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Title: The role of fibrillar collagen in tissue function
Creator: Ma, Yin
Date: 2020
Description: Fibrillar collagen plays an important role in maintaining soft tissue integrity and providing chemical and physical cues for cell fate...
Show moreFibrillar collagen plays an important role in maintaining soft tissue integrity and providing chemical and physical cues for cell fate decisions. Collagen remodeling, which alternates the amount, distribution, and biomechanics of collagen, primarily type I (COLI) and type III (COLIII), can change tissue properties. This process is essential not only in biological developments but also in pathological processes. Thus, it is meaningful to understand the correlation between collagen remodeling and tissue dysfunction and investigate the cells' response to fibrous protein matrices. However, current studies in biochemical analysis of collagen and biomechanical study of tissues were carried out at different scales. So it is hard to correlate the data to draw solid conclusions. In this thesis research, we used two collagen disorder associated pathological conditions, pelvic organ prolapse (POP) and micropapillary serous carcinoma (MPSC) of the fallopian tube, as models to unravel the correlation between tissue dysfunctions and the impaired microenvironment relevant to the composition, nanostructure, and biomechanics of a collagen fibril. In the case of POP, we found the collagen fibers in tissues of POP patients were less abundant but stiffer than those of non-POP individuals, implying a loose and fragile matrix that is weakly integrated with other components of the connective tissue to provide adequate support of the pelvic organs. On the other hand, the collagen D-period, the characteristic banding feature which signals the proper assembly of collagen molecules, decreased in POP tissues. We surmised that the molecular level changes of collagen in POP were accountable for the weak matrix mechanics, verified by a systematic in vitro study. We also examined the collagen matrix alternation in MPSC of the fallopian tube, which is thought to cause ovarian cancer via metastasis. Since cancer metastasis is often related to collagen remodeling, we examined the collagen matrix alternation in this disease. We observed the heterogeneous distribution of COLI and COLIII in the papillae of the tumor tissue. Noticeably, COLI was accumulated at the papillae tip, whereas COLIII was dominant at the papillae base. We also observed the absence of collagen matrix between the micropapillary tip and the fibrosis base. Such an uneven collagen distribution implies that the matrix exerted distinctive forces on the tumor cells to regulate their behaviors, including cell migration, directional growth, and shedding from the primary tumor to initiate metastasis. These conclusions have been supported by the results of our in vitro experiments. In investigating the effect of the microenvironment on cell behavior, we established and validated an AFM-based method to collect and quantitatively analyze the mRNA samples from targeted live cells at the single-cell level. This method overcomes issues, such as severe cell damage or even cell death, the capability of time-dependent and in situ analyses, in current methods. The application of the method in studying heterogeneous gene expression in single cells and the interaction between cancer cells and cancer-associated fibroblasts was demonstrated. We also demonstrated that this method can be potentially used to quantitatively analyze the gene expression level changes in a targeted cell in response to the microenvironment.
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Title: NON-DESTRUCTIVE CANCER DETECTION IN LYMPH NODE USING PAIRED-AGENT MOLECULAR IMAGING
Creator: Li, Chengyue
Date: 2020
Description: Identification of cancer spread to tumor-draining lymph nodes through lymph node dissection and histology offers critical information for...
Show moreIdentification of cancer spread to tumor-draining lymph nodes through lymph node dissection and histology offers critical information for guiding treatment in many cancer types, including breast, melanoma, head and neck, lung and gynecologic cancers, as the lymphatic system serves as the primary route for metastasis. Lymph node biopsy involves localization of tumor-draining lymph nodes, followed by their surgical removal and histological assessment. However, the procedure is associated with overtreatment concerns and some considerable morbidity, including lymphedema, seroma formation, and restricted arm movement. Moreover, conventional histological analyses are time-consuming and laborious, yet pathologists generally examine less than 1% of the volume of each lymph node, leading to undetected micrometastasis (tumor clusters 0.2-2mm in diameter) in 30-60% of cases. In response to these limitations in standard lymph node dissection protocol, there is a significant need for the development of lymph node imaging strategies that are capable of identifying metastatic cancer as a means of staging a patient’s cancer without the need for invasive and time-intensive conventional pathology. Paired-agent imaging molecular imaging protocols have been spearheaded by our group and entail co-administration of a control imaging agent with a molecular targeted agent as a way to account for nonspecific uptake and retention. The overall goal of my thesis was to methodically design, optimize and evaluate the clinical utility of a paired-agent lymph node imaging protocol to achieve levels of sensitivity and specificity in nodal staging not possible with current conventional methods, less invasively and at a fraction of the time and cost.
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Title: AMPLIFICATION AND PURIFICATION OF RECOMBINANT PRO-DEATH BAXΔ2 PROTEINS FOR STRUCTURE ANALYSIS
Creator: Zhou, Yi
Date: 2020
Description: BaxΔ2 is an isoform of the pro-apoptotic Bax family of proteins, which is an important anti-cancer protein. BaxΔ2 behaves differently from...
