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Title: Voxel Transformer with Density-Aware Deformable Attention for 3D Object Detection
Creator: Kim, Taeho
Date: 2023
Description: The Voxel Transformer (VoTr) is a prominent model in the field of 3D object detection, employing a transformer-based architecture to...
Show moreThe Voxel Transformer (VoTr) is a prominent model in the field of 3D object detection, employing a transformer-based architecture to comprehend long-range voxel relationships through self-attention. However, despite its expanded receptive field, VoTr’s flexibility is constrained by its predefined receptive field. In this paper, we present a Voxel Transformer with Density-Aware Deformable Attention (VoTr-DADA), a novel approach to 3D object detection. VoTr-DADA leverages density-guided deformable attention for a more adaptable receptive field. It efficiently identifies key areas in the input using density features, combining the strengths of both VoTr and Deformable Attention. We introduce the Density-Aware Deformable Attention (DADA) module, which is specifically designed to focus on these crucial areas while adaptively extracting more informative features. Experimental results on the KITTI dataset and the Waymo Open dataset show that our proposed method outperforms the baseline VoTr model in 3D object detection while maintaining a fast inference speed.
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Title: Quantification of Imaging Markers at Different MRI Contrast Weightings, Vasculature, and Across Field Strengths
Creator: Nguyen, Vivian S.
Date: 2024
Description: Quantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and...
Show moreQuantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and cross-patient and cross-center studies. It enables earlier detection of disease, complements biopsy, and provides a clear numeric scale for differentiation of disease states. However, quantitative MRI acquisitions and post-processing are not trivial, which makes it hard to implement the clinical setting. This along with the variability in clinically used acquisitions and post-processing techniques leads to difficulty in establishing reliable, consistent, and accurate quantitative information. There is a critical need for rigorous validation of quantitative imaging biomarkers, both for current and novel quantitative imaging techniques. This dissertation seeks to both validate current quantitative MR imaging techniques and develop new ones in the heart and brain by: 1) examining the data variability and the loss in tag fidelity that occurs when quantitative cardiac tagging is incorrectly run post-Gadolinium injection; 2) quantifying the negative impact of unexpected relaxometric behavior observed in low field MR imaging for low inversion times during T1 mapping; 3) validating retrospectively calculated T1 as a biomarker for Multiple Sclerosis progression; 4) and prototyping an oxygen extraction fraction (OEF) mapping technique for the purpose of stroke prediction and establishment of a numeric scale for tissue health for stroke patients.Assessment of pre-Gadolinium and post-Gadolinium cardiac tag quality showed that post-Gadolinium tags are less saturated (p = 0.012) and have a wider range of saturation, contrast, and sharpness. This results in a loss of information in the late cardiac cycle and impeding quantification of myocardial function.Investigation of 64mT T1 mapping revealed unique relaxometric behavior in that at low inversion times (<250 ms), the signal response curve displayed an increase in signal intensity or a plateau in signal intensity dependent on T1 relaxation time. Inclusion of this increase or plateau in signal intensity negatively impacted T1 fitting algorithms, leading to their failure or incorrectly calculated T1 values. The maximum peak signal intensity before the null point was found to be 210 ms, which impacts current low field T1 mapping protocols which use an initial inversion time of 80-110 ms.Validation of retrospectively calculated T1 as a biomarker in Multiple Sclerosis revealed that T1 of normal appearing brain tissue correlates with measures of Multiple Sclerosis progression (EDSS, BPF, and disease duration) with normal appearing white matter T1 correlating with BPF (r = -0.49, p = 0.0018); putamen T1 correlating with EDSS (r = 0.48, p = 2.40e-03), with BPF (r = 0.69, p = 2.04e-06), and disease duration (r = -0.37; p = 0.02); and globus pallidus T1 correlating with disease duration (r = -0.42; p = 0.0093). Lesion T1 is reflective of MS severity whereas MTR is not.Finally, development of an oxygen extraction fraction (OEF) mapping technique showed that application of independent component analysis (ICA) to cardiac gated spiral-trajectory phase images yielded components that feature stenosis features observed in magnitude images. These ICA components form the basis of OEF mapping from phase images. This dissertation presents four studies that seek to improve either current quantitative MR imaging protocols in the heart, or to develop and validate new quantitative MR imaging techniques in the brain for the purpose of monitoring disease progression or predicting disease.
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Title: Voxel Transformer with Density-Aware Deformable Attention for 3D Object Detection
Creator: Kim, Taeho
Date: 2023
Description: The Voxel Transformer (VoTr) is a prominent model in the field of 3D object detection, employing a transformer-based architecture to...
