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Title: Expanding the Magic Circle and the Self: Integrating Discursive Topics into Games
Creator: da Rosa Faller, Roberto
Date: 2020
Description: This study focuses on games for self-development and how they communicate ideas, challenge established assumptions, cause reflection, and...
Show moreThis study focuses on games for self-development and how they communicate ideas, challenge established assumptions, cause reflection, and provoke change. It explores the integration of discursive topics – specifically those perceived as difficult, political, philosophical, taboo, or controversial – into games, and how to manage player exposure to these topics through design while avoiding player disengagement to achieve self-development goals. Using a Research Through Design approach, this study was conducted in two phases. The first exploratory phase resulted in an analytical framework with four distinct lenses: engaging play experience; player’s emotional investment; the friction points of discursive topics; and, controlled exposure to the topic. During the second phase, this framework was used to analyze eight case studies and three prototypes. The resultant insights from analysis revealed five categories – topic depiction, emotional climate, emotional anchors, topic delivery, and exposure timing – that form the Discursive Topic Integration Framework for self-development. This framework offers a new theoretical perspective for design scholars and practicing designers about how to manipulate the “magic circle” (a safe temporary space for the act of play), by intentionally designing for discursive topics and their friction points. It contributes strategies about when, how, how frequently, and with what intensity discursive topics may be introduced and abstracted in games. It frames the discursive topic, creates the emotional climate, and anchors the player inside the magic circle of the game so that they feel engaged, motivated, and curious without becoming overwhelmed. This study also generated two additional frameworks, including: the Self-Development Opportunity Matrix that can be used to generate or evaluate self-development goals; and, the Five Categories of Transitional and Traumatic Experiences that can assist in the design of games and other experiences that build a person’s capacity, self-determination, and commitment to positive change.
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Title: Development of a novel ultra-nanocrystalline diamond (UNCD) based photocathode and exploration of its emission mechanisms
Creator: Chen, Gongxiaohui
Date: 2020
Description: High quality electron sources are one of the most commonly used probing tools used for the study of materials. Photoemission cathodes, capable...
Show moreHigh quality electron sources are one of the most commonly used probing tools used for the study of materials. Photoemission cathodes, capable of producing ultra-short and ultra-high intensity beams, are a key component of accelerator based light sources and some microscopy tools. High quantum efficiency (QE), low intrinsic emittance, and long lifetime (or good vacuum tolerance) are three of the most critical features for a photocathode; however, these are difficult to achieve simultaneously and trade-offs need to be made for different applications. In this work, a novel semi-metallic material of nitrogen-incorporated ultrananocrystalline diamond ((N)UNCD) has been studied as a photocathode. (N)UNCD has many of the unique diamond properties, such as low intrinsic as-grown surface roughness (at the order of 10~nm) due to its nanometer scale crystalline size, relatively long lifetime in air, high electrical conductivity with nitrogen doping, and potentially high QE performance due to the high grain boundary densities where most of electron emission occurs. High contrast interference of incident and reflected radiation within (N)UNCD thin films was observed, and this feature allows fast thickness determination based on an analytical optics methodology. This method has been extended to study and calculate the etching rates of two commonly used O$_2$ and H$_2$ plasmas for use with future (N)UNCD microfabrication processes. The mean transverse energy (MTE) of (N)UNCD was determined over a wide UV range in a DC photogun. Unique MTE behavior was observed; it did not scale with photon energy unlike most metals. This behavior is associated with emission from spatially-confined states in the graphite regions (with low electron effective mass) between the diamond grains. Such behavior suggests that beam brightness many be increased by the simple mechanism of increasing the photon energy so that the QE increases, while the MTE remains constant.Two individual (N)UNCD photocathodes synthesized two years apart have been characterized in a realistic RF photogun. Both the QE and intrinsic emittance were characterized. It was found that the QE of $\sim4.0\times 10^{-4}$, is more than an order of magnitude higher than that of most commonly used metal cathodes (such as Cu and Nb). The intrinsic emittance (0.997~$\mu$m/mm) is comparable to that of photocathodes now deployed in research accelerators. The most impressive feature is the excellent robustness of (N)UNCD material; there was no evidence of performance degradation, even after years-long atmospheric exposure. The results of this work demonstrate that a cathode made of (N)UNCD material is able to achieve balanced performance of three of the primary critical photocathode figures-of-merit.
