Search results

Title: Biophysical and Computational Characterization of CinDel Edits of Dystrophin
Creator: Stojkovic, Vladimir
Date: 2022
Description: Duchenne muscular dystrophy (DMD) is a degenerative genetic disease caused by a genetic defect that results in the absence of dystrophin, a...
Show moreDuchenne muscular dystrophy (DMD) is a degenerative genetic disease caused by a genetic defect that results in the absence of dystrophin, a protein with an important stabilizing role in muscle cells. DMD causes progressive muscle degeneration leading to the loss of ambulation, and typically results in death before the third decade of life. Treatments for DMD aim to restore dystrophin expression and typically do so by producing edited or modified dystrophins. The only FDA approved therapy, exon skipping, produces dystrophin edits at exon boundaries but emerging therapeutic approaches like gene replacement therapy and CRISPR-Cas9-based gene editing techniques like CinDel allow for greater flexibility and are not constrained to exon boundary edits. However, understanding of what makes a “good”, functional edit is limited so it is not clear how to make use of this increased flexibility to produce optimal edits which are believed to be necessary for robust treatment. In an effort to improve understanding of the biophysics of these non-exon edits, we have embarked on a mixed experimental and computational study of a set of CinDel edits in the D19-D21 region of the dystrophin central rod domain. First, we have conducted an Alphafold structure prediction-based screen of a subset of possible edits in this region and selected one edit for follow-up characterization. We then compared this computationally-selected edit to three other heuristically designed edits experimentally and computationally by molecular dynamics simulations. We found that the computationally selected edit is significantly more thermodynamically stable than the other edits in the cohort. This edit also generally exhibited more favorable properties in MD simulations across multiple measures such as helicity, STR-junction unwinding and conformational variability.
Show less

Title: Health Information Seeking, Depression, and Satisfaction with Life in Racial/ethnic Minority vs. White individuals with Spinal Cord Injuries
Creator: Stipp, Kelsey
Date: 2022
Description: Health information is available both traditionally by conversations with health care professionals, and non-traditionally via use of the...
Show moreHealth information is available both traditionally by conversations with health care professionals, and non-traditionally via use of the Internet and other media sources. Health information is crucial to individuals with chronic health conditions and/or disabilities, such as spinal cord injury (SCI), to promote health, minimize comorbidities, and improve quality of life (QOL). Methods of health information seeking have been shown to differ between individuals who are racial/ethnic minority individuals and individuals who are White. Existing research appears to show health information seeking may increase QOL in populations with chronic health conditions and/or disabilities. However, it is unclear how aspects of QOL differ between individuals within the SCI population by race/ethnicity. The present study used Chi Square analyses to test racial/ethnic group differences in health information seeking and multiple analysis of covariance (MANCOVA) to test whether method of health information seeking and aspects of QOL, specifically depression and satisfaction with life, were moderated by race/ethnicity. An adult sample of 9,403 individuals with SCI who completed a survey on their injury, health, and QOL between 2011 and 2016 was used. Participants identified their source of health information as traditional (i.e., conversations with health care professionals) or non-traditional (e.g., newspaper, television, radio, etc.). Results indicated non-traditional sources of health information were utilized more frequently regardless of race/ethnicity. Unexpectedly, moderation results suggested that associations between source of health information and depression and satisfaction with life did not differ by race/ethnicity. However, source of health information was associated with satisfaction with life and depression for the entire sample. Study findings demonstrate the shift towards non-traditional (e.g., newspaper, television, radio, etc.) health information seeking within the SCI population. Further, findings support previous empirical work demonstrating the association between method of health information seeking and depression and satisfaction with life. These findings can be used to improve dissemination of accurate health information to the SCI population via non-traditional sources. Further research should include more diverse samples of individuals to better understand health information seeking as well as depression and satisfaction with life within the SCI population.
Show less

Title: A Functionalized 2D Boron Nitride Electrode for Rechargeable Batteries
Creator: Tatagari, Vignyatha Reddy
Date: 2021
Description: Motivated by the great performance of the graphene oxide battery and its poor safety, in the present work, an attempt is made to fabricate an...
Show moreMotivated by the great performance of the graphene oxide battery and its poor safety, in the present work, an attempt is made to fabricate an alternative battery from functionalized 2-dimensional (2D) boron nitride. The expectation is that functionalized boron nitride can exhibit the same great electrochemical performance as graphene oxide while it would be much more thermally stable. Toward this goal, synthetic opportunities were explored to realize -OBF3 functionalized hexagonal boron nitride. Both top-down and bottom-up synthetic approaches were considered and implemented. In the top-down methods, commercially available bulk hexagonal boron nitride (h-BN) is reacted with functionalization agents such as LiOBF3 and LiOH.BF3. Synthesis of these functionalization agents and their reactions with h-BN were carried out in several different ways. Bottom-up synthetic approach using Boric Acid and Urea was utilized to synthesize turbostratic boron nitride (t-BN), which is an intermedier in the commercial synthesis of hexagonal boron nitride. Turbostratic boron nitride contains exfoliated and -OH functionalized monolayers of boron nitride. An attempt is made to esterify the -OH groups of turbostratic boron nitride to obtain the desired -OBF3 functionalized monolayers of h-BN. Initial electrochemical tests on turbostratic boron nitride and its esterified form are carried out along with ionic conductivity measurements. Only a very limited electrochemical activity was observed due to a low degree of functionalization in these materials, indicating the need for improved synthetic procedures to achieve the desired target materials.
Show less