Show moreThe Voxel Transformer (VoTr) is a prominent model in the field of 3D object detection, employing a transformer-based architecture to comprehend long-range voxel relationships through self-attention. However, despite its expanded receptive field, VoTr’s flexibility is constrained by its predefined receptive field. In this paper, we present a Voxel Transformer with Density-Aware Deformable Attention (VoTr-DADA), a novel approach to 3D object detection. VoTr-DADA leverages density-guided deformable attention for a more adaptable receptive field. It efficiently identifies key areas in the input using density features, combining the strengths of both VoTr and Deformable Attention. We introduce the Density-Aware Deformable Attention (DADA) module, which is specifically designed to focus on these crucial areas while adaptively extracting more informative features. Experimental results on the KITTI dataset and the Waymo Open dataset show that our proposed method outperforms the baseline VoTr model in 3D object detection while maintaining a fast inference speed.
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Title: Quantification of Imaging Markers at Different MRI Contrast Weightings, Vasculature, and Across Field Strengths
Creator: Nguyen, Vivian S.
Date: 2024
Description: Quantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and...
Show moreQuantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and cross-patient and cross-center studies. It enables earlier detection of disease, complements biopsy, and provides a clear numeric scale for differentiation of disease states. However, quantitative MRI acquisitions and post-processing are not trivial, which makes it hard to implement the clinical setting. This along with the variability in clinically used acquisitions and post-processing techniques leads to difficulty in establishing reliable, consistent, and accurate quantitative information. There is a critical need for rigorous validation of quantitative imaging biomarkers, both for current and novel quantitative imaging techniques. This dissertation seeks to both validate current quantitative MR imaging techniques and develop new ones in the heart and brain by: 1) examining the data variability and the loss in tag fidelity that occurs when quantitative cardiac tagging is incorrectly run post-Gadolinium injection; 2) quantifying the negative impact of unexpected relaxometric behavior observed in low field MR imaging for low inversion times during T1 mapping; 3) validating retrospectively calculated T1 as a biomarker for Multiple Sclerosis progression; 4) and prototyping an oxygen extraction fraction (OEF) mapping technique for the purpose of stroke prediction and establishment of a numeric scale for tissue health for stroke patients.Assessment of pre-Gadolinium and post-Gadolinium cardiac tag quality showed that post-Gadolinium tags are less saturated (p = 0.012) and have a wider range of saturation, contrast, and sharpness. This results in a loss of information in the late cardiac cycle and impeding quantification of myocardial function.Investigation of 64mT T1 mapping revealed unique relaxometric behavior in that at low inversion times (<250 ms), the signal response curve displayed an increase in signal intensity or a plateau in signal intensity dependent on T1 relaxation time. Inclusion of this increase or plateau in signal intensity negatively impacted T1 fitting algorithms, leading to their failure or incorrectly calculated T1 values. The maximum peak signal intensity before the null point was found to be 210 ms, which impacts current low field T1 mapping protocols which use an initial inversion time of 80-110 ms.Validation of retrospectively calculated T1 as a biomarker in Multiple Sclerosis revealed that T1 of normal appearing brain tissue correlates with measures of Multiple Sclerosis progression (EDSS, BPF, and disease duration) with normal appearing white matter T1 correlating with BPF (r = -0.49, p = 0.0018); putamen T1 correlating with EDSS (r = 0.48, p = 2.40e-03), with BPF (r = 0.69, p = 2.04e-06), and disease duration (r = -0.37; p = 0.02); and globus pallidus T1 correlating with disease duration (r = -0.42; p = 0.0093). Lesion T1 is reflective of MS severity whereas MTR is not.Finally, development of an oxygen extraction fraction (OEF) mapping technique showed that application of independent component analysis (ICA) to cardiac gated spiral-trajectory phase images yielded components that feature stenosis features observed in magnitude images. These ICA components form the basis of OEF mapping from phase images. This dissertation presents four studies that seek to improve either current quantitative MR imaging protocols in the heart, or to develop and validate new quantitative MR imaging techniques in the brain for the purpose of monitoring disease progression or predicting disease.
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Title: Extremal and Enumerative Problems on DP-Coloring of Graphs
Creator: Sharma, Gunjan
Date: 2024
Description: Graph coloring is the mathematical model for studying problems related to conflict-free allocation of resources. DP-coloring (also known as...
Show moreGraph coloring is the mathematical model for studying problems related to conflict-free allocation of resources. DP-coloring (also known as correspondence coloring) of graphs is a vast generalization of classic graph coloring, and many more concepts of colorings studied in the past 150+ years. We study problems in DP-coloring of graphs that combine questions and ideas from extremal, structural, probabilistic, and enumerative aspects of graph coloring. In particular, we study (i) DP-coloring Cartesian products of graphs using the DP-color function, the DP coloring counterpart of the Chromatic polynomial, and robust criticality, a new notion of graph criticality; (ii) Shameful conjecture on the mean number of colors used in a graph coloring, in the context of list coloring and DP-coloring; and (iii) asymptotic bounds on the difference between the chromatic polynomial and the DP color function, as well as the difference between the dual DP color function and the chromatic polynomial, in terms of the cycle structure of a graph. These results respectively give an upper bound and a lower bound on the chromatic polynomial in terms of DP colorings of a graph.