Show moreBaxΔ2 is an isoform of the pro-apoptotic Bax family of proteins, which is an important anti-cancer protein. BaxΔ2 behaves differently from Baxα to induce apoptosis. The current computationally predicted model of BaxΔ2 is based on known Baxα structure, which is considered biased. Therefore, the elucidation of the BaxΔ2 crystal structure is critical. The goal of this project was to obtain a sufficient amount of purified recombinant Bax∆2 protein for crystallization. We cloned full-length BaxΔ2 fused with a poly-histidine tag on either N-terminus (His-Bax∆2) or C-terminus (Bax∆2-His) into an inducible bacterial expression vector. We found that His-Bax∆2 proteins were expressed better than Bax∆2-His, which totally inhibit host growth. However, the protein concentration of His-Bax∆2 was still too low to be detected by Coomassie blue staining. To increase His-Bax∆2 expression and avoid cytotoxicity, we further tested different bacterial host cells and applied the chaperone system. However, all attempts could not overcome Bax∆2 cytotoxicity and the protein expression levels were not high enough to be feasible for further large-scale purification. The mechanism underlying how Bax∆2 inhibits bacterial growth is still a mystery because Bax∆2 eukaryotic targets (mitochondria and caspases) do not exist in bacteria. Further experiments are required to explore the mechanism of Bax∆2 cytotoxicity in bacteria, so as to finally optimize and elevate the BaxΔ2 protein yields.
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Title: Transactive Energy Market for Electric Vehicle Charging Stations in Constrained Power and Transportation Networks
Creator: Affolabi, Larissa Arielle Sèfiath
Date: 2023
Description: In response to the urgent need for decarbonization, our society is actively working towards reducing carbon emissions across various sectors....
Show moreIn response to the urgent need for decarbonization, our society is actively working towards reducing carbon emissions across various sectors. These efforts have resulted in the widespread adoption of distributed energy resources (DERs) in the electricity sector and the widespread adoption of electric vehicles (EVs) in the transportation sector. The growing popularity of EVs has resulted in rapid growth of charging infrastructure to meet the increasing demand. Recently, combined efforts across those two sectors have gained popularity with the deployment of EV charging stations (EVCSs) with on-site DERs like solar photovoltaic and/or battery energy storage systems not only to defer or avoid the need for power distribution equipment upgrades but also to achieve more environmentally friendly outcomes in terms of decarbonization goals. To increase transportation electrification, we need to expand further the charging infrastructure. The key challenge lies in accelerating charging station deployment while ensuring the safe and efficient operation of the power distribution system where most of this new load will be concentrated. Numerous research efforts have been dedicated to the study of EVCSs, with a focus on either optimizing the pricing of charging services or addressing the energy management challenges from the perspective of system operators. While these aspects are crucial, it is essential to recognize the importance of attracting private sector stakeholders to invest in and support the expansion of the EVCS network. Relying solely on subsidies is insufficient to finance the necessary scale of EVCS deployment required to accelerate the widespread adoption of EVs. The increasing adoption of EVCSs integrated with on-site DERs highlights the potential for Transactive Energy Market (TEM) operations among EVCSs. However, unlike regular prosumers, EVCS operations are uniquely influenced by both the power distribution and the transportation networks. In light of this issue, this dissertation proposes several multi-agent frameworks that leverage on-site DERs at EVCSs to establish a secondary revenue stream through a TEM. This dissertation investigates the technical and economic aspects of these multi-agent frameworks. At its core, we propose two holistic frameworks to solve the energy management problem of EVCSs within a TEM environment. Modeled as independent profit-driven entities, each EVCS optimally schedules its operation based on the day-ahead traffic assignment problem solved by the traffic operator agent. For the TEM clearing process, we propose two distinct lines of approach. First, a centralized approach where a single entity assumes both the market operator and grid operator functions. This integrated approach streamlines the decision-making process and ensures coordinated operations between the market and the power grid. Second, a decentralized approach, where separate entities take on the roles of the market operator and grid operator, respectively. This decentralized structure allows for more flexibility and distributed decision-making within the TEM. Furthermore, in contrast to many TEM related studies that overlook the complexity of the power distribution system, we introduce a comprehensive three-phase unbalanced optimal power flow model. This model incorporates features such as network reconfiguration and tap changers, allowing for a more accurate representation and understanding of the power distribution system's operation. Various case studies are used to prove the effectiveness of our proposed lines of approach to EVCSs’ day-ahead energy management problem.
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Title: Unraveling the Factors Affecting Virus Adhesion to Food Contact Materials and Virus-Virus Interaction – A Nanoscopic Study
Creator: Guo, Ao
Date: 2020
Description: Food safety is a worldwide issue nowadays since pathogens cause diseases, even death. Human enteric viruses are a major cause of non-bacterial...