Title: PIMMINER: A HIGH-PERFORMANCE PIM ARCHITECTURE-AWARE GRAPH MINING FRAMEWORK
Creator: Su, Jiya
Date: 2022
Description: Graph mining applications, such as subgraph pattern matching and mining, are widely used in real-world domains such as bioinformatics, social...
Show moreGraph mining applications, such as subgraph pattern matching and mining, are widely used in real-world domains such as bioinformatics, social network analysis, and computer vision. Such applications are considered as a new class of data-intensive applications that generate massive irregular computation workloads and memory accesses, which degrade the performance and scalability significantly. Leveraging emerging hardware, such as process-in-memory (PIM) technology, could potentially accelerate such applications. In this paper, we propose PIMMiner, a high-performance PIM architecture graph mining framework. We first identify that current PIM architecture cannot be fully utilized by graph mining applications. Next, we propose a set of optimizations that enhance the locality, and internal bandwidth utilization and reduce remote bank accesses and load imbalance through cohesive algorithm and architecture co-designs. We compare PIMMiner with several state-of-the-art graph mining frameworks and show that PIMMiner is able to outperform all of them significantly.
Show less

Title: DO ACT CONSTRUCTS MODERATE ASSOCIATIONS BETWEEN SOCIAL MEDIA AND EATING PATHOLOGY?
Creator: Badillo Regan , Krystal E
Date: 2022
Description: Limited research has assessed individuals with disordered eating and their social media use. Additionally, there has been limited...
Show moreLimited research has assessed individuals with disordered eating and their social media use. Additionally, there has been limited investigation into psychotherapy constructs that could be used when addressing social media use in those with eating pathology. This study aims to improve the existing literature on social media and eating pathology by recruiting a sample of probable eating disorders and assessing if Acceptance and Commitment Therapy (ACT) constructs moderate the relation between social media and eating pathology. It is anticipated that 1) eating disorder pathology severity will be positively correlated with photo-based social media behavior; 2) eating disorder symptom severity will be positively associated with importance of social media; and 3) those who score higher in mindful eating, body image flexibility, and body image acceptance will have a weaker positive association between ED pathology and importance of social media and those who score lower in body image cognitive fusion will have a weaker positive association between ED pathology and importance of social media mindful eating, body image flexibility, body image acceptance, and body image cognitive fusion will moderate the relation between eating disorder symptom severity and social media use. To test the hypotheses women with a probable eating disorder (N=121) completed online questionnaires via prolific. The majority of participants identified as non-Hispanic (81%) and White (45.5%). Results suggest that there are associations between ED pathology, ACT constructs, Importance of Twitter and Instagram, and photo-based behaviors but not Importance of Facebook. Additionally, the moderation models examined were not statistically significant. Implications of these findings are discussed as well as future direction for research and clinical work.
Show less

Title: A Network Analysis of the Six Core Processes Associated with Acceptance and Commitment Therapy
Creator: Bailey, Jennifer Rose
Date: 2022
Description: According to the theoretical model of Acceptance and Commitment Therapy, six core processes comprise a latent factor of psychological...
Show moreAccording to the theoretical model of Acceptance and Commitment Therapy, six core processes comprise a latent factor of psychological flexibility: present moment, chosen values, committed action, self as context, cognitive defusion, and acceptance. Little research has directly examined the unique relations among the processes. The present study extended our knowledge of the structure and relations between these processes by examining the relative importance and influence of a single process to the system of processes as a whole utilizing network analysis with a sample of 277 adult, non-clinical participants. Committed action was the most central of all the processes, demonstrating the highest strength centrality and most number of edges. Cognitive defusion and present moment also showed high strength centrality, suggesting that these processes exert the greatest influence on other processes in the network based on partial correlations controlling for all other constructs. Results provided support for the conceptualization of the three response styles (i.e., open, centered, and engaged). The addition of neuroticism to the core processes network showed little effect on the number of edges present between the six core processes. Neuroticism was strongly related to cognitive defusion and more weakly related to committed action. Results not only increased our understanding of the relations between processes and provided knowledge that may be useful to our understanding of the ACT theoretical model, but it also may have potential clinical implications, such as aiding in the identification of treatment targets to enhance psychological flexibility.
Show less

