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Title: Combining Simulation and Emulation for Planning and Evaluation of Smart Grid Security, Resilience, and Operations
Creator: Hannon, Christopher
Date: 2020
Description: The modern power grid is a complex, large scale cyber-physical system comprising of generation, transmission and distribution elements....
Show moreThe modern power grid is a complex, large scale cyber-physical system comprising of generation, transmission and distribution elements. However, advancements in information technology have not yet caught up to the legacy operational technology used in the electric power system. Coupled with the proliferation of renewable energy sources, the electric power grid is in a transition to a smarter grid; operators are now being equipped with the tools to make real-time operational changes and the ability to monitor and provide situational awareness of the system. This shift in electric power grid priorities requires an expansive and reliable communication network to enhance efficiency and resilience of the Smart Grid. This trend calls for a simulation-based platform that provides sufficient flexibility and controllability for evaluating network application designs, and facilitating the transition from in-house research ideas into production systems. In this Thesis, I present techniques to efficiently combine simulation systems, emulation systems, and real hardware into testbed systems to evaluate security, resilience, and operations of the electric power grid. While simulating the dynamics of the physical components of the electric power grid, the cyber components including devices, applications, and networking functions are able to be emulated or even implemented using real hardware. In addition to novel synchronization algorithms between simulation and emulation systems, multiple test cases in applying software-defined networking, an emerging networking paradigm, to the power grid for security and resilience and phasor measurement unit analytics for grid operations are presented which motivate the need for a simulation-based testbed. The contributions of this work lay in the design of a virtual time system with tight controllability on the execution of the emulation systems, i.e., pausing and resuming any specified container processes in the perception of their own virtual clocks, and also lay in the distributed virtual time based synchronization across embedded Linux devices.
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Title: A NEURAL NETWORK BASED MODEL FOR BIOMASS GASIFICATION IN FLUIDIZED BED
Creator: Dirbaz, Mohsen
Date: 2020
Description: Biomass is a renewable energy resource and its utilization has received great attention due to its life cycle carbon-neutrality and the...
Show moreBiomass is a renewable energy resource and its utilization has received great attention due to its life cycle carbon-neutrality and the potential to substitute fossil fuel to produce a variety of energy-related products. Thermochemical gasification is an important route for conversion of biomass that results in a product gas mainly consisting of H2, CO, CO2, CH4 and other light hydrocarbons that can be used as fuel gas to generate power, or as well as raw material to produce a variety of chemicals. Among the existing gasifiers, fluidized beds (FB) offer many advantages such as high conversion efficiency and great flexibility over types of feedstock.More than 200 data sets of biomass gasification in fluidized bed were collected featuring a wide range of operating condition and fuel types. An axiom-based reasoning was used to develop a multiphase statistical pathway needed as a precondition to effectively quantify the entanglements of different important factors in the process.Specifically, by creating an interconnected chain of analysis based on trigonometric functions, geometric projections, and design of a statistical inference tool utilizing neural network units, multiple partial measures of associations between biomass constituents, and operating condition were effectively consolidated and embedded in a single characteristic matrix that consequently led to detection of monotonic relationships for prediction of carbon conversion efficiency and product gas yield. The black box model in comparison to three different models showed better accuracy in predicting four major components of product gas, over the largest applicable range of all the influential parameters of the process, namely, temperature, air equivalent ratio, steam to biomass ratio, and type of fuel. In part of our methodology, we introduce a novel technique for obtaining a dynamical property value for stationary objects, based on a “specific computational time” of an “abstract mechanical operation on characteristics matrices”. The specific computational time (sct) showed excellent capability in capturing the non-equilibrium factor of the process which itself was function of several interrelated variables.
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Title: THE SPATIAL BLOCK: NATURAL VENTILATION IN HOT AND DRY CLIMATES OF TURKEY
Creator: BAY, EZGI
Date: 2020
Description: The housing deficit is a global problem. In Turkey, solutions to remedy scarce, unaffordable, and low-grade housing are being proposed by TOKI...
Show moreThe housing deficit is a global problem. In Turkey, solutions to remedy scarce, unaffordable, and low-grade housing are being proposed by TOKI, the governmental mass housing administration. Its residential projects based on ‘standard regulations’ and ‘high-rise typologies’ have been widely criticized. The ‘one size fits all’ approach is known for its limited exploration of contemporary needs of this society. Low quality urban and architectural conditions in TOKI projects are believed to marginalize the living standards of the residents. Sprawling rapidly throughout different regions around the country, a permanent complaint of TOKI residents is related to outdoor and indoor thermal conditions. As consequence of this ‘homogenization effect’, overheated and underheated conditions are experienced in these ‘naturally ventilated buildings’ designed with few considerations regarding the surrounding environment. Minimal research has been done on how TOKI towers perform under extreme seasonal conditions and what other building forms could be used in consonance with localized Turkish climates. Most TOKI projects have been developed for ‘hot and dry climates’ that also correspond to areas with larger urban growth from recent migrations. Through post-occupancy evaluations, this dissertation investigates a TOKI built in this climatic context. At the same time, this study brings new ‘typological’ alternatives analyzed through energy simulations and computer fluid dynamics (CFD). These methods are intended to bring clarity about the dynamic of thermal stress inside this project, and how renewable sources, such as prevailing winds, could be used to alleviate thermal related problems in consonance with ‘building forms’ derived from ‘vernacular architecture’ in this region.Inputs from residents illustrate the dynamics of thermal stress and reliance on natural ventilation in summer conditions. It is confirmed through results of the Predicted Percentage Dissatisfied (PPD) and the Air Changes per Hour (ACH) obtained from Simulations in the IES-VE software. The relationship between human thermal comfort and indoor microclimate in TOKI housing can be improved through the reformulation of its residential typologies. The ‘Spatial Block’ approach presented in this dissertation brings the idea of how urban and architectural decisions in addition to improving indoor climatic conditions and thermal satisfaction or residents, brings them improved social integration.
