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Title: SALMONELLA SURVIVAL AND TRANSCRIPTOMIC RESPONSE ON FRESH-CUT CANTALOUPE FLESH WITH AND WITHOUT ORGANIC ACID PRETREATMENT
Creator: Zhou, Xinyi
Date: 2020
Description: Outbreaks of Salmonella enterica associated with fresh-cut melons are becoming more frequent in recent years. Antimicrobial activity of...
Show moreOutbreaks of Salmonella enterica associated with fresh-cut melons are becoming more frequent in recent years. Antimicrobial activity of organic acids on fresh-cut melons have been previously studied. However, little is known about the molecular mechanism behind the antimicrobial activity of organic acid.Four strains of S. enterica were utilized: Newport 36796 and 339652, and Typhimurium LT2 and 46249. Both high and low inoculation levels were performed. For low level, each strain was individually cultured and spot-inoculated onto separate 100 g untreated fresh-cut cantaloupe samples resulting in 4 log-CFU/g. For high level, samples were first submerged into 2% citric acid or malic acid for 1 minute or left as untreated control. Cantaloupe were spot inoculated with one of four strains which resulted in 7-log CFU/g. All inoculated samples were air-dried for 1 h then stored at 4°C for 7 d in deli containers. Enumeration was conducted at 0, 1, 3, 5, and 7 d. Duplicate samples were used in each of three independent trials and results were analyzed by Student’s t-test, p≤0.05. Samples for sequencing were prepared using the TruSeq Stranded mRNA kit and run on a MiSeq according to the manufacturer instructions.For low inoculation level, population of all four strains increased significantly from 0 to 3 d. The two cantaloupe outbreak-related strains (Newport 339652 and Typhimurium 46249) increased significantly between 0 and 7 d from 3.44±0.11 to 3.76±0.13 and 3.36±0.12 to 3.78±0.19 log CFU/g, respectively. For high inoculation level, the population on the untreated cantaloupe was 6.55±0.18 log CFU/g at 7 d, whereas it was significantly lower on the citric and malic acid-treated cantaloupes (6.26 ± 0.09 log CFU/g and 6.07 ± 0.18 log CFU/g). After 1 d, S. enterica genes were downregulated up to 437.4-fold compared and upregulated up to 23.2-fold. The notable downregulated genes encoded proteins related to catalyzing metabolism (L-aspartate oxidase) and also related to nutrient uptake (PstC).The results of this study can aid in understanding population dynamics of S. enterica on fresh-cut cantaloupes and efficacy of malic and citric acids. The results can also aid in understanding mechanism underlying S. enterica survival on fresh-cut cantaloupes.
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Title: Silkworm silk - CNT composite fibers: fabrication, characterization and application in cell stimulation for tissue regeneration
Creator: Zheng, Shuyao
Date: 2019
Description: Silk fibroin, a structural protein of the Bombyx mori cocoons, is widely studied for biomedical applications because of its strong mechanical...
Show moreSilk fibroin, a structural protein of the Bombyx mori cocoons, is widely studied for biomedical applications because of its strong mechanical property, biocompatibility, low degradation rate and ease of processing. In this study, we incorporated functionalized CNT in silkworm silk proteins to generate biocomposite fibers by electrospinning. The electro-spun (E-spun) fibers were unidirectionally aligned with a diameter at the sub-micrometer scale, mimicking the locally oriented ECM proteins in native tissues. The addition of a minute amount of CNT not only reinforced the stability and the mechanical strength of the flexible scaffolds, but also rendered the fibers electrical conductivity to not only facilitate the E-spun fiber formation but also grant the fibers an additional functionality that can be utilized for cell stimulation. It is known that endogenous electric field is present in the human body at various locations and plays critical physiological roles through its effect on cell proliferation, migration and activation mediated by its interference with growth factor secretion and intracellular signaling pathways. Electrical stimulation (ES) has been widely investigated as a potential method to regulate cell functions for the treatment of a number of diseases. It has been reported that in dermal fibroblasts, ES induces the secretion of FGF-1 and FGF-2 which promotes cell proliferation, contraction, migration, and activation/differentiation into myofibroblasts for increased collagen synthesis in favor of tissue repair. In this work, the modulation effect of the aligned E-spun SWS-CNT fibers was examined by their application in inducing polarization and activation of fibroblasts with cellular deficit, like those from pelvic organ prolapse (POP) patients. These cells are characterized by low productivity of collagen with abnormally high COLI/COLIII ratio, leading to a loose and fragile collagen network, decreased integration among the tissue constituents and reduced tissue strength. Electrical stimulation boosted the collagen productivity by 20 folds in cells on silk-CNT than on pure silk due to silk-CNT’s high electrical conductivity. The developed approach can be potentially utilized to remedy the dysfunctional fibroblasts for therapeutic treatment of diseases and health conditions associated with collagen disorder.