Title: Sharpen Quality Investing: A PLS-based Approach
Creator: Jiao, Zixuan
Date: 2022
Description: I apply a disciplined dimension reduction technique called Partial Least Square (PLS) to construct a new quality factor by aggregating...
Show moreI apply a disciplined dimension reduction technique called Partial Least Square (PLS) to construct a new quality factor by aggregating information from 16 individual signals. It earns significant risk-adjusted returns and outperforms quality factors constructed by alternative techniques, namely, PCA, Fama-Macbeth regression, a combination of PCA and Fama-Mabeth regression and a Rank-based approach. I show that my quality factor performs even better during rough economic patches and thus appears to hedge periods of market distress. I further show adding our quality factor to an opportunity set consisting of the other classical factors increases the maximum Sharpe ratio.
Show less

Title: CHARACTERIZATION OF HERBS AND SPICES PHYTOCHEMICALS AND PHARMACOKINETIC PROFILE OVER 24-HOUR AFTER CONSUMPTION IN OVERWEIGHT/OBESE ADULTS
Creator: Huang, Yudai
Date: 2022
Description: The health benefits of herbs and spices (H/S) have been known since ancient times. They are a rich source of phytochemicals, such as phenolic...
Show moreThe health benefits of herbs and spices (H/S) have been known since ancient times. They are a rich source of phytochemicals, such as phenolic compounds and terpenoids. However, there is limited information on their absorption and metabolism in humans. Therefore, the primary objective of this study is to identify and characterize phytochemical compounds in H/S mixtures and their absorption and metabolism in the human body over 24 h. H/S and plasma samples used in this study were from a randomized, single-blinded, 4-arm, 24 h, multi-sampling, single-center crossover clinical trial (Clincaltrials.gov NCT03926442) conducted in obese or overweight adults (n=24, aged 37 ± 3 years, BMI=28.4 ± 0.6 kg/m2). Plasma samples were collected at baseline (t=0 h), 0.5, 1, 2, 4, 5.5, 7, and 24 h after consuming a high-fat high-carbohydrate (HFHC) meal with salt and pepper (control) or the control meal with 6 g of three different H/S mixtures (Italian herb: rosemary, basil, thyme, oregano, and parsley in the same ratio; cinnamon; and pumpkin pie spice containing cinnamon, ginger, nutmeg and allspice, the ratio unknown). The phytochemical compounds in the H/S mixtures and their metabolites in human plasma were tentatively identified and quantified by dynamic multiple reaction monitoring transitions on UHPLC-QQQ-MS/MS. Statistical analysis was conducted on SAS-PC 9.4 using non-parametric test via NPAR1WAY procedure. A total of 79 phytochemical compounds were quantified from samples of three H/S mixtures and pepper, of which 36 were flavonoids conpounds, 8 were terpenoids, 27 phenolic acids, and 9 were identified as other compounds. Acetone showed the highest extraction ability for both (poly)phenols and terpenoids in H/S compared to other organic solvents (50% and 80% methanol, ethyl acetate and chloroform). Italian herb contains 763.1 mg/100 g flavonoids, 879 mg/100 g phenolic acids, and 498.6 mg/100g terpenoids; cinnamon contains 981 mg/100 g flavonoids, 11.2 mg/100g phenolic acids, 292.3 mg/100g coumarin, and 1977.1 mg/100 g cinnamaldehyde; pumpkin pie spice contains 655.8 mg/100 g flavonoids, 17.1 mg/100 g phenolic acids, 226.5 mg/100 g coumarin, and 1633 mg/100 g cinnamaldehyde. A total of 47 metabolites were tentatively identified and quantified in plasma samples after H/S consumption over 24 h. Plasma concentrations of carnosic acid derivatives and the glucuronidation products increased after intake of Italian herb, and the Area under the curve (AUC0-24h) was significantly different from control (all P < 0.05) except carnosol glucuronide. Carnosic acid and carnosol had Tmax at 3.4±1.1 and 1.8±0.3 h, respectively, while both of their conjugated glucuronides kept increasing until 24 h. Coumarin glucuronide was increased by cinnamon and pumpkin pie spice consumption with peak concentrations reached at between 1.5-1.6 h. The AUC0-24h after both meals were significantly different from control meal, both P < 0.05. Our results suggest that H/S contain diverse categories of phytochemical compounds that are absorbed and metabolized in the human body into various metabolites in response to 3 different H/S test meals and their appearance in the blood starts as early as around 0.5 h and extends to as long as 24 h for select metabolites.
Show less