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Title: DATA PRIVACY AND DEEP LEARNING IN THE MOBILE ERA: TRACEABILITY AND PROTECTION
Creator: Chen, Linlin
Date: 2020
Description: Privacy and deep learning have been two of the most exciting research trends in both academia and industry. On the one hand, big data rapidly...
Show morePrivacy and deep learning have been two of the most exciting research trends in both academia and industry. On the one hand, big data rapidly expedite lots of data orientated applications, especially like deep learning services. With the tremendous value exhibited by the data, the privacy of data subjects who generate the data, has also raised much attention. Meanwhile more regulations and legislation have been enacted or enforced, intending to enforce the companies and organizations to strictly comply with the personal privacy protection while collecting or utilizing their data. All these moves will substantially change the ways to train the deep learning models and provide AI services, and in some ways might hinder the development of deep learning if not coming up with some sophisticated mechanisms. On the other hand, deep learning has been showing incredibly promising performance in a variety of areas like face recognition, voice recognition, recommendation & advertising, autonomous driving, medical imaging, etc.. This keeps us thinking will deep learning also in turn influence privacy and be leveraged to compromise privacy. Meanwhile we also observe that mobile devices become so ubiquitous that more shares of data are generated on mobile devices, and mostly those data are both extremely sensitive for data subjects as well as extremely valuable for developing deep learning. We shouldn’t neglect the impact of mobile devices on both privacy and deep learning.In this thesis I explore the research on the interactions between privacy and deep learning, especially with the mobile devices being involved in. Specifically I work on: 1). How does privacy change the way we use the data when building deep learning models, and present the mechanism for privacy protection towards deep learning. 2). How does deep learning in turn make privacy more vulnerable to be compromised, and demonstrate the privacy compromise by facilitating deep learning to trace the source mobile devices and link the personal identities.
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Title: A FRAMEWORK FOR MANAGING UNSPECIFIED ASSUMPTIONS IN SAFETY-CRITICAL CYBER-PHYSICAL SYSTEMS
Creator: Fu, Zhicheng
Date: 2020
Description: For a cyber-physical system, its execution behaviors are often impacted by its operating environment. However, the assumptions about a cyber...
Show moreFor a cyber-physical system, its execution behaviors are often impacted by its operating environment. However, the assumptions about a cyber-physical system’s expected environment are often informally documented, or even left unspecified during the system development process. Unfortunately, such unspecified assumptions made in cyber-physical systems, such as medical cyber-physical systems, can result in patients’ injures and loss of lives. Based on the U.S. Food and Drug Administration (FDA) data, from 2006 to 2011, there were 5,294 recalls and 1,154,451 adverse events resulting in 92,600 patient injuries and 25,800 deaths. One of the most critical reasons for these medical device recalls is the violations of unspecified assumptions. These compelling data motivated us to research unspecified assumptions issues in safety-critical cyber-physical systems, and develop approaches to reduce the failures caused by unspecified assumptions.In particular, this thesis is to study the issues of unspecified assumptions in cyber-physical system design process, and to develop an unspecified assumption management framework to (1) identify unspecified assumptions in system design models; (2) facilitate domain experts to perform impact analysis on the failures caused by violating unspecified assumptions; and (3) explicitly model unspecified assumptions in system design models for system safety validation and verification.Before starting to develop the unspecified assumption management framework, we first need to study how unspecified assumptions may be introduced into cyber- physical systems. We took cases from the FDA medical device recall database to analyze the root causes of medical device failures. By analyzing these cases, we found two important facts: (1) one of the major reasons that causes medical device recalls is violation of some unspecified assumptions; and (2) unspecified assumptions are often introduced into the system design models through syntactic carriers. Based on the two findings, we propose a framework for managing unspecified assumption in cyber- physical system development process. The framework has three components. The first component is called the Unspecified Assumption Carrier Finder (UACFinder), which is to identify unspecified assumptions in system design models through automatically extracting syntactic carriers associated with unspecified assumptions. However, as the number of unspecified assumptions identified from system design models can be large, and it may not be always feasible for domain experts to validate and address the most safety-critical assumptions at different system development phases. Therefore, the second component of the framework is a methodology that uses the Failure Mode and Effects Analysis (FMEA) based prioritization approach to facilitate domain experts to perform impact analysis on unspecified assumptions identified by the UACFinder and asses their safety-critical level. The third component of the framework describes a model architecture and corresponding algorithms to model and integrate assumptions into system design models, so that system safety associated with these unspecified assumptions can be validated and formally verified by existing tools.We also have conducted case-studies on representative system models to demonstrate how UACFinder can identify unspecified assumptions from system design mod- els, and how the FMEA based prioritizing approach can facilitate domain experts to verify the appropriateness of identified assumptions. In addition, case studies are also conducted to demonstrate how system safety properties can be improved by modeling and integrating unspecified assumptions into system models. The results of case-studies indicate that the unspecified assumption management framework can identify unspecified assumptions, facilitate domain experts to validate and verify the appropriateness of identified assumptions, and explicitly specify assumptions that would cause defects in these systems.