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Title: H1 LUBRICANT TRANSFER FROM A HYDRAULIC PISTON FILLER INTO A SEMI-SOLID FOOD SYSTEM
Creator: Chao, Pin-Chun
Date: 2020
Description: The machinery used to prepare, and process food products need grease and oil for the lubrication of machine parts. H1 (food-grade) lubricants...
Show moreThe machinery used to prepare, and process food products need grease and oil for the lubrication of machine parts. H1 (food-grade) lubricants commonly used in the food industry are regulated as indirect additives by the FDA because they may become components of food through transfer due to incidental contact between lubricants and foods. The maximum level of H1 lubricants currently permitted in foods is 10 ppm, which was derived from FDA data gathered over 50 years ago. Although modern equipment has been designed to minimize the transfer of lubricants during processing and packaging, incidental food contact can still occur resulting from leaks in lubrication systems or over-lubrication. However, there is a lack of data for the FDA to evaluate and determine whether safety issues in the aspect of chemical contamination should be addressed concerning the use of food-grade lubricants in the production of foods. This research was conducted to determine the transfer of an H1 lubricant (Petrol-Gel) into a semi-solid model food from a hydraulic piston filler during conventional operating conditions at 25°C and 50°C. Xanthan gum solutions with concentrations of 2.3% at 25°C and 1.9% at 50°C were used to simulate the viscosity of ketchup at 50°C (970 cP). Petrol-Gel H1 lubricant with a viscosity grade of 70 cSt at 40°C was selected and the aluminum (Al) in the lubricant was targeted as a tracer metal. Analytical methods to quantify Al in both Petrol-Gel and xanthan gum solutions were successfully developed and validated by using inductively coupled plasma – mass spectrometry (ICP-MS) combined with microwave-assisted acid digestion technique. The concentration of Al in the Petrol-Gel was determined to be 3103 ± 26 μg/g. A total of 1.35 g of Petrol-Gel was applied to four ring gaskets in the filler, and 50 g samples of xanthan gum solution were collected into a 100-mL polypropylene tube (DigiTube) with low leachable metals during 500 filling cycles (the full capacity of the piston filler hopper).Results showed that the concentrations of Petrol-Gel transferred into 2.3% xanthan gum solution at 25°C ranged from 1.6 to 63.5 μg/g. A total of 64.47 mg of the applied Petrol-Gel (1.35 g) was transferred into 25 liters of the solution. The average concentration of Petrol-Gel in 2.3% xanthan gum solution was calculated to be 2.84 μg/g, which was lower than the current regulatory limit of 10 ppm. In general, the transfer of Petrol-Gel during the first 100 filling cycles was higher at 50°C than at 25°C. The concentration of Petrol-Gel transferred into 1.9% xanthan gum solution at 50°C for the first 100 filling cycles ranged from 1.6 to 35.06 μg/g and was 6.37 μg/g on average. This research will help FDA to calculate more realistic limits of the H1 lubricants permissible in foods at modern food processing conditions as well as estimate consumer dietary exposure to these indirect food additives.
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Title: WASTEWATER COLLECTION SYSTEM MODELING: TOWARDS AN INTEGRATED URBAN WATER AND ENERGY NETWORK
Creator: Wang, Xiaolong
Date: 2020
Description: Wastewater collection systems, among the oldest features of urban infrastructure, are typically dedicated to collect and transport wastewater...