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Title: Agency and Pathway Thinking as Mediators of The Relationship Between Caregiver Burden And Life Satisfaction Among Family Caregivers Of People With Parkinson’s Disease: An Application Of Snyder’s Hope Theory
Creator: Springer, Jessica Gabrielle
Date: 2024
Description: In the United States, there are 47.9 million caregivers providing care to family members with disabilities. Those providing care to someone...
Show moreIn the United States, there are 47.9 million caregivers providing care to family members with disabilities. Those providing care to someone who has Parkinson’s Disease (PD), a complex degenerative movement disorder, may have a unique caregiving experience, given that disease-related factors (e.g. motor and non-motor symptoms) can contribute to worsening caregiver burden and life satisfactions (LS). PD has an increasing incidence of 90,000 new cases per year, likely resulting in an increased need for caregivers. Caregiving research frequently focuses on the mediators between caregiver burden and LS including social support, coping skills, and appraisals. Research that has specifically focused on caregivers of people with PD (Pw/PD) is significantly limited. Hope is a “positive motivational characteristic comprised of agency and pathways thinking that can help facilitate drive towards one’s goal while also serving as a buffer against negative events” (Snyder et al.,1991). The goal of this study is to understand Snyder’s hope theory as it relates to caregiver burden and LS for caregivers of Pw/PD. Specifically, we hypothesized that (a) caregiver burden will be negatively correlated with agency thinking, pathways thinking, and LS among caregivers of Pw/PD. In addition, pathways thinking, and agency thinking will be positively associated with LS, and (b) agency thinking, and pathways thinking will mediate the relationship between caregiver burden and LS among caregivers of Pw/PD. The study sample consisted of 249 caregivers of Pw/PD who completed an online anonymous questionnaire. Correlations between agency and pathways thinking, LS, caregiver burden, and sociodemographic factors were evaluated. A parallel mediation analysis was run to evaluate the mediating roles of pathways and agency thinking in the relationship between caregiver burden and LS. Results indicated that LS was significantly and negatively correlated with caregiver burden. LS was significantly and positively correlated with both pathways and agency thinking. Pathways thinking had no indirect effect on the relationship of caregiver burden on LS. Agency thinking had a negative, indirect effect on the relationship suggesting that agency thinking partially mediated the relationship between caregiver burden and LS. Clinical implications and future directions are discussed.
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Title: Prediction and Control of In-Cylinder Processes in Heavy-Duty Engines Using Alternative Fuels
Creator: Pulpeiro Gonzalez, Jorge
Date: 2024
Description: This Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal...
Show moreThis Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal combustion (IC) engines, particularly heavy-duty engines utilizing alternative fuels. The research endeavors to contribute to the field of model-based control of engines through the development and implementation of innovative methodologies. The primary emphasis is on the development of diagnostic methods, control-oriented models and advanced control strategies for compression ignition engines using alternative fuels. The first key topic explores the determination of the Most Representative Cycle for Combustion Phasing Estimation based on cylinder pressure measurements. The method developed extracts crucial information from experimental data obtained from four distinct engines: the heavy-duty single-cylinder GCI engine, the light-duty multi-cylinder diesel engine, a CFR engine, and a single-cylinder light-duty Spark Ignition (SI) engine. This work lays the foundation for precise combustion phasing estimation, a critical parameter for engine control. The second major contribution involves the development of control-oriented models for Variable Geometry Turbochargers (VGT) and inter-coolers. Two models are established: a data-driven turbocharger model and an empirical inter-cooler model. These models are meticulously calibrated and validated using experimental data from a multi-cylinder light-duty diesel engine, providing valuable insights into the behavior of these components under varying conditions. The outcomes contribute to facilitate predictive control of engine air systems. The third core aspect of the thesis revolves around Model Predictive Control of Combustion Phasing in heavy-duty compression-ignition engines utilizing alternative fuels. A combustion phasing and engine load model is derived from experimental data and incorporated into an MPC framework. The MPC strategy is subsequently tested in the heavy-duty GCI test cell and compared against a conventional Proportional-Integral-Derivative (PID) control strategy. The results showcase the effectiveness of the MPC approach in achieving precise control of combustion phasing, demonstrating its potential for optimizing engine performance. In summary, this Ph.D. thesis contributes significantly to the field of engine controls by advancing diagnostic techniques, control-oriented models, and implementing a cutting-edge MPC-based control strategy for compression ignition engines using alternative fuels. The research findings not only enhance the understanding of in-cylinder processes but also pave the way for more efficient and sustainable heavy-duty engines using alternative fuels.
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Title: Independence and Graphical Models for Fitting Real Data
Creator: Cho, Jason Y.
Date: 2023
Description: Given some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m)...
