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Title: Development of Microfluidic Platform to Study Insulin Resistance
Creator: Tanataweethum, Nida
Date: 2020
Description: Insulin resistance, a precursor for the development of type 2 diabetes (T2D), propagates among heterologous tissues through dysregulated lipid...
Show moreInsulin resistance, a precursor for the development of type 2 diabetes (T2D), propagates among heterologous tissues through dysregulated lipid flux, as well as dysregulated glucose production, and secretion of cytokines, adipokines and hepatokines. Although T2D is characterized by systemic insulin resistance, disruption of insulin signaling in the liver and adipose tissue recapitulates many aspects of T2D, including enhance endogenous glucose production as well as defects of insulin action. Mechanistic studies often aim to provide fundamental understanding of the observations from human and animal studies. Due to the complexity of animal models and the multifactorial character of T2D, there is a strong need to develop advanced experimental systems such as in vitro models that can enable the recapitulation of the complex physiology of the in vivo system and enable investigation of the pathological pathways as well as identify novel treatment options. The overall goal of this study was to develop insulin resistant models of adipose tissue and liver to study the metabolic function of each organ as well as to the organ-organ crosstalk. To accomplish this goal, four specific aims were pursued: (1) Establish adipose tissue on-a-chip to study the metabolic function of the adipocytes in flow culture; (2) Develop towards an insulin resistant adipose on-a-chip to study the metabolic function of adipocytes in setting of insulin resistance; (3) Develop insulin resistant liver on-a-chip to investigate the metabolic function of hepatocytes in setting of insulin resistance; (4) Develop adipose-liver on-a-chip in setting of insulin resistance to identify the metabolic interaction between organs.
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Title: Exploiting contextual information for deep learning based object detection
Creator: Zhang, Chen
Date: 2020
Description: Object detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great...
Show moreObject detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great progress made in recent years, object detection is still a challenging task. One of the keys to improving the performance of object detection is to utilize the contextual information from the image itself or from a video sequence. Contextual information is defined as the interrelated condition in which something exists or occurs. In object detection, such interrelated condition can be related background/surroundings, support from image segmentation task, and the existence of the object in the temporal domain for video-based object detection. In this thesis, we propose multiple methods to exploit contextual information to improve the performance of object detection from images and videos.First, we focus on exploiting spatial contextual information in still-image based object detection, where each image is treated independently. Our research focuses on extracting contextual information using different approaches, which includes recurrent convolutional layer with feature concatenation (RCL-FC), 3-D recurrent neural networks (3-D RNN), and location-aware deformable convolution. Second, we focus on exploiting pixel-level contextual information from a related computer vision task, namely image segmentation. Our research focuses on applying a weakly-supervised auxiliary multi-label segmentation network to improve the performance of object detection without increasing the inference time. Finally, we focus on video object detection, where the temporal contextual information between video frames are exploited. Our first research involves modeling short-term temporal contextual information using optical flow and modeling long-term temporal contextual information using convLSTM. Another research focuses on creating a two-path convLSTM pyramid to handle multi-scale temporal contextual information for dealing with the change in object's scale. Our last work is the event-aware convLSTM that forces convLSTM to learn about the event that causes the performance to drop in a video sequence.
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Title: IMAGE-ANALYSIS WITH FIJI PROGRAM ON PERIPHERAL BLOOD MONOCULAR CELLS AFTER CONSUMPTION OF HIGH-FAT, HIGH CARBOHYDRATE MEAL WITH OR WITHOUT ADDITION OF SPICES – A SINGLE-CENTER RANDOMIZED, BLINDED, PLACEBO-CONTROLLED, 4-ARM, 24HR ACUTE CROSSOVER STUDY
Creator: Tsai, Meng Fu
Date: 2020
Description: Chronic low-grade inflammation plays a significant role in developing various chronic diseases, such as cardiovascular disease and type II...
Show moreChronic low-grade inflammation plays a significant role in developing various chronic diseases, such as cardiovascular disease and type II diabetes. Western-type diets characterized by high-fat (saturated fat) and high-carbohydrate (HFHC) calories induce oxidative stress leading to inflammation. Polyphenol rich foods, such as berries, tea, and herbs and spices, have antioxidant properties. Spices have been shown to have anti-inflammatory effects in cell and animal studies; however, data are limited in humans. In the present study, we hypothesized that bioactive polyphenolic compounds in herbs and species would reduce diet-induced inflammation in overweight and obese (OW/OB) individuals. In a randomized, single-blinded 4-arm, 24-h, crossover clinical trial, sixteen OW/OB adults consumed an HFHC meal with and without three herbs and spices combinations, including Italian herbs (rosemary, basil, thyme, oregano, and parsley), cinnamon and pumpkin pie spice (cinnamon, ginger, nutmeg, and allspice) on four separate occasions at least three days apart. Markers of inflammation were assessed before and at 2, 4, 5.5, and 7 hours after meal consumption by tracking nuclear translocation of nuclear factor kappa B (NF-κB), a transcription factor in inflammatory signaling, in human peripheral blood monocular cells (PBMCs) and by measuring plasma interleukin-6 (IL-6), a pro-inflammatory cytokine. Nuclear translocation of NF-κB and the proportion of PBMCs activated were estimated through a new method leveraging machine-learning immunofluorescence image analysis. Metabolic markers were also investigated by RX Daytona automated clinical chemistry analyzer. Statistical analysis was conducted using a statistical package for the social sciences (SPSS) (α<0.05, significance). Preliminary results suggested the pumpkin pie spice mixture may improve inflammatory status. Compared to the control meal, the meal with pumpkin spice reduced nuclear translocation of NF-κB and proportion of PBMCs activation, p=0.007, and p=0.005, respectively. The addition of herbs/spices in HFHC meal had no apparent effect on postprandial glucose, insulin, or IL-6 concentrations compared to the control meal. Increased triglyceride concentrations were suggested after consuming the meal with Italian herbs compared to control (p=0.004). Overall, the results of this research suggested the potential of pumpkin pie spice as having anti-inflammatory effects in the context of a typical western-style eating pattern. A major component of this research was to develop a new method for assessing real-time inflammation in the human body. While the method and data are encouraging, upgrading image resolution and programming will be the subject of future research.