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Title: IDENTIFICATION OF BAX∆2 FRAMESHIFTING REGION VIA DUAL LUCIFERASE ANALYSIS
Creator: Reiner, Katherine
Date: 2020
Description: The antitumor protein Bax is susceptible to microsatellite instability (MSI) mutations that alter its open reading frame by changing Baxs’...
Show moreThe antitumor protein Bax is susceptible to microsatellite instability (MSI) mutations that alter its open reading frame by changing Baxs’ microsatellite of eight guanines (G8) to seven guanines (G7). This mutation results in a frameshift that is corrected by alternative splicing, making Bax∆2. Evidence shows that non-MSI mutated full length Bax∆2 (Bax∆2 G8) can be found in tissue. However, the extra guanine in Bax∆2 should result in premature termination of protein synthesis. Therefore, we believe that Bax∆2 is capable of +1 frameshifting to correct the out of frame sequence caused by splicing. The dual luciferase assay system is a useful tool for measuring frameshifting and in this study, we cloned full length Bax∆2 G8 into a dual luciferase vector to analyze frameshifting. Using this method, we found that the full length Bax∆2 G8 sequence has 3.5% frameshifting activity. To further determine whether the frameshifting occurs in or near the G8 microsatellite, we focused on several truncated constructs containing the first three exons. The results from dual luciferase assay showed that frameshifting activity was high in the constructs containing the G8 microsatellite but diminished when the G8 microsatellite region was removed. Surprisingly, constructs containing exon 4 and 5, which are away from the predicted frameshifting region, also showed frameshifting activity. One possibility to explain these results is that mRNA structures, which are critical to frameshifting, could be altered by construct truncation and consequently lead to artificial frameshifting. Thus, using truncated constructs may not be a viable option for testing frameshifting activity. To maintain mRNA integrity, point mutations within the full sequence, could be a better option to identify the frameshifting site.
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Title: PURIFICATION AND ANALYSIS OF BAXΔ2 PROTEIN AGGREGATES FROM MAMMALIAN CELLS
Creator: Wang, Xiling
Date: 2020
Description: BaxΔ2 is a unique isoform of the proapoptotic protein Bax that does not target mitochondria. The proapoptotic function of BaxΔ2 is through...
Show moreBaxΔ2 is a unique isoform of the proapoptotic protein Bax that does not target mitochondria. The proapoptotic function of BaxΔ2 is through forming cytotoxic aggregates in the cytosol. The cytotoxicity of BaxΔ2 is known as associated with the BH3 killing domain and the C-terminus, which recruits caspase 8. BaxΔ2 proteins without C-terminal form large cytosolic protein aggregates unable to induce caspase 8-dependent cell death. Since abnormal cytosolic protein aggregates often contain complexes of proteins that involved in many diseases, we would like to purify BaxΔ2 aggregates and examine their components. In this study, we expressed GFP-tagged BaxΔ2(Δ6) in the Bax-negative HCT116 cell line and purified the aggregates via different digestion processes. We found that most aggregates were trapped into a DNA pellet after cell lysis. Digestion with DNase could release the aggregates, which were susceptible to detergent solvent. The yield of purification is very low and needed improvement. The results from Western Blot showed that, in addition to BaxΔ2 proteins, stress granule protein TIAR was also potentially in the aggregates. Identification of the components inside aggregates will help us to understand the mechanism of BaxΔ2 cytotoxicity.
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Title: Machine Learning (ML) for Extreme Weather Power Outage Forecasting in Power Distribution Networks
Creator: Bahrami, Anahita
Date: 2023
Description: The Midwest region experiences a diverse range of severe weather conditions throughout the year. During the warmer months, thunderstorms,...