Show moreWastewater collection systems, among the oldest features of urban infrastructure, are typically dedicated to collect and transport wastewater from users to water resource recovery facilities (WRRFs). Since the 1970s, wastewater engineers and scientists have come to understand that wastewater collection systems can bring benefits for urban water and energy networks, including thermal energy recovery and converting pipelines to bioreactors. However, there is little knowledge about the temporal and spatial changes of collection systems parameters that are important for these applications. Furthermore, the vast majority of existing studies of these applications have focused on laboratory or extremely small-scale systems; there have been few studies about beneficial applications associated with large-scale systems. The purpose of this study is to increase our understanding of how urban wastewater collection systems can bring potential benefits to urban water and energy systems. Models describing wastewater hydraulics, temperature, and water quality can provide valuable information to help evaluate thermal energy recovery and wastewater pretreatment feasibility. These kinds of models, and supporting data from a case study, were used in this study; sizes of the theoretical wastewater collection systems range from 2.6 L/s to 52 L/s, and the sample locations of the case study had flows ranging from 2.3 L/s to 24.5 L/s. A cost-benefit analysis of wastewater source heat pumps was used to evaluate the thermal energy recovery feasibility for different sizes of wastewater collection systems. Results show that the large collection system can support a large capacity heat pump system with a relatively low unit initial cost. Small collection systems have a slightly lower unit operating cost due to the relatively high wastewater temperature. When the heat pump system capacity design was based on the average available energy from the collection system, larger systems have lower payback times; the lowest payback time is about 3.5 years. The wastewater quality model was used to describe the dissolved oxygen (DO) and organic matter concentrations changes in the collection system. The model provides a framework for predicting pretreatment capability. Model results show that DO concentration is the limiting parameter for organic matter removal. Larger collection systems can provide more organic matter removal because they provide relatively longer retention times, and they offer the potential for greater DO reaeration. The model can also be used to identify environmental conditions in sewer pipelines, providing information for potential issues predication.
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Title: COMPREHENSIVE ANALYSIS OF EXON SKIPPING EDITS WITHIN DYSTROPHIN D20:24 REGIONS
Creator: Niu, Xin
Date: 2020
Description: Exon skipping is a disease modifying therapy that operates at the RNA level. In this strategy, oligonucleotide analog drugs are used to...
Show moreExon skipping is a disease modifying therapy that operates at the RNA level. In this strategy, oligonucleotide analog drugs are used to specifically mask specific exons and prevent them from being included in the mature mRNA. Exon skipping can also be used to restore protein expression in cases where a genetic frameshift mutation has occurred, and this how it is applied to Duchenne muscular dystrophy, DMD. DMD most commonly arises as a result of large exonic deletions that juxtapose flanking exons of incompatible reading frame, which abolishes dystrophin protein expression. This loss leads to the pathology of the disease, which is severe, causing death generally in the second or third decade of life. Here, the primary aim of exon skipping is to restore the reading frame by skipping an exon adjacent to the patient’s original. While restoring some protein expression is good, how removing some region from the middle of protein affects its structure and function is unclear. Complicating this in this case is that the dystrophin gene is very large, containing 79 exons. Many different underlying deletions are knowns, and exon skipping can be applied in many ways. It has previously been shown that many exon-skip edits result in structural perturbations of varying degrees. Very few studies are focused on the protein biophysical study and it is still basically unclear whether and how such editing can be done to minimize such perturbations. In order to provide the solid evidences which prove the significant variation among those cases (especially for the clinically relevant cases) and better understanding the general principles of “what makes a good edit”, we examine a systematic and comprehensive panel of possible exon edits in a region of the dystrophin protein. The domain D20:24 of dystrophin rod region are selected for its entirety which is separated by hinge region (mostly random coiled structure) and addition of other STRs will not disrupt the structure stability. Also D20:24 regions lie in the Hot Spot region II (HS2) which holds the most number of DMD patients. During the comprehensive scan, we identify for the first time, exon edits that appear to maintain structural stability similar to wild-type protein and those clinically relevant edits. Then we figure out the factors that appear to be correlated with the degree of structural perturbation, such as the number of cooperative protein domains, as well as how the edited exon structure interacts with the protein domain structure. Our study is the first systematic and comprehensive scan for an entire multiple STRs domain. This would help us understand the protein nature of various exon skipping edits and provide useful target for clinical treatment. Also the knowledge we learned may be applied to produce more sophisticated CRISPR edits in the future work.