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Title: Integrity based landmark generation: A method to generate landmark configurations that guarantee mobile robot localization safety
Creator: Chen, Yihe
Date: 2020
Description: From the bronze-age city Nineveh to the modern metropolitan like Tokyo, traffic shape cities and profoundly affect the life of people. Similar...
Show moreFrom the bronze-age city Nineveh to the modern metropolitan like Tokyo, traffic shape cities and profoundly affect the life of people. Similar to how the wide-spreading of automobile had modified the modern cities in early 20th century, we are now standing on the eve of yet another traffic revolution. With the vast spreading of autonomous/semi- autonomous robotics application, it is important for the urban designers to design or retrofit urban environment that is safe and friendly to the autonomous robots; As more robots are deployed in life-critical situations, such as autonomous passenger vehicles, it is imperative to consider their safety, and in particular, their localization safety. While it would be ideal to guarantee safety in any environment without having to physically modify said environment, this is not always possible and one may have add landmarks or active beacons to reach an acceptable level of safety for landmark-based localization. Localization safety is assessed using integrity, the primary safety metric used in open-sky aviation applications that has been recently applied to mobile robots and can ac- count for the impact of rarely occurring, undetected faults. Conventional integrity monitor- ing method has high dependency on GPS system, while the traditional Global Navigation Satellite System - Inertia Measurement Unit (GNSS-IMU) based localization does not ap- plied in the metropolitan areas due to the signal blocking and multi-pathing problem caused by high-rise structures. Thus, this dissertation concentrates on the feature based integrity monitoring method. This dissertation formulates environmental localization safety problem as a system- atic optimization problem: given the robot’s trajectory and the current landmark map, add the minimal number of new landmarks at certain location such that the integrity risk along the trajectory is below a given safety threshold. This dissertation proposes two algorithms to solve the problem: Integrity-based Landmark Generator (I-LaG) and Fast I-LaG. I-LaG adds fewer landmarks but it is relatively computationally expensive; Fast I-LaG is less com- putationally intensive at the expense of more landmarks. Both simulation and experimental results are presented.
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Title: ENHANCED OPTICAL TOMOGRAPHY IN DIFFUSE MEDIA USING OPTICAL GATING OF EARLY PHOTONS
Creator: Ghosh, Aishwarya
Date: 2020
Description: Tissue biopsies, where a volume of tissue is removed from a patient, typically through needle extraction, provides critical information about...
Show moreTissue biopsies, where a volume of tissue is removed from a patient, typically through needle extraction, provides critical information about the cellular and molecular aspects of an individual patient’s health and/or disease. However, current pathological assessments of tissue biopsies evaluate less than 1% of the volume of the tissue (e.g., one to a few 5-micron slices are sectioned out of the biopsy and stained/processed for microscopic analysis). Since the bulk of tissue biopsy is carried out through optical imaging (absorption or fluorescence), a more 3D, “whole-biopsy” view is conceivably possible with optical projection tomography (OPT). The challenge with OPT has been that for clinically relevant sized biopsies, most photons undergo multiple scattering events that lead to loss of spatial resolution that makes accurate pathological analysis intractable. In my MS thesis, I worked on the development of an enhanced OPT system that employs optical gating based on non-linear up-conversion of infrared ultrashort laser pulses to isolate “early-arriving” photons that experience significantly less scatter than the bulk of photons transiting a scattering biological sample. Considering the complexity of such a system, the entirety of my MS thesis work was spent constructing and testing the femtosecond optical gated OPT system and though I was unable to validate its operation in biological samples, simulations suggest that the properties we were able to achieve could allow high resolution optical imaging in 0.1-1 cm-diameter specimens.
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Title: UTILITY OF WATERSHED MODELS: IMPROVING TMDL DEVELOPMENT THROUGH A MARGIN OF SAFETY ESTIMATION AND UNCERTAINTY COMMUNICATION
Creator: Nunoo, Robert
Date: 2020
Description: Watershed models are used to represent the physical, chemical, and biological mechanisms that determine the fate and transport of pollutants...