Show moreThe Midwest region experiences a diverse range of severe weather conditions throughout the year. During the warmer months, thunderstorms, heavy rain, lightning, tornadoes, and high winds pose a threat, while the colder season brings ice storms, snowstorms, high winds, and sleet storms, all of which can cause significant damage to the environment, properties, transportation systems, and power grids. The average climate in the Midwest is influenced by factors such as latitude, solar input, water systems' typical positions and movements, topography, the Great Lakes, and human activities. The combination of these conditions during different seasons contributes to the development of various types of storms. Therefore, it is crucial to predict the impacts of such atmospheric events on distribution and transmission lines, enabling utilities to assess and implement preventive measures and strategies to minimize the economic losses associated with these disasters. Additionally, the accurate classification of storm modes through an automated system allows operators to study trends in relation to climate change and implement necessary strategies to ensure grid reliability and resilience.In recent years, a significant number of power outages have occurred due to extreme ice formation on transmission and distribution networks, posing a threat to the power grid's resilience and reliability. To prepare power providers for snowstorms, extensive research has been conducted on snow accretion on power lines. Over the past two decades, many scientists have turned to machine learning (ML) algorithms for predicting ice accretion on overhead conductors, as ML models demonstrate superior accuracy compared to statistical forecasting models when it comes to forecasting challenging and fine-grained problems. However, most existing models primarily focus on predicting ice formation on power lines and fail to forecast the resulting damage to the distribution network. Therefore, this project proposes a model for predicting power outages caused by snow and ice storms in the distribution network. The goal is to aid in the planning process for disaster response and ensure the resilience and reliability of the power grid. The proposed outage prediction model incorporates statistical and machine learning techniques, taking into account features related to weather conditions, storm events, and information about the power network feeders.
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Title: Application of Blockchain and Artificial Intelligence Methods in Power System Operation and Control
Creator: Farhoumandi, Matin
Date: 2023
Description: The proliferation of distributed energy resources (DERs) and the large-scale electrification of transportation infrastructure are driving...
Show moreThe proliferation of distributed energy resources (DERs) and the large-scale electrification of transportation infrastructure are driving forces behind the ongoing evolution for transforming traditionally passive consumers into prosumers (both consumers and producers) in a coordinated system of power distribution network (PDN) and urban transportation network (UTN). In this new paradigm, peer-to-peer (P2P) energy trading is a promising energy management strategy for dynamically balancing the supply and demand in electricity markets. In this thesis, we propose the applications of artificial intelligence technology to power system operation and control. First, blockchain (BC) is applied to electric vehicle charging station (EVCS) operations to optimally transact energy in a hierarchical P2P framework. In the proposed framework, a decentralized privacy-preserving clearing mechanism is implemented in the transactive energy market (TEM) in which BC’s smart contracts are applied in a coordinated PDN and UTN operation. The effectiveness of the proposed TEM and its solution approach are validated via numerical simulations which are performed on a modified IEEE 123-bus PDN and a modified Sioux Falls UTN. Second, machine learning and deep learning methods are applied to short-term forecasting of non-conforming net load (STFNL). STFNL plays a vital role in enhancing the secure and efficient operation and control of power systems. However, power system consumption is affected by a variety of external factors and thus includes high levels of variations. These variations cause STFNL to be a challenging task as more DERs are integrated into the power grid. This thesis proposes two commonly used machine learning and deep learning methods, i.e., ensemble bagged and long short-term memory, for STFNL. The advantages, features and applications of these methods are expanded in a proposed fusion forecasting model that improves the STFNL accuracy. Additionally, data engineering and preprocessing options are used to increase the accuracy of the proposed fusion model. A comparative study based on practical load data is performed to demonstrate that the proposed fusion methodology can reach a relatively higher forecasting accuracy with lower error indices. Index Terms—Blockchain, deep learning and machine learning, electric vehicle charging stations, non-conforming net load forecasting, peer-to-peer transactive energy, power distribution and transportation networks, distributed energy resources, behind-the-meter supply resources.
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Title: Migration of Silver from Silver Zeolite/Low-Density Polyethylene Films into Food Stimulants
Creator: Sayeed, Maryam
Date: 2023
Description: Zeolites are naturally occurring or synthetic crystalline microporous aluminosilicate structures with remarkable catalytic, adsorption, and...
