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Title: LOCAL VISCOELASTIC PROPERTIES OF SOFT ANISOTROPIC FIBROUS TISSUE
Creator: Gallo, Nicolas Remy
Date: 2020
Description: The current aging population, with more than 80 million "baby boomers", will present a steep medical challenge for our society in a...
Show moreThe current aging population, with more than 80 million "baby boomers", will present a steep medical challenge for our society in a foreseeable future. Half of the adults over 85 years old are predicted to be diagnosed with Alzheimer's disease by 2050. With healthcare cost reaching over 700 billion dollars in the United States, early detection of Alzheimer's disease (AD) and other co-existing neurodegenerative diseases is crucial to improve the recovery odds in patients and to decrease individual care cost. This work seeks to tackle this problem by proposing a novel computational framework toward improving the measurement of shear visco-elastic properties of brain white matter (WM), which vary with age. These measurements practically represent the effective (average) response of many cells and are typically obtained by using rheology or elastography. Although the former is direct, the latter requires the solution of an inverse problem based on a priori mechanical tissue model. The mechanical anisotropy of WM has previously not been fully explored although many inconsistencies have been reported in brain MRE experiments. To account for these inconsistencies a transversely isotropic constitutive model for the brain WM is proposed to interpret prior experiments involving 7 young and 4 older healthy men. By employing a novel inversion scheme, we report the local variation of the effective transverse and axial shear moduli in two well aligned WM structures (corpus callosum: CC; and cortical spinal tract: CST) for both the young and old cohort of healthy subjects part of the study. This work reports statistically significant changes in local regional variation of the transverse modulus across the CC for the young cohort. In the older cohort, the trend was similar yet not statistically significant. A novel candidate biomarker, the shear anisotropy metric, defined as the ratio of the transverse and axial shear moduli, found statistically significant local regional variation across the CC but not in the CST. Healthy aging was observed to decrease both transverse and axial in both CC and CST, although the variation was significant only for the CC. Finally, in an effort to understand the cause of effective transverse mechanical properties variation in WM with aging, the connection between effective and intrinsic contribution of WM cellular constituents is established. The intrinsic mechanical contributions of axons and glial matrix are separated by fitting the estimates of the effective shear moduli to a microscopic composite fiber model of myelinated axons embedded in the glial matrix. This work provides a method to establish a baseline for healthy brain mechanical properties thus promising to increase the specificity of MRE toward early diagnosis of neurodegenerative diseases. Additional oscillating disc rheology experiments with decellularized porcine myocardium, and the fabrication of a stable heterogeneous phantom matching the mechanical, diffusional and electrical properties of the WM provide foundational knowledge for due development and validation of MRE methodologies employed in other tissues.
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Title: WHY AND WHY-NOT PROVENANCE FOR QUERIES WITH NEGATION
Creator: Lee, Seokki
Date: 2020
Description: Explaining why an answer is in the result of a query or why it is missing from the result is important for many applications including...
Show moreExplaining why an answer is in the result of a query or why it is missing from the result is important for many applications including auditing, debugging data and queries, hypothetical reasoning about data, and data exploration. Both types of questions, i.e., why and why-not provenance, have been studied extensively, but mostly in isolation. A recent study shows that unification of why and why-not provenance can be achieved by developing a provenance model for queries with negation. In many complex queries, negation is natural and yields more expressive power. Thus, supporting both types of provenance and negation together can be useful for, e.g., debugging (missing) data over complex queries with negation. However, why-not provenance and — to a lesser degree — why provenance, can be very large resulting in severe scalability and usability challenges.In this thesis, we introduce a framework that unifies why and why-not provenance. We develop a graph-based provenance model that is powerful enough to encode the evaluation of queries with negation (First-Order queries). We demonstrate that our model generalizes a wide range of provenance models from the literature. Using our model, we present the first practical approach that efficiently generates explanations, i.e., parts of the provenance that are relevant to the query outputs of interest. Furthermore, we present a novel approximate summarization technique to address the scalability and usability challenges. Our technique efficiently computes pattern-based provenance summaries that balance informativeness, conciseness, and completeness. To achieve scalability, we integrate sampling techniques into provenance capture and summarization. We implement these techniques in our PUG (Provenance Unification through Graphs) system which runs on top of a relational database. We demonstrate through extensive experiments that our approach scales to large datasets and produces comprehensive and meaningful (summaries of) provenance.