Show moreFood safety is a worldwide issue nowadays since pathogens cause diseases, even death. Human enteric viruses are a major cause of non-bacterial foodborne gastroenteritis. In the United States, they are the most life-threatening pathogenic agents for the foodborne illnesses. The fecal-oral route is responsible for the attachment and transmission of such foodborne pathogens, which lead to contamination of food-contact materials (FCMs) during food preparation, enhancing the risk of transmission. The interaction between viruses and contact surface is the source of virus adhesion.Due to lack of knowledge on virus adhesion to various FCMs, this thesis aims to reveal the key factors that mediate the virus-FCM and virus-virus interactions in order to effectively prevent virus infection or spread. The objectives are (1) to identify the physical and chemical features of a material surface that affect virus adhesion to determine an optimal FCM, (2) to reduce virus adhesion via nanofabrication of a material’s surface; (3) to investigate the effect of thermal inactivation (heat treatment) on virus-virus interaction toward the establishment of a non-culture-based infectivity assay for laboratory assessment of the effectiveness of disinfection methods. In this study, virus adhesion on various FCMs, including glass, polyvinyl chloride (PVC), polyethylene (PE) and graphite which have been widely used in food storages, food packages and utensil handling during food preparations, was investigated. Male-specific coliphage (MS2) was used as a virus surrogate of the highly infectious human enteric virus with similar physiochemical properties. Atomic force microscopy (AFM) was predominantly used in quantitative analyses of the strength of MS2 adhesion to various food-contact surfaces. Dynamic light scattering (DLS) was applied in MS2 dimensional analysis in aqueous suspension. Moreover, surface modification, such as nanofabrication, was employed to create controllable surface textures to reduce virus adhesion on FCM. Thermal inactivation was employed as a disinfection method. A comparative study was carried out to differentiate the active and inactivated MS2 in the virus-FCM and the virus-virus interactions. The results of this examination indicate that a material’s surface property, such as topography, hydrophobicity and surface charge, contributed to virus adhesion in aqueous phase at neutral pH (=7.4). Each surface feature played a distinctive role; however, the combined effect as well as the chemical signature of a virion’s surface determined the virus-FCM interaction. A delicate control of a surface’s chemical affinity and physical feature is expected to effectively reduce/interfere virus adhesion. It was also discovered that thermally inactivated MS2 particles became larger, softer, and more hydrophobic. These properties can be utilized in developing a non-culture-based assay to assess the effectiveness of disinfection methods for human enteric viruses, which can hardly be cultured in laboratory.
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Title: BIG DATA AS A SERVICE WITH PRIVACY AND SECURITY
Creator: Hou, Jiahui
Date: 2020
Description: With the increase of data production sources like IoT devices (e.g., smartwatches, smartphones) and data from smart home (health sensor,...
Show moreWith the increase of data production sources like IoT devices (e.g., smartwatches, smartphones) and data from smart home (health sensor, energy sensors), truly mind-boggling amounts of data are generated daily. Building a big data as a service system, that combines big data technologies and cloud computing, will enhance the huge value of big data and tremendously boost the economic growth in various areas. Big data as a service has evolved into a booming market, but with the emergence of larger privacy and security challenges. Privacy and security concerns limit the development of big data as a service and increasingly become one of the main reasons why most data are not shared and well utilized. This dissertation aims to build a new incrementally deployable middleware for the current and future big data as a service eco-system in order to guarantee privacy and security. This middleware will retain privacy and security in the data querying and ensure privacy preservation in data analysis. In addition, emerging cloud computing contributes to providing valuable services associated with machine learning (ML) techniques. We consider privacy issues in both traditional queries and ML queries (i.e., ML classification) in this dissertation. The final goal is to design and develop a demonstrable system that can be deployed in the big data as a service system in order to guarantee the privacy of data/ service owners as well as users, enabling secure data analysis and services.Firstly, we consider a private dataset composed of a set of individuals, and the data is outsourced to a remote cloud server. We revisit the classic query auditing problem in the outsourcing scenario. Secondly, we study privacy preserving neural network classification where source data is randomly partitioned. Thirdly, we concern the privacy of confidential training dataset and models which are typically trained in a centralized cloud server but publicly accessible, \ie online ML-as-a-Service (MLaaS). Lastly, we consider the offline MLaaS systems. We design, implement, and evaluate a secure ML framework to enable MLaaS on clients' edge devices, where a ``encrypted'' ML models are stored locally.
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Title: LOW-DOSE CARDIAC SPECT USING POST-FILTERING, DEEP LEARNING, AND MOTION CORRECTION
Creator: Song, Chao
Date: 2019
Description: Single photon emission computed tomography (SPECT) is an important technique in use today for the detection and evaluation of coronary artery...