Show moreWatershed models are used to represent the physical, chemical, and biological mechanisms that determine the fate and transport of pollutants in waterbodies (Daniel 2011). These models, in general, are used for exploratory, planning, and regulatory purposes (Harmel et al. 2014). Watershed models have numerous applications; one such use is the development of total maximum daily load (TMDL). TMDL is the amount of pollution a waterbody can receive without becoming impaired. Because of the challenge of uncertainty associated with models and the TMDL development process, the United States Clean Water Act Section 303 (d)(1)(c) requires that a margin of safety (MOS) be specified to account for uncertainty in TMDLs. The question of how MOS is estimated in TMDL was identified as a problem by the National Research Council (NRC 2001). Since the identification of the problem about two decades ago, there have been very few inventories or audits of approved TMDL studies. This study describes a natural language processing and machine learning aided review of the MOS in approved TMDLs from 2002 to 2016. The study determined whether the MOS values incorporated followed a pattern and examined whether there exist a relationship between MOS values and some ecological conditions. Relatively few TMDLs were based on some form of calculation to estimate explicit MOS values; these TMDLs constituted only 16% of the reviewed sample. The remaining 84% used conventional values, but few of those studies provided reasons for their selected values. A statistical assessment of those MOS values revealed that the MOS depended on States (location of waterbody), USEPA regions, waterbody type, designated water use, TMDL model used, and dataavailability. The findings indicate that few TMDL developers are following the National Research Council’s suggestions of using a rigorous uncertainty estimation approach for rational choices for the MOS. An adaptive approach based on Bayes-Discrepancy was proposed for estimating an MOS for a TMDL. The approach is based on the Bayesian hierarchical framework of estimating uncertainty associated with watershed models. With this approach, TMDL developers can communicate the effects of their watershed model. The approach was applied to a Ferson Creek model of the Fox River watershed to access variability and uncertainty in the model results, and also estimate possible MOS values for two monitoring stations in the watershed. Results suggest that an MOS of 0.04 mg/L could lead to a 0.1 probability of violating the water quality standard for an underpredicting model. The Bayes-discrepancy estimation method will enable TMDL developers and watershed managers to strike a balance between implementation options and water quality concerns.
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Title: THE INTERACTION BETWEEN COINAGE OR ALKALI METALS AND POLYAROMATIC HYDROCARBONS
Creator: Liu, Shuyang
Date: 2020
Description: Theoretical study on versatile chemistry of buckybowls and related polyaromatic hydrocarbons has been comprehensively accomplished and...
Show moreTheoretical study on versatile chemistry of buckybowls and related polyaromatic hydrocarbons has been comprehensively accomplished and documented. Polyaromatic hydrocarbons from simple double bond to fullerene C60, as one of major family in buckybowls has shown a wide potential in development of various specifically purposed materials. Complexes with coinage metals evidenced tunable donor ability of related polyaromatic systems’ π-surface. Moreover, functionalization with small ligands cations interact with these π-surface also show some patterns which have certain enlightenment to the experiment. By adding the methyl group on corannulene, to pursue the relationship between geometry and stabilization which provide an alternative strategy of developing. Further study of alkali metals interacts with annulene, continuously adding with crown ether to mimic experiment environment display an interesting pattern. In the end, extended topics of some applications with computational chemistry, such as the help of Raman spectrum of L-focus.
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Title: NANOMATERIALS FOR ADVANCED BATTERY CATHODES
Creator: Moazzen, Elahe
Date: 2020
Description: Cathode materials are key components that directly determine the power density of a battery. One of the most effective ways of developing high...
Show moreCathode materials are key components that directly determine the power density of a battery. One of the most effective ways of developing high power density cathodes is bringing them into the nano-scale world, which results in many expected and unexpected properties. Some of the desired characteristics include faster charge/discharge kinetics, improved capacity retention and structural stability due to the higher surface to volume ratio and shorter ion diffusion paths. In this dissertation a number of uniquely designed nano-sized cathode materials and nanocomposites are developed and investigated for alkaline aqueous and lithium ion battery applications. Nickel hydroxide (Ni(OH)2), which is one of the most important cathode materials in alkaline batteries, suffers from low conductivity, which usually leads to inefficient discharge and incomplete utilization of the material. A series of Ni(OH)2/Co(OH)2 core/shell nanoplatelets were synthesized and systematically investigated as cathode materials. Structure-property correlations revealed that electrochemical behavior and reversibility of Co(OH)2 redox conversion depended non-linearly on the average shell thickness, with the best performance (99.6% of theoretical capacity of the composite material) achieved at shell thickness of 1.9 ± 0.3 nm. Two fundamental phenomena were suggested to be responsible for the superior performance: templated shell deposition and galvanic coupling of core and shell materials.Manganese (IV) oxide (MnO2), which is another practical cathode that has a great potential to be utilized for a variety of energy storage systems, still has some major challenges including reversible cycling in rechargeable batteries. One of the most crucial challenges is the fact that polymorphs of MnO2 have different electrochemical activities as aqueous and Li-ion battery cathodes. However, most synthetic samples contain a mixture of polymorphs, which makes the structure-property correlations more complicated. This dissertation reports on systematic studies correlating synthesis, thermal and mechanical processing, and composite formation with polymorph composition, electrochemical performance and ion intercalation mechanisms. Among all the results, several main conclusions were reached: 1) Through control of the synthesis parameters and post-processing, desired phase compositions and nanoparticle morphologies, which optimize MnO2 performance in aqueous alkaline electrolyte, can be achieved. Nanoparticles with higher fraction of the akhtenskite polymorph showed higher reversible capacities in LiOH electrolyte (~210 mAh g-1), with stable performance for over 50 cycles. The effects of sub-nanoparticle organization of MnO2 polymorphs by thermal treatment without any morphology change on cycling performance, phase activation, and charge/discharge mechanisms in LiOH electrolyte as well as the detailed mechanism of the polymorph conversion during annealing were studied and for the first time, demonstrating that the electrochemical activity of MnO2 material strongly depends not only on the lattice structure of individual polymorphs but also on the sub-nanoparticle polymorph architecture and interphases.2) Several processing strategies, including thermal and mechanical processing, and composite fabrication were utilized to develop functional MnO2 cathodes for Li-ion batteries. Improvements in capacity and cycling performance were correlated to the presence of the pyrolusite phase of MnO2 and the crystallite size. Composite fabrication by graphene oxide wrapping also provided significant performance improvements through polymorph composition control and improved conductivity.