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Title: ENLARGED PERIVASCULAR SPACES IN COMMUNITY-BASED OLDER ADULTS
Creator: Javierre Petit, Carles
Date: 2020
Description: Enlarged perivascular spaces (EPVS) have been associated with aging, increased stroke risk, decreased cognitive function and vascular dementia...
Show moreEnlarged perivascular spaces (EPVS) have been associated with aging, increased stroke risk, decreased cognitive function and vascular dementia. Furthermore, recent studies have investigated the links of EPVS with the glymphatic system (GS), since perivascular spaces are thought to play a major role as the main channels for clearance of interstitial solutes from the brain. However, the relationship of EPVS with age-related neuropathologies is not well understood. Therefore, more conclusive studies are needed to elucidate specific relationships between EPVS and neuropathologies. After demonstration of their neuropathologic correlates, detailed assessment of EPVS severity could provide as a potential biomarker for specific neuropathologies.In this dissertation, our focus was twofold: to develop a fully automatic EPVS segmentation model via deep learning with a set of guidelines for model optimization, and to evaluate both manual and automatic assessment of EPVS severity to investigate the neuropathologic correlates of EPVS, and their contribution to cognitive decline, by combining ex-vivo brain magnetic resonance imaging (MRI) and pathology (from autopsy) in a large community-based cohort of older adults. This project was structured as follows. First, a manual approach was used to assess neuropathologic and cognitive correlates of EPVS burden in a large dataset of community-dwelling older adults. MR images from each participant were rated using a semiquantitative 4-level rating scale, and a group of identified EPVS was histologically evaluated. Two groups of participants in descending order of average cognitive impairment were defined based and studied. Elasticnet regularized ordinal logistic regression was used to assess the neuropathologic correlates of EPVS burden in each group, and linear mixed effects models were used to investigate the associations of EPVS burden with cognitive decline. Second, a fully automatic EPVS segmentation model was implemented via deep learning (DL) using a small dataset of 10 manually segmented brain MR images. Multiple techniques were evaluated to optimize performance, mainly by implementing strategies to reduce model overfitting. The final segmentation model was evaluated in an independent test set and the performance was validated with an expert radiologist. Third, the DL segmentation model was used to segment and quantify EPVS. Quantified EPVS (qEPVS) were evaluated by combining ex-vivo MRI, pathology, and longitudinal cognitive evaluation. EPVS quantification allowed to study qEPVS both in the whole brain and regionally. Two different qEPVS metrics were studied. Elastic-net regularized linear regression was used to assess the neuropathologic correlates of qEPVS within each region of interest (ROI) under study, and linear mixed effects models were used to investigate the associations of qEPVS with cognitive decline. Finally, a preliminary study investigated the longitudinal associations of qEPVS with time. The DL segmentation model was re-trained using 4 in-vivo MR images. EPVS were segmented and quantified in a large longitudinal cohort where each participant was imaged at multiple timepoints. Factors that influenced segmentation performance across timepoints were evaluated, and linear mixed effects models controlling for these factors were used to investigate the associations of qEPVS with time.
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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: Investigating anti-biofilm and anti-persister activities of natural compounds and antimicrobial proteins
Creator: Jin, Xing
Date: 2020
Description: Bacterial biofilm formation is frequently involved in the development of chronic infectious diseases. Inhibiting biofilms is challenging due...
