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Title: Habitat 2022+
Creator: Cho, San Lae Lae
Date: 2021
Description: Globalization and urbanization have led a vast group of population to shift from rural and suburban areas to urban centers. According to the...
Show moreGlobalization and urbanization have led a vast group of population to shift from rural and suburban areas to urban centers. According to the United Nation’s (UN) projection, around 2.5 billion more people will live in the cities by 2050. For cities to accommodate such a population, cities can grow horizontally or vertically. If cities were to grow horizontally, this population would need to commute majorly by car which has a very high carbon footprint. By building vertically, the population’s commute becomes more efficient if the vertical structure is built as such is a city within a city. Although having existed for 500 years, tall buildings and skyscrapers have been topics of controversy for their excessive use of resources, ignoring environmental and contextual problems. In order to mitigate this sustainability issue, mass timber as a construction material has been recently introduced into the American market. Mass timber is the building material for a carbon neutral future according to Council on Tall Buildings and Urban Habitats (CTBUH). Another means is to grow plants around the buildings meaning they are regrowing greenery back into nature with the hopes to take a step towards mitigating climate change. In addition, with the argument of tall buildings lacking neighborhood-like qualities that for instance, a Chicago block of housing may give, more and more tall buildings around the world have tried to implement the lush spaces onto the building perimeters. These spaces with plants and trees mimicking nature can exist as both indoor and outdoor spaces. While neighborhoods have parks, these spaces or sky gardens will substitute as modified parks for skyscrapers.With psychological benefits tied to spaces linked to nature in high-rises, such spaces should be integrated in all high rise, residential buildings. Today, in addition to Covid pandemic, many people practice working from home. Meanwhile, it is human nature since birth to want to be surrounded by plants and nature, either spending time under a tree or lying on the grass. To mitigate spending excessive amounts of hours indoors, spaces linked to nature have become crucial in providing a sense of peace and reconnecting back to nature. However, currently architecture that has nature integrated, results in spaces only for the wealthy. Furthermore, architecture in the US is so commercially driven with developers aiming for the most cost effective, most efficient and largest floor areas. For nature to be more available to the living spaces of middle class and ideally working class, the city planners and city development authorities need to get involved. For instance, the city could aid by allocating some of the tax collected to build more green architecture. With the tax fund assistance from the city, high quality living of green architecture will become available and much more affordable.Another option to making living more affordable is by implementing co-living. Despite the Covid-19 pandemic, co-living remains relatively high in demand in Chicago according to Chicago Tribune. For the younger generations such as the Millennials and younger, it is predicted that due to the nature of student loan debts, these generations are less likely to be financially well off after graduation. Hence, they are less likely to establish a family as soon as the previous generations, as most people tend to start a family when they feel financially stable.Hence, in this design thesis, a certain prototype will be tested out regarding some of these issues. This is just one option to the issues above and there are many options and other nuances still available to explore.
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Title: RE-DEFINING LABOR HOUSING COMMUNITIES IN DUBAI
Creator: Chavadi, Sanjana Mrutyunjaya
Date: 2022
Description: From the moment they are duped into believing in a utopian lifestyle, to their day to-day working and living conditions once they arrive in...
Show moreFrom the moment they are duped into believing in a utopian lifestyle, to their day to-day working and living conditions once they arrive in the country, to the denial of theirrights for years after they are stuck in the country, the migration of workers from other countries into the Emirates is a neglected humanitarian issue. The United Arab Emirates and several other GCC countries have a heinous habit of recruiting illiterate foreigners into their country and abusing them as if they were modern-day slaves. Many nations and individuals have legal control over immigrants by applying the Kafala sponsorship system and ignoring international norms and rights established by organizations like the International Labor Organization. While the Kafala system is only one of many aspects of the whole problem, this thesis will seek to identify the influence of architecture on the lives of the South Asian labor force who work behind the beautiful façade of the United Arab Emirates by reconstructing the labor community. These colossal structures are built and shown while the individuals who construct them are ignored and hidden. Immigrant low income labor employees bear the brunt of their hard life-work imbalance with the intention of providing assistance to their family in their home nations. The labor force of Dubai becomes the major target of the terrorists, isolated from Dubai's pleasure amenities, socially detached from the rest of the population, and separated from their creations. By creating a landmark and developing a sense of social coherence, integration, and empowerment among the labor community, this initiative intends to bridge the divide and commemorate the labor community. This project will propose a new sort of community and housing typology that embraces the ideals of modularity, adaptability, and community as a solution to the immigrant worker dilemma.