Title: Advances in Distribution System State Estimation
Creator: Huang, Jianqiao
Date: 2022
Description: With the increasing penetration of renewable energy in the distribution system, the system states are becoming more volatile. How to maintain...
Show moreWith the increasing penetration of renewable energy in the distribution system, the system states are becoming more volatile. How to maintain the normal operation is an urgent question to the operators. Distribution system state estimation (DSSE) is the key to the monitor and control of distribution systems.Distribution systems feature a larger number of nodes and heterogeneous measurements. Due to these features, directly employing traditional state estimation methods cannot provide fast and accurate estimation results. The existing semidefinite programming based methods show promising for the accuracy, but it is not scalable for a large system. In this thesis, we propose fast and accurate DSSE methods. First, we improve the efficiency of the state-of-art SDP-DSSE method, convex iteration (CI) method. We design a scalable convex iteration method, CDQC, by fully exploiting the radial topology of distribution system. However, the efficiency of CDQC depends on efficient feeder partition solution. It is time-consuming to get a good partition especially when the system is large. Hence, we propose a bus injection based semidefinite relaxation method (SDR-BIM) that fully exploits the radial topology of the network without the need for partitioning the networks. However, SDR-BIM has numerical issue for large scale network. This motivates us to design a branch power model based SDR-DSSE method. The proposed SDR-BPM-DSSE method improves the numerical stability and the increase in the average estimation error of voltage is less than $0.04\%$. To further improve the computational efficiency, we developed a generalized linear power flow model (GLDF) and propose an iterative method to solve the DSSE based on GLDF.Finally, the efficiency and accuracy of the proposed methods are validated on IEEE 13-bus, 37-bus, 123-bus, and 8500-node test feeders.
Show less

Title: Single Factor and Multifactor Risk Model to Measure Concentration Risk of Credit Portfolio under Basel Regulations
Creator: Ji, Junjie
Date: 2022
Description: My research discussed the essential part of Basel regulations, which is calculating the regulatory capital of bank portfolios using the...
Show moreMy research discussed the essential part of Basel regulations, which is calculating the regulatory capital of bank portfolios using the asymptotic single risk factor model (ASRF) under the internal rating-based approach (IRB). I’m trying to analyze whether the regulatory model is strong enough to measure the credit risk of banks portfolios accurately. Is the model capable of reflecting and controlling the concentration risk involved in bank portfolios? By relaxing the single factor assumption, there are models and methods to calculate unexpected loss (defined as VaR) and required capital. In my research, I propose and validate the models in different scenarios and evaluate whether they can effectively catch the tail risk of bank portfolios without overcharging required capital. My research proved that ASRF lacks the sensitivity to capture sector concentration risk. There are advantages, as well as shortcomings of each multifactor model. I propose that banks include the appropriate multifactor model in the risk management process based on their portfolios' characteristics. The result and related discussion will also contribute to addressing the conflict of banks' profitability and risk control under the Basel regulatory framework.
Show less

Title: Apalutamide Modulates the Expression of Regulatory Genes for Prostate Cancer Cell Invasion and Migration In Vivo and In Vitro
Creator: Qualter, Gina E.
Date: 2022
Description: The next generation antiandrogen, Apalutamide (Apa), improves both overall survival and metastasis-free survival in men with castration...
Show moreThe next generation antiandrogen, Apalutamide (Apa), improves both overall survival and metastasis-free survival in men with castration-resistant prostate cancer (CRPC). In vitro and in vivo studies were performed to characterize the mechanistic effects of Apalutamide on prostate cancer cell proliferation, invasion, and migration, and the expression of genes that regulate these processes. Apalutamide inhibited the proliferation of LNCaP human prostate cancer cells in both the presence and absence of dihydrotestosterone (DHT), and also inhibited LNCaP cell migration/invasion. At the mRNA level (RT-PCR), Apalutamide down-regulated the expression of androgen receptor (AR), c-Myc, MMP-2, MMP-9, DANCR, and lncRNA, and up-regulated TIMP-2 expression. Similar data were obtained for protein expression (western blot). In the in vivo study, male Hi-Myc mice received daily oral administration of Apalutamide beginning at age 8 weeks for 2 months, 3.5 months, or 5 months. Daily oral administration of Apalutamide reduced accessory sex gland weights by over 50% at all three time points, inhibited the progression of prostatic intraepithelial neoplasms (PIN) to cancer, and significantly affected the expression of genes that regulate invasion and migration. However, in vitro findings indicated that resistance to Apalutamide through the emergence of the AR splice variant 7 (AR-V7) following extended treatment is possible and may be reversed following knockdown of AR-V7 gene expression.In summary, these results suggest that while Apalutamide is an effective inhibitor of prostate cancer invasion/migration, further investigation into the mechanism of AR-V7 mediated Apalutamide-resistance and strategies to overcome resistance may be indicated to improve prostate cancer patient outcomes following extended periods of treatment.
Show less