Show moreZeolites are naturally occurring or synthetic crystalline microporous aluminosilicate structures with remarkable catalytic, adsorption, and ion-exchange properties. Their unique framework of pores, channels, and cages with precise dimensions makes them an excellent fit for ion exchange and storage. Silver-exchanged zeolite (Ag/Y) composites may be incorporated into polymer matrices to create antimicrobial packaging materials. The slow release of Ag from nanosilver-enabled polymer nanocomposites (PNCs) may inhibit the growth of bacteria and other pathogens on the film’s surface, improving food quality and reducing food waste. However, the migration of Ag ions from the film into food matrices is of great concern as it could expose humans to high concentrations of a heavy metal from dietary sources. The amount of migration depends on various factors, including the potential form of Ag and its concentration in the film, the film thickness, and the storage conditions.The primary objective of this study is to investigate the effect of the form of Ag bound to the zeolite on the migration behavior of Ag from Ag/Y incorporated low-density polyethylene (LDPE) films. For Ag/Y-incorporated LDPE PNCs with distinct Ag species, the Ag migration into the water and Squirt (a commercial soft drink) was at least four times higher from films containing zeolites exchanged with ionic Ag versus zeolites exchanged with nanoparticulate Ag. Similarly, migration into 9 wt % aqueous Domino sugar (granulated sucrose) solution was seven times higher in the ionic silver-incorporated film than in the nanoparticulate Ag film. This study suggests that it is important to consider the form of Ag in silver-exchanged zeolite while producing packaging materials since the potential form of Ag in the PNCs might significantly affect Ag migration behavior.
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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: Nanopore sensing for environmental and biomarker analysis
Creator: Arora, Pearl
Date: 2024
Description: Nanopore stochastic sensing is a powerful analytical tool for detecting target molecules through a nanoscale pore. The analyte and electrolyte...
Show moreNanopore stochastic sensing is a powerful analytical tool for detecting target molecules through a nanoscale pore. The analyte and electrolyte ions are subjected to a voltage bias which drives them to translocate through the nanopore, resulting in disruptions in the ionic current. These disruptions are translated to blockage events which can serve as a signature of the analyte. Owing to its unique features of single-molecule and label-free sensing, nanopore technique has been exploited in a wide array of applications such as detection of metal ions, proteins, DNA, microRNA, toxic agents etc. In this dissertation, projects showcasing nanopore’s sensing capability of different biomarkers and in the detection of a wide range of target molecules based on non-covalent interactions are presented. Particularly in the first two projects, nanopore detection of ferric ions relevant to environmental regulation as well as a biomarker for human health and a miRNA-based biomarker for oral cancer and oral related diseases are summarized. Ferric ions, which are benign if present in balanced quantities but can be toxic otherwise, are detected by using an engineered multifunctional nanopore and a chelating organophosphonic acid ligand. The chelate complex formed after ferric ions bind to ligand gives significantly different event signatures than the free ligand in the solution enabling ferric ion detection. Even in the presence of interfering ions, the ferric ions could be recognized easily because of the conformational changes brought in the nanopore lumen by the interaction of the interfering metal ions with the His-tags of the nanopore which in turn resulted in variations in the characteristics of blocking events. In the second project, miR31, an oral cancer biomarker, is selectively detected with the help of an engineered nanopore, and a DNA based probe. Several probes with variations in length, composition and position of the overhangs or probes with no overhangs were compared and studied as the probes play a crucial role in capturing the target of interest with high specificity. Our strategically designed probe emerged as the most effective in capturing the target even in presence of large background from human saliva samples and enhanced the sensitivity of the system. In the first two projects, nanopores are utilized for selective and specific detection of certain target molecules. However, in order to analyze diverse range of analytes, numerous sensing systems have to be constructed which can be a time-consuming and challenging task. To circumvent this limitation, in the third project, diverse recognition sites based on various non-covalent interactions are incorporated into the α-hemolysin protein pore to achieve detection of not just a single analyte but broad category of molecules such as cations, anions, aromatic and hydrophobic compounds.
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Title: Effect of organic acid treatment in reducing Salmonella on six types of sprout seeds
Creator: Yang, Dachuan
Date: 2023
Description: Fresh sprouts present a special food safety concern as their growing conditions also favor the growth of pathogens such as Salmonella....