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Title: Mothers’ Vaccination Decision: The Relation Between Science Skepticism, Social Networks, Vaccination Beliefs, and Fear of ASD
Creator: Lockwood, Maria Izabel Kugelmas Guarita
Date: 2021
Description: Vaccines are instrumental in stopping the spread of disease, yet some parents choose to not vaccinate their children. Despite scientific...
Show moreVaccines are instrumental in stopping the spread of disease, yet some parents choose to not vaccinate their children. Despite scientific evidence that childhood vaccines are safe, there is an increasing number of children in the United States and the United Kingdom who are not getting vaccinated. The current study investigates different factors that may be associated with mothers’ decision to vaccinate their children. This study examines the relations between skepticism in science, vaccination beliefs, fear of having a child with Autism Spectrum Disorder (ASD), social network recommendations, and maternal decision to vaccinate. Participants included 293 expectant mothers in the United States and the United Kingdom. Results indicated that mothers who are pro-vaccine and mothers who are vaccine-hesitant have different score profiles across scales that measure skepticism in science, vaccination beliefs, and fear of having a child with ASD. Specifically, we found that relative to mothers who are vaccine-hesitant, mothers who are pro-vaccine: (1) indicated less skepticism in science; (2) had fewer anti-vaccination beliefs; (3) did not statistically differ on their fear of having a child with ASD; and (4) had a smaller percentage of their social network advocating against vaccination. Thus, the study adds to the research literature, as it illustrates that mothers who are vaccine-hesitant differ from mothers who are pro-vaccine on key factors.
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Title: Data-Driven Methods for Soft Robot Control and Turbulent Flow Models
Creator: Lopez, Esteban Fernando
Date: 2022
Description: The world today has seen an exponential increase in its usage of computers for communication and measurement. Thanks to recent technologies,...
Show moreThe world today has seen an exponential increase in its usage of computers for communication and measurement. Thanks to recent technologies, we are now able to collect more data than ever before. This has dawned a new age of data-driven methods which can describe systems and behaviors with increasing accuracy. Whereas before we relied on the expertise of a few professionals with domain-specific knowledge developed over years of rigorous study, we are now able to rely on collected data to reveal patterns, develop novel ideas, and offer solutions to the world’s engineering problems. No domain is safe. Within the engineering realm, data-driven methods have seen vast usage in the areas of control and system identification. In this thesis we explore two areas of data-driven methods, namely reinforcement learning and data-driven causality. Reinforcement learning is a method by which an agent learns to increase its selection of ideal actions and behaviors which result in an increasing reward. This method was applied to a soft-robotic concept called the JAMoEBA to solve various tasks of interest in the robotics community, specifically tunnel navigation, obstacle field navigation, and object manipulation. A validation study was conducted to show the complications that arise when applying reinforcement learning to such a complex system. Nevertheless, it was shown that reinforcement learning is capable of solving three key tasks (static tunnel navigation, obstacle field navigation, and object manipulation) using specific simulation and learning hyperparameters. Data-driven causality encompasses a range of metrics and methods which attempt to uncover causal relationships between variables in a system. Several information theoretic causal metrics were developed and applied to nine mode turbulent flow data set which represents the Moehlis model. It was shown that careful consideration into the method used was required to identify significant causal relationships. Causal relationships were shown to converge over several hundred realizations of the turbulent model. Furthermore, these results match the expected causal relationships given known information of self-sustaining processes in turbulence, validating the method’s ability to identify causal relationships in turbulence.
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Title: Synthesis and Photophysical Characterization of Novel Aromatic Triplet Dyes for Photodynamic Therapy Applications
Creator: Morgan, Jayla A
Date: 2022
Description: Photodynamic therapy is a biomedical approach to treating specific types of cancerous tumor cells and harmful bacteria. The core principle of...
Show morePhotodynamic therapy is a biomedical approach to treating specific types of cancerous tumor cells and harmful bacteria. The core principle of photodynamic therapy involves the usage of a photosensitizer, which is an agent with the capability of transforming molecular, triplet state oxygen, into a reactive oxygen species upon a reaction with near-infrared (NIR) light. The reactive oxygen species has been demonstrated to cause apoptosis among harmful cells without damaging cancer free cells. The effectiveness of photodynamic is highly dependent upon the identity of the photosensitizer; a powerful and efficient photosensitizer should be non-toxic, exhibit high light absorption capabilities, and should produce large amounts of the reactive oxygen species. A novel chromophore bis-iodo-dipyrrolonaphthyridine-dione was demonstrated to have all vital characteristics of an ideal photosensitizer, however produced low amounts of the reactive oxygen species of interest due to the chemical instability of a carbon-halogen bond present in the molecule. Various subsequent halogenations (bis-bromo and bis-chloro) completed in order to remedy this instability revealed specific regioselectivity in regards to the dipyrrolonaphthyridinedione parent that are exhibited upon substituents effects by the substrate, electronic effects exhibited by the reagents of interest, and overall photophysical characterization of the molecules.