Show moreGiven some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m) contingency table with nonzero rows or nonzero columns, we will be testing the goodness-of-fit of various independence models to the dataset using a variation of Metropolis-Hastings that uses Markov bases as a tool to get a Monte Carlo estimate of the p-value. This variation of Metropolis-Hastings can be found in Algorithm 3.1.1. Next we will consider the problem: ``out of all possible undirected graphical models each associated to some graph with m vertices that we test to fit on our dataset, which one best fits the dataset?" Here, the m attributes are labeled as vertices for the graph. We would have to conduct 2^(mC2) goodness-of-fit tests since there are 2^(mC2) possible undirected graphs on m vertices. Instead, we consider a backwards selection method likelihood-ratio test algorithm. We first start with the complete graph G = K(m), and call the corresponding undirected graphical model ℳ(G) as the parent model. Then for each edge e in E(G), we repeatedly apply the likelihood-ratio test to test the relative fit of the model ℳ(G-e), the child model, vs. ℳ(G), the parent model, where ℳ(G-e) ⊆ℳ(G). More details on this iterative process can be found in Algorithm 4.1.3. For our dataset, we will be using the alcohol dataset found in https://www.kaggle.com/datasets/sooyoungher/smoking-drinking-dataset, where the four attributes of the dataset we will use are ``Gender" (male, female), ``Age", ``Total cholesterol (mg/dL)", and ``Drinks alcohol or not?". After testing the goodness-of-fit of three independence models corresponding to the independence statements ``Gender vs Drink or not?", ``Age vs Drink or not?", and "Total cholesterol vs Drink or not?", we found that the data came from a distribution from the two independence models corresponding to``Age vs Drink or not?" and "Total cholesterol vs Drink or not?" And after applying the backwards selection likelihood-ratio method on the alcohol dataset, we found that the data came from a distribution from the undirected graphical model associated to the complete graph minus the edge {``Total cholesterol”, ``Drink or not?”}.
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Title: APPLYING THE PSYCHOLOGICAL FLEXIBILITY MODEL TO EXAMINE PREDICTORS OF ENGAGEMENT AND SUCCESS IN A WEIGHT MANAGEMENT PROGRAM FOR VETERANS
Creator: Pieczynski, Jessica
Date: 2015, 2015-07
Description: Weight management success is contingent upon treatment utilization and engagement. Unfortunately, low enrollment, poor attendance, and high...
Show moreWeight management success is contingent upon treatment utilization and engagement. Unfortunately, low enrollment, poor attendance, and high attrition from weight management programs are major barriers for long-term weight loss. This study aimed to applying the psychological flexibility model to the problem of weight management engagement. The current study evaluated the hypotheses that lower experiential avoidance, the process of changing, suppressing, or avoiding unpleasant experiences in an effort to regulate behavior, and higher values congruence, behaving consistently with one’s values, predict treatment engagement and successful weight loss. Participants were 183 overweight and obese veterans (91.3% Male, 77.6% African American). Participants completed a demographics questionnaire, the Acceptance and Action Questionnaire for Weight-Related Problems (AAQ-W) and the Valued Living Questionnaire (VLQ). Analyses revealed that experiential avoidance significantly predicted probability of enrolling (OR=1.03, p<.01). Experiential avoidance and values congruence were not significantly related to attendance, and experiential avoidance approached significance for dropout (OR=6.54, p=.08). AAQ-W was related to baseline BMI (β=7.49, p<.001) and 3-month BMI trajectory (β= 0.54, p<.01) for enrollees, while experiential avoidance predicted 3-month weight change for nonenrollees (β =0.28, p<.05). The extant research on weight management suggests that much can be done to improve treatment outcomes. Increasing engagement is a major component of improving weight management success. The findings from this study suggest that targeting psychological flexibility can be a means to achieving this goal. Future weight management research should continue to explore this relationship.
Ph.D. in Psychology, July 2015
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Title: SPECTRUM ALLOCATIONS ALGORITHMS IN WIRELESS NETWORKS
Creator: Xu, Ping
Date: 2011-04-26, 2011-05
Description: All wireless devices rely on access to the radio frequency spectrum, which has been chronically regulated by static spectrum allocation...
Show moreAll wireless devices rely on access to the radio frequency spectrum, which has been chronically regulated by static spectrum allocation policies. With the recent fast growing of spectrum-based services and devices, the remaining spectrum available for future wireless services is being exhausted, known as the spectrum scarcity problem. The current fixed spectrum allocation scheme leads to significant spectrum white spaces (including spectral, temporal, and geographic), where many allocated spectrum blocks are used only in certain geographical areas and/or in brief periods of time. In this work, we design and analyze variant spectrum allocation algorithms for better spectrum utilization and study some fundamental performance bounds for networks with opportunistic spectrum utilization. We first propose spectrum allocation algorithms for offline model, in which all spectrum requests are known when allocation decision is made. Then we also addresse the problems in online model, where allocation decision should be made when only a few spectrum requests are known. In the online model, we focus on two different cases. The first one assumes no statistic of future spectrum requests are known, and the second one assumes some statistic is known or can be learned. For all these models, we design efficient spectrum allocation methods and analytically prove most of them are asymptotically optimal. Our extensive simulation results also verify our theoretical conclusion.
Ph.D. in Computer Science, May 2011
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Title: EFFECTIVENESS OF CLEANlNG REGIMENS FOR REMOVlNG MILK RESIDUE FROM A PILOT -SCALE HTST PROCESSING LINE
Creator: Du, Qian
Date: 2011-11-30, 2011-12
Description: Undeclared allergens can be introduced into foods due to cross-contact during manufacture. Effective cleaning is essential for preventing...