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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: Far Eastern Spatial Techique Utilized in Architectural Design
Creator: Qian, Zhao
Date: 2010-05-01, 2010-05-01
Description: This project spans techniques used in path, enclosure, play of light, perspective illusion, and time measurement. Concepts are arrived at by...
Show moreThis project spans techniques used in path, enclosure, play of light, perspective illusion, and time measurement. Concepts are arrived at by rational thought, expressing individual experience accessible by persons practicing meditation.
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Title: RECIPROCAL INTERACTIONS BETWEEN RED RASPBERRY POLYPHENOLS AND GUT MICROBIOME COMPOSITION AND METABOLIC HEALTH
Creator: Zhang, Xuhuiqun
Date: 2020
Description: Red raspberries (RRB) and fructo-oligosaccharides (FOS) have been associated with reduced risk of developing cardio-metabolic diseases. RRB...
Show moreRed raspberries (RRB) and fructo-oligosaccharides (FOS) have been associated with reduced risk of developing cardio-metabolic diseases. RRB are uniquely high in anthocyanin- and ellagitannin- type (poly)phenols, however, these (poly)phenols have low bioavailability. Gut microbiota can improve (poly)phenol bioavailability through fermentation processes generating absorbable metabolites and altering gut microbiota structure. However, clinical evidence on the effects of RRB intake on the gut microbiome, (poly)phenolic metabolites and metabolic health is lacking. Further, fermentable carbohydrates (FOS) that selectively stimulate gut microbiota growth may enhance metabolite generation. Therefore, the aim of this research is to investigate the interactions between the gut microbiome and RRB, and explore added effects of FOS as a possible nutritional strategy for improving metabolic health of at risk individuals with prediabetes and insulin resistance (PreDM-IR). Through a series of investigations drawn from a randomized clinical trial (RCT), the following hypotheses were tested: 1) Individuals with PreDM-IR will have a distinctive gut microbiome, and lower capacity to metabolize (poly)phenols compared to healthy individuals; 2) RRB intake for 4-week will increase microbial-derived (poly)phenolic metabolites and adding FOS will augment the effect; 3) RRB intake will improve metabolic risk factors in PreDM-IR and adding FOS will augment the RRB effect; 4) RRB and RRB+FOS supplementations will alter the structure of the gut microbiome explaining variances observed in metabolites and metabolic outcomes. In this single-blinded, crossover RCT, adults with PreDM-IR (n=26) and a healthy group (n=10) consumed 1 cup RRB (fresh weight equivalence) per day or RRB with 8g FOS per day for 4 weeks in random order separated by 4-week washout. Metabolic risk factors, (poly)phenolic metabolites and metagenomic profile were assessed before and after supplementation. Baseline characterization before supplementation revealed distinctive metabolites and metagenomics profiles related to metabolic status. After 4-week RRB, microbial (poly)phenolic metabolites, metabolic health indices and gut microbiome structure beneficially shifted in PreDM-IR group. Adding FOS increased specific microbial species and phenolic metabolites that correlated with β-cell function in PreDM-IR. Overall, nutritional strategies incorporating RRB and FOS may improve metabolic health of individuals with PreDM-IR through modulating gut microbiome composition and the capacity to metabolize RRB (poly)phenols.
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Title: WIENER-HOPF FACTORIZATION FOR TIME-INHOMOGENEOUS MARKOV CHAINS AND BAYESIAN ESTIMATIONS FOR DIAGONALIZABLE BILINEAR STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS
Creator: Cheng, Ziteng
Date: 2021
Description: This thesis consists of two major parts, and contributes to two areas of research in stochastic analysis: (i) Wiener-Hopf factorization (WHf)...