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Title: Video Object Detection using CenterNet
Creator: Mondal, Madhusree
Date: 2021
Description: This thesis investigates the options of video object detection with key-point-based approaches. The problem of recognizing, locating, and...
Show moreThis thesis investigates the options of video object detection with key-point-based approaches. The problem of recognizing, locating, and tracking objects in videos has been a challenging task in the computer vision area. There are few applications on key-point-based object detectors like CornerNet and CenterNet. At the first stage, this work involves the use of the previously proposed CenterNet module as a baseline detector on each frame of the Imagenet Video dataset. Then we apply an RNN module to exploit the temporal information from the past frames for better results.There are challenges in video object detection compared to still image-based object detection. It is not efficient to apply a still-image-based detector on each frame independently because we cannot exploit the temporal contextual information in videos since neighboring frames in a video are highly correlated. Object detection from videos suffers from motion blur, video focus, rare poses, etc. To overcome these issues one way of improving CenterNet for video object detection is to propagate the previous reliable detection results to boost the detection performance.
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Title: REDUCED-ORDER MODELING OF UNSTEADY FLOW OVER TWO COLLINEAR PLATES AT LOW REYNOLDS NUMBERS
Creator: Almashjary, Abdulrahman N
Date: 2021
Description: Wakes of bluff bodies that exhibit unsteady behavior are a topic of great interest in the study of fluid dynamics. Vortex formation in these...
Show moreWakes of bluff bodies that exhibit unsteady behavior are a topic of great interest in the study of fluid dynamics. Vortex formation in these wakes depends significantly on the Reynolds number and the arrangement of the bluff bodies in the computation domain. To attain a comprehensive understanding of the unsteady wakes of adjacent bodies, we examine the emerged flow patterns in the wake of two bodies when subjected to different flow regimes and geometric configurations. This work aims to develop a reduced-order model that can capture the dynamics and predict the time evolution of specific parameters in the flowfield. Investigations including direct numerical simulations of two collinear plates normal to the flow were performed. Flowfield data and forces exerted on the plates were collected using a numerical code of an immersed boundary projection method (IBPM). The conducted numerical simulations pursued classifying the flow patterns by systematically varying the Reynolds number and the gap between the two plates. It was found that at small gap spacings, a typical von Karman vortex street is observed. Whereas at larger gap spacings, both a biased and a flip-flopping gap flow are detected. Prevalent coherent structures present in various flow regimes can be extracted via data-driven modeling techniques. The proper orthogonal decomposition (POD) method is used in this framework, from which projection-based reduced-order models are developed utilizing the governing equations of fluid flows. Single and broadband spectra are observed in the unsteady wake of the two-plate configuration. The amplitude and frequency of the time-evolution of the true POD modes and the predicted models are assessed using the spectral proper orthogonal decomposition (SPOD), an empirical method to extract coherent structures one frequency at a time from fluid flows. It was found that these reduced-order models are able to recover the frequency content from non-time resolved data.
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Title: DEVELOPING FUSION BACTERIOCINS FOR ERADICATING PSEUDOMONAS AERUGINOSA BIOFILMS
Creator: An, Sungjun
Date: 2022
Description: The opportunistic pathogen Pseudomonas aeruginosa is a leading cause of morbidity and mortality in cystic fibrosis patients and...
Show moreThe opportunistic pathogen Pseudomonas aeruginosa is a leading cause of morbidity and mortality in cystic fibrosis patients and immunocompromised individuals. Due to its remarkable ability to resist antibiotics, eradicating P. aeruginosa has become increasingly difficult. As previously reported, we have successfully engineered a colicin-secretion system that kills target biofilm cells rapidly and selectively in multispecies biofilms as well as demonstrated the potential of using live microorganisms engineered to produce antimicrobial colicin protein to treat biofilm-associated infections. In this study,we constructed a fusion colicin-pyocin that could target P. aeruginosa by DNase activity of colicin E2. The newly engineered bacteriocin-secretion system upon the shift in target, maintained biofilm inhibition capacity. Both during biofilm formation and after its development, the system was able to suppress the P. aeruginosa biofilm. This result opened up the possibility that it could be used for novel live biotherapeutics. A further study was conducted to overcome the challenge of requiring an exogenous inducer. We applied the concept of Quorum-Sensing signal that recognize autoinducer as a trigger of fusion colicin-pyocin producing genetic circuit so that it automates the production and secretion of fusion colicin-pyocin as soon as the genetic circuit senses the target population growing. This study demonstrated that combining the domains of colicin and pyocin could broaden the genetic circuit target range, maintaining strain specificity, while employing the QS system could remove the fundamental problem of diffusion or degradation of extra compounds as they approach engineered cells.