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Title: Development of Human Brain Atlas Resources
Creator: Qi, Xiaoxiao
Date: 2020
Description: Digital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers,...
Show moreDigital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers, training data for machine learning algorithms, functional connectivity analysis and so on. A brain atlas typically consists of brain templates of different imaging modalities that are representative of individual brains under study in a standard atlas space and semantic labels that delineate brain regions according to the characteristics of the underlying tissue.The IIT Human Brain Atlas project has developed the state-of-the-art diffusion tensor imaging (DTI) template, high angular resolution diffusion imaging (HARDI) template, and anatomical templates for the young adult brain in a standardized space. The probabilistic maps of gray matter (GM) labels and tissue segmentations were also constructed based on the anatomical information of the atlas. This thesis introduced an enhanced T1-weighted template that were developed by combining information from both diffusion and anatomical data. The GM labels and tissue segmentation maps in the standardized space were also improved. Existing white matter (WM) atlases typically lack specificity in terms of brain connectivity. A new approach named regionconnect was developed in this work based on precalculated average healthy adult brain connectivity information stored in standard space in a fashion that allows fast retrieval and integration. This thesis first generated and evaluated the white matter connectome of the IIT Human Brain Atlas v.5.0. Next, the new white matter connectome was used to develop multi-layer, connectivity-based labels for each white matter voxel of the atlas, consistent with the fact that each voxel may contain axons from multiple connections. The regionconnect algorithm was then developed to rapidly integrate information contained in the multi-layer labels across voxels of a white matter region and to generate a list of the most probable connections traversing that region. The regionconnect algorithm as well as the white matter tractogram and connectome, multi-layer, connectivity-based labels, and associated resources developed for the IIT Human Brain Atlas v.5.0 in this work are available at www.nitrc.org/projects/iit. Furthermore, it was well established that use of a young adult atlas in studies of older adults is inappropriate due to the age-related characteristic changes of the brain, resulting in an increasing demand of digital brain atlases for the older adults. To fulfill this demand, a function of fiber orientation distribution (fODF) template that is representative of older adults was developed in a standardized atlas space for studies of white matter of older adult human brains, which built a solid foundation for the development of the white matter resources for the older adults human brain atlas.
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Title: AMPLIFICATION AND PURIFICATION OF RECOMBINANT PRO-DEATH BAXΔ2 PROTEINS FOR STRUCTURE ANALYSIS
Creator: Zhou, Yi
Date: 2020
Description: BaxΔ2 is an isoform of the pro-apoptotic Bax family of proteins, which is an important anti-cancer protein. BaxΔ2 behaves differently from...
Show moreBaxΔ2 is an isoform of the pro-apoptotic Bax family of proteins, which is an important anti-cancer protein. BaxΔ2 behaves differently from Baxα to induce apoptosis. The current computationally predicted model of BaxΔ2 is based on known Baxα structure, which is considered biased. Therefore, the elucidation of the BaxΔ2 crystal structure is critical. The goal of this project was to obtain a sufficient amount of purified recombinant Bax∆2 protein for crystallization. We cloned full-length BaxΔ2 fused with a poly-histidine tag on either N-terminus (His-Bax∆2) or C-terminus (Bax∆2-His) into an inducible bacterial expression vector. We found that His-Bax∆2 proteins were expressed better than Bax∆2-His, which totally inhibit host growth. However, the protein concentration of His-Bax∆2 was still too low to be detected by Coomassie blue staining. To increase His-Bax∆2 expression and avoid cytotoxicity, we further tested different bacterial host cells and applied the chaperone system. However, all attempts could not overcome Bax∆2 cytotoxicity and the protein expression levels were not high enough to be feasible for further large-scale purification. The mechanism underlying how Bax∆2 inhibits bacterial growth is still a mystery because Bax∆2 eukaryotic targets (mitochondria and caspases) do not exist in bacteria. Further experiments are required to explore the mechanism of Bax∆2 cytotoxicity in bacteria, so as to finally optimize and elevate the BaxΔ2 protein yields.
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Title: 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: 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: 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: 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: 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: Defense-in-Depth for Cyber-Secure Network Architectures of Industrial Control Systems
Creator: Arnold, David James
Date: 2024
Description: Digitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To...