Title: FACILITATORS AND BARRIERS TO PRE-EXPOSURE PROPHYLAXIS (PREP) UPTAKE WILLINGNESS FOR FULL-SERVICE SEX WORKERS
Creator: Ramos, Stephen D
Date: 2022
Description: Full-service sex workers (FSSW) are individuals who exchange direct sexual services for goods, money, or other services (Centers for Disease...
Show moreFull-service sex workers (FSSW) are individuals who exchange direct sexual services for goods, money, or other services (Centers for Disease Control and Prevention, 2022a). FSSW report relatively poorer physical and mental health compared to others (Ramos et al., 2022; Rekart, 2005). Related, the CDC indicates that due to the nature of sex work, sex workers may be disproportionately at-risk for contracting Human Immunodeficiency Virus (HIV; Centers for Disease Control and Prevention, 2022a). However, a variety of factors may relate to HIV-risk in this population. Specifically, different multi-level factors may relate to sex workers’ willingness to use pre-exposure prophylaxis (PrEP), a once-daily HIV preventative medication (Centers for Disease Control and Prevention, 2022a). While highly effective against HIV, PrEP uptake in several key HIV populations is slow (Holloway et al., 2017). Here, I adapted the Social-Ecological Model (Kaufman et al., 2014), with the assistance of lived-experience members and community organizations in developing and disseminating the study, to assess barriers and facilitators towards PrEP uptake willingness for FSSW and investigated a distal-proximal stigma-based mediation analysis to PrEP willingness. I found that two barriers and two facilitators initially emerged as significant predictor of PrEP uptake willingness. However, in adopting a more conservative approach, only (a) anticipating stigmatizing disapproval from others, and (b) providing others with PrEP knowledge, independently remained as a significant barrier and facilitator to PrEP uptake willingness, respectfully. Mediation analysis did not yield a distal-proximal stigma-based mediation of PrEP uptake willingness. Implications for future research, clinical work, and policy are discussed.
Show less

Title: POLYTRAUMA CLINICAL TRIAD ASSOCIATED ATTENTION AND MEMORY FUNCTIONING
Creator: Ramirez, Amanda M.
Date: 2021
Description: The purpose of the current study was to explore cognitive functioning associated with the polytrauma clinical triad in a sample of post-9/11...
Show moreThe purpose of the current study was to explore cognitive functioning associated with the polytrauma clinical triad in a sample of post-9/11 veterans. More specifically, it sought to determine if a component (i.e., PTSD, mTBI, or pain), in the context of the triad, accounted for variability in attention and memory functioning as measured by neuropsychological assessments. The study also sought to evaluate the relation between PTSD and cognition more comprehensively by examining if the four PTSD symptom clusters were associated with differential patterns of neuropsychological performances. Participants included 111 veterans who served in Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn, otherwise known as post-9/11 veterans. Participants completed a brief structured interview and neuropsychological battery. Several hierarchical regressions examined the association between the polytrauma clinical triad and performances on select measures of attention and memory. Results indicated that the triad did not significantly predict sustained attention, visual memory, or verbal memory. These findings suggested that despite the rates of the polytrauma clinical triad among a significant portion of post-9/11 veterans, the current evidence does not support the presence of related cognitive impairment.
Show less

Title: Contract Rollover and Volatility
Creator: Chen, Yue
Date: 2022
Description: In futures markets, approaching the expiration days, most market participants close out existing positions of front month contract and open...
Show moreIn futures markets, approaching the expiration days, most market participants close out existing positions of front month contract and open new positions of next month contract. The object of this dissertation is to evaluate the impact of contract rollover activities on unconditional volatility and conditional volatility modeling. First, two contract rollover measures, volume ratio and open interest ratio of front contract over next contract are created. Second, this study investigates the impact of contract rollover measures on both unconditional volatility estimation models and conditional volatility estimation models. Third, it examines the roles of contract rollover activities in unconditional volatility prediction models. Last, to further explore the relationship between contract rollover measures and unconditional volatilities, the vector autoregressive model is conducted to test granger causality. The findings show that the volume ratio and open interest ratio have significant impact on unconditional volatilities and conditional volatility in soybean, wheat, gold, copper, crude oil, and natural gas futures markets, except on conditional volatility in silver futures market. Alternative models that incorporate contract rollover measures outperform benchmark models that do not incorporate contract rollover measures in both estimation models and prediction models. Moreover, the findings provide the strong evidence that there is significant bidirectional granger causality among volume ratio, open interest ratio and unconditional volatilities in all investigated futures markets. The empirical results confirm the important role of contract rollover on volatility behavior and are beneficial to futures exchanges to set and monitor margins precisely for their customer’s trading accounts in commodity futures markets.
Show less