Show moreUndeclared allergens can be introduced into foods due to cross-contact during manufacture. Effective cleaning is essential for preventing allergen cross-contact on shared processing lines. The objectives of this project were to evaluate the effectiveness of cleaning treatments on removing milk residue from a pilot-scale HTST processing line, and measure the levels of milk transferred into juice processed on an inadequately cleaned processing line. Nonfat milk was processed (81ºC,17 sec) on an HTST processing line followed by several cleaning regimens including 1) a 15 min water flush, 2) a 15 min water flush + a 60 min wash using full-strength chlorinated alkaline detergent (CAD) at 81ºC and a flow rate of 55-60 gal/h , 3) a 15 min water flush + a 60 min wash with ¼-strength CAD at 81ºC and flow rate of 55-60 gal/h, 4) a 15 min water flush + a 15 min full-strength CAD at 81ºC and flow rate of 55-60 gal/h, 5) a 15 min water flush + a 60 min full-strength CAD at 70ºC and flow rate of 55-60 gal/h, 6) a 15 min water flush + a 60 min full-strength CAD at 81ºC and flow rate of 27.7 gal/h, 7) a 15 min water flush + a 60 min full-strength CAD containing 1% milk at 81ºC and flow rate of 55-60 gal/h, 8) a a full cleaning cycle (15 min water flush + 60 min full-strength CAD at 81 ºC + 15 min water flush + 30 min acid detergent at 70 ºC + 15 min water flush + 15 min flush with 200 ppm sodium hypochlorite sanitizer at room temperature, flow rate of 55-60 gal/h). After each cleaning treatment, simulated apple juice was processed on the same processing line, collected and tested for presence of milk using a quantitative ELISA. The adequacy of the cleaning treatments was also assessed by determining the absence/presence of milk residue in sampling ports located in the processing line with ATP swabs, protein swabs and a milk-specific lateral flow kit. All clean treatments and analyses were done in triplicate. Milk was detected at levels of 59-150 μg/mL (ppm) in simulated apple juice processed on the HTST line after a 15 min water flush. No milk was detected in juice processed on the line cleaned with full-strength CAD or a full cleaning cycle. Lower milk levels in apple juice were detected with some of the intermediate cleaning regimens (¼-strength CAD, shorter cleaning time, reduced temperature of CAD, lower flow rate 27.7 gal/h of CAD cleaning and CAD with 1% milk). Swabs of sampling ports revealed the presence of milk/protein residue and high ATP levels after the water flush. Cleaning treatments using full-strength CAD reduced ATP levels and resulted in the no detectable of protein/milk residue in most sampling ports and in simulated apple juice. Reuse of CAD containing high levels of milk may result in milk cross-contact into juice subsequently processed on the milk processing line. This work illustrates the importance of validated cleaning procedures to prevent allergen cross-contact on shared processing lines.
M.S. in Food Safety and Technology, December 2011
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Title: FIBRONECTIN INFLUENCES THE RATE OF ASSEMBLY AND STRUCTURAL CHARACTERISTICS OF THE FIBRIN MATRIX AND A MAP OF LYSINE PEGYLATION SITES IN FIBRONECTIN
Creator: Ramanathan, Anand
Date: 2015, 2015-07
Description: Fibronectin serves multiple roles during tissue formation and wound healing, functioning through interactions with cells and extracellular...
Show moreFibronectin serves multiple roles during tissue formation and wound healing, functioning through interactions with cells and extracellular molecules. The overall objective of my research was to investigate fibronectin biochemistry on responses associated with wound healing. My approach was to engineer relevant in vitro models highlighting fibronectin functionality in tissues and link this work to more complex wound healing systems. My research goals were accomplished through the following three specific aims: (1) Determine the role of fibronectin on the kinetics of formation and structure of a fibrin-fibronectin matrix, (2) Determine the effect of protease on the activity of fibronectin in decellularized extracellular matrices and (3) Map the sites of polyethylene glycol conjugation or PEGylation to lysine residues in fibronectin. Aim 1: I demonstrated that fibronectin increased the initial rate of fibrin matrix formation and altered the fibrin matrix structure. These findings are novel because they link results from light absorbance studies to microcopy analyses and demonstrate the influence of fibronectin on fibrin matrix structural characteristics. Aim 2: I demonstrated a link between fibronectin proteolysis and reduced cell adhesion in decellularized extracellular matrices. This study demonstrates the susceptibility of fibronectin to proteolysis in the extracellular matrix and the resulting loss of matrix functionality, placing weight on bioengineering strategies to stabilize fibronectin against proteolysis. Aim 3: I examined proteolytic fragments of native and PEGylated fibronectin to map fibronectin lysine residues that are conjugated PEG. From four key chymotryptic fragments that span fibronectin and are recognized by specific monoclonal antibodies, I provide a map of lysine PEGylation sites for fibronectin. Moreover, I show that lysine PEGylation of fibronectin occurs asymmetrically on the dimer arms. Knowledge of the lysine PEGylation sites can be used to plan future experiments for investigating fibronectin biochemical interactions in complex in vitro and in vivo models. In accomplishing these specific aims, I identified key biomolecular mechanisms involving fibronectin and created relevant in vitro models to study these interactions. The work detailed in this thesis lays the foundation for future experiments to investigate fibronectin functionality and develop therapeutic strategies targeting fibronectin biochemistry in tissue development.