Show moreSingle photon emission computed tomography (SPECT) is an important technique in use today for the detection and evaluation of coronary artery diseases. The image quality in cardiac SPECT can be adversely affected by cardiac motion and respiratory motion, both of which can lead to motion blur and non-uniform heart wall. In this thesis, we mainly investigate imaging de-noising algorithms and motion correction methods for improving the image quality in cardiac SPECT on both standard dose and reduced dose.First, we investigate a spatiotemporal post-processing approach based on a non-local means (NLM) filter for suppressing the noise in cardiac-gated SPECT images. Since in recent years low-dose studies have gained increased attention in cardiac SPECT owing to its potential radiation risk, to further improve the image quality on reduced dose, we investigate a novel de-noising method for low-dose cardiac-gated SPECT by using a three dimensional residual convolutional neural network (CNN). Furthermore, to reduce the negative effect of respiratory-binned acquisitions and assess the benefit of this approach in both standard dose and reduced dose using simulated acquisitions. Inspired by the success in respiratory correction, we investigate the potential benefit of cardiac motion correction for improving the detectability of perfusion defects. Finally, to combine the benefit of above two types of motion correction, dual-gated data acquisitions are implemented, wherein the acquired list-mode data are further binned into a number of intervals within cardiac and respiratory cycle according to the electrocardiography (ECG) signal and amplitude of the respiratory motion.
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Title: Analysis of High-Fidelity Experiments and Simulations of the Flow in Simplified Urban Environments
Creator: Stuck, Maxime
Date: 2020
Description: The mean ﬂow and turbulence statistics of the ﬂow through a simpliﬁed urban environment, which is an active research area in order to improve...
Show moreThe mean ﬂow and turbulence statistics of the ﬂow through a simpliﬁed urban environment, which is an active research area in order to improve the knowledge of turbulent ﬂow in cities, is investigated. This is useful for civil engineering, pedestrian comfort and for health concerns caused by pollutant spreading. In this work, we provide analysis of the turbulence statistics obtained both from highly-quality stereoscopic particle image-velocimetry (SPIV) measurements (from Monnier et al.) and well-resolved large eddy simulations (LES) by Torres et al. A detailed comparison of both databases reveals the impact of the geometry of the urban array on the ﬂow characteristics and provides for a good description of the turbulent features of the ﬂow around a simpliﬁed urban environment. The most prominent features of this complex ﬂow include coherent vortical structures such as the so-called arch vortex, the horseshoe vortex, or the roof vortex. These structures of the ﬂow have been identiﬁed by an analysis of the turbulence statistics. The inﬂuence of the geometry of the urban environment (and particularly the street width and the building height) on the overall ﬂow behavior has also been studied.
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Title: INTELLIGENT SOLID STATE CIRCUIT BREAKERS USING WIDE BANDGAP SEMICONDUCTORS
Creator: Zhou, Yuanfeng
Date: 2021
Description: Electricity, in its predominant form of alternating current (AC), is at the heart of modern civilization. However, direct current (DC)...
Show moreElectricity, in its predominant form of alternating current (AC), is at the heart of modern civilization. However, direct current (DC) electricity is re-emerging, offering higher transmission efficiency, better system stability, better match with modern electrical loads, and easier integration of renewable and storage resources than AC. DC power is gaining tractions in HVDC or MVDC grids, DC data centers, photovoltaic farms, EV charging infrastructures, shipboard, and aircraft power systems. However, DC fault protection remains a major challenge. Interruption of DC currents is extremely difficult due to the lack of current zero crossings which are naturally available in AC power systems. Conventional mechanical breakers only offer a very limited DC current interruption capability even after significant power derating. Hybrid circuit breakers (HCBs) offers a relatively low conduction loss but a response time too slow to protect many low-impedance DC grids. Solid state circuit breakers (SSCBs) can quickly interrupt a DC fault current within tens of microseconds but suffer from high conduction losses. Furthermore, it is generally difficult for an SSCB to distinguish between a short circuit fault and a normal inrush current condition during the start-up of a capacitive load.The purpose of this thesis is to develop a tri-mode, intelligent solid-state circuit breaker technology using wide bandgap semiconductors (especially Gallium Nitride transistors), referred to as iBreaker. The iBreaker design methodology includes the use of mΩ-resistance GaN and SiC devices, new circuit topology and control techniques beyond the commonly used ON/OFF switch configuration, and integration of intelligent functions without increasing component count. The iBreaker adopts a distinct pulse width modulation (PWM) current limiting (PWM-CL) state in addition to the conventional ON and OFF states to facilitate soft startup, fault authentication, and fault location functions. Key design elements, such as use of wide bandgap (particularly GaN) switches, tri-mode operation, combined digital and analog control, the bidirectional buck topology, variable PWM frequency control and universal hardware/software architecture, are discussed in detail. Multiple iBreaker prototypes, rated at 380 V/20 A and 1000 V/10 A, respectively, are built and tested to validate the proposed SSCB design concept. 99.95% transmission efficiency, passive cooling, and μs-scale response time are demonstrated experimentally.
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Title: Systematic Serendipity: A Study in Discovering Anomalous Astrophysics
Creator: Giles, Daniel K
Date: 2020
Description: In the present era of large scale surveys, big data presents new challenges to the discovery process for anomalous data. Advances in astronomy...