Title: INFORMATION EFFICIENCY AND THE EFFECT OF HIGH FREQUENCY TRADING IN THE U.S. FUTURES MARKETS
Creator: CHA, SEUNG YOUN
Date: 2021
Description: The paper gives an empirical analysis with the U.S. futures market data on how High Frequency Trading, HFT can improve the information...
Show moreThe paper gives an empirical analysis with the U.S. futures market data on how High Frequency Trading, HFT can improve the information efficiency of asset prices. Various analyses were conducted to determine the degree of efficiency of information in futures high-frequency trading. The paper tries to explain the effect of high-frequency trading on the efficiency of the market in various ways and tries to propose stepping stones for developing a new market analysis measure.The research builds a coherent framework for analyzing both linear and non-linear market efficiency and applies it to a variety of futures contracts using high- frequency data. The major finding of this paper is that market efficiency levels vary widely over time depending on market characteristics. The paper also finds that HFT activities are higher when the market is inefficient. The paper analyzes the relationship between high frequency trading activities and market efficiency and discovers the mechanism. The story that HFT activity responds to market efficiency needs is especially strong in the E-mini, S&P500 futures contract.
Show less

Title: Hedge Fund Replication With Deep Neural Networks And Generative Adversarial Networks
Creator: Chatterji, Devin Mathew
Date: 2022
Description: Hedge fund replication is a means for allowing investors to achieve hedge fund-like returns, which are usually only available to institutions....
Show moreHedge fund replication is a means for allowing investors to achieve hedge fund-like returns, which are usually only available to institutions. Hedge funds in total have over $3 trillion in assets under management (AUM). More traditional money managers would like to offer hedge fund-like returns to retail investors by replicating their performance. There are two primary challenges with existing hedge fund replication methods, difficulty capturing the nonlinear and dynamic exposures of hedge funds with respect to the factors, and difficulty in identifying the right factors that reflect those exposures. It has been shown in previous research that deep neural networks (DNN) outperform other linear and machine learning models when working with financial applications. This is due to the ability of DNNs to model complex relationships, such as non-linearities and interaction effects, between input features without over-fitting. My research investigates DNNs and generative adversarial networks (GAN) in order to address the challenges of factor-based hedge fund replication. Neither of these methods have been applied to the hedge fund replication problem. My research contributes to the literature by showing that the use of these DNNs and GANs addresses the existing challenges in hedge fund replication and improves on results in the literature.
Show less

Title: Improving Utility and Efficiency for Privacy Preserving Data Analysis
Creator: Liu, Bingyu
Date: 2022
Description: In recent decades, the smart cities are incorporating with Internet-of-Things (IoT) infrastructures for improving the citizens’ quality of...
Show moreIn recent decades, the smart cities are incorporating with Internet-of-Things (IoT) infrastructures for improving the citizens’ quality of life by leveraging information/data. The huge amount of data is extracted and generated from the devices (e.g., mobile applications, GPS navigation systems, urban traffic cameras, etc.), or city sectors such as Intelligent Transportation Systems (ITS), Resource Allocation, Utilities, Crime Detection, Hospitals, and other community services.This dissertation aims to systematically research the Data Analysis in IoT System, which mainly consists of two aspects: Utility and Efficiency. First, ITS as a representative system in IoT in the smart city, I present the work on privacy preserving for the trajectories data, which is achieved by the differential privacy technique with a novel sanitation framework. Moreover, I have studied the resource allocation problem in two different approaches: Cryptographic computation and Hardware en- claves with the utility and efficiency accordingly. For the Cryptographic computation approach, I utilize Secure Multi-party Computation (SMC) technique for achieving the privacy-aware divisible double auction without a mediator. Besides, I also pro- pose a hardware-based solution Trusted Execution Environment (TEE) for performance improvement. At the same time, integrity and confidentiality are also able to be guaranteed. The proposed hybridized Trusted Execution Environment (TEE)- Blockchain System is designed for securely executing smart contract. Finally, I have studied the Cryptographic Video DNN Inference for the smart city surveillance, which privately inferring videos (e.g., action recognition, and video, and classification) on 3D spatial-temporal features with the C3D and I3D pre-trained DNN models with high performance. This dissertation proposes the privacy preserving frameworks and mechanisms are able to be applied efficiently for IoT in the real-world.
Show less