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Title: FUNCTIONAL CONNECTIVITY LABELS FOR THE MULTICHANNEL IIT AND RUSH UNIVERSITY AGING (MIITRA) ATLAS
Creator: Badhon, Rashadul Hasan
Date: 2022
Description: In the field of medical imaging, a brain atlas refers to a specific model of the brain of a population where different parts of the atlas...
Show moreIn the field of medical imaging, a brain atlas refers to a specific model of the brain of a population where different parts of the atlas correspond to different anatomical parts of the average brain of the population. A brain atlas is composed of MRI templates and semantic labels and is a crucial component of neuroscience for its critical role in facilitating spatial normalization, temporal characterization and automated segmentation for the purposes of voxel-wise, region of interest and network analyses. Building a brain atlas requires registering multi-dimensional brain datasets from a population into a reference space and, during the last decade, the advent of new technologies and computational modeling approaches has made it possible to build high-quality, detailed brain atlases. At the same time developments in data acquisition now allow the construction of comprehensive brain atlases containing a variety of information about the brain. The Multichannel Illinois Institute of Technology and Rush university Aging (MIITRA) atlas project is developing a high-quality comprehensive atlas of the older adult brain containing a multitude of templates and labels. These templates are constructed with state-of-the-art spatial normalization of high-quality data and as a result, they are characterized by higher image quality, are more representative of the brain of non-demented older adults and provide higher inter-subject spatial normalization accuracy of older adult data compared to other available templates. The methodology used in the development of the MIITRA templates facilitates the construction of accurate structural and connectivity labels. Functional connectivity MRI reveals sets of functionally connected brain regions, forming networks, by investigating synchronous fluctuations in MRI signal over time across these brain regions during rest. The purpose of this work was to generate functional connectivity labels for several brain networks in MIITRA space.
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Title: IDENTIFICATION OF THE RIBOFLAVIN BINDING SITE IN VIBRIO CHOLERAE ION PUMPING NQR COMPLEX
Creator: Lee, Chia-Hsing
Date: 2021
Description: NQR is a six-subunit complex that transfers electrons from NADH to ubiquinone, one of the essential enzymes in the bacterial respiratory chain...
Show moreNQR is a six-subunit complex that transfers electrons from NADH to ubiquinone, one of the essential enzymes in the bacterial respiratory chain of many pathogens such as Vibrio cholerae, Pseudomonas aeruginosa, Chlamydia trachomatis. Its electron transfer path requires three different flavin cofactors to facilitate: FAD, FMN, and riboflavin. The FMN in subunit B (FMNB) brings electrons to riboflavin and then transfers it to the final electron receptor UQ in subunit B, coupled with the Na+ pumping mechanism. NQR has a unique evolutionary history, and one of the pieces of evidence is that NQR has been reported as the only one flavoenzyme that uses riboflavin as its redox cofactor. However, the binding site of riboflavin has not been well understood. To gain insight into the electron transfer at this site in V.cholerae NQR, we generated mutants at the interface of subunits B, D, and E where the possible location of riboflavin is. To characterize these mutants, we assessed NQR properties with different approaches including enzyme kinetics and flavin radical profiling. We found that the mutagenesis surrounding the hydrophobic pocket disrupted the NQR activity, and cause the loss of neutral radical, but did not interfere with the binding affinity between the substrates and NQR. This study will help to understand electron transfer better in NQR and develop the drugs targeting the riboflavin binding site in the future.
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Title: The Impact of Supplementary Cementitious Materials on Strength Development in Concrete
Creator: Lallas, Zoe Nicole
Date: 2022
Description: This thesis outlines the specific properties of fly ash, silica fume, slag, and a variety of natural pozzolans that affect strength...
Show moreThis thesis outlines the specific properties of fly ash, silica fume, slag, and a variety of natural pozzolans that affect strength development in concrete mix designs. It presents a comprehensive summary of select research studies which examined the fresh and hardened properties of concrete made with supplementary cementitious materials (SCMs) to better understand how these materials affect compressive strength development in concrete. The considerations necessary for precast fabrication and other applications in which early-age strength is a crucial concern are of particular importance, as SCMs often slow the rate of strength development in concrete. While SCM usage is common in concrete, replacement quantities are limited and heavily regulated, with the potential for further incorporation into concrete in higher replacement amounts, given continued research on how to best integrate SCMs to maximize strength properties, through the use of chemical admixtures, accelerators, and heat controlled curing regimes as needed.