Show moreThis thesis consists of two major parts, and contributes to two areas of research in stochastic analysis: (i) Wiener-Hopf factorization (WHf) for Markov Chains, (ii) statistical inference for Stochastic Partial Differential Equations (SPDEs).WHf for Markov chains is a methodology concerned with computation of expectation of some types of functionals of the underlying Markov chain. Most results in WHf for Markov chains are done in the framework of time-homogeneous Markov chains. The major contribution of this thesis in the area of WHf for Markov chains are: • We extend the classical theory to the framework of time-inhomogeneous Markov chains. • In particular, we establish the existence and uniqueness of solutions for a new class of operator Riccati equations. • We connect the solution of the Riccati equation to some expectations of interest related to a time-inhomogeneous Markov chain. Statistical inference for SPDEs regards estimating parameters of a SPDE based on available and relevant observations of the underlying phenomenon that is modeled by the given SPDE. We summarize the contribution of this thesis in the area statistical inference for SPDEs as follows: • We conduct the statistical inference for a diagonalizable SPDE driven by a multiplicative noise of special structure, using spectral approach. We show that the corresponding statistical model fits the classical uniform asymptotic normality (UAN) paradigm. • We prove a Bernstein-Von Mises type result that strengthens the existing results in the literature. • We prove the asymptotic consistency, asymptotic normality and asymptotic efficiency of two Bayesian type estimators.
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Title: Essays on Empirical Corporate Finance
Creator: Yang, Zihao
Date: 2020
Description: This thesis consists of two essays on empirical corporate finance. The first essay examines the influence of corporate tax on corporate social...
Show moreThis thesis consists of two essays on empirical corporate finance. The first essay examines the influence of corporate tax on corporate social responsibility (CSR) investment. This essay takes advantage of the dynamic changes on state corporate taxes from 2003 to 2016 and explores the causal effects of the tax changes on firms’ CSR outcomes. Applying a difference-in-difference approach, I find that tax effects on CSR are asymmetric. Tax cuts lead to significant improvement of CSR ratings, especially in the concern issues. Tax hikes, on the other hand, lead to deterioration of CSR strength, but have no effect on CSR concerns. I also find that CSR investment from financial constrained firms is more sensitive to tax changes. The second essay studies the financial effect of suppliers’ initial public offering (IPO) on their customer companies. By analyzing matched supplier companies and their large customers, I find that customer companies lose value in both short-run and long-run time periods after suppliers’ IPO events. These customer companies also have higher risk compared to those whose suppliers do not go public. Moreover, I explore the channels of suppliers’ IPO effect on their customers. The results show that suppliers diversify customers and reduce trade credit after IPO. Finally, I find that the supply chain relationships are more likely to terminate after suppliers going public.
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Title: Exchange: Reinvisioning Infrastructure in the Union Stockyards
Creator: Miskowiec, Jason
Date: 2012-05-01, 2012-05
Description: The Exchange Project proposes the physical framework to enable a transformation of existing industrial related infrastructure, a different way...
Show moreThe Exchange Project proposes the physical framework to enable a transformation of existing industrial related infrastructure, a different way to understand the city and the way we live in it at the pedestrian level. The project primarily is a connective element to unite surrounding communities as well as the conversion of an unused building. Physically, the proposition of the connective element manifests itself as an eco-boulevard, looking at a new interaction between surrounding community and a mostly absent natural environment. This begins by rethinking surface and its uses including green spaces, parks, farming, gardening, playgrounds and open space primarily used for industry.
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Title: A NOVEL HYDROPONICS SYSTEM FOR PRODUCING SAFE AND HEALTHY SPROUTS
Creator: Azizinia, Mehdi
Date: 2019
Description: Sprouts can be considered as one of the most nutritious and cheap nutritional sources. Due to these advantages, sprouts consumption has...