Title: A BIM-BASED LIFE CYCLE ASSESSMENT TOOL OF EMBODIED ENERGY AND ENVIRONMENTAL IMPACTS OF REINFORCED CONCRETE TALL BUILDINGS
Creator: Ma, Lijian
Date: 2022
Description: Today 55 percent of population in the world lives in urban areas which is expected to increase to 68 percent by the year 2050. In the cities,...
Show moreToday 55 percent of population in the world lives in urban areas which is expected to increase to 68 percent by the year 2050. In the cities, high-rise buildings as symbols of the modern cityscape are dominating the skylines, but the data to demonstrate their embodied energy and environmental impacts are scarce, compared to low- or mid-rise buildings. Reducing the embodied energy and environmental impacts of buildings is critical as about 42 percent of primary energy use and 39 percent of the global greenhouse gas (GHG) emissions come from the building sector. However, it is an overlooked area in embodied energy and environmental impacts of tall buildings. This doctoral research aims to investigate the effects of tall buildings on embodied energy and environmental impacts by using process-based life cycle assessment (LCA) methodology within Building Information Modelling (BIM) environment, which provides construction industry platform to incorporate sustainability information in architectural design. This doctoral research is carried out through a literature review on embodied energy of high-rise buildings. Current LCA methods of buildings are also discussed in the literature review. It then develops a framework for BIM-based assessment of the embodied energy and environmental impacts of tall buildings. To achieve that, a case study of tall reinforced concrete building is applied, by using ISO 14040 and 14044 guidelines with available database, Revit and Tally application in Revit. The author concentrates on embodied energy and environmental impacts of reinforced concrete tall buildings. Finally, the association between design and construction variables with embodied energy and environmental impacts is explored. This research will lead to significant contributions. A comprehensive study on embodied energy and environmental impacts of high-rise building will address a major gap in LCA literature. Researchers and environmental consultants can use the results of this research to create design tools to evaluate environmental impacts of high-rise buildings. Also, architects can use the results of this research to develop insight into the environmental performance of tall buildings in early design stage. Architects and engineers can also use the results to optimize tall building design for low embodied energy and environmental impacts. Finally, the results of this research will enable architects, engineers, planners, and policymakers develop more sustainable built environments.
Show less

Title: Active Load Control in a Synchronized and Democratized (SYNDEM) Smart Grid
Creator: Lv, Zijun
Date: 2021
Description: Smart grid is envisioned to take advantage of modern information and communication technologies in achieving a more intelligent grid in order...
Show moreSmart grid is envisioned to take advantage of modern information and communication technologies in achieving a more intelligent grid in order to facilitate: Integration of renewable resources; Integration of all types of energy storage; Two-way communication between the consumer and utility so that end users can actively participate. The Synchronized and Democratized (SYNDEM) smart grid is regarded as the next generation smart grid. The objective of the SYNDEM smart grid is for all active players in a grid, large or small, conventional or renewable, supplying or consuming, to be able to equally and laterally regulate the grid in a synchronous manner to enhance the stability, reliability, and resiliency of future power systems. In a SYNDEM smart grid, power electronic converters are controlled to behave as conventional synchronous machines. Such converters are called virtual synchronous machines (VSMs).Following the SYNDEM structure, this thesis mainly focuses on developing the VSM technology for the automatic grid regulation at the demand side. The major aim and objective is to achieve active or intelligent loads that can flexibly and automatically take part in grid regulation. Moreover, the active load is expected to have similar grid regulation behavior as other active players in the grid, for e.g., renewable generations. To achieve this, a droop-controlled rectifier is proposed that acts as a general interface for a load to grid. The rectifier is controlled as a VSM so that a load equipped with such a rectifier can take part in grid regulation continuously like a traditional synchronous machine. Such a rectifier has a built-in storage port, in addition to the normal AC and DC ports. The flexibility required by the AC port to support the grid is provided by the storage port. The DC-bus voltage of the storage port is able to fluctuate with in a wide range to exchange energy with the grid.In order to further take use of the energy in the storage port (DC-bus capacitor) of a rectifier more reasonably and increase the support time to grid, an adaptive droop mechanism is proposed. Under such a droop mechanism, the rectifier can automatically change the power consumed according to the grid voltage variations as well as its potential to provide grid support. To achieve this, a flexibility coefficient is introduced to indicate the power flexibility level of the DC-bus capacitor. Then this flexibility coefficient is embedded into the universal droop controller (UDC) to make it adaptive. Hence, the adaptive droop controller has a changing droop coefficient corresponding to the power flexibility of a rectifier, so it can take advantage of the energy stored in its DC-bus capacitor wisely to support the grid. This droop controller can also be applied into connection between two SYNDEM smart grids. To achieve this, a grid bridge (GB) that enables autonomous and equal regulation between two SYNDEM grids is proposed. The real power transferred through a GB has linear relationship with the voltage deviation between the two micro-grids connected. The micro-grid with a higher voltage will automatically provide power to the lower one. Moreover, the power direction of a GB is bidirectional and determined by the grid voltage difference, this makes the two micro-grids equal to each other. The GB is physically a back-to-back converter. In order to achieve autonomous and equal regulation, both sides of the back-to-back converter are controlled under droop controller with the same droop coefficients. The VSM control technology is also developed to control Modular multilevel converters (MMCs) for high voltage applications. Like active loads introduced above, the MMCs can take part in the grid regulation according to the droop mechanism designed. In order to eliminate the circulating current that exists in MMCs, proportional-resonant (PR) controllers are adopted to inject second-order harmonics to the MMCs to suppress the second order circulating current. The dynamics, implementation and operation of the VSM-like MMC are introduced and analyzed. Particularly, how the VSM control algorithm works with the circulating current control in MMCs is presented. An IIT SYNDEM Smart Grid Testbed is built in an aim of achieving a minimize realization of the SYNDEM system. Extensive experiments are done on the system to show the operational scenarios when the proposed active loads are integrated in the system. There are in total eight nodes in the IIT SYNDEM testbed, which contains two utility grids, one AC load, one DC load, two solar farms and two wind farms. All the nodes are connected to a local grid through VSMs, so that they can take part in the local grid regulations in similar ways. The IIT SYNDEM Smart Grid Testbed is described in details and experimental results are provided to show the dynamic and steady performance of the IIT SYNDEM smart grid.
Show less