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Title: Enhancing Explanation Generation in the CaJaDE system using Interactive User Feedback
Creator: Lee, Juseung
Date: 2022
Description: In today’s data-driven world, it is becoming increasingly difficult to interpret and understand query results after going through several...
Show moreIn today’s data-driven world, it is becoming increasingly difficult to interpret and understand query results after going through several manipulation steps, especially on a large database. There is a need for automated techniques that explain query results in a meaningful way. A recent study, CaJaDE(Context-Aware Join-Augmented Deep Explanations), presents a novel approach to generating explanations of query results including crucial contextual information. However, it becomes difficult to interpret explanations since the search space increases exponentially.In this thesis, we propose a new approach that introduces a user interaction model for a purpose of enhancing the generation of explanations in the CaJaDE system. We implemented a user interaction model that consists of three modules: User Selection, Recommendation Score, and User Rating. With these modules, our approach guides a user while exploring relevant join graphs, and lets them be involved in the decision-making process while generating join graphs. We demonstrate through performance experiments and user study that our approach is an effective method for users to understand explanations.
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Title: Relations Between Inhibitory Control, Teacher Support, and Externalizing Behaviors in Elementary School Children
Creator: Kurian, Jennifer
Date: 2021
Description: The aim of this study was to examine the relation between child hot and cool inhibitory control (IC) at the beginning of the school year and...
Show moreThe aim of this study was to examine the relation between child hot and cool inhibitory control (IC) at the beginning of the school year and externalizing behaviors at the end of the year, and to determine if teacher support moderates this relation in early elementary school. Participants included a diverse sample of 138 children in grades 1 (n = 62) and 2 (n = 76), with a mean age of 7.2 years (SD = 10.1 months), about half of whom were male. Hot IC was assessed with the Puzzle Box Task and cool IC with the Happy-Sad Stroop Task. Teacher support was rated by independent observers using the Adapted Teaching Style Rating Scale. A composite teacher-report score based on ratings on subscales from two measures, the Strengths and Weaknesses of Attention Deficit Hyperactive Disorder Symptoms and Normal Behavior and the Strengths and Difficulties Questionnaire, was used to assess externalizing behavior at both time points. Results of hierarchical regression analyses revealed that, contrary to expectation, neither hot nor cool IC significantly predicted child externalizing behavior at the end of the school year. A moderation analysis also failed to show a significant moderating effect for teacher support. The only variable that significantly predicted externalizing behavior at the end of the year was externalizing behavior at the beginning of the year. There were significant concurrent associations between hot IC and externalizing behaviors at both the beginning and end of the school year. These findings suggest that externalizing behaviors in early elementary school are relatively stable. Thus, early and comprehensive intervention may be critical for implementing prevention strategies designed to increase self-regulation and thereby decrease externalizing behaviors after formal school entry.
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Title: Growth kinetics of Salmonella enterica and Listeria monocytogenes during rehydration of dehydrated corn and subsequent storage
Creator: Mate, Madhuri
Date: 2022
Description: Dehydrated vegetables, including corn, are often used in restaurants and retail grocers. They do not support the growth of pathogens as their...
Show moreDehydrated vegetables, including corn, are often used in restaurants and retail grocers. They do not support the growth of pathogens as their moisture content is very low. After rehydration, these food products attain high water activity values suitable with neutral pH for the survival and proliferation of foodborne pathogens, including Salmonella enterica and Listeria monocytogenes. The purpose of the study was to examine the extent to which dehydrated corn supports the growth of S. enterica and L. monocytogenes during rehydration at 5 or 25°C water and following storage at 5, 10, and 25°C temperatures at 1, 3, 5 and 7 d intervals. Fresh corn was dehydrated at 60°C for 24 h. Dehydrated corn was inoculated with a 4-strain cocktail of either S. enterica or rifampicin-resistant L. monocytogenes, resulting in 4 log CFU/g, and held at ambient temperature for 24 h. This corn was then rehydrated using either 5 or 25°C water for 24 h. Throughout rehydration, corn samples were removed at intervals and enumerated. To enumerate S. enterica and L. monocytogenes, the samples were homogenized with BPB and BLEB respectively and cultivated on TSAYE with overlaid XLD or BHIARif200, respectively. Rehydrated corn was then stored at 5, 10, or 25°C and enumerated at intervals 1,3,5 and 7 d. Triplicate samples were assessed at each timepoint and three independent experiments were conducted for each rehydration water temperature. Growth rates were determined by DMFit and statistically analyzed using Student t-test. A p-value ≤0.05 was considered significant. Overall the growth rate of S. enterica was higher when rehydrated in 5°C water temperature and then stored at 25°C and was determined to be 0.61 ± 0.23 log CFU/g per d. This timepoint was also the shortest time required to increase by 1 log which was: 1.64 d, i.e. 39 h. For L. monocytogenes, the 25°C water rehydration showed the fastest growth rate when stored at 25°C. It took only 1.58 d or 37.8 h for 1 log increase in the population. After 5°C water rehydration of corn the highest populations of mesophilic bacteria and yeasts and molds were observed for 25°C storage ranging from 8.43 to 9.39 log CFU/g and 4.75 to 7.87 log CFU/g, respectively. After 25°C water rehydration, the highest population of mesophilic bacteria, 8.88 log CFU/g, was observed at 5°C storage at 5 d; yeasts and molds were 8.70 log CFU/g for 25°C storage on the same day. The results of this study determined that S. enterica and L.monocytogenes could survive and grow in dehydrated plant foods during rehydration and storage, highlighting the need for product assessments for these types of foods.