Show moreDigitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To achieve these gains, the Internet of Things (IoT) has become an integral component of network infrastructures. However, integrating embedded devices expands the network footprint and softens cyberattack resilience. Additionally, legacy devices and improper security configurations are weak points for ICS networks. As a result, ICSs are a valuable target for hackers searching for monetary gains or planning to cause destruction and chaos. Furthermore, recent attacks demonstrate a heightened understanding of ICS network configurations within hacking communities. A Defense-in-Depth strategy is the solution to these threats, applying multiple security layers to detect, interrupt, and prevent cyber threats before they cause damage. Our solution detects threats by deploying an Enhanced Data Historian for Detecting Cyberattacks. By introducing Machine Learning (ML), we enhance cyberattack detection by fusing network traffic and sensor data. Two computing models are examined: 1) a distributed computing model and 2) a localized computing model. The distributed computing model is powered by Apache Spark, introducing redundancy for detecting cyberattacks. In contrast, the localized computing model relies on a network traffic visualization methodology for efficiently detecting cyberattacks with a Convolutional Neural Network. These applications are effective in detecting cyberattacks with nearly 100% accuracy. Next, we prevent eavesdropping by applying Homomorphic Encryption for Secure Computing. HE cryptosystems are a unique family of public key algorithms that permit operations on encrypted data without revealing the underlying information. Through the Microsoft SEAL implementation of the CKKS algorithm, we explored the challenges of introducing Homomorphic Encryption to real-world applications. Despite these challenges, we implemented two ML models: 1) a Neural Network and 2) Principal Component Analysis. Finally, we hinder attackers by integrating a Cyberattack Lockdown Network with Secure Ultrasonic Communication. When a cyberattack is detected, communication for safety-critical elements is redirected through an ultrasonic communication channel, establishing physical network segmentation with compromised devices. We present proof-of-concept work in transmitting video via ultrasonic communication over an Aluminum Rectangular Bar. Within industrial environments, existing piping infrastructure presents an optimal solution for cost-effectively preventing eavesdropping. The effectiveness of these solutions is discussed within the scope of the nuclear industry.
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Title: Estimation of Platinum Oxide Degradation in Proton Exchange Membrane Fuel Cells
Creator: Ahmed, Niyaz Afnan
Date: 2024
Description: The performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) can be significantly hampered due to the degradation of the...
Show moreThe performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) can be significantly hampered due to the degradation of the platinum catalyst. The production of platinum oxide is a major cause of the degradation of the fuel cell system, negatively affecting its performance and durability. In order to predict and prevent this degradation, this research examines a novel method to estimate degradation due to platinum oxide formation and predict the level of platinum oxide coverage over time. Mechanisms of platinum oxide formation are outlined and two methods are compared for platinum oxide estimation. Linear regression and two Artificial Neural Network (ANN) models, including a Recurrent Neural Network (RNN) and Feed-forward Back Propagation Neural Network (FFBPNN), are compared for estimation. The estimation model takes into account the influence of cell temperature and relative humidity.Evaluation of relative errors (RE) and root mean square error (RMSE) illustrates the superior performance of RNN in contrast to GT-Suite and FFBPNN. However, both RNN and GT-Suite showcase an average error rate below 5% while the FFBPNN had a higher error rate of approximately 7%. The RMSE of RNN shows mostly less compared to FFBPNN and GT-Suite, however, at 50% training data, GT-Suite shows lowest RMSE. These findings indicate that GT-Suite can be a valuable tool for estimating platinum oxide in fuel cells with a relatively low RE, but the RNN model may be more suitable for real-time estimation of platinum oxide degradation in PEM fuel cells, due to its accurate predictions and shorter computational time. This comprehensive approach provides crucial insights for optimizing fuel cell efficiency and implementing effective maintenance strategies.
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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: Three Essays on the Internet Economy
Creator: Sun, Yidan
Date: 2024
Description: In an era of digital platforms, the integrity and visibility of consumer reviews, the dynamics of digital advertising markets, and the role of...