Show moreFresh sprouts present a special food safety concern as their growing conditions also favor the growth of pathogens such as Salmonella. Contamination in sprouts often originates from the seeds used for sprouting. The Produce Safety Rule requires that seeds used to grow sprouts be treated to reduce pathogens. The treatments may be applied by sprout growers or by seed suppliers. Although 20,000 ppm calcium hypochlorite is the most used seed treatment method, the high chlorine level can be hazardous to workers and the environment. Alternative seed treatment methods that are safe and environmentally friendly are needed. In addition, a post-treatment drying step is needed when seed suppliers are using chemical seed treatment methods. This study evaluated the efficacy of an organic acid solution for reducing Salmonella on six types of seeds (alfalfa, clover, radish, mung bean, onion, and broccoli). The impact of treatment on seed germination and sprout yield was also examined. Ten grams of seeds inoculated with a five-serotype cocktail of Salmonella were pre-rinsed with 40 ml of water twice and treated with 75.7 ml of the organic acid solution for 1 hour. The treated seeds were either not rinsed or rinsed with 40 ml of water twice before being dried in the biological safety cabinet for 24 hours. The Salmonella level, germination percentage, and sprout yield of seeds treated with water, seeds treated with the organic acid solution, seeds treated with organic acid, dried, and rinsed, and seeds treated with organic acids, dried, and not rinsed were compared. Salmonella reductions that could be achieved with this organic acid solution treatment were less than 0.5 log CFU/g without drying, 0.6-2.0 log CFU/g with drying and rinse, or 1.6-2.9 log CFU/g with drying and no rinse. Drying significantly enhanced the treatment efficacy (p < 0.05 ) on alfalfa, radish, mung bean, and onion seeds. If seeds were not rinsed after treatment, the log reductions achieved on mung bean and onion seeds were significantly higher (p < 0.05). If seeds were treated and rinsed, the germination rates of six types of seeds were not affected (p > 0.05) regardless of whether the seeds were dried or not. All treatments significantly decreased the sprout yield of clover seeds by 13% (p < 0.05 ). If seeds were not rinsed after treatment, the germination rates of clover and broccoli seeds were reduced by 7 and 9%, respectively, and the sprout yield of alfalfa seeds was reduced by 35%. Overall, the organic acid solution was ineffective when compared with 20,000 ppm calcium hypochlorite in reducing Salmonella on sprout seeds, although the drying step after treatment could improve the treatment efficacy.
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Title: Utilizing Image Processing in Evaluation of Fibroblast Stimulation for Collagen Remodeling
Creator: Yoon, Shin Hae
Date: 2023
Description: This research delves into the realm of image processing as a pivotal component in the evaluation of fibroblast stimulation for collagen...
Show moreThis research delves into the realm of image processing as a pivotal component in the evaluation of fibroblast stimulation for collagen remodeling. The study focuses on unraveling the intricate synergy between electrospun silk fibroin-carbon nanotube (SF-CNT) fibers and electrical stimulation, working in harmony to enhance tissue regeneration. Building upon our previous work, we successfully engineered SF-CNT fibers through the electrospinning process, yielding highly aligned structures reminiscent of natural extracellular matrix proteins. These fibers were fortified with water stability through post-treatment with ethanol vapor, while subtle additions of carbon nanotubes (CNTs) significantly improved fiber alignment, strength, and conductivity without compromising biocompatibility. This innovative platform served as a cell culture matrix for fibroblasts harvested from pelvic organ prolapse (POP) patients, facilitating electrical stimulation that triggered a substantial increase in collagen production. In this study, we harnessed the power of various image-processing software tools, including ImageJ and Python, to analyze immunostained images of fibroblasts obtained from POP patients. Under carefully tailored electrical stimulation conditions, the stimulated cells exhibited an astonishing up to 11.97-fold increase in alpha-smooth muscle actin (α-SMA) expression, unequivocally signifying the successful activation of myofibroblasts. Additionally, in an animal model employing LOX-knockout mice to mimic collagen disorders associated with POP, the application of optimized electrical stimulation conditions for patient 003 led to a remarkable surge in collagen production and structural enhancement, underlining the potential of electrical stimulation in expediting tissue remodeling. Intriguingly, fibroblasts from patient 005 and patient 006 exhibited a distinct response, shedding light on the influence of POP severity on cellular behavior. This study firmly reinforces the imperative of personalized therapeutic approaches, emphasizing the need to customize treatment strategies to align with individual patient characteristics through innovative biological image analysis techniques.
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Title: Empowering Visually Impaired Individuals With Holistic Assistance Using Real-Time Spatial Awareness System
Creator: Yu, Xinrui
Date: 2024
Description: The integration of artificial intelligence (AI) into daily life opens unprecedented avenues for enhancing the experiences of visually impaired...
Show moreThe integration of artificial intelligence (AI) into daily life opens unprecedented avenues for enhancing the experiences of visually impaired individuals, offering them greater autonomy and quality of life. This thesis introduces a Visually Impaired Spatial Awareness (VISA) system designed to assist visually impaired individuals holistically through a structured approach. At the foundational level, the VISA system incorporates several key technologies to interpret the surroundings and assist in basic navigation tasks. It utilizes Augmented Reality (AR) markers to facilitate recognition of places and aid in navigation, employs neural network models for advanced object detection and tracking, and leverages depth information for accurate object localization. Progressing to the intermediate level, the VISA system integrates the data obtained from object detection and depth sensing to assist in more complex navigational tasks such as obstacle avoidance and pathfinding toward a desired destination. At the advanced level, the VISA system synthesizes the capabilities developed at the foundational and intermediate levels to enhance the spatial awareness of visually impaired users, allowing them to undertake complex tasks, such as navigating complex environments and locating specific items. The VISA system also emphasizes efficient human-machine interaction, incorporating text-to-speech and speech-to-text technologies to facilitate natural and intuitive communication between the user and the system. The VISA system's performance was evaluated in different environments simulating real-world scenarios. The experimental results show that the user can interact with our system intuitively with minimal effort, and affirm that the VISA system can effectively assist the visually impaired user in locating and reaching for objects, navigating indoors, identifying merchandise, and recognizing both handwritten and printed texts.