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Title: RADIAL MAP ASSESSMENT APPROACH FOR DEEP LEARNING DENOISED CARDIAC MAGNETIC RESONANCE RECONSTRUCTION SHARPNESS
Creator: Mo, Fei
Date: 2021
Description: Deep Learning (DL) and Artificial Intelligence (AI) play important roles in the computer-aided medical diagnostics and precision medicine...
Show moreDeep Learning (DL) and Artificial Intelligence (AI) play important roles in the computer-aided medical diagnostics and precision medicine fields, capable of complementing human operators in disease diagnosis and treatment but optimizing and streamlining medical image display. While incredibly powerful, images produced via Deep Learning or Artificial Intelligence should be analyzed critically in order to be cognizant of how the algorithms are producing the new image and what the new imagine is. One such opportunity arose in the form of a unique collaborative project: the technical development of an image assessment tool that would analyze outputs between DL-based and non DL-based Magnetic Resonance Imaging reconstruction methods.More specifically, we examine the operator input dependence of the existing reference method in terms of accuracy and precision performance, and subsequently propose a new metric approach that preserves the heuristics of the intended quantification, overcomes operator dependence, and provides a relative comparative scoring approach that may normalize for angular dependence of examined images. In chapter 2 of this thesis, we provide a background description pertaining to the two imaging science principles that yielded our proposed method description and study design. First, if treated naively, the examined linear measurement approach exhibits potential bias with respect to the coordinate lattice space of the examined image. Second, the examined DL-based image reconstruction methods used in this thesis warrants an elaborate and explicit description of the measured noise and signal present in the reconstructed images. This specific reconstruction approach employs an iterative scheme with an embedded DL-based substep or filter to which we are blinded. In chapters 3 and 4 of this thesis, the imaging and DL-based image reconstruction experiments are described. These experiments employ cardiac MRI datasets from multiple clinical centers. We first outline the clinical and technical background for this approach, and then examine the quality of DL-based reconstructed image sharpness by two alternative methods: 1) by employing the gold-standard method that addresses the lattice point irregularity using a ‘re-gridding’ method, and 2) by applying our novel proposed method inspired by radial MRI k-space sampling, which exploits the mathematical properties of uniform radial sampling to yield the target voxel counts in the ‘gridded’ polar coordinate system. This new measure of voxel counts is shown to overcome the limitation due to the operator-dependence for the conventional approach. Furthermore, we propose this metric as a relative and comparative index between two alternative reconstruction methods from the same MRI k-space.
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Title: PER – AND POLYFLUOROALKYL SUBSTANCES FATE AND TRANSPORT IN SEDIMENTS, SAND, AND ADSORBENT MEDIA
Creator: Manwatkar, Prashik
Date: 2022
Description: Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are two important organic chemicals of the per- and polyfuoroalkyl...