Show moreBacterial biofilm formation is frequently involved in the development of chronic infectious diseases. Inhibiting biofilms is challenging due to their tolerance against conventional antibiotics which are not effective to penetrating biofilm matrix to kill the cells residing in biofilms. Metabolically dormant cells known as persisters are also not eradicated by antibiotic treatment. Therefore, novel antimicrobial drugs that can kill non-growing persisters or inhibit biofilms are needed urgently. Here, we investigate the anti-biofilm and anti-persister activities of new drug candidates including plant extracts, fatty acids and colicins. We firstly screened 50 different plant extracts on enterohemorrhagic E. coli and Listeria monocytogenes, and identified Cancavalia ensiformis-derived lectin Concanavalin A (ConA) inhibits biofilm formation of enterohemorrhagic E. coli and Listeria monocytogenes by binding to carbohydrates on bacterial cell surface. Biofilm results support that ConA lectin can be applied for developing anti-adherent and anti-biofilm agents to control biofilms. Also, fatty acids may be promising candidates as anti-persister or anti-biofilm agents, because some fatty acids exhibit antimicrobial effects. We screened a fatty acid library consisting of 65 different fatty acid molecules for altered persister formation. We found that undecanoic acid, lauric acid, and N-tridecanoic acid inhibited E. coli persister cell formation including enterohemorrhagic E. coli EDL933. These fatty acids were all medium chain saturated forms. Furthermore, the fatty acids repressed EHEC biofilm formation (for example, by 8-fold for lauric acid) without having antimicrobial activity. This study demonstrates that medium chain saturated fatty acids can serve as anti-persister and anti-biofilm agents that may be applied to treat bacterial infections. Colicins, a type of antimicrobial bacteriocins, are considered as a viable alternative of conventional antibiotics due to their unique cell killing mechanisms that can damage cells by pore-forming on the cell membrane, nuclease activity, and cell wall synthesis inhibition. In this study, we utilized cell-free protein synthesis to produce colicins with different modes of action. We optimized the production yield and activity of colicins in cell-free system. Also, we tested effect of cell-free produced colicins on persister cell formation and biofilm formation. We illustrated that colicins kill persister cells and biofilm cells. Moreover, colicins produced from the engineered probiotic E. coli cells, which can be used as a living medicine, specifically and significantly eradicate target biofilms without affecting other bacterial population. Colicins have great potential to be an antibiotic alternative, and engineered probiotic E. coli is a potential candidate for engineered bacterial therapeutics.
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Title: DIAGNOSING AND TREATING ADHD: CLINICIAN CHARACTERISTICS, METHODS OF DIAGNOSIS, DIAGNOSTIC RATES, AND TREATMENT RECOMMENDATIONS
Creator: Haak, Christopher Luke
Date: 2019
Description: Attention-deficit/hyperactivity disorder (ADHD) is one of the top five most common referrals among all neuropsychologists (Sweet et al. 2015)...
Show moreAttention-deficit/hyperactivity disorder (ADHD) is one of the top five most common referrals among all neuropsychologists (Sweet et al. 2015) and continues to elicit public and professional concern about over-diagnosis in children (Sciutto & Eisenberg, 2007) and under-diagnosis in adults (Asheron et al., 2012; Kooji et al., 2010). In recent years, the prevalence of ADHD has increased (Polanczyk et al., 2007 & 2014, Thomas et al., 2015). It is unclear what is driving these changes though changes in criteria may be playing a role (van de Voort et al., 2014). Further, there has been little research on whether professional training, beliefs, and practice factors can influence the likelihood to diagnose ADHD. The purpose of this study was to examine the extent to which neuropsychologists’ professional characteristics, training, and beliefs about ADHD diagnosis and treatment influence their likelihood to diagnose ADHD. The study also evaluated whether there are differences in assessing and treating ADHD based upon the client population focus (child, lifespan, or adult) of neuropsychologists. Participants in this study were 106 neuropsychologists from across the United States and Canada who were recruited through neuropsychology listservs to participate in an online survey. Results indicated that population focus was associated with significant differences in approach to diagnosing and treating ADHD, with child- and lifespan-focused neuropsychologists reporting higher rates of ADHD diagnosis. Additionally, having a higher percent of clinical cases in which ADHD is a referral question and greater self-reported adherence to following full diagnostic criteria for making a diagnosis were associated with higher ADHD diagnostic rates, controlling for age, gender, ethnicity, and other professional characteristics. This study is among the first to examine specific clinician factors impacting diagnostic rates and its findings have several implications for practice and research.
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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: High-latitude plasma drift structuring from a first principles ionospheric model
Creator: Kim, Heejin
Date: 2020
Description: In the high-latitude ionosphere dense plasma formations called polar cap patches are sometimes observed. These patches are often associated...
Show moreIn the high-latitude ionosphere dense plasma formations called polar cap patches are sometimes observed. These patches are often associated with ionospheric scintillation, a rapid fluctuation in the amplitude and phase of a radio signal that degrades communications and navigation systems. Predicting polar cap patch movement across the polar cap is an important subject for enabling forecasting of the scintillation.Lagrangian coherent structures (LCSs) are ridges indicating regions of maximum fluid separation in a time-varying flow. In previous studies, the Ionosphere-Thermosphere Algorithm for Lagrangian Coherent Structures (ITALCS) predicted the location of LCSs. These LCSs were shown to constrain polar cap patch source and transport regions for flow assumed to due to $\vec{E} \times \vec{B}$ plasma drift. The LCSs were predicted based on an empirical model of the high-latitude electric field for $\vec{E}$. In this thesis, the LCSs are generated using the first principles ionospheric model SAMI3 (SAMI3 is Another Model of the Ionosphere) as the model for electric field. The work relies on an understanding of various magnetic coordinate systems in space science, and includes three different approaches for attempting to generate the $\vec{E} \times \vec{B}$ drift as the flow fields that are to input to ITALCS. Finally, a representative LCS result is obtained with SAMI3 and shown to be at the high latitudes on the dayside, similar to prior work, but spanning a shorter longitudinal range.
