstrate a complicated nature of evaporation and its connection to the magnetic field topology. …

Rare Event Sampling In Applied Stochastic Dynamical Systems, Yiming Yu

Dissertations

Predicting rare events is a challenging problem in many complex systems arising in physics, chemistry, biology, and materials science. Simulating rare events is often prohibitive in such systems due to their high dimensionality and the numerical cost of their simulation, yet analytical expressions for rare event probabilities are usually not available. This dissertation tackles the problem of approximation of the probability of rare catastrophic events in optical communication systems and spin-torque magnetic nanodevices. With the application of the geometric minimum action method, the probability of pulse position shifts or other parameter changes in a model of an actively mode-locked laser …

Dual Modality Optical Coherence Tomography : Technology Development And Biomedical Applications, Farzana Rahmat Zaki

Dissertations

Optical coherence tomography (OCT) is a cross-sectional imaging modality that is widely used in clinical ophthalmology and interventional cardiology. It is highly promising for in situ characterization of tumor tissues. OCT has high spatial resolution and high imaging speed to assist clinical decision making in real-time.

OCT can be used in both structural imaging and mechanical characterization. Malignant tumor tissue alters morphology. Additionally, structural OCT imaging has limited tissue differentiation capability because of the complex and noisy nature of the OCT signal. Moreover, the contrast of structural OCT signal derived from tissue’s light scattering properties has little chemical specificity. Hence, …

Speciation Of Gaseous Oxidized Mercury Molecules Relevant To Atmospheric And Combustion Environments, Francisco J. Guzman

Dissertations

Mercury is a pervasive and highly toxic environmental pollutant. Major anthropogenic sources of mercury emissions include artisanal gold mining, cement production, and combustion of coal. These sources release mostly gaseous elemental mercury (GEM), which upon entering the atmosphere can travel long distances before depositing to environmental waters and landforms. The deposition of GEM is relatively slow, but becomes greatly accelerated when GEM is converted to gaseous oxidized mercury (GOM) because the latter has significantly higher water solubility and lower volatility. Modeling GOM deposition requires the knowledge of its molecular identities, which are poorly known because ultra-trace (tens to hundreds part …