Show morePerfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are two important organic chemicals of the per- and polyfuoroalkyl substances (PFAS) group that have contaminated land, water, and the air since 1950. The continuous release of PFAS from the surface of land into water is not easy to forecast and an appropriate treatment method needs to be economically viable since there are currently around 42,000 suspect industrial and municipal sites in the United States. For a true reproduction of real-world pollution patterns, we constructed polypropylene tanks, performed laboratory-based experiments, and analyzed the samples using EPA method 533. In this study, we examined the fate and transport of long- and short-chain PFAS, including PFOA, PFOS, and perfluorobutanesulfonic acid (PFBS), from sediments, adsorbent media, and sands under overlaying water tanks. Granular activated carbon (GAC), biochar (BC), and Fluorosorb® (FS) were also added between the contaminated sediments and the sand layer in order to observe capping effectiveness. As one of the best ways to treat contaminated sediments on a large scale, adsorbent beds may reduce contaminants migration and support the degradation of contaminants. We found that all three chemicals were able to pass through the adsorbent layers of 3-4 inches from 4-5 inches of contaminated sediments and reach the top surface of the beds (25-30 inches). In the top 5-7 inches, PFBS concentration varied from 0.28 ppb to 0.78 ppb for all adsorbent tanks for 7 days. Whereas the bottom contaminated sediments concentrations of PFBS were 8518 ppb to 9481 ppb. We also observed the concentrations at top ports increased by 0.59 ppb to 2.31 ppb in 21 days, and ultimately, 0.58 ppb to 7.07 ppb in 69 days. While PFOA and PFOS found different metabolites in all layers, they provided noticeably lesser concentrations in contaminated sediments compared to PFBS. Further, the results of this study can be useful for validating the contaminant transport model predictions by identifying linear or nonlinear sorption equilibrium processes and diffusion-dispersion processes in sediment, sand, and various adsorbent media.
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Title: AN IMPROVED VALIDATED METHOD FOR THE DETERMINATION OF SHORT-CHAIN FATTY ACIDS IN HUMAN FECAL SAMPLES BY GC-FID
Creator: Freeman, Morganne M
Date: 2022
Description: Short-chain fatty acids (SCFAs) are metabolites produced by the gut microbiota through the fermentation of non-digestible carbohydrates....
Show moreShort-chain fatty acids (SCFAs) are metabolites produced by the gut microbiota through the fermentation of non-digestible carbohydrates. Recent studies suggest that gut microbiota composition, diet and metabolic status play an important role in the production of SCFAs. Current methods for the analysis of SCFAs are complex and inconsistent between research studies. The primary objective of this study was to develop a simplified method for standardized SCFA analysis in human fecal samples by gas chromatography with flame ionization detection (GC-FID). A secondary objective was to apply the method to fecal samples from a previous randomized, crossover clinical trial comparing participants with pre-diabetes mellitus and insulin resistance (IR-group, n=20) to a metabolically healthy reference group (R-group, n=9) after daily consumption of a red raspberry smoothie (RRB, 1 cup fresh-weight equivalent) with or without fructo-oligosaccharide (RRB + FOS, 1 cup RRB + 8g FOS) over a 4-week intervention period. Extraction parameters, including solvent selection and water content of the sample, were investigated before finalizing the method. Freeze-dried fecal samples (0.5 g) were suspended in 5 mL of milli-Q water, vortexed and centrifuged at 3,214 x g for 10 minutes. The supernatant was transferred to a clean tube, acidified with 5.0 M HCl and centrifuged again at 12,857 x g for 5 minutes. The resulting supernatant was transferred to a GC vial for analysis by GC-FID. Linear regression data for standards at concentrations 5-2000 ppm ranged from 0.99994-0.99998. Limit of detection (LOD) ranged from 0.02-0.23 µg/mL. Limit of quantification (LOQ) ranged from 0.08-0.78 µg/mL. The validated method was then applied to fecal samples collected from a previously conducted study. Nine SCFAs were identified and quantified (acetic, propionic, iso-butyric, butyric, iso-valeric, valeric, 4-methyl valeric, hexanoic and heptanoic acids). Statistical analysis (Student’s t-test, ANCOVA) was performed on PC-SAS 9.4 (SAS Institute). Acetic acid was significantly lower in the IR-group compared to the R-group before starting intervention (baseline, Week 0, IR v R-group, p=0.014). Intervention analysis comparing RRB to RRB + FOS at 4 weeks (WK4) showed a significant difference in 4-methyl valeric acid (p = 0.040) in the R-group. Trends of decreased SCFA content after 4-weeks of RRB and RRB + FOS compared to baseline were observed in both groups, though changes were not significantly different between dietary interventions at 4 weeks (p>0.05). Metabolic status and dietary intervention are discussed in relation to their impact on SCFA content in fecal samples and mechanisms of biological use as a metabolite. Limitations of the study include sample size and using only feces and not other biological samples for SCFAs analysis, which may be considered for future research.
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Title: Child Temperament, Attachment, and Loneliness: The Mediating Effects of Social Competence
Creator: Evans, Lindsey M
Date: 2021
Description: Chronic loneliness is a risk factor associated with adverse psychological, physical, and academic outcomes. Converging evidence suggests that...