Ph.D. in Chemical Engineering, July 2015
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Title: EFFECTS OF FUEL PROPERTIES ON THE COMBUSTION PROCESS OF AN ADVANCED DIESEL ENGINE
Creator: Ramos Silva, Cedric Zacarias
Date: 2015, 2015-12
Description: Internal combustion engines are encountered in our everyday lives in passenger cars and heavy-duty vehicles such as trucks and buses. While...
Show moreInternal combustion engines are encountered in our everyday lives in passenger cars and heavy-duty vehicles such as trucks and buses. While conventional compression ignition engines burn diesel fuel with an oxidizer (generally air) in a combustion chamber, much recent research has focused on improving the efficiency of combustion and reducing vehicle pollutant output through the usage of fuels with properties which differ from those of diesel fuel. In particular, this study focuses on a dual fuel engine in which two fuels (usually gasoline or diesel fuel mixed with an alternate fuel) are separately injected and combusted. Results from an Argonne National Laboratory test cell utilizing a 13 Liter (L) heavy duty dual fuel engine running in a combustion mode known as Reactivity Controlled Compression Ignition (RCCI) were leveraged in this work. In a RCCI engine, two fuels of different reactivities (low reactivity and high reactivity) are used in order to control in-cylinder fuel reactivity and allow for the optimization of combustion phasing and duration. In addition, RCCI combustion has been shown to produce low amounts of nitrogen oxides (NOx) as well as particulate matter (PM) emissions which may eliminate the need for expensive after-treatment systems. The combustion shaping capabilities and low emissions of RCCI dual fuel engines enable reductions in heat transfer losses and as such the increase of fuel efficiency. In order to understand the dynamics of such engines, a detailed simulation model of a RCCI dual fuel engine was constructed and developed using the Gamma Technologies (GT) simulation suite in particular GT-POWER and GT-SUITE. Modeling of the complex gas exchange process as well as the combustion process of the 13L RCCI dual fuel engine were both undertaken. This model was then leveraged to examine the effect of fuel properties on the combustion process using GT simulation suite. Experimental data from the 13L engine at Argonne was used to validate the models of the gas exchange and combustion processes. For the gas exchange process as well as the combustion process, the results from the simulation model fairly accurately match the experimental data from the Argonne engine. To achieve RCCI, the engine is equipped with a complex air handling system which includes two turbochargers as well as exhaust gas recirculation (EGR). To ensure that the gas exchange process was accurately captured, the experimental intake pressure, EGR fraction (EGR mass flow rate divided by the sum of EGR mass flow rate and air mass flow), fresh airflow rate, maximum in-cylinder pressure, IMEP and exhaust pressure were compared with the simulation results given by GT-POWER and GT-POST. By modeling the engine components in GT-POWER and adding additional control algorithms, the previously mentioned parameters predictions were within 10% of the engine data. The combustion process was modeled using a Direct-Injection Jet (DI-Jet) combustion model. The DI-Jet model is a predictive combustion model which predicts the burn rate, combustion rate and NOx emissions. This model was calibrated by comparing the experimental and simulation heat release curves. Particular attention is given to accurately capturing the start of combustion and ignition delay period because they affect the combustion process the most.
M.S. in Mechanical and Aerospace Engineering, December 2015
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Title: MOTIVES FOR SOCIAL MEDIA USE AMONG PRACTITIONERS AT NONPROFIT ORGANIZATIONS
Creator: Roback, Andrew J.
Date: 2017, 2017-05
Description: I used the motivation concept from activity theory to derive a fundamental notion of why workers at nonprofit organizations (NPOs) use social...
Show moreI used the motivation concept from activity theory to derive a fundamental notion of why workers at nonprofit organizations (NPOs) use social media sites. This study rejects the notion that practitioners are not taking full advantage of social media sites by not using every available feature and engaging in dialogic communication. Existing work relies too extensively on the dialogic model of communication and frequently focuses on only top-tier NPOs, ignoring the context in which smaller NPOs operate and producing recommendations that are of little practical value. To investigate this issue, I reviewed existing best practices as portrayed in NPO social media strategy guides, and used the principles of activity theory to survey practitioners at human services NPOs in Chicago. I collected data on user motivation for using Facebook and Twitter by asking users to review past posts on these sites and describe their purpose in posting this information. Using this information, I trained an automated text classifier to classify a large corpus of posts based on four types of motivations: soliciting, promoting, sharing, and credit-giving. This dissertation builds off recent studies that question existing wisdom on “effective” use of social media by NPOs and argues for an expanded consideration of user agency and intent when using social media.