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Title: Characterization of turbulent mixing near roadways based on measurements of short-term turbulence kinetic energy and traffic conditions
Creator: Hu, Zhice
Date: 2020
Description: Turbulence determines how vehicle emissions mix with the surrounding air and determine the distribution of pollutants on the roadway and...
Show moreTurbulence determines how vehicle emissions mix with the surrounding air and determine the distribution of pollutants on the roadway and downwind. 600 5-min near roadway simultaneous measurements (2016 to 2018) of turbulent kinetic energy (TKE), meteorological conditions, and traffic information (vehicle flow rate, density, and traffic mix (LDVs & HDVs) were used to characterize TKE. Short-term measurements (5 min.) were required to characterize the large variation in traffic flow rate that occurred in short time periods. Two roadways (Lakeshore Drive (LSD), Dan Ryan Expressway (DRE)) with distinctly different traffic composition (HDV%) and road configurations were selected for monitoring. Results indicate that variations in near-road wind speed (0.5 to 3.5 m s-1) had only a slight influence on TKE measurements. Background contributed 40% of the total measured TKE. The average dissipation rate traffic-induced TKE from on-road to near-road measurement was 90%. The average near roadway TKE (background subtracted) was 0.6 (m2 s-2) (0.2 st. dev) for LDVs only, and 0.8 (m2 s-2) (0.3 st. dev) for mixed fleet traffic flow (HDV averaged 8.4%). The increase in TKE was related to the increase in the HDV flow rate for free-flow traffic conditions but not for congestion conditions. TKE generated by individual HDVs was significantly higher than TKE generated from individual LDVs for free-flow traffic conditions. HDVs represent only a small fraction of the vehicle fleet mix (typical 1 to 10%) so that the overall effect of HDVs in changing vehicle fleet is difficult to quantify. However, the single HDV can induce near 11 times TKE than a single LDV in free-flow condition, which can validate the significant variation in the ensemble mean traffic-induced TKE under the same traffic fleet flow that is due to HDVs.
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Title: APPLICATIONS OF INTEGRATED DESIGN METHODOLOGIES: HYBRID AUTOMATION OF DESIGN SEQUENCING AND ITS INFLUENCE ON COMPLEX DESIGN PROJECTS
Creator: Elshanshoury, Waleed Farouk Omar
Date: 2020
Description: After the early development of Sketchpad in 1963 by Ivan Sutherland at MIT, the first system permitted drawing geometries parametrically;...
Show moreAfter the early development of Sketchpad in 1963 by Ivan Sutherland at MIT, the first system permitted drawing geometries parametrically; computation and algorithm aided design have significantly influenced the design practice. Computation and AAD are design approaches in which the medium of expression is logic instead of geometry. These approaches raised the curtain to various utilities, including but not limited to form-finding, automation, optimization, and robotic fabrication. Computational design and algorithm aided design are becoming fundamental approaches in most design practices because of their capability to solve complex problems.This thesis begins with a timeline presenting the evolution in design derivers and manifests how designers considered ideal design throughout history. This timeline starts with architecture approaches in ancient times when beauty, durability, and functions were the first principles to identify good architecture. It ends with the creation of computational technologies, which affected the design process and its logic. It will also investigate relations between software engineering and building design, where both fields intertwine with each other in general methodologies.This research examines how computation can generate integrated design systems to approach city planning and architectural design. IDS employs data, forces, and algorithms to construct a design system instead of solid geometries. This system combines the different design processes and chronological phases in interconnected blocks. This approach manages big data and assists in decision-making using automation, optimization, and machine learning technologies.This paper examines existing precedents, applications, and design projects that utilize IDS, including form-finding, materials, and energy. It will establish how evaluation criteria, simulations, solution optimizations, and processes automation play a vital role in integrated design systems. IDS is a dynamic workflow centered on principles and consists of components and aiding tools. This research explores technological aiding tools for these systems that help increase design performance and efficiencies using voice commands and automated functions.
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Title: UTILIZING BACTERIAL INTERACTIONS TO CONTROL PATHOGENIC BIOFILM FORMATION
Creator: Fang, Kuili
Date: 2020
Description: Many chronic infections involve bacterial biofilms, which are difficult to eliminate using conventional antibiotic treatments. Biofilm...