Show moreIn the present era of large scale surveys, big data presents new challenges to the discovery process for anomalous data. Advances in astronomy are often driven by serendipitous discoveries. Such data can be indicative of systematic errors, extreme (or rare) forms of known phenomena, or most interestingly, truly novel phenomena which exhibit as-of-yet unobserved behaviors. As survey astronomy continues to grow, the size and complexity of astronomical databases will increase, and the ability of astronomers to manually scour data and make such discoveries decreases. In this work, we introduce a machine learning-based method to identify anomalies in large datasets to facilitate such discoveries, and apply this method to long cadence light curves from NASA's Kepler Mission. Our method clusters data based on density, identifying anomalies as data that lie outside of dense regions in a derived feature space. First we present a proof-of-concept case study and we test our method on four quarters of the Kepler long cadence light curves. We use Kepler's most notorious anomaly, Boyajian's Star (KIC 8462852), as a rare `ground truth' for testing outlier identification to verify that objects of genuine scientific interest are included among the identified anomalies. Additionally, we report the full list of identified anomalies for these quarters, and present a sample subset of identified outliers that includes unusual phenomena, objects that are rare in the Kepler field, and data artifacts. By identifying <4% of each quarter as outlying data, under 6k individual targets for the dataset used, we demonstrate that this anomaly detection method can create a more targeted approach in searching for rare and novel phenomena.We further present an outlier scoring methodology to provide a framework of prioritization of the most potentially interesting anomalies. We have developed a data mining method based on k-Nearest Neighbor distance in feature space to efficiently identify the most anomalous light curves. We test variations of this method including using principal components of the feature space, removing select features, the effect of the choice of k, and scoring to subset samples. We evaluate the performance of our scoring on known object classes and find that our scoring consistently scores rare (<1000) object classes higher than common classes, meaning that rarer objects are successfully prioritized over common objects. The most common class, categorized as miscellaneous stars without any major variability, and rotational variables compose well over two-thirds of the KIC, yet are considerably underrepresented in the top outliers. We have applied scoring to all long cadence light curves of quarters 1 to 17 of Kepler's prime mission and present outlier scores for all 2.8 million light curves for the roughly 200k objects.
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Title: Defense-in-Depth for Cyber-Secure Network Architectures of Industrial Control Systems
Creator: Arnold, David James
Date: 2024
Description: Digitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To...
Show moreDigitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To achieve these gains, the Internet of Things (IoT) has become an integral component of network infrastructures. However, integrating embedded devices expands the network footprint and softens cyberattack resilience. Additionally, legacy devices and improper security configurations are weak points for ICS networks. As a result, ICSs are a valuable target for hackers searching for monetary gains or planning to cause destruction and chaos. Furthermore, recent attacks demonstrate a heightened understanding of ICS network configurations within hacking communities. A Defense-in-Depth strategy is the solution to these threats, applying multiple security layers to detect, interrupt, and prevent cyber threats before they cause damage. Our solution detects threats by deploying an Enhanced Data Historian for Detecting Cyberattacks. By introducing Machine Learning (ML), we enhance cyberattack detection by fusing network traffic and sensor data. Two computing models are examined: 1) a distributed computing model and 2) a localized computing model. The distributed computing model is powered by Apache Spark, introducing redundancy for detecting cyberattacks. In contrast, the localized computing model relies on a network traffic visualization methodology for efficiently detecting cyberattacks with a Convolutional Neural Network. These applications are effective in detecting cyberattacks with nearly 100% accuracy. Next, we prevent eavesdropping by applying Homomorphic Encryption for Secure Computing. HE cryptosystems are a unique family of public key algorithms that permit operations on encrypted data without revealing the underlying information. Through the Microsoft SEAL implementation of the CKKS algorithm, we explored the challenges of introducing Homomorphic Encryption to real-world applications. Despite these challenges, we implemented two ML models: 1) a Neural Network and 2) Principal Component Analysis. Finally, we hinder attackers by integrating a Cyberattack Lockdown Network with Secure Ultrasonic Communication. When a cyberattack is detected, communication for safety-critical elements is redirected through an ultrasonic communication channel, establishing physical network segmentation with compromised devices. We present proof-of-concept work in transmitting video via ultrasonic communication over an Aluminum Rectangular Bar. Within industrial environments, existing piping infrastructure presents an optimal solution for cost-effectively preventing eavesdropping. The effectiveness of these solutions is discussed within the scope of the nuclear industry.
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Title: DEFAULT RISK AND MOMENTUM PREMIUM
Creator: Zhang, Yi
Date: 2022
Description: Birge and Zhang (2018) reported that combining common factors models with functions of the default risk improves models' performance to...
Show moreBirge and Zhang (2018) reported that combining common factors models with functions of the default risk improves models' performance to explain stock returns. Default risk contains firm specific information and may help to explain momentum premium that compensates investors for the firm specific risk exposures. In this paper, we confirmed that the forward-looking measure of default risk, as proposed by Birge and Zhang (2018), seems to capture some pricing information in the momentum premium. This provides an alternative to explain the underlying risks associated with the momentum strategy.