Ph.D. in Technical Communication, May 2017
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Title: DEVELOPING METHODS TO IDENTIFY SURROGATES FOR ESCHERICHIA COLI O157:H7 IN VALIDATION OF FRESH PRODUCE WASHING PROCESSES
Creator: Rolfe, Catherine
Date: 2016, 2016-07
Description: Cross-contamination during fresh produce washing is commonly prevented using chlorine treatment. Surrogate microorganisms have been widely...
Show moreCross-contamination during fresh produce washing is commonly prevented using chlorine treatment. Surrogate microorganisms have been widely used in process validation and to assess microbial cross-contamination. Fresh produce washing incorporates physical, chemical, biological and kinetic factors which create an intricate process for which little is known regarding surrogate selection. The purpose of this study was to identify the important elements relevant to produce washing processes and identify methods that will be used in surrogate selection. The behavior of three (3) non-pathogenic microorganisms (generic E. coli Nissle 1917 EcN, Pediococcus pentosaceus and lettuce isolate 813-F1) were examined in comparison to E. coli O157:H7 based on phenotypic similarities. Chlorine inactivation kinetics of E. coli O157:H7 and the non-pathogenic strains were evaluated with varying pH levels (6.5 and 8.0) and exposure times (3-30 seconds). Detachment of leaf-bound E. coli O157:H7 and non-pathogenic strains at different inoculation levels (approximately 2 and 6 log CFU/mL) and drying conditions (aging time, temperature) in wash water was examined. Chlorine inactivation at pH 6.5 resulted in a range of viability corresponding to E. coli O157:H7 and the non-pathogenic strains; demonstrating a sharp inactivation curve for E. coli O157:H7, EcN and P. pentosaceus. Whereas, inactivation at pH 8.0 allowed more survival relating to exposure time for all microorganisms. Detachment from inoculated leaves at 2 and 6 log CFU/mL inoculation showed steady survival levels in wash water at 0 ppm and lower survival at 1 ppm for all strains excluding 813-F1; 813-F1 was consistently less chlorine-sensitive in chlorine inactivation assays and more cross-contamination to wash water was observed for this strain. Aging time of inoculated bacteria on leaves was not seen to have remarkable effects on bacterial transfer during washing. These results suggest assay methods of chlorine inactivation at pH 6.5 and detachment with 6 log CFU/mL initial inoculation may be useful in selecting appropriate surrogates for fresh produce washing.
M.S. in Food Safety and Technology, July 2016
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Title: AUTOMATED SLICING METHODS FOR LARGE EVENT TRACES
Creator: Smith, Raymond D.
Date: 2012-05-02, 2012-05
Description: Many long-running computer systems record events as they execute, resulting in a dynamic record of system behavior. In large systems, the...
Show moreMany long-running computer systems record events as they execute, resulting in a dynamic record of system behavior. In large systems, the event trace may contain thousands of entries and when faced with a problem for analysis, programmers must sort through many disparate events to find those that are related to the system behavior under study and eliminate those that are not. In this research we investigated automatic reduction of event traces to reduce the volume of events and assist in analysis of behavior of large systems. Our approach was to adapt the techniques used in program slicing to compute event trace slices as a means of reduction. Two methods for slicing of event traces were proposed and investigated. The Event Dependence Based method (EDB) uses information available in the event trace to identify dependencies between events and to compute an event trace slice that meets a slicing criterion. The Model Dependence Based method (MDB) incorporates the use of an executable state-based system model to achieve further reduction of traces. The method identifies model-based dependences in the trace to compute trace slices. An experimental study was performed on simulated systems, representative of state-based software systems present in industry to analyze and compare the EDB and MDB slicing methods. Both methods provided significant reduction of event traces, particularly for systems with a low degree of sharing and interaction among resources. However, the MDB method significantly outperformed the EDB method for systems with a high degree of resource sharing.
Ph.D. in Computer Science, May 2012
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Title: RENEWABLE ENERGY IN MICROGRID: A STOCHASTIC OPTIMIZATION APPROACH
Creator: Jin, Hongwei
Date: 2014, 2014-12
Description: A Microgrid is a group of interconnected loads and distributed energy resources within clearly defined electrical boundaries that acts as a...
Show moreA Microgrid is a group of interconnected loads and distributed energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid and that connects and disconnects from such grid to enable it to operate in both grid-connected or island mode. The optimized energy scheduling problem is significant to both utilities and community consumers. In this thesis, I present an approach by analyzing the historical weather data and renewable energy data, and build a two-stage stochastic program with a long term view towards minimizing costs. The underlying stochastic process that generates uncertainty in demand and supply in power network is the local weather, thus understanding solar radiation as a function of weather is significant to us. First, two simple methods, which are majority rule and flexible time selection, are proposed with the purpose of handling noisy raw data and giving a relatively precise prediction of renewable energy consumption and overall energy demands. Then, I implement a deterministic strategy, a two-stage stochastic program and a repeated stochastic program using AMPL, a mathematical modeling language. Every stochastic program is defined as based on 42 scenarios from the weather conditions. In the final step, I solve the model using CPLEX and compare optimal solutions based on a year-long Monte Carlo simulation. Ignoring installation and maintenance costs, the Microgrid can make some profit by an optimized control based on our modeling approach utilizing the stochastic optimization paradigm. Although there are only slight differences between three models, the repeated two-stage stochastic model gives the best long-term results.