Show moreMany chronic infections involve bacterial biofilms, which are difficult to eliminate using conventional antibiotic treatments. Biofilm formation is a result of dynamic intra- or inter-species interactions. However, the nature of molecular interactions between bacteria in multi-species biofilms are not well understood compared to those in mono-species biofilms. The first project (Chapter 3) investigated the ability of probiotic Escherichia coli Nissle 1917 (EcN) to outcompete the biofilm formation of pathogens including enterohemorrhagic E. coli (EHEC), Pseudomonas aeruginosa, Staphylococcus aureus, and S. epidermidis. When dual-species biofilms were formed, EcN inhibited the EHEC biofilm population by 14-fold compared to EHEC mono-species biofilms. This figure was 1,100-fold for S. aureus and 8,300-fold for S. epidermidis; however, EcN did not inhibit P. aeruginosa biofilms. In contrast, commensal E. coli did not exhibit any inhibitory effect toward other bacterial biofilms. We identified that EcN secretes DegP, a bifunctional (protease and chaperone) periplasmic protein, outside the cells and controls other biofilms. Although three E. coli strains tested in this study expressed degP, only the EcN strain secreted DegP outside the cells. The deletion of degP disabled the activity of EcN in inhibiting EHEC biofilms, and purified DegP directly repressed EHEC biofilm formation. Hence, probiotic E. coli outcompetes pathogenic biofilms via extracellular DegP activity during dual-species biofilm formation. Enterohemorrhagic Escherichia coli O157:H7 (EHEC) is a pathogen causing the outbreaks of hemorrhagic colitis. Conventional antibiotics treatment is not recommended for EHEC infection as antibiotics trigger Shiga toxin production of EHEC and aggravate hemolytic-uremic syndrome. EHEC biofilm formation is closely associated with its virulence expression. Previously, we identified that probiotic E. coli Nissle 1917 (EcN) secretes DegP resulting in the inhibition of EHEC biofilm formation in a dual culture. DegP is a serine protease exhibiting both proteolytic and chaperone functions and binds to outer membrane proteins (OMPs) of target cells. However, the extracellular function of DegP is not clear. We hypothesized that binding of DegP to OMPs of EHEC might inhibit EHEC biofilm formation by affecting the adhesion ability or changing biofilm-related gene regulations of EHEC. We constructed EHEC mutants lacking ompA, ompC, or ompF individually and in combination and assessed their biofilm formation in the presence of DegP-secreting EcN in the co-culture or by adding purified DegP. It was found that both ompA and ompC double deletion decreased EHEC single species biofilm, and also caused that DegP inhibited more EHEC biofilm (about 25 fold inhibition) than DegP inhibited EHEC wt biofilm (about 10 fold), indicating that OmpA and OmpC are more related to EHEC biofilm than OmpF, and OmpA and OmpC might deplete DegP inhibitory functions. On the other hand, DegP S210A, a DegP mutant lacking protease function, inhibited EHEC wt biofilm, indicating that DegP’s biofilm inhibition function is not from its protease activity. Additionally, EHEC transcription profiles in the presence of DegP showed that DegP up-regulated expressions of cellulose production related genes (csgD and bcsA) and motility related genes (flhD, qseB), which were all involved in EHEC biofilm inhibition, and down-regulated Shiga toxin 2 virulence gene (stx2). Besdies, DegP promoted EHEC cellulose production and motility, which is consistent with transcription profile, and Shiga toxin 2 production will be further tested. This study reveals a new function of DegP secreted by EcN in controlling biofilms and leads us to develop an alternative strategy to control biofilm-related infections. Foodborne pathogen Listeria monocytogenes biofilm formation renders these cells highly resistant to current sanitation methods, and probiotics may be a promising approach to the efficient inhibition of Listeria biofilms. In the Chapter 5 study, three Leuconostoc mesenteroides strains of lactic acid bacteria isolated from kimchi were shown to be effective probiotics for inhibiting Listeria biofilm formation. Biofilms of two L. monocytogenes serotypes, 1/2a (ATCC15313) and 4b (ATCC19115), in dual-species culture with each probiotic strain were decreased by more than 40-fold as compared with single-species Listeria biofilms; for instance, a reduction from 5.4 times 10^6 CFU/cm2 L. monocytogenes ATCC19115 in single-species biofilms to 1.1 times 10^5 CFU/cm2 in dual-species biofilms. Most likely, one of the Leuconostoc strains, L. mesenteroides W51, led to the highest Listeria biofilm inhibition without affecting the growth of L. monocytogenes. The cell-free supernatant from the L. mesenteroides W51 culture containing large protein molecules (> 30 kDa) also inhibited Listeria biofilms. These data indicate that Leuconostoc probiotics can be used to repress L. monocytogenes biofilm contamination on surfaces at food processing facilities.
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Title: A MICROFLUIDIC INTESTINAL-MICROBIOTA PLATFORM TO STUDY DRUG METABOLISM
Creator: Wang, Chengyao
Date: 2020
Description: The intestine is the main site that orally administered drugs are primarily metabolized, absorbed, and distributed. The trillions of bacteria...