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Title: ENVIRONMENTAL AND SOCIAL SUSTAINABILITY IMPLICATIONS OF DOWNTOWN HIGH-RISE VS. SUBURBAN LOW-RISE LIVING: A CHICAGO CASE STUDY
Creator: Du, Peng
Date: 2015, 2015-12
Description: This research is focused on quantitatively investigating and comparing the environmental and social sustainability of people’s lifestyles in...
Show moreThis research is focused on quantitatively investigating and comparing the environmental and social sustainability of people’s lifestyles in terms of embodied energy, operational energy use, and overall satisfaction with their quality of life in both downtown high-rise and suburban low-rise living using Chicago, IL and a surrounding suburban area of Oak Park, IL as a case study. Specifically, in both cases, the study seeks to evaluate factors such as the embodied energy of the materials that comprise buildings in each location; the predicted and actual monthly energy consumption of the homes; travel via all modes of transport including automobile, public transport, walking, and biking; and the embodied and operational energy of the infrastructure to support each mode of transportation. In addition, this research also engages with the individual building occupants, including single individuals, couples, and families, in a large subset of downtown and suburban Chicago households to directly evaluate perceptions of their life satisfaction and sense of community, which offers a unique direct comparison between dense high-rise and suburban low-rise living. The findings of the study show that downtown high-rise living in Chicago accounts for approximately 58% more life-cycle energy per person per year than Oak Park low-rise living, on average, contrary to some common beliefs (best estimates were ~260 and ~165GJ/person/year, respectively). Building operational energy was estimated to be the single largest contributor of the total life-cycle energy in both the downtown high-rise and suburban low-rise cases, followed by vehicle OE. The findings of the study also show that downtown high-rise residents were associated with higher life satisfaction than suburban low-rise residents when controlling for demographic differences in the research sample. Residence type was not found to be associated with sense of community when controlling for demographic differences, and the factor that was found to be significantly associated with sense of community was household size in the research sample. Also, accessibility and safety were found as the strongest predictors of overall residential environment for individuals.
Ph.D. in Architecture, December 2015
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Title: OBJECT DETECTION AND VISUAL TRACKING SYSTEM
Creator: Kumar Moosad, Aditya Uday
Date: 2013, 2013-12
Description: The aim of the project is to design visual object detection and target tracking system. Such a system has been extensively used in military...
Show moreThe aim of the project is to design visual object detection and target tracking system. Such a system has been extensively used in military applications, but these days they find use in the civilian domain too, such as fault detection, geological surveys, remote sensing and domestic policing. Object detection and target tracking systems find use in robots and unmanned vehicles. In order to navigate and perform various operations on its own, these vehicles need to have intelligence. Therefore, developing an algorithm that would enable the robotic device to act on its own and make necessary changes to its trajectory would be a major breakthrough. Many algorithms have been developed to achieve this objective but they usually run in a pre-defined environment. In this project it is assumed that the environment is unknown and the drone has only visual data obtained by its frontend camera. The algorithm for object detection is based on the concept of determining image contours and utilizing the principle of image moments. Contours help detect the object and moment of the object is used to determine its size and therefore, its distance from camera. The algorithm for tracking has been developed using the Shi Tomasi algorithm for corner point detection and the pyramidal Lucas- Kanade optical flow algorithm to determine the motion vectors of the corner points. This is followed by the calculation of the local scale variance of these points and then estimating the time to collision. With these results the robotic device would be in a position to change its direction or trajectory. Therefore this algorithm performs real-time image processing of visual data provided by the drone and gives some kind of visual intelligence to the drone.
M.S. in Electrical Engineering, December 2013
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Title: EFFECTS OF CHROMIUM COMPOUNDS ON INSULIN-MEDIATED GLUCOSE UPTAKE
Creator: Yang, Liu
Date: 2012-04-13, 2012-05
Description: Chromium supplementation has been highlighted by its biological function in improvement of glucose metabolism. As essential trace nutrition,...
Show moreChromium supplementation has been highlighted by its biological function in improvement of glucose metabolism. As essential trace nutrition, chromium complex has great therapeutic potential in the alleviation of metabolic disorders, especially type II diabetes. This study is aimed at investigating the effect of two newly synthesized chromium (III) complexes Cr2(μ-OH)2(C4O4)2(H2O)4·(H2O)2, Cr2(μ-OH)2(μ1,2- C4O4)2(C2H6SO)4·(H2O)2 in comparison with a commercial compound CrCl3·6H2O on glucose uptake, as well as toxicity. We found that with 100 nM insulin stimulus, Cr2(μ- OH)2(C4O4)2(H2O)4·(H2O)2 significantly increased cellular glucose uptake, while Cr2(μ- OH)2(μ1,2-C4O4)2(C2H6SO)4·(H2O)2 inhibited the insulin-stimulated glucose uptake. Morphology study indicated that a relatively low concentration of these three complexes had little toxicity to cells within 24 h, but a higher concentration would lead to cell death. Cell growth curve supported the notion that the chromium (III) compounds in this study had no obvious cellular toxicity. Therefore, these results suggest that the newly synthesized less toxic chromium has a great potential in improvement of glucose metabolism in response to insulin. This study may provide valuable information in the treatment or management of diabetes. Keywords: Chromium, Insulin, Glucose uptake, Glucose metabolism, diabetes, type II diabetes
M.S. in Biology, May 2012
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Title: EFFICIENCY OF PATENT CONTRACTS
Creator: Liang, Shao-huai
Date: 2014, 2014-05
Description: This thesis attempts to analyze the incentive compatible (IC) region for the royalty contract in an innovation context. It also describes the...