Show moreSprouts can be considered as one of the most nutritious and cheap nutritional sources. Due to these advantages, sprouts consumption has increased significantly in recent decades. However, because of their susceptible nature to microbial growth, numerous outbreaks associated with this fresh produce have occurred and thus the safety of the sprout is of major concern. A novel kinetic hydroponics system (KHS) was developed to optimize an improve safe sprout production. In KHS, sprouting seeds are able to grow under water while air is continuously introduced. In this study, effect of various airflow rates and light on yield, germination percentage, and physical properties of sprout were examined. In addition, microbial growth during the shelf life of sprout grown, using conventional and KHS methods were monitored. Moreover, the efficacy of chlorine-based sanitizers for reducing microbial loads during KHS sprout production was tested. Results showed that air flow rate had a positive impact on yield. However, higher airflow (8 and 10 feet3/minute) significantly lowered yield. Also, KHS has a significant higher yield compare with conventional method (110.30±4.88 versus 66.19±2.66 g). KHS did not have positive impact on germination percentage. Germination percentage was almost the same in KHS and conventional method (80.67±1.15% versus 81.33±1.53%). Moreover, when various light wavelengths were used, germination percentage increased significantly in KHS (from 91±2.65 to 96±1% in various wavelengths). In terms of color, there were no significant differences in color of sprouts in both systems. In KHS, when dark conditions applied, stem length was significantly higher (31.32±3.55 mm) than those sprouts treated with light. For example, stem length in white light was 8.54±1.32 mm. In contrast, leaves length was significantly higher when light used (highest was 6.67±0.49 mm for combination of blue and red lights compare to 3.19±0.22 mm for dark KHS). Analyzing microbial background showed that sprouts produced in KHS had lower total aerobic counts compared with conventional system (7.24±0.49 versus 8.22±0.18 log CFU/g respectively). However, after 21 days of shelf study at 4°C sprouts in both systems almost had the same counts (10.02±0.70 versus 9.55±0.49 log CFU/g in KHS and conventional systems respectively).
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Title: NUMERICAL ANALYSIS ON MAXIMUM LIKELIHOOD ESTIMATORS FOR LINEAR PARABOLIC STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS
Creator: Zhang, Jun
Date: 2019
Description: The thesis contributes to the numerical analysis on statistical inference for stochastic partial differential equations (SPDEs). We study the...
Show moreThe thesis contributes to the numerical analysis on statistical inference for stochastic partial differential equations (SPDEs). We study the maximum likelihood estimation problem of the drift parameter for a large class of linear parabolic SPDEs. As in the existing literature on statistical inference for SPDEs, we take a spectral approach, and assume that one path of the first N Fourier modes is observed continuously in a fixed finite time interval [0, T]. We first provide a review of the asymptotic properties of the maximum likelihood estimator (MLE) of the drift parameter in the large number of Fourier modes regime, N  ∞, while the time horizon T > 0 is fixed. The main part of this thesis is dedicated to the numerical study of the asymptotic properties of the MLEs for two examples of linear parabolic SPDEs: the one-dimensional stochastic heat equation and a d-dimensional linear, diagonalizable, parabolic SPDE, where d  ℕ. For the one-dimensional stochastic heat equation, we perform the sensitivity analysis to assess the effect of changes in model parameters on the speed of convergence of the MLE. For the second linear parabolic SPDE, our simulations verify the theoretical results in the literature that both the consistency and asymptotic normality of the MLE hold for such equation only when d ≥ 2.
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Title: Mathematics of Civil Infrastructure Network Optimization
Creator: Rumpf, Adam Andrew
Date: 2020
Description: We consider a selection of problems from civil infrastructure network design that are of great importance in modern urban planning but have,...