Show moreThe intestine is the main site that orally administered drugs are primarily metabolized, absorbed, and distributed. The trillions of bacteria that inhabit the intestine influence health and regulate important biochemical factors, such as the activity of enzymes pertinent to drug metabolism. However, this has not been systematically studied partly due to the challenges of recapitulating the unique and complex intestinal microenvironment that includes (1) the presence of mammalian and microbial cells and (2) a unique partitioned oxygenation proﬁle across the lumen to the subepithelial mucosa from anaerobic to the richly vascularized oxygenated. This thesis reports the development of a microfluidic device in which is integrated a membrane synthesized from a key element of mucosal basal lamina, collagen, and precisely controlled partitioned oxygen environment. The device enabled excellent cell viability and long-term function. More importantly, it enabled the coculture of intestinal epithelial cells and aerobic and anaerobic bacteria in the partitioned oxygen environment. These experiments on one hand allowed the measurement of cellular oxygen consumption rate under perfusion, which could be used to study microbial regulation of oxidative metabolism in epithelial cells. On the other hand, the device allowed a systematic examination of the role of different gut bacteria strains on the regulation of factors that are important in drug metabolism, namely, transporters and phase I enzymes. Our studies highlighted the importance of direct communication between the intestinal cells and the gut bacteria with major findings being that species-specific differences exist in the regulation of drug metabolism. This work will be useful for (1) the discovery of novel regulators of drug metabolizing enzymes, (2) developing new pharmacokinetic models, and (3) advancing precision medicine models for patients.
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Title: Population Dynamics of Listeria monocytogenes in Nut, Seed and Legume Butters
Creator: Zhang, Xinyuan
Date: 2020
Description: Nut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that...
Show moreNut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that some pathogens, such as Listeria monocytogenes, can survive for long periods of time in butters, such as almond butter. However, information on the persistence of L. monocytogenes in butters is lacking. The purpose of this study was to determine the population dynamics of L. monocytogenes in butters stored at 5 and 25°C. Nut (almond, hazelnut, pecan), seed (pumpkin, sesame, sunflower), legume (peanut and soy) and butters containing chocolate (hazelnut and peanut) were inoculated with a 4-strain cocktail of rifampicin-resistant L. monocytogenes at 4 (high inoculation) or 1 log CFU/g (low inoculation). High inoculation butters were mixed by hand for 15 min and 100-g portions were weighed into deli-style containers with lids and stored at 5 or 25°C for 12 mo (370 d). Low inoculation butters were stored in 25- g portions in stomacher bags at 25°C for 6 mo (180 d). During storage, 25 g from the 100- g high inoculation portion or 25 g from the low inoculation samples, in triplicate, were homogenized with 225 mL BPB (or BLEB for FDA BAM enrichments when necessary) and serial dilutions of the homogenate were plated onto BHIA with rifampicin for enumeration of L. monocytogenes. Data were statistically analyzed using Student’s t-test (α=0.05). The average initial population of L. monocytogenes in the butters was 3.58±0.25 log CFU/g for the high inoculation butters; L. monocytogenes was detected through enrichments for all low inoculation butters. After 12 mo storage at 5°C, the population of L. monocytogenes decreased by 1.34, 1.27, 1.72, 2.04 and 0.93 log CFU/g in almond, hazelnut, peanut with chocolate, hazelnut with chocolate and pecan butter, respectively, when inoculated at the higher level. Significantly less population reduction was observed in pumpkin, sesame, soy, peanut and sunflower butters (1.08, 0.61, 0.84, 0.05 and 0.40 log CFU/g, respectively). After 12 mo storage at 25°C, the L. monocytogenes population in all butters, with the exception of sunflower butter, decreased to below the limit of enumeration (1.67 log CFU/g), but the pathogen was still present via enrichment. For low inoculation butters, L. monocytogenes was present as determined by enrichment in all butters in at least one of two trials after 6 mo. The results of this study provide information on the survival of L. monocytogenes in different butter types when stored at different temperatures.
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Title: DEVELOPMENT AND APPLICATION OF A NATIONALLY REPRESENTATIVE MODEL SET TO PREDICT THE IMPACTS OF CLIMATE CHANGE ON ENERGY CONSUMPTION AND INDOOR AIR QUALITY (IAQ) IN U.S. RESIDENCES
Creator: Fazli, Torkan
Date: 2020
Description: Americans spend most of their time inside residences where they are exposed to a number of pollutants of both indoor and outdoor origin....
Show moreAmericans spend most of their time inside residences where they are exposed to a number of pollutants of both indoor and outdoor origin. Residential buildings also account for over 20% of total primary energy consumption in the U.S. and a similar proportion of greenhouse gas emissions. Moreover, climate change is expected to affect building energy use and indoor air quality (IAQ) through both building design (i.e., via our societal responses to climate change) and building operation (i.e., via changing meteorological and ambient air quality conditions). The overarching objectives of this work are to develop a set of combined building energy and indoor air mass balance models that are generally representative of both the current (i.e., ~2010s) and future (i.e., ~2050s) U.S. residential building stock and to apply them using both current and future climate scenarios to estimate the impacts of climate change and climate change policies on building energy use, IAQ, and the prevalence of chronic health hazards in U.S. homes. The developed model set includes over 4000 individual building models with detailed characteristics of both building operation and indoor pollutant physics/chemistry, and is linked to a disability-adjusted life years (DALYs) approach for estimating chronic health outcomes associated with indoor pollutant exposure. The future building stock model incorporates a combination of predicted changes in future meteorological conditions, ambient air quality, the U.S. housing stock, and population demographics. Using the model set, we estimate the total site and source energy consumption for space conditioning in U.S. residences is predicted to decrease by ~37% and ~20% by mid-century (~2050s) compared to 2012, respectively, driven by decreases in heating energy use across the building stock that are larger than coincident increases in cooling energy use in warmer climates. Indoor concentrations of most pollutants of ambient origin are expected to decrease, driven by predicted reductions in ambient concentrations due to tighter emissions controls, with one notable exception of ozone, which is expected to increase in future climate scenarios. This work provides the first known estimates of the potential magnitude of impacts of expected climate changes on building energy use, IAQ, and the prevalence of chronic health hazards in U.S. homes.