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Title: Framework For Cloud-Based BIM Governance
Creator: Mehraj, Isma
Date: 2020
Description: Due to the rapid adoption of building information modeling (BIM) in the architecture, engineering, and construction (AEC) every building can...
Show moreDue to the rapid adoption of building information modeling (BIM) in the architecture, engineering, and construction (AEC) every building can be visualized and interpreted even before its foundation touches the ground. BIM methods are expanding and have entered mainstream use that requires immediate consideration. BIM is new and difficult to operate as mostly due to the enormous amount of data that causes improper data management. The objective of this study is to formulate a cloud-based BIM governance framework with a focus on practical issues for its implementation in the construction organizations. A framework was developed to study Data Management, Team Collaboration, Data Organization, and Legal Assurance as major constructs. It is expected that the constructs will provide a benchmark for BIM cloud governance implementation for BIM /VDC engineers to follow. The incorporation of this framework in BIM practices would produce new opportunities for the AEC community to work in collaboration and increase efficiency in data sharing. A survey among a wide spectrum of BIM/VDC practitioners from major construction organizations in the United States was conducted to explore and find evidence of the strength of the constructs. We anticipate that this framework will provide a basis for assessment and recognition of pivoting, driving factors for practical and effective BIM implementation.
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Title: Essays in Corporate Risk Management for Oil Industry
Creator: Lu, You
Date: 2020
Description: This dissertation includes three chapters with a series of empirical investigations in areas of corporate risk management in the oil industry...
Show moreThis dissertation includes three chapters with a series of empirical investigations in areas of corporate risk management in the oil industry.In the first chapter, I overview the oil industry. I introduce different crude oil-related business segments and how market risks affect them. The types of available financial hedging strategies and hedging instruments are also discussed.The second chapter studies the rationales for corporate risk management and the effects of the financial hedging activities on firm value. I revisit the hedging positions of U.S. oil producers and find evidence that for firms that purely involving in upstream activities, the hedging activities add to their market value. The sensitivity of Tobin’s Q to oil price variance is stabilized by hedging activities. Besides, there is an optimal hedging level, and over hedging will hurt firm value. Though firms claim that their hedging decisions are subject to the oil price movement in their annual report, my evidence does not support that firm’s hedging decisions are impacted by oil price movement.The third chapter investigates the effects of operational hedging on firm value and commodity price risks. It explores a novel type of operational hedging - the natural operational hedging positions between the upstream crude oil producers and the downstream oil consumers. Using hand-collected data of 272 unique oil-producing firms, I find that operational hedging is a substitute for financial hedging. Operational hedging is sufficiently effective in reducing firms’ exposure to oil price risk. Consistent with hedging theory, I also find that operational hedging adds to the firm value measured by Tobin’s Q.
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Title: Exploring differences in eating disorder symptomatology and treatment outcomes between sexual minority and heterosexual women in eating disorder treatment programs
Creator: Murray, Matthew Ford
Date: 2020
Description: Research on eating disorder (ED) symptomatology in sexual minority (SM) women is limited and has demonstrated inconsistent findings with...
Show moreResearch on eating disorder (ED) symptomatology in sexual minority (SM) women is limited and has demonstrated inconsistent findings with respect to how they differ from heterosexual women. Further, many studies combine SM women into one group, potentially masking important sub-group differences. Existing data appears to suggest that SM women may be at similar or increased risk for certain types of disordered eating behaviors and present with body image concerns that may differ from heteronormative female body ideals. However, it is unclear how weight and shape control behaviors differ across sexual orientations in women seeking treatment for EDs, and if there are differences in treatment outcomes. The present study used analyses of variance and covariance to test 1) group differences in frequency and severity of ED symptomatology and 2) differences in group by time interaction effects as an indicator of treatment outcomes in a sample of 3,120 adult women of diverse sexual orientations who presented for ED treatment between 2015 and 2018. Participants identified their sexuality as heterosexual, lesbian, bisexual, or other/unsure. Results indicated notable group differences in ED symptoms upon admission to treatment. Bisexual women, in particular, presented to treatment at younger ages, with higher BMIs, and more severe illnesses than heterosexual women. Further, results from the present study suggest that despite such differences, women across sexual orientation groups achieved similar treatment outcomes. These findings underscore the importance of subgroup analyses of ED symptoms in SM women and have both clinical and research implications related to ED psychopathology in this population.
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Title: Testing Models of Minority Stress and Cognitive Escape in a Large Sample of Lesbian/Gay Individuals
Creator: Manser, Kelly
Date: 2020
Description: Compared to heterosexual individuals, gay/lesbian individuals experience health and sociopolitical disparities. Health disparities include...