Show moreThis thesis attempts to analyze the incentive compatible (IC) region for the royalty contract in an innovation context. It also describes the contracts that induce the licensee and the patentee to obtain the maximum pro t when using this licensing contract. We analyze the IC region for cost-reducing innovations " and royalty ratios in two situations: the non-drastic innovation and the drastic innovation. We also nd when licensing occurs, there is an e ciency loss. However, the IC region can limit the e ciency loss. Then, we extend our results to a two-stage game in order to check whether the royalty contract is still a good contract for both the licensee and the patentee from a pro t perspective. In stage two, when the size of innovation is smaller than the size of innovation in stage one, royalty contracts are inferior to other contracts. However, when the size of innovation in stage two is greater than that in stage one, the royalty contract is an improvement over other contracts.
PH.D in Management Science, May 2014
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Title: MICRO-SCALE EHD CONDUCTION-DRIVEN PUMPING AND HEAT TRANSFER ENHANCEMENT IN SINGLE- AND TWO-PHASE SYSTEMS
Creator: Pearson, Matthew
Date: 2011-04-19, 2011-05
Description: Electrohydrodynamic (EHD) pumping methods rely on the interaction between electric fields and the flow fields of a dielectric fluid....
Show moreElectrohydrodynamic (EHD) pumping methods rely on the interaction between electric fields and the flow fields of a dielectric fluid. Conduction pumping is one EHD pumping mechanism, which offers many advantages over other EHD pumping methods (for example, a simple design, no degradation of the working fluid, and no need for a temperature gradient). Conduction pumping can be used in an adiabatic context to pump a working fluid or it can be applied to deliver substantial enhancement to single- and two-phase heat transfer processes. Experimental studies of conduction pumping to date have focused on macro-scale devices with applied voltages on the order of 10 kV. However, like many other EHD concepts, conduction pumping depends primarily on the intensity of the imposed electric field. Therefore, at the micro-scale, the reduced physical size can be accompanied by a reduction in the magnitude of the applied voltage to levels that are significantly more manageable. Furthermore, the simplicity of EHD conduction pumps, such as the lack of moving parts, high reliability, and physical compactness, make them an attractive method for pressure generation in micro-scale fluid and heat transfer devices. This experimental study examines the fundamental behavior and performance of EHD conduction pumping at the micro-scale. The pump is embedded in a rectangular, adiabatic micro-channel, and the single-phase flow and pressure generation of the pump are characterized. The EHD pumping of single- and two-phase flows in micro-channels in the presence of heat transfer is also studied and the corresponding enhancement to single- and two-phase heat transfer is quantified. In an additional study, micro-scale electrodes are embedded within a flat, heated surface to examine the ability of the conduction pump to provide electrically-enhanced wetting of the heated surface during pool boiling. A model based on hydrodynamic instability theory is generated to quantify the influence of the EHD conduction pumping on the pool boiling critical heat flux. Finally, this technology is incorporated into two unique, novel, heat transport devices akin to a heat pipe but in which the primary driving force for the liquid is conduction pumping, not capillarity.
Ph.D. in Mechanical and Aerospace Engineering, May 2011
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Title: OPTIMAL ROUTING ALGORITHMS IN ENERGY-HARVESTING WIRELESS SENSOR NETWORKS
Creator: Martinez, Gina
Date: 2014, 2014-12
Description: Harnessing energy from environmental sources such as solar and wind is an attractive solution to the critical energy limitation problem in...
Show moreHarnessing energy from environmental sources such as solar and wind is an attractive solution to the critical energy limitation problem in wireless sensor networks. Energy harvesting can potentially provide the network with perpetual and sustainable operation, or it can prolong network lifetime even for high consumption applications so as to justify the high cost of deployment. However, in order to efficiently utilize harvested energy, the energy source dynamics need to be incorporated into the network design. One way to do so is to make the network layer routing algorithm energy-harvest-aware. One common property of environmental energy sources is that they are generally only intermittently available. To address this, a storage unit such as a rechargeable battery can be introduced into the system. However, this is only a partial solution due to finite buffer storage capacities that cause harvested energy to be wasted when full. In this work, we aim to maximize the network lifetime by optimizing the energy availability and consumption alignment. To realize this objective, we first show that the minimization of energy wastage is a necessary condition to the maximization of available network energy. We then propose an on-demand routing algorithm that maximizes the total residual network energy by minimizing the energy consumption and wastage. Next, we illustrate the tradeoff between the two objectives of maximizing the total network energy and maximizing the minimum network energy in prolonging network lifetime. Then, we propose a linear-programming routing solution that maximizes a utility objective function based on this tradeoff. Although these routing approaches are shown to achieve high energy utilization, they are still based on deterministic harvest and consumption models. In the last part of this work, we propose a routing algorithm by applying the Semi-Markov Decision Process. Using this method, we are able to incorporate a comprehensive consideration of stochastic solar availability and traffic models, heterogeneous network properties such as non-uniform energy buffer capacities and consumption rates, and the optimization of an analytical formulation for network lifetime.