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Title: Characterization of Radiation Damage Effects in High-Energy Neutrino Target Graphite using Low-Energy Ions
Creator: Burleigh, Abraham C.
Date: 2023
Description: Exposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can...
Show moreExposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can result in a shortened operation lifetime. The dominant factors in this process are currently thought to be mechanical in nature resulting primarily from microstructural effects that lead to thermal and structural changes in bulk material properties. As currently planned beam facilities with increased proton energy and intensity begin to come online it will be important to thoroughly understand these processes, and ideally to be able to predict the effects of new beam designs on target properties. Direct analysis of targets exposed to existing high-energy proton beams is complicated by several factors, such as very limited access to proton beam facilities, high associated costs, irradiation times on the order of months, and the resulting radioactivity of irradiated samples that requires special facilities for post-irradiation examination. Much of the existing literature concerning irradiation damage in graphite has been focused on the needs of the nuclear engineering community, however high-energy proton targets operate in a much different environment. In comparison to graphite irradiated in a nuclear reactor, graphite used in proton beam targets receives a higher dose rate, have greater gas production, and experience short irradiation pulses as opposed to continuous irradiation. Low-energy ion irradiation offers a method of inducing similar levels of radiation damage to high-energy protons while avoiding many of the difficulties and limitations associated with high-energy proton beams and the corresponding activated specimen testing. My research described in this thesis focused on investigating how low-energy ion irradiation could be used to induce the same or similar types of microstructural alteration and mechanical property degradation as that seen in high-energy neutrino production target graphites by varying damage levels and irradiation temperatures prior to post-irradiation characterization.
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Title: Investigation of Electrochemical Properties and Fabrication of Lithium- and Sodium-ion Batteries
Creator: Chen, Changlong
Date: 2023
Description: Since the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy...
Show moreSince the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy supply and less environmental concerns has been significantly increased. This triggered tremendous efforts from both academy and industry in building better Li-ion batteries. Along the research and development over past 30 years, the performance of current Li-ion batteries has met some basic needs in our daily life, such as powering electronic devices and electric vehicles for a short time, while superior capabilities, like extended operating life, stable function under extreme circumstances, is always pursued. Under the pressure from these ever-growing demands, the corresponding Li-ion battery production is faced with a lot of new challenges. Regarding the battery production, the present Li-ion battery manufacturing heavily relies on the use of certain repo-toxic solvent, N-methyl-2-pyrrolidone (NMP), which arouses safety concerns to human health. In the pursuit of a higher energy density, silicon anode, bearing ten times the gravimetric capacity of commercially-dominating graphite anode, is intensively studied as the anode material for next-generation Li-ion batteries. However, its degradation mechanism is not completely revealed yet, which makes the methods of effective optimizations hard to be developed. In terms of the cost control, Na-ion batteries have been revisited and have received extra attention in the past decade owing to the abundance in raw materials and the high compatibility with state-of-art Li-ion industry while blank space in understanding primary electrochemical properties, such as impedance signals, has not been totally filled. This will also cause the misunderstandings in such interpretation and, thereby, postpone the pace of relevant advancement. Targeting these proposed issues, this thesis provides a series of feasible solutions via careful investigation and rational analysis with the aid of various advanced (non)electrochemical techniques, which offers a few unique perspectives in studying Li- and Na-ion batteries, and further facilitates the following research and development in the corresponding communities.
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Title: Characterization of Radiation Damage Effects in High-Energy Neutrino Target Graphite using Low-Energy Ions
Creator: Burleigh, Abraham C.
Date: 2023
Description: Exposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can...