Title: Machine learning applications to video surveillance camera placement and medical imaging quality assessment
Creator: Lorente Gomez, Iris
Date: 2022
Description: In this work, we used machine learning techniques and data analysis to approach two applications. The first one, in collaboration with the...
Show moreIn this work, we used machine learning techniques and data analysis to approach two applications. The first one, in collaboration with the Chicago Police Department (CPD), involves analyzing and quantifying the effect that the installation of cameras had on crime, and developing a predictive model with the goal of optimizing video surveillance camera location in the streets. While video surveillance has become increasingly prevalent in policing, its intended effect on crime prevention has not been comprehensively studied in major cities in the US. In this study, we retrospectively analyzed the crime activities in the vicinity of 2,021 surveillance cameras installed between 2005 and 2016 in the city of Chicago. Using Difference-in-Differences (DiD) analysis, we examined the daily crime counts that occurred within the fields-of-view of these cameras over a 12-month period, both before and after the cameras were installed. We also investigated their potential effect on crime displacement and diffusion by examining the crime activities in a buffer zone (up to 900 ft) extended from the cameras. The results show that, collectively, there was an 18.6% reduction in crime counts within the direct viewsheds of all of the study cameras (excluding District 01 where the Loop -Chicago's business center- is located). In addition, we adapted the methodology to quantify the effect of individual cameras. The quantified effect on crime is the prediction target of our 2-stage machine learning algorithm that aims to estimate the effect that installing a videocamera in a given location will have on crime. In the first stage, we trained a classifier to predict if installing a videocamera in a given location will result in a statistically significant decrease in crime. If so, the data goes through a regression model trained to estimate the quantified effect on crime that the camera installation will have. Finally, we propose two strategies, using our 2-stage predictive model, to find the optimal locations for camera installations given a budget. Our proposed strategies result in a larger decrease in crime than a baseline strategy based on choosing the locations with higher crime density.The second application that forms this thesis belongs to the field of model observers for medical imaging quality assessment. With the advance of medical imaging devices and technology, there is a need to evaluate and validate new image reconstruction algorithms. Image quality is traditionally evaluated by using numerical figures of merit that indicate similarity between the reconstruction and the original. In medical imaging, a good reconstruction strategy should be one that helps the radiologist perform a correct diagnosis. For this reason, medical imaging reconstruction strategies should be evaluated on a task-based approach by measuring human diagnosis accuracy. Model observers (MO) are algorithms capable of acting as human surrogates to evaluate reconstruction strategies, reducing significantly the time and cost of organizing sessions with expert radiologists. In this work, we develop a methodology to estimate a deep learning based model observer for a defect localization task using a synthetic dataset that simulates images with statistical properties similar to trans-axial sections of X-ray computed tomography (CT). In addition, we explore how the models access diagnostic information from the images using psychophysical methods that have been previously employed to analyze how the humans extract the information. Our models are independently trained for five different humans and are able to generalize to images with noise statistic backgrounds that were not seen during the model training stage. In addition, our results indicate that the diagnostic information extracted by the models matches the one extracted by the humans.
Show less

repository.iit

Search the repository

Pages

Pages