Show moreCompared to heterosexual individuals, gay/lesbian individuals experience health and sociopolitical disparities. Health disparities include higher prevalence of binge drinking, tobacco use, and cardiovascular disease (CVD) among gay/lesbian individuals. Sociopolitical disparities are rooted in structural stigma and include policies and norms that fail to protect, or actively discriminate against, gay/lesbian individuals. These health and sociopolitical disparities can be understood by converging two theories previously tested among gay/lesbian individuals – minority stress and cognitive escape. Minority stress theory asserts factors such as structural stigma may relate to proximal stress and negative health sequelae in targeted minority groups, while cognitive escape theory suggests escape-related behaviors like substance use may mediate links between systemic factors and individual health. This study used binary logistic regressions to test mediation models in which substance use mediated links between structural stigma and health within a large sample of gay/lesbian individuals. Structural stigma was operationalized as number of sexual orientation anti-discrimination laws, health was operationalized as presence versus absence of any CVD conditions, and substance use was operationalized as binge drinking and tobacco use. Models were tested in an aggregated sample, and also in sex/gender subsamples. In bivariate and component-path analyses, structural stigma predicted smoking frequency across samples. Stigma-binge drinking linkages were more salient among lesbian women compared to gay men. According to Sobel tests, smoking status mediated the stigma-CVD status relation for males-only and combined-sex samples. Study strengths, limitations, and implications are discussed.
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Title: A Biodegradable Microsphere-Hydrogel Ocular Drug Delivery System for Treatment of Choroidal Neovascularization
Creator: Liu, Wenqiang
Date: 2020
Description: Current standard of care for neovascular age-related macular degeneration (AMD) requires repeated intravitreal bolus injections of anti...
Show moreCurrent standard of care for neovascular age-related macular degeneration (AMD) requires repeated intravitreal bolus injections of anti-vascular endothelial growth factors (anti-VEGFs). This frequent repeated injection regimen present increased risks of potential complications including endophthalmitis, retinal detachment, intravitreal hemorrhage, and cataract. In addition, pharmacokinetic profiles of drugs are non-optimal, since the peak level of drug after bolus injections may cause potential toxic effect while the quick clearance later may render subtherapeutic concentration. Finally, the significant socioeconomic burden upon patients, family, and healthcare systems cannot be ignored. Therefore, a controlled delivery system for anti-VEGF drugs is in high demand to reduce injection frequencies, minimize potential risks, and improve efficacy.The overall goal of this study was to develop a biodegradable and injectable drug delivery system (DDS) capable of releasing therapeutic anti-VEGF (aflibercept) for six months. Based on our previous non-degradable DDS for anti-VEGFs, this work sought to introduce biodegradable polymeric crosslinker into the hydrogel matrix to make the DDS biodegradable. To accomplish this goal, three specific aims were pursued: (1) Development of a biodegradable and injectable microsphere-hydrogel DDS for controlled release of aflibercept for six months, important biomaterial parameters including thermoresponsive behavior, injectability, in vitro degradation and biocompatibility, release kinetics, and drug bioactivity were characterized to obtain the optimal DDS formulation; (2) Evaluation of long-term in vivo efficacy of aflibercept-loaded DDS in laser-induced CNV model; (3) Investigation of in vivo safety and biocompatibility of DDS injection and its degradation products.
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Title: SALMONELLA SURVIVAL AND TRANSCRIPTOMIC RESPONSE ON FRESH-CUT CANTALOUPE FLESH WITH AND WITHOUT ORGANIC ACID PRETREATMENT
Creator: Zhou, Xinyi
Date: 2020
Description: Outbreaks of Salmonella enterica associated with fresh-cut melons are becoming more frequent in recent years. Antimicrobial activity of...
Show moreOutbreaks of Salmonella enterica associated with fresh-cut melons are becoming more frequent in recent years. Antimicrobial activity of organic acids on fresh-cut melons have been previously studied. However, little is known about the molecular mechanism behind the antimicrobial activity of organic acid.Four strains of S. enterica were utilized: Newport 36796 and 339652, and Typhimurium LT2 and 46249. Both high and low inoculation levels were performed. For low level, each strain was individually cultured and spot-inoculated onto separate 100 g untreated fresh-cut cantaloupe samples resulting in 4 log-CFU/g. For high level, samples were first submerged into 2% citric acid or malic acid for 1 minute or left as untreated control. Cantaloupe were spot inoculated with one of four strains which resulted in 7-log CFU/g. All inoculated samples were air-dried for 1 h then stored at 4°C for 7 d in deli containers. Enumeration was conducted at 0, 1, 3, 5, and 7 d. Duplicate samples were used in each of three independent trials and results were analyzed by Student’s t-test, p≤0.05. Samples for sequencing were prepared using the TruSeq Stranded mRNA kit and run on a MiSeq according to the manufacturer instructions.For low inoculation level, population of all four strains increased significantly from 0 to 3 d. The two cantaloupe outbreak-related strains (Newport 339652 and Typhimurium 46249) increased significantly between 0 and 7 d from 3.44±0.11 to 3.76±0.13 and 3.36±0.12 to 3.78±0.19 log CFU/g, respectively. For high inoculation level, the population on the untreated cantaloupe was 6.55±0.18 log CFU/g at 7 d, whereas it was significantly lower on the citric and malic acid-treated cantaloupes (6.26 ± 0.09 log CFU/g and 6.07 ± 0.18 log CFU/g). After 1 d, S. enterica genes were downregulated up to 437.4-fold compared and upregulated up to 23.2-fold. The notable downregulated genes encoded proteins related to catalyzing metabolism (L-aspartate oxidase) and also related to nutrient uptake (PstC).The results of this study can aid in understanding population dynamics of S. enterica on fresh-cut cantaloupes and efficacy of malic and citric acids. The results can also aid in understanding mechanism underlying S. enterica survival on fresh-cut cantaloupes.