Show moreWe consider a selection of problems from civil infrastructure network design that are of great importance in modern urban planning but have, until relatively recently, gone largely ignored in mathematical literature. Each of these problems is approached from the perspective of network optimization-based modeling, with a major focus placed on the development of efficient solution algorithms.We begin with a study of the phenomenon of interdependent civil infrastructure networks, wherein the functionality of one network (such as a telecommunications system) requires the input of resources from another network (such as the electrical power grid). We first consider a linear relaxation of an established binary interdependence minimum-cost network flows model, including its unique modeling applications and its use as part of a randomized rounding approximation algorithm for the mixed integer model. We also develop a generalized network simplex algorithm for the efficient solution of this generalized minimum-cost network flows problem. We then move on to consider a trilevel network interdiction game for use in planning the fortification of interdependent networks subject to targeted attacks. A variety of solution algorithms are developed for both the binary and the linear interdependence models, and the linear interdependence model is used to develop an approximation algorithm for the more computationally expensive binary model.We then develop a public transit network design model which incorporates a social access objective in addition to traditional operator cost and user cost objectives. The model is meant for use in planning minor modifications to a public transit network capable of improving equity of access to important services while guaranteeing that service levels remain within a specified tolerance of their initial values. A hybrid tabu search/simulated annealing algorithm is developed to solve this model, which is then applied to a test case based on the Chicago public transit network with the objective of improving equity of primary health care access across the city.
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Title: An experimental study on the effects of partial sleep deprivation on disordered-eating urges and behaviors
Creator: Johnson, Nicole Kathryn
Date: 2020
Description: Previous research has linked sleep disturbances with disordered eating. Studies have also shown that one night of partial sleep deprivation...
Show morePrevious research has linked sleep disturbances with disordered eating. Studies have also shown that one night of partial sleep deprivation causes increases in food intake and appetite disturbances. However, the effects of sleep deprivation on disordered eating are unclear as research has yet to examine the effects of one night of partial sleep deprivation (≤ 4 hours of sleep) on disordered eating in a representative adult female sample. Adult, female participants (N=40) completed eligibility and baseline measures reporting medical conditions, eating disorder symptoms, sleep disturbances, depressed mood, and anxiety symptoms. Participants were randomized to either the sleep-deprived condition (~50% of their average sleep duration) or the habitual-sleep condition (~100% of their average sleep duration). The morning after the sleep condition, participants completed self-report appetite and disordered eating measures before and after consuming a test meal and later that evening. The following statistical analyses, adjusted for multiple comparisons (p<0.002), found no significant group differences: independent samples t-tests (outcome: pre-meal appetite, disordered eating, and test-meal consumption), multivariate analyses of variance (MANOVAs; outcome: pre- and post-meal area under the curve disordered eating and appetite), repeated measures ANOVAs (time X group; outcome: pre- and post-meal appetite and disordered eating), analyses of covariance (ANCOVAs; controlling for pre-meal ratings; outcome: disordered eating at follow-up), and chi-square tests (outcome: follow-up appetite and disordered eating). Despite finding no support for the effect of sleep deprivation on disordered eating, this study extends previous research as a novel study using the experimental manipulation of sleep deprivation to examine its effects on disordered eating.
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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: Exploring Growth After Vision Loss
Creator: BANGLE, MELISSA
Date: 2020
Description: Despite recent advances in our knowledge of positive growth following the onset of chronic illness or disability, little to no effort has been...
Show moreDespite recent advances in our knowledge of positive growth following the onset of chronic illness or disability, little to no effort has been made to understand how the phenomenon of growth might be experienced by individuals who are blind or visually impaired. This not only limits our understanding of how growth is experienced, but also our understanding of the experiences associated with vision loss. This qualitative study explores the perspectives and experiences of growth held by 35 adults with acquired disability due to severe vision impairment and blindness. Additionally, participants discussed their views on how growth can be experienced within the context of adjusting to vision loss. Results indicate that some individuals do experience positive psychological growth after vision loss which can lead to positive changes in one’s life. They also demonstrate that the structure of growth after vision loss shares some similarities with existing growth models like the model for Post Traumatic Growth. Results also suggest that growth may be an outcome of becoming well-adjusted to vision loss; although, the nature of the transition from adjustment to growth remains less clear. Specific factors that may facilitate growth are explored and implications for facilitation of successful adjustment and growth in the context of vision rehabilitation are discussed.