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Title: An Alternative Approach for the Jefferson Lab Electron-Ion Collider Ion Accelerator Complex
Creator: Martinez Marin, Jose Luis
Date: 2020
Description: An assessment by the National Academy of Sciences (NAS) of the scientific merit for a future Electron Ion Collider (EIC) in the US concluded...
Show moreAn assessment by the National Academy of Sciences (NAS) of the scientific merit for a future Electron Ion Collider (EIC) in the US concluded that such a facility would be unique in the world and enable indispensable research on current and compelling scientific questions. This assessment confirmed the recommendations of the 2015 Nuclear Science Advisory Committee (NSAC) for an EIC with highly polarized beams of electrons and ions, sufficient luminosity and sufficient, variable center-of-mass energy. Proposals were requested for a cost-effective design that uses existing accelerator infrastructure to reduce the risk; one of two major proposals submitted for consideration originated from the Thomas Jefferson National Accelerator Facility (JLab). The Jefferson Laboratory Electron-Ion Collider (JLEIC) would use the Continuous Electron Beam Accelerator Facility (CEBAF) at JLab as a full-energy electron injector. The primary accelerator challenges are twofold: producing and maintaining a high degree of polarization for both beams, and achieving high luminosity. This thesis project was part of an effort to produce an alternative, low-risk and cost- effective design for the JLEIC ion complex. The primary goal was not to find a replacement for the JLEIC ion complex design, but rather to investigate alternative options for the different components of the ion complex that could lower the overall cost, reduce its footprint, mitigate risk, and identify possible staging or future upgrades of the project. The platform for this thesis was the alternative design for the JLEIC ion complex that included (1) a more compact ion linac, (2) two staged ion boosters instead of one before injection to the collider ring, with a more compact and lower energy Pre-Booster ring as the first stage, and (3) the dual use of the electron storage ring (e-ring) as a second stage ion Large Booster.The alternative design was first investigated for medium energy (65-GeV center-of-mass), and was then upgraded following the National Academy of Sciences (NAS) review to higher energy (100-GeV center-of-mass). Developing a more cost-effective design and meeting all the requirements is challenging due to several constraints imposed on the alternative approach -- for example, the use of only room-temperature magnets for both ion boosters. There are also space limitations, the need to keep the shape and crossing angle of the ion Large Booster the same as the collider ring, ensuring reasonable length and aperture requirements for the magnets, and avoiding transition crossing for all the rings, which can cause beam dilution and instabilities.Development of both the Medium-Energy and the High-Energy options is presented. The Medium-Energy option consists of a 135 MeV injector linac, a 3 GeV octagonally-shaped Pre-Booster ring and a 11 GeV Large Booster. The High-Energy option consists of a 150 MeV (~ 40 MeV/u for Pb) injector linac, a 8 GeV (~ 2.04 GeV/u for Pb) non figure-8 Pre-Booster ring and a 40 GeV proton (~ 16 GeV/u for Pb) Large Booster, which would also serve as the electron storage ring (e-ring). The figure-8 shape of the Large Booster helps to maintain high polarization. High luminosity is achieved following a strategy to have a high bunch repetition rate of the colliding beams, very short bunch lengths, and small transverse emittances; the main concern here is to provide a lattice that is consistent with these requirements. The main results reported are the lattice design optimization and consolidation, benchmarking of the beam optics with different codes such as ELEGANT, COSY-Infinity, MAD-X, TRACE-3D, and Zgoubi, and spin resonance simulation results. Spin dynamics studies were performed for the linac and the Pre-Booster, and mechanisms to preserve the polarization are proposed. Beam formation and non-linear effects such as chromaticity, space charge, and intra-beam scattering were also studied to gain understanding of how the alternative approach could affect the baseline beam formation scheme and to ensure that the beam requirements are met through the injector chain with this alternative approach. It was shown that the polarization can be preserved through the alternative ion complex even with the more compact linac and a Pre-Booster that does not have a figure-8 shape by using a sufficiently long spin correction solenoid in the linac and a partial Siberian snake in the Pre-Booster. The baseline beam formation scheme could still be used to reach the required beam characteristics for collider injection. Cooling is not needed in the more compact Pre-Booster, and the large, higher energy booster helps to avoid space charge effects at extraction. This study has confirmed the effectiveness of the alternative approach as concerns the optics, acceleration, polarization, and beam formation. The ion injectors are sufficiently compact, and the ion Large Booster size and shape are consistent with the e-ring requirements, enabling the desired dual functionality of that machine. This work created a basis for design discussions during the JLEIC design process. The final High-Energy design for the JLEIC ion complex adopted design features that came from the alternative design studies, which were derived in part from this work—in particular, the shorter, lower-energy linac, the use of two boosters in the injection chain before the collider ring, and the ability to have only room-temperature magnets in the boosters, with superconducting magnets used only in for the collider ring.