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Title: IMPROVING KNOWLEDGE OF MICROBIAL DYNAMICS ON BUILDING MATERIALS UNDER HIGH MOISTURE CONDITIONS
Creator: ZHAO, DAN
Date: 2020
Description: Most buildings experience some kind of high moisture event(s) throughout their life cycles, often resulting from water leaks or migration of...
Show moreMost buildings experience some kind of high moisture event(s) throughout their life cycles, often resulting from water leaks or migration of water vapor through the enclosure. Dampness and moisture in buildings leads to fungal growth and is associated with adverse human health outcomes. Although the dynamics of fungal growth on buildings materials has been investigated for decades, few studies have integrated modern chemical or microbiological analytical methods (e.g., DNA sequencing, qPCR, etc.) to understand microbial dynamics on materials held at high humidity conditions. Moreover, most mold growth prediction models remain relatively simplistic and rely solely on empirical data for visible mold growth. To bridge some of these gaps, this research aims to improve understanding of microbial growth and community dynamics on building materials under high moisture conditions and to improve our ability to predict microbial growth and community dynamics under a variety of conditions. Five distinct but overlapping research objectives are used to achieve these goals, including: (1) evaluating the growth of microorganisms on wetted building materials and identifying relationships between specific microbial taxa, metabolites, and environmental variables; (2) identifying inherent material chemistry drivers of fungal growth susceptibility and their relation to microbial community structure; (3) exploring how fluctuating moisture exposures impact bacterial and fungal growth and dynamics on building materials; (4) investigating microbial interactions using isolated communities on a single material; and (5) evaluating and improving existing mathematical mold growth models.
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Title: IMPLEMENTING ASYNCHRONOUS DISCUSSION AS AN INSTRUCTIONAL STRATEGY IN THE DEVELOPMENTAL MATHEMATICS COURSES TO SUPPORT STUDENT LEARNING
Creator: Zenati, Lynda
Date: 2020
Description: Remedial known as developmental coursework are designed to get under-prepared students ready for college. Ninety one percent of colleges offer...
Show moreRemedial known as developmental coursework are designed to get under-prepared students ready for college. Ninety one percent of colleges offer remedial courses in mathematics and English (Seo, 2014). Evidence suggests that traditional teaching methods do not enable all students to engage with the types of academic literacy constitutive to higher education (Lea and Street, 2006). The popularity of online discussion has been made possible through their availability in most LMS which are widely used in higher education (Dahlstrom, Brooks, & Bichsel, 2014). This study aimed at examining the use of asynchronous discussion (AD) as an instructional strategy to help alleviate some of the difficulties developmental math students make in different topics. Participants were 15 students enrolled in Summer, 2019 semester at a Community College. Results showed that students’ performance increased from pretest to posttest for students’ who participated in AD. Comparison was made with two other sections of the same course at the same college taught by two different instructors. Controlling for prior academic ability, results showed a statistically significant difference between students’ performance in the posttest in the section that utilized the AD but not the other two sections. Content analysis of students' posts showed the use of AD at least temporarily corrected students’ misconceptions when they were active and Consistent. Results were mixed for the lurker and the passive students. Moreover, correlation analysis showed no relationship for the frequency of interaction; however, a significant relationship was found for the quality of participation and students’ performance as measured by the final exam. Furthermore; no relationship between the CoI presences and students’ performance. Students’ reflections indicated that students valued the online experience. Benefits were related to students’ engagement and collaborative learning. Obstacles included students’ behavior, timing and the structure of the AD. This may imply that using structured AD may help in building a community of learners. Also, instructor presence and facilitation were necessary to promote deep learning. Future research can build on this finding by replicating the study using a bigger sample size and a longer period to allow students to reflect and discuss any conflict with their peers.
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Title: FUNCTIONALIZED NANOSCALE MATERIALS FOR PROTEIN BIOMARKER DETECTION
Creator: Zhang, Youwen
Date: 2020
Description: Proteins are vital biomolecules in living organisms which function as the working element for many aspects of life. An abnormal expression of...