Ph.D. in Electrical and Computer Engineering, December 2014
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Title: COORDINATION OF STORAGE WITH RENEWABLE ENERGY RESOURCES IN POWER SYSTEMS
Creator: Khodayar, Mohammad Esmaeil
Date: 2012-07-16, 2012-07
Description: The ever-increasing penetration of variable wind energy in power systems affects the hourly dispatch of thermal power generation in...
Show moreThe ever-increasing penetration of variable wind energy in power systems affects the hourly dispatch of thermal power generation in electricity markets. The coordination of wind power generation units with pumped-storage hydro (PS) generation could relieve the variability of wind energy and increase its hourly dispatchability. In this dissertation, a coordination methodology for wind and pumped-storage hydro (PS) units in the dayahead operation planning of power systems is proposed. With coordination, the PS unit can offset intrahour wind energy imbalances (i.e., deviations from hourly schedules) and minimize wind energy curtailments. The wind-PS coordination based on the application of stochastic security-constrained unit commitment (Stochastic SCUC) is evaluated in which, the hourly bus- level coordinated scheduling of wind energy and PS is compared with the system-level coordinated operation strategies in the day-ahead scheduling of power systems. Volatility of wind generation can also reduce the profit in day-ahead market by imposing potential imbalance charges in a generating company (GENCO). The dayahead price-based scheduling strategy for the coordination of wind and storage units in a GENCO is proposed based on the stochastic price-based unit commitment (PBUC) which considers volatilities in day-ahead intra-hour market prices and wind power generation when scheduling wind and storage units. The increased utilization of Plugin Electric Vehicles (PEVs), which consume electricity rather than fossil fuel for driving, offers unique economic and environmental opportunities, and brings out new challenges to electric power system operation and planning. The proposed approach evaluates the effect of integrating a large number of electric vehicles (EVs) on power grid operation and control. The coordinated integration of aggregated PEV fleets and renewable energy sources (wind energy) in power systems is studied by stochastic security-constrained unit commitment (Stochastic SCUC) model, which minimizes the expected grid operation cost while considering the random behavior of the many PEVs. Finally, the role of high reliability distribution system (HRDS) in microgrid operations is evaluated. HRDS, which offers a higher operation reliability and fewer outages in microgrids, is applied to looped networks in distribution systems. The storage system would enhance the microgrid reliability while offering hourly ancillary services and demand response for reducing operation costs. The HRDS implemented at Illinois Institute of Technology (IIT) is used as a case study along with the local DER to increase the load point reliability and decrease the operation cost of the microgrid.
Ph.D. in Electrical Engineering, July 2012
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Title: A SYSTEMS APPROACH TO MINIMIZE PESTICIDE HAZARDS ASSOCIATED WITH FRESH VEGETABLES
Creator: Kalle, Niranjan
Date: 2011-07-27, 2011-07
Description: Pesticides are used in agriculture for eradicating pests and to increase the yield and productivity crops. These pesticides show much effect...
Show morePesticides are used in agriculture for eradicating pests and to increase the yield and productivity crops. These pesticides show much effect on health of humans. There are different types of pesticides such as Insecticides, Herbicides, Fungicides and Pyrethroids. While there is a benefit for the use of pesticides, there can be a negative impact to human health. Exposure to these pesticides from ingestion or oral intake is the most common route of pesticide exposure. Removal of these pesticides from fruits and vegetables would lower the exposure and risk to human health from these pesticides. The objective of this research is to study the effectiveness of various washing methods for the reduction of pesticide residues from fresh fruits and vegetables. Samples of cherry tomatoes were treated with pesticide formulation of 120ppm which is prepared by mixing 6 pesticides (Bifenthrin, Chlorothalonil, Cyhalothrin, Cypermethrin, Malathion and Permethrin). Treated tomatoes were washed with solutions (water, Sodium hypochloride (80ppm), Peroxy acetic acid(80ppm), and Tween20(0.1%)). Ultrasonicator is used as a tool for washing along with the washing solvents. The % reduction of pesticides was determined by extracting the sample through QuECHERS (AOAC 2007.01) method and analyzed by using GC-MS and LC-MS/MS. The analysis of pesticide residues extracted from tomato samples by GC-MS and LC-MS/MS showed a significant reduction in pesticides when washed with peroxy acetic acid compared to sodium hypochlorite and Tween20. Washing with ultrasonicator in combination with washing solvents showed 10% more reduction than washing alone with solutions.
M.S. in Food Safety and Technology, July 2011
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