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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: A Multi-level Data Integration Approach for the Convergence of HPC and Big Data Systems
Creator: Feng, Kun
Date: 2020
Description: HPC is moving towards exascale (10^18 operations per second) following the trend that has continued for over half a century. Such an extremely...
Show moreHPC is moving towards exascale (10^18 operations per second) following the trend that has continued for over half a century. Such an extremely compelling computing power brings huge opportunities for scientists to explore their problems with larger sizes and finer granularity. As a result, the data volume produced and consumed by extreme-scale computing has increased dramatically. To gain useful scientific insights, scientists analyze tremendous amounts of data, which stresses the storage systems and requires efficient data access. Besides the data volume increase, the variety of I/O subsystems grows as well to meet the drastically different, often conflicting I/O requirements of numerous applications. HPC and BD, as two major camps of extreme-scale computing, have been developed separately for a long time and diverged from computing and storage paradigms. However, recent developments have proven the convergence of them leads to more efficient scientific output. Hence, unification between these ecosystems is necessary to accelerate extreme-scale computing with the collaboration of applications from both camps. Therefore, integrated I/O has become a major issue that needs to be addressed as the extreme computing community moves forward.This study explores improvement by proposing a new integrated data access system for extreme-scale computing. We enhance the BD framework to adapt to the change of integrated data access requirement by enabling direct processing of scientific data from PFS at the HPC site. Our framework can perform up to 8x faster than the state-of-the-art solutions in representative workloads. We design a new advanced I/O middleware service to utilize data aggregation resources to facilitate integrated data access in scientific workflows with both HPC and BD applications. Our middleware service can reach up to 10x speedup against the default solution and 133% better performance than existing solutions. We propose a novel storage integration solution on the storage side to unite all the storage resources, to unify the namespace across all the storage systems, and provide an ultimate integrated data access service. The integrated solution can speed up a real workflow with integrated data access requirements by up to 6.86x over existing solutions. The three-level integration at the application level, middleware level, and storage level provide us a systematic hierarchical I/O integration. Our implementation results show that the three-level optimized design and implementation is feasible and effective. It improves the state-of-the-art solutions and helps us to achieve an enhanced I/O system towards extreme-scale computing to support both HPC and BD applications.
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Title: Effect of Phosphorus Additions on Polycrystalline Ni-base Superalloys
Creator: Li, Linhan
Date: 2020
Description: In recent years, advanced polycrystalline Ni-base superalloys have been developed with elevated levels of γ′ forming elements and high level...
Show moreIn recent years, advanced polycrystalline Ni-base superalloys have been developed with elevated levels of γ′ forming elements and high level of refractory elements as solid-solution strengtheners in an effort to extend the temperature capability. Moreover, the properties of the grain boundaries become more important and this necessitates the need to study of effects of minor additions of interstitial P for grain structure optimization. Due to the increased level of refractory elements employed, powder-processed Ni-base superalloys tend to have a high propensity to form Topologically Close-Packed (TCP) phases, which was found to be further promoted by the addition of P. A systematic study of the phase stability of high refractory content powder-processed Ni-base superalloys with three levels of P additions revealed an increased tendency to form Laves phase as a function of P additions. Additions of P were discovered to not only depress the incipient melting temperature to stabilize the eutectic Laves phase, but also promote Laves phase formation during the aging heat treatment and the following isothermal exposure. During the thermal exposure, excessive formation of Laves phase promoted the formation of a basket-weave structure comprised of an intertwined mixture of Laves and Sigma phase. The stabilization of the Laves phase structure due to P additions was found to be consistent with Density Functional Theory (DFT) calculations and could be rationalized through structure maps that relate the valence electron concentration and relative size differences. Additionally, a variation of grain structure obtained via either a sub-solvus or super-solvus solution heat treatment was noted to some extent vary the P segregation level at high-angle grain boundaries, thereby affecting the phase stability. For a sub-solvus solutioned grain structure that possessed a high length density of high-angle grain boundaries, the Laves phase formation was depressed for alloys with a low level of P addition. However, the phase stability variation associated with Laves phase formation was moderate when high concentrations of P were present. The effect of P addition on the γ′ microstructure variation is limited, which was confirmed by microstructure observations as well as through the short-term 0.6%-strain stress relaxation tests at high temperature. Heat treatment variations to modify the secondary and tertiary γ′ microstructures were discovered to exert a much more significant influence on the 0.6%-strain stress relaxation behavior. When a higher initial strain of 2% was applied, the stress relaxation behavior of the powder-processed Ni-base superalloys was found to be microstructure independent. The creep ductility of Waspaloy was determined to be notably reduced by the P additions due to the enhanced precipitation of M23C6 carbide at the grain boundaries. Excessive precipitation of M23C6 carbide increased the likelihood of brittle fracture when tested under low temperature/high stress creep conditions. However, the P addition as well as the excessive precipitation of M23C6 carbide did not impact the creep behavior as the dominant deformation was transgranular in nature when tested under high temperature/low stress conditions.
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