Show moreIn an era of digital platforms, the integrity and visibility of consumer reviews, the dynamics of digital advertising markets, and the role of software development kits (SDKs) emerge as pivotal elements shaping user experiences and platform economics. My research spans three distinct but interconnected domains: the impact of safety reviews on Airbnb, the effects of privacy protections on digital advertising markets, and the significance of SDK releases in the evolution of Apple's iOS app market. We find that critical reviews concerning the safety of an Airbnb listing's vicinity influence guest bookings negatively and, therefore, could boost platform revenues if such reviews were obscured, highlighting a misalignment between consumer interests and platform revenue objectives. This effect is more pronounced in low-income and minority neighborhoods, suggesting a nuanced impact on different community segments. In the digital advertising sector, we identify that data frictions disproportionately harm small publishers, especially when associated with smaller ad intermediaries, underscoring the vulnerability of niche players to market and regulatory changes. Lastly, our analysis of the iOS app market reveals the instrumental role of SDK releases in fostering the app ecosystem's growth, independent of the expanding iPhone user base. Together, these findings underscore the complex interplay between consumer feedback, technological advancements, and market dynamics in digital environments, urging a balanced approach that safeguards consumer interests while fostering innovation and equitable market practices.
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Title: Integrating Deep Learning And Innovative Feature Selection For Improved Short-Term Price Prediction In Futures Markets
Creator: Tian, Tian
Date: 2024
Description: This study presents a novel approach for predicting short-term price movements in futures markets using advanced deep-learning models, namely...
Show moreThis study presents a novel approach for predicting short-term price movements in futures markets using advanced deep-learning models, namely LSTM, CNN_LSTM, and GRU_LSTM. By incorporating cophenetic correlation in feature preparation, the study addresses the challenges posed by sudden fluctuations and price spikes while maintaining diversification and utilizing a limited number of variables derived from daily public data. However, the effectiveness of adding features relies on appropriate feature selection, even when employing powerful deep-learning models. To overcome this limitation, an innovative feature selection method is proposed, which combines cophenetic correlation-based hierarchical linkage clustering with the XGBoost importance listing function. This method efficiently identifies and integrates the most relevant features, significantly improving price prediction accuracy. The empirical findings contribute valuable insights into price prediction accuracy and the potential integration of algorithmic and intuitive approaches in futures markets. Moreover, the developed feature preparation method enhances the performance of all deep learning models, including LSTM, CNN_LSTM, and GRU_LSTM. This study contributes to the advancement of price prediction techniques by demonstrating the potential of integrating deep learning models with innovative feature selection methods. Traders and investors can leverage this approach to enhance their decision-making processes and optimize trading strategies in dynamic and complex futures markets.
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Title: The Voderettes: Gender, Labor, and Techno-Utopia at the 1939 New York World's Fair
Creator: Simon, Sara M. B.
Date: 2024
Description: This thesis explores the labor demands of the Voder, the electrical speech synthesis machine developed by Bell Labs to be a major component of...
Show moreThis thesis explores the labor demands of the Voder, the electrical speech synthesis machine developed by Bell Labs to be a major component of AT&T's 1939 New York World's Fair exhibit. With the United States emerging from the Great Depression, and with political tensions escalating across the globe, the paper situates the Voder's labor demands within the historical context of the fair. Specifically, I explore the decision to have young women operate the Voder, the intricacies of the machine cloaked by the warm presence of its highly-skilled female operator. Using archival records from Bell Labs engineers, the paper exposes the previously unacknowledged engineering contributions of Voder operators in the years before the fair. These young women not only influenced major decisions about the Voder's mechanics but also gave early credence to the notion that developing a performance with the machine could make for a thrilling fair exhibit. Moreover, the paper argues that at the fair itself, AT&T and Bell Labs executives used the Voder operators to normalize a new vision of a technological utopia that relied heavily and conspicuously on the infrastructural labor of women. Given the Voder's legacy, as a tool that laid critical groundwork for voice encryption technology, the paper adds important context to the historical record, highlighting the young women at the heart of the machine.
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