Show moreExposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can result in a shortened operation lifetime. The dominant factors in this process are currently thought to be mechanical in nature resulting primarily from microstructural effects that lead to thermal and structural changes in bulk material properties. As currently planned beam facilities with increased proton energy and intensity begin to come online it will be important to thoroughly understand these processes, and ideally to be able to predict the effects of new beam designs on target properties. Direct analysis of targets exposed to existing high-energy proton beams is complicated by several factors, such as very limited access to proton beam facilities, high associated costs, irradiation times on the order of months, and the resulting radioactivity of irradiated samples that requires special facilities for post-irradiation examination. Much of the existing literature concerning irradiation damage in graphite has been focused on the needs of the nuclear engineering community, however high-energy proton targets operate in a much different environment. In comparison to graphite irradiated in a nuclear reactor, graphite used in proton beam targets receives a higher dose rate, have greater gas production, and experience short irradiation pulses as opposed to continuous irradiation. Low-energy ion irradiation offers a method of inducing similar levels of radiation damage to high-energy protons while avoiding many of the difficulties and limitations associated with high-energy proton beams and the corresponding activated specimen testing. My research described in this thesis focused on investigating how low-energy ion irradiation could be used to induce the same or similar types of microstructural alteration and mechanical property degradation as that seen in high-energy neutrino production target graphites by varying damage levels and irradiation temperatures prior to post-irradiation characterization.
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Title: Investigation of Electrochemical Properties and Fabrication of Lithium- and Sodium-ion Batteries
Creator: Chen, Changlong
Date: 2023
Description: Since the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy...
Show moreSince the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy supply and less environmental concerns has been significantly increased. This triggered tremendous efforts from both academy and industry in building better Li-ion batteries. Along the research and development over past 30 years, the performance of current Li-ion batteries has met some basic needs in our daily life, such as powering electronic devices and electric vehicles for a short time, while superior capabilities, like extended operating life, stable function under extreme circumstances, is always pursued. Under the pressure from these ever-growing demands, the corresponding Li-ion battery production is faced with a lot of new challenges. Regarding the battery production, the present Li-ion battery manufacturing heavily relies on the use of certain repo-toxic solvent, N-methyl-2-pyrrolidone (NMP), which arouses safety concerns to human health. In the pursuit of a higher energy density, silicon anode, bearing ten times the gravimetric capacity of commercially-dominating graphite anode, is intensively studied as the anode material for next-generation Li-ion batteries. However, its degradation mechanism is not completely revealed yet, which makes the methods of effective optimizations hard to be developed. In terms of the cost control, Na-ion batteries have been revisited and have received extra attention in the past decade owing to the abundance in raw materials and the high compatibility with state-of-art Li-ion industry while blank space in understanding primary electrochemical properties, such as impedance signals, has not been totally filled. This will also cause the misunderstandings in such interpretation and, thereby, postpone the pace of relevant advancement. Targeting these proposed issues, this thesis provides a series of feasible solutions via careful investigation and rational analysis with the aid of various advanced (non)electrochemical techniques, which offers a few unique perspectives in studying Li- and Na-ion batteries, and further facilitates the following research and development in the corresponding communities.
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Title: Effect of Stress Triaxiality and Lode Angle on Ductile Fracture
Creator: Nia, Mahan
Date: 2023
Description: Although many ductile damage accumulation studies have been done in recent years, there is still insufficient research towards the development...
Show moreAlthough many ductile damage accumulation studies have been done in recent years, there is still insufficient research towards the development of ductile fracture models, mainly due to the difficulty of performing experiments under different states of multiaxial stress. The goals of this Ph.D. research are to (i) produce much-needed experimental data, (ii) investigate the performance of existing models against these data, and (iii) develop a new predictive ductile fracture model validated by experiments. The new model seeks to predict the fracture strain as a function of the stress triaxiality and normalized Lode angle. One of the prominent works in this area was done by Bai and Wierzbicki in 2008 by testing 2024-T351 aluminum alloy. They proposed an asymmetric 3D empirical fracture model with six model parameters. Thus, the Bai method was investigated alongside a new model for predicting ductile fracture. For that purpose, 2139-T8 aluminum alloy was chosen for our experimental program to evaluate these models better, and the data extracted from Bai's work was also used as an additional data set. An extensive experimental program was considered to create different stress states in the material, including tensile tests (with round smooth and four round notched and plate specimens), torsion, compression (with four smooth and two notched specimens), and shear-compression experiments (two different sizes). The specimens were longitudinally machined from a block of 2139-T8 aluminum alloy. The combined effects of two variables, stress triaxiality and normalized Lode angle, define a 3D fracture envelope for fracture strain. A parallel FE simulation (fine-tuned by the experimental results) has been performed for each experiment to evaluate the evolution of stress triaxiality and Lode angle in the gauge section of the specimens with complicated geometries. Finally, these results were used in developing two predictive fracture models. The first model is based on the Bai-Wierzbicki form of fracture. The second one is a new model that has been presented in this research. This new model is a modification of the Johnson-Cook fracture model and considers the simultaneous effects of Lode angle and stress triaxiality in fracture. The original Johnson-Cook fracture model (1984) does not consider the Lode angle effect. In the end, errors in the proposed approach to modeling ductile fracture have been compared to errors from Bai's work, resulting in the conclusions and recommendations for future studies.