Show moreChronic loneliness is a risk factor associated with adverse psychological, physical, and academic outcomes. Converging evidence suggests that young children experience and can reliably report on their own loneliness. Due to the significant negative sequalae associated with childhood loneliness, it is critically important to examine risk factors for child loneliness. The aims of this study were two-fold: (a) to examine if temperament (i.e., negative affect, effortful control, and inhibitory control) and attachment security assessed at 4 years of age predict loneliness at age 6; and (b) to determine if social competence at age 5 mediates the relation between temperament and attachment security at age 4 and loneliness at age 6. Participants included a diverse sample of 796 4-year old children, about half of whom were male. At age 4, temperament was assessed with the Rothbart Child Behavior Questionnaire and three inhibitory control tasks, and attachment security was assessed with the Attachment Q-Sort. At age 5, the Social Skills Rating Scale was used to assess social competence, and, at age 6, loneliness was assessed with the Loneliness and Social Dissatisfaction Questionnaire. Results of hierarchical regression analyses indicated that lower levels of effortful control and inhibitory control at age 4 significantly predicted higher levels of loneliness at age 6. Also, lower levels of negative affect and higher levels of effortful control and attachment security at age 4 significantly predicted higher levels of social competence at age 5. However, social competence at age 5 did not predict loneliness at age 6. There was no evidence that social competence at age 5 mediated the relation between age 4 temperament, attachment security and age 6 loneliness. These findings reveal that early self-regulation is associated with later child-reported loneliness and that intervention for children who struggle with cognitive regulation may be effective in decreasing risk for later loneliness.
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Title: Improvement and Validation of Multiyear Auroral Analysis to Categorize Scintillation Event Layer
Creator: English, Breanna R.
Date: 2022
Description: Ionospheric irregularities scintillate electromagnetic waves, such as Global Positioning System (GPS) signals, as they pass through the...
Show moreIonospheric irregularities scintillate electromagnetic waves, such as Global Positioning System (GPS) signals, as they pass through the ionosphere, especially in auroral zones. A previous method was developed to determine which layer of the ionosphere these scintillation events occurred in by analyzing optical all sky images (ASI). The results of determining the ionospheric scattering layer using the ratio of 630 nm (red) intensity to 428 nm (blue) intensity were compared to a radar-based method of determining the scintillation layer, and it was found that the results disagreed. In this work, the ASI method is critically analyzed to identify possible errors or sensitivities in the original method that might resolve the discrepancy. This is done by improving and validating the nighttime auroral cloud detection method by comparing to National Oceanic and Atmospheric Administration (NOAA) satellite cloud data. Then a sensitivity analysis is performed on the ASI method to determine which parameters of the method the results are sensitive to. The keogram cloud detection method is improved by automating the selection of the keogram time points that are used to calculate a flat-field gain correction, and by calculating the flat field gain for each year rather than calculatingit once and using it for all years of the study. Keogram cloud detection using the coefficient of variation is verified by comparing the keogram results to true sky conditions based on NOAA cloud mask data, and using detection theory to determine the optimal coefficient of variation threshold. We find that the ideal keogram threshold was 0.37 producing a disagreement rate of 22.4%. The ASI image analysis criteria tested are: the ASI azimuth and elevation mapping files, the magnetic zenith limit, the number of pixels of the ASI that are being analyzed, the duration of the scintillation event that is analyzed, and the red-to-blue ratio threshold. It is found that only changing the red-to-blue ratio threshold has a significant effect on the ASI method, with the red-to-blue ratio that minimizes the number of misattributed layers found to be 1.43.
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Title: TOPICDP – ENSURING DIFFERENTIAL PRIVACY FOR TOPIC MINING
Creator: Sharma, Jayashree
Date: 2021
Description: Topic mining enables applications to recognize patterns and draw insights from text data, which can be used for applications such as sentiment...
Show moreTopic mining enables applications to recognize patterns and draw insights from text data, which can be used for applications such as sentiment analysis, building of recommender systems and classifiers. The text data can be a set of documents or emails or product feedback and reviews. Each document is analysed using probabilistic models and statistical analysis to discover patterns that reflects underlying topics.TopicDP is a differentially private topic mining technique, which injects well-calibrated Gaussian noise into the matrix output of the topic mining model generated from LDA algorithm. This method ensures differential privacy and good utility of the topic mining model. We derive smooth sensitivity for the Gaussian mechanism via sensitivity sampling, which resses the major challenges of high sensitivity in case of topic mining for differential privacy. Furthermore, we theoretically prove the differential privacy guarantee and utility error bounds of TopicDP. Finally, we conduct extensive experiments on two real-word text datasets (Enron email and Amazon Product Reviews), and the experimental results demonstrate that TopicDP can generate better privacy preserving performance for topic mining as compared against other state-of-the-art differential privacy mechanisms.
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