M.S. in Applied Mathematics, December 2014
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Title: GENDER DIFFERENCES IN POSTCONCUSSIVE SYMPTOMS OF SPORT-RELATED CONCUSSIONS IN CHILDREN AND ADOLESCENTS
Creator: Gretencord Roy, Ashley Aline
Date: 2016, 2016-07
Description: Current research on concussions indicates that both younger age and female gender are associated with a greater number of symptoms and a...
Show moreCurrent research on concussions indicates that both younger age and female gender are associated with a greater number of symptoms and a lengthier postconcussive recovery time. The aim of this research was to examine postconcussive symptoms (PCS) resulting from a sports-related concussion in both male and female children/adolescents. Data was collected using neuropsychology measures (Auditory Consonant Trigrams Test, Conners' Continuous Performance Test-2nd edition, Immediate Post-Concussion Assessment and Cognitive Testing, Woodcock Johnson Tests of Achievement- Third Edition, and Behavior Assessment System for Children-2nd edition) and a neurological evaluation. Participants included 132 children/adolescents (10-18 years) who had sustained a sports-related concussion. Results indicated evidence of subtle, but clinically significant, impairments in executive functioning. This was particularly true for those with a premorbid attention, learning, and/or mood disorder. In addition, a history of previous concussions was associated with a higher number of reported cognitive PCS. Hierarchical regression analyses were conducted for each of the dependent measures. As predicted, female gender was associated with increased executive dysfunction and a higher report of cognitive and emotional/behavioral PCS. Contrary to hypotheses, younger age was associated with less executive dysfunction and fewer reported cognitive PCS. No interaction between age and gender was identified. Implications of the findings are discussed.
Ph.D. in Psychology, July 2016
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Title: OPTIMAL TRANSMISSION SWITCHING AND SECURITY-CONSTRAINED UNIT COMMITMENT CONSIDERING DEMAND-SIDE PARTICIPATION
Creator: Ma, Ruicheng
Date: 2015, 2015-05
Description: Transmission topology is traditionally considered as fixed elements in electrical system. Transmission line states used to be presumably set...
Show moreTransmission topology is traditionally considered as fixed elements in electrical system. Transmission line states used to be presumably set as closed for the whole system, or sometimes open for security check purposes. In the development of a smart grid, however, the optimization of the use of transmission has been proposed as an advanced transmission technology. Optimal transmission switching (OTS) is a straightforward method to enhance grid controllability: to mitigate transmission violation, re-dispatch power generation, and meet changing demand with existing infrastructure. Previous papers have shown that co-optimization of generation and transmission problem will improve the economic performance. This thesis provides the formulation and solution methodology for applying OTS in day-ahead security-constrained unit commitment (SCUC) scheduling. Base case and contingency case are examined to ensure the feasibility of the solution. The OTS applications also consider the demand-side participation such as demand response (DR) and renewable energy. The results are presented based on a modified 6-bus system.
M.S. in Electrical Engineering, May 2015
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Title: BLAME, COPING, AND PYCHOSOCIAL OUTCOMES IN CAREGIVERS OF FAMILY MEMBERS WITH ACQUIRED BRAIN INJURY
Creator: Dedios-stern, Samantha L.
Date: 2015, 2015-05
Description: Acquired brain injury (ABI) is associated with many physical and psychiatric conditions. Oftentimes, the individual’s family members are...
Show moreAcquired brain injury (ABI) is associated with many physical and psychiatric conditions. Oftentimes, the individual’s family members are responsible for providing long-term care, leaving caregivers vulnerable to negative effects of caregiving including stress, physical, and psychological problems. Attribution theory suggests that when individuals experience distress, they may generate causal explanations for their circumstances by attributing blame regarding why the event happened. Frequently, blame attributions involve identifying the problem as being within another person. The objective of this study was to investigate caregiver coping strategies as possible mediators between caregiver family member blame and caregiver psychosocial outcomes among caregivers of individuals with ABI. Caregivers of individuals with ABI (n = 94) completed a brief online survey of self-report measures regarding coping (emotion-focused, problemfocused, and dysfunctional strategies), blame (direct, indirect, and preoccupation with blame), depressive symptoms, and quality of life (QOL). Bootstrapping mediation analyses were then conducted to investigate the mediating role of caregiver coping strategy between blame attributions, and either depressive symptoms or QOL. Results demonstrated that the use of more dysfunctional coping strategies significantly mediated the relationship between indirectly blaming one’s family member for their injury and subsequent depressive symptoms and QOL. Furthermore, using more dysfunctional coping strategies also significantly mediated the relationship between preoccupation with blame and depressive symptoms. Implications for intervention and future research are discussed.
M.S. in Psychology, May 2015
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