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Title: Two Essays on Mergers and Acquisitions
Creator: Xu, Yang
Date: 2024
Description: This dissertation is composed of two self-contained chapters that both relate to mergers and acquisitions (M&A). In the first essay, we...
Show moreThis dissertation is composed of two self-contained chapters that both relate to mergers and acquisitions (M&A). In the first essay, we examine the Delaware (DE) reincorporation effect on firms’ post-IPO behaviors on mergers and acquisitions. We find that firms’ DE reincorporation decisions enhance the likelihood of engaging in M&A as targets. However, as a tradeoff, DE reincorporated firms get lower takeover valuations compared to stay-at-home-state firms, and the acquisition of reincorporated firms is less likely to be successful. Our second essay aims to explore the role of the options market in price discovery for M&A. We find that the predictive power of the changes in implied volatility of the target firm stock for the takeover outcome is statistically and economically significant. The risk arbitrage portfolios incorporating filters derived from the options on stocks of the target firms generate annualized risk-adjusted abnormal returns between 2.6% and 5%, depending on the portfolio weighting method, the threshold of filters for the implied volatility change, and the asset pricing models applied for abnormal returns. The results are robust to different empirical setups and are not explained by traditional factors.
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Title: Measurement and Control of Beam Energy at the Fermilab 400 MeV Transfer Line
Creator: Mwaniki, Matilda W.
Date: 2023
Description: Linac is the first machine in the Accelerator chain at Fermilab where particles are accelerated from 35 keV to 400 MeV and travel to the...
Show moreLinac is the first machine in the Accelerator chain at Fermilab where particles are accelerated from 35 keV to 400 MeV and travel to the Booster where they are stripped of the extra electrons to become protons. Tuning Linac is performed using diagnostics to ensure stable intensity and energy while minimizing uncontrolled particle loss. I have been revisiting diagnostics in the Linac in order to understand their signals and to ensure their data is reliable. I revisited Beam Loss Monitors (BLMs) for the loss data confidence. For the confidence of energy data there were two approaches. The first approach was time-of-flight measurements using Beam Position Monitors (BPMs) and beam velocity stripline pick-up that provides beam phase data. The second approach used the relation between beam position data from BPMs and dispersion values from MAD-X simulation to calculate energy. Our goal after understanding the data from the Linac diagnostics and finding the data reliable is to control the Linac parameters using Machine Learning techniques to increase the reliability and quality of beam delivered from Linac.
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Title: Ultrasound Image Guided Robot Arm for Targeted Delivery of Therapeutic Drugs and MicroRNA for Cancer Therapy
Creator: Nagarajan Parimala, Abishek
Date: 2024
Description: Molecular imaging has revolutionized medical diagnostics by providing detailed insights into biological processes at the molecular level...
Show moreMolecular imaging has revolutionized medical diagnostics by providing detailed insights into biological processes at the molecular level within the living subject. Ultrasound Molecular Imaging (USMI) has emerged as a promising diagnostic imaging modality by utilizing targeted contrast agents to unveil crucial molecular information, including vascular biomarkers associated with cancer and other diseases. Despite its potential, the transition of Ultrasound Contrast Agents (UCA) from preclinical evaluation to FDA-approved clinical use faces challenges due to the short in vivo half-life of Micro-Bubbles (MBs), necessitating repeated administrations for comprehensive assessments. Moreover, conventional ultrasound imaging methods suffer from limited scanning areas and single-target focus, leading to low throughput in preclinical evaluations.This thesis addresses these challenges by proposing a robot-assisted whole-body scanning pipeline for preclinical evaluations in Ultrasound Molecular Imaging. By integrating a robotic arm into the imaging setup, this approach enhances scanning flexibility and precision, enabling scans across the entire body of a mouse. This extension of the imaging time window allows for comprehensive assessments without the need for repeated contrast agent administrations. Additionally, the ability to simultaneously scan multiple targets within the same session significantly increases the throughput of preclinical assessments, thereby improving the efficiency and reliability of Ultrasound Molecular Imaging in clinical translation.
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