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Title: Is emotion regulation a mediator between parenting skills and treatment outcome in Parent-Child Interaction Therapy?
Creator: Butler, Kristina
Date: 2020
Description: Disruptive behavior disorders are prevalent in preschool children and are associated with a range of negative developmental sequelae. There is...
Show moreDisruptive behavior disorders are prevalent in preschool children and are associated with a range of negative developmental sequelae. There is extensive evidence that Parent-Child Interaction Therapy (PCIT) is an effective behavioral parent training program for decreasing disruptive behaviors in young children. However, the mechanism that accounts for the reduction in externalizing behaviors in PCIT is not well understood. Children’s emotion regulation (ER) is one possible mechanism that accounts for treatment effectiveness. Parenting skills focused on in PCIT serve to increase warmth in caregiver-child interactions, which, in turn, lead to increases in children’s ER skills. ER also has been shown to moderate externalizing behaviors in PCIT. However, to date, there are no longitudinal studies that have examined ER as a mediator in PCIT. The aim of this study was to determine if child ER serves as a mediator between changes in parenting skills and decreases in externalizing behavior problems after PCIT treatment. A diverse sample of 67 children and their mothers participated in PCIT treatment in a community mental health center. All variables were assessed twice, at baseline and after treatment. Positive parenting skills (“Do Skills”) and negative ones (“Don’t Skills”) were assessed during a video recorded 5-minute task using the Dyadic Parent-Child Interaction Coding System. Child ER was assessed during a video recorded 5-minute clean-up task with a behavioral coding scheme adapted from previous research. Child behavior problems were measured using the Child Behavior Checklist Externalizing Scale. Difference scores used in the final analyses were calculated by subtracting the baseline score from the final assessment score for each measure.Results of linear regression analyses revealed a significant, negative relation between changes in ER and externalizing behavior problems. Findings did not support ER as a partial mediator between parenting skills and child externalizing problems. However, moderation analyses indicated that change in ER moderated the relation between change in positive parenting skills (Do Skills) and change in behavior problems, such that the interaction was significant for greater changes in ER. Specifically, increases in Do Skills led to less improvement in disruptive behaviors in children whose ER skills decreased. Also, increases in Do Skills led to greater reductions in behavior problems in children whose ER skills showed greater improvement. This study provides evidence that change in ER moderates changes in Do Skills and change in externalizing problems in PCIT. Findings also suggest that adding strategies to PCIT that focus on increasing child ER may enhance effectiveness of this treatment.
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Title: CULTURALLY SENSITIVE HELP-SEEKING AMONG ASIAN INTERNATIONAL AND ASIAN AMERICAN COLLEGE STUDENTS
Creator: Tsen, Jonathan Yee-jon
Date: 2020
Description: Asian populations are rapidly rising, representing the fastest growing racial group of immigrants in the U.S. with many seeking higher...
Show moreAsian populations are rapidly rising, representing the fastest growing racial group of immigrants in the U.S. with many seeking higher education. While many face risk for poor mental health outcomes and high suicidal ideation, Asian college students report lower rates seeking mental health services than White Americans. The purpose of this study was to test a culturally sensitive help-seeking model for Asian international and Asian American college students, and to capture relevant psychological and cultural factors that influence help-seeking. This study used an observational design to build on the current research and evaluated the effects of acculturation, enculturation, public stigma of help-seeking, self-stigma of help-seeking, and attitudes on willingness to seek psychological services. Four hundred and fifty-eight students (Age M = 23.93, SD = 4.36) represented by 265 Asian International Students and 193 Asian American Students. Using a path analysis, results demonstrated a poorly fitted model, suggesting that acculturation, enculturation, public stigma, self-stigma, attitudes, and willingness do not relate significantly to each other when viewed altogether in a model. This remained true even when modifications to the model were made, and when observing the model within only Asian American student sample or Asian international student sample. However, significant direct effects were observed between enculturation and public stigma in the total sample, as well as separately in Asian American or Asian international samples. These findings highlight the importance of exploring with different methodological approaches to gain insight on other important psychological and cultural factors that impact help-seeking among Asian international and Asian American college students.