Show moreProteins are vital biomolecules in living organisms which function as the working element for many aspects of life. An abnormal expression of proteins or expression of unique proteins is often associated with certain disease. Accordingly, proteins have become valuable biomarkers for disease diagnosis and prognosis. So far, numerous methods have been developed for detections of protein biomarkers. However, most of them suffer from the lack of accuracy, sensitivity, and specificity for clinical diagnostic applications. With the rapid advancement in nanotechnology, functional nanoscale materials, which could overcome the biocompatibility and biological recognition ability, have been widely used to develop sensitive and selective biosensors.In this dissertation, two kinds of functionalized nanoscale materials-based sensing strategies are investigated for protein biomarker detection. One strategy takes advantages of graphene oxide (GO) and utilizes fluorescence resonance energy transfer (FRET) for fast and sensitive protease detection by covalent attaching fluorescently labeled protease substrate peptide to the GO surface. This type of GO-based fluorescence sensor is highly sensitive (with a detection limit of picomolar concentration) and selective (other structure similar proteases does not interfere with the target analyte detection). In addition, it could accurately analyze serum samples. With this strategy, we have successfully achieved the detection of the HIV-1 PR (HIV-1 protease, a significant biomarker for AIDS) and ADAMs (a disintegrin and metalloproteinases, a biomarker for human cancers). It could be visualized that this GO platform could be utilized to detect various proteases by only changing the peptide substrate and solution pH. In addition, by coupling multiple substrate peptides on the GO surface, we developed a multiplex GO sensing system for simultaneously profiling of the activities of a panel of MMPs/ADAMs. Under the assistance of joint entropy and programming, our sensor could identify up to 5 types of human cancers, and offers the potential to detect other cancer types by changing biomarkers.The other strategy is to utilize nanopore stochastic sensing to detect proteins, which involves measuring the ionic current modulation generated by analytes’ electro-osmotic flow through a chemical functionalized nanoscale sized pore. As a sensitive and label-free technique, nanopores have been highly recognized as one of the emerging techniques to detect analytes at the single-molecule level. Unlike DNA molecules which are uniformly charged, proteins are an isotropically charged molecules, which have low translocation probability through a nanopore. Since the protein pore-based sensing system is not suitable as deployable tools for detection of proteins due to the size limitation and fragile nature of the biological membranes. In this project, we fabricated solid-state nanopores using PET membranes followed by chemical functionalization of their inner surfaces. The modified- PET nanopore was sensitive and could detect HIV-1 protease at picomolar concentration. More importantly, the modified-nanopore sensor was selective, and could differentiate the target protein from others such as Trypsin, BSA and HSA. Furthermore, the modified PET nanopore strategy developed in this work provide a general platform for exploring fundamental protein dynamics and rapid detection of proteins at the single-molecule level
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Title: USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Creator: Wang, Xiaoyu
Date: 2020
Description: Separation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with...
Show moreSeparation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with thermal separations, can lead to significant energy savings in chemical process industries. However, the main obstacle of experiments is that many separation processes are not well understood at the fundamental molecular level. In this dissertation, we use computational molecular modeling tools, mainly classical molecular dynamics (MD), to clarify molecular forces and provide detail at a molecular level, which can aid in the understanding of transport process and designing materials for a proposed application.In the first study, we investigated separation of water/alcohol vapor using zeolite membranes. Experimentally, the separation of water/isopropanol (IPA) mixtures shows a dramatic decrease in selectivity due to increase of IPA flux as the feed water concentration decrease when using the sodium A zeolite membrane. We used molecular dynamics simulations to help our experimental collaborators understand these puzzling results. The MD results reveal that the water molecules gather around the defect pores on the zeolite membrane, which stops the IPA from going through the membrane and has a positive effect on separation.Then, we studied the HPLC used to separate chiral drug mixtures. One popular chiral stationary phase, amylose tris(3,5-dimethylphenyl carbamate) (ADMPC), has been investigated using both experimental and computational methods; however, the dynamic nature of the interaction between enantiomers and ADMPC, as well as the solvent effects on the ADMPC-enantiomer interaction, are currently absent from the chiral recognition mechanism. We used MD simulations to model the ADMPC in different solvents to elucidate the chiral recognition mechanism from a new dynamic perspective. The ADMPC is found to hold the left-handed helical structure in both methanol and heptane/IPA (90/10); however, the ADMPC has a more extended average structure in heptane/IPA. We developed a model where the ADMPC atoms were restricted in the MD simulation. To better understand the molecular dynamic chiral recognition that provides the retention factor and the elution order in HPLC, we examined hydrogen bonding lifetimes, and mapped out ring-ring interactions between the drugs and the ADMPC. We discover several MD metrics related to hydrogen-bonding lifetimes and correlate them with HPLC results. One metric provides a prediction of the correct elution order 90%, and the ratios of these quantities for the enantiomers provide linear correlation (0.85 coefficient) with experimental retention factors.In the following study, we presented an improved model wherein multiple ADMPC polymer strands are coated on an amorphous silica slab. Using various MD techniques, we successfully coated ADMPCs onto the surface without losing the structural character of the backbone in the solvent. This model provides more opportunities for chiral molecules interacting with ADMPC, resulting in a better agreement compared with experiment when using the overall average metric. The new model also provides the possibility for drug molecules to interact with two polymer strands simultaneously, which is not possible in the previous single-strand model. For a better understanding of why some metrics are better predictors than others, we used charts of the distribution of hydrogen bonding lifetimes to display the information for various donor-acceptor pairs. The results are more consistent than the previous models and resolves the problematic cases of thalidomide and valsartan.Besides the membrane-based separations, immiscible liquid-liquid equilibrium states were also studied. We successfully predicted results based on MD simulations and showed comparable accuracy with experimental data. This method has applications in liquid-liquid extraction which is widely used in industrial separation process.
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