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Title: A Complete Machine Learning Approach for Predicting Lithium-Ion Cell Combustion
Creator: Almagro Yravedra, Fernando
Date: 2020
Description: The object of the herein thesis work document is to develop a functional predictive model, able to predict the combustion of a US18650 Sony...
Show moreThe object of the herein thesis work document is to develop a functional predictive model, able to predict the combustion of a US18650 Sony Lithium-Ion cell given its current and previous states. In order to build the model, a realistic electro-thermal model of the cell under study is developed in Matlab Simulink, being used to recreate the cell's behavior under a set of real operating conditions. The data generated by the electro-thermal model is used to train a recurrent neural network, which returns the chance of future combustion of the US18650 Sony Lithium-Ion cell. Independently obtained data is used to test and validate the developed recurrent neural network using advanced metrics.
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Title: Gaussian Process Assisted Active Learning of Physical Laws
Creator: Chen, Jiuhai
Date: 2020
Description: In many areas of science and engineering, discovering the governing differential equations from the noisy experimental data is an essential...
Show moreIn many areas of science and engineering, discovering the governing differential equations from the noisy experimental data is an essential challenge. It is also a critical step in understanding the physical phenomena and prediction of the future behaviors of the systems. However, in many cases, it is expensive or time-consuming to collect experimental data. This article provides an active learning approach to estimate the unknown differential equations accurately with reduced experimental data size. We propose an adaptive design criterion combining the D-optimality and the maximin space-filling criterion. The D-optimality involves the unknown solution of the differential equations and derivatives of the solution. Gaussian process models are estimated using the available experimental data and used as surrogates of these unknown solution functions. The derivatives of the estimated Gaussian process models are derived and used to substitute the derivatives of the solution. Variable-selection-based regression methods are used to learn the differential equations from the experimental data. The proposed active learning approach is entirely data-driven and requires no tuning parameters. Through three case studies, we demonstrate the proposed approach outperforms the standard randomized design in terms of model accuracy and data economy.
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Title: The Relation Between Community Violence Exposure and Young Children's Psychopathology Symptoms
Creator: Gibson, Lynda L
Date: 2020
Description: Chronic community violence exposure (CVE) has become an everyday issue for many children living in inner-city neighborhoods. However, few...
Show moreChronic community violence exposure (CVE) has become an everyday issue for many children living in inner-city neighborhoods. However, few studies have examined the effects of CVE on symptoms of psychopathology in young children. The primary aim of this study was to examine the relation between CVE and internalizing and externalizing symptoms in preschool children. Another goal was to determine if the relations between CVE and both types of symptoms were affected by the type of exposure, the location of the event, and the relationship between the child and the individual involved in the event. A signal-contingent ecological momentary assessment (EMA) design was used in which 32 caregivers reported on their age 3-5 year-old children’s exposure to community violence, and their internalizing and externalizing symptoms for one week. A total of 152 events of community violence were reported during this period, revealing that the children were exposed to an alarmingly high frequency of these events. Results of multilevel model (MLM) analyses showed that increased frequency of momentary CVE was associated with more severe caregiver-reported internalizing and externalizing symptoms throughout one-week. Additionally, witnessed CVE, situations occurring near home, and situations involving someone known by the child strengthened the association between CVE and symptom severity. The present findings reveal that some of the long-term negative effects associated with trauma exposure occur in a shorter time-span when children are exposed to community violence on a daily basis. They also provide guidelines that can be used to inform future assessment of CVE and strategies that may be effective for intervention.
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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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