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Title: Child Temperament, Attachment, and Loneliness: The Mediating Effects of Social Competence
Creator: Evans, Lindsey M
Date: 2021
Description: Chronic loneliness is a risk factor associated with adverse psychological, physical, and academic outcomes. Converging evidence suggests that...
Show moreChronic loneliness is a risk factor associated with adverse psychological, physical, and academic outcomes. Converging evidence suggests that young children experience and can reliably report on their own loneliness. Due to the significant negative sequalae associated with childhood loneliness, it is critically important to examine risk factors for child loneliness. The aims of this study were two-fold: (a) to examine if temperament (i.e., negative affect, effortful control, and inhibitory control) and attachment security assessed at 4 years of age predict loneliness at age 6; and (b) to determine if social competence at age 5 mediates the relation between temperament and attachment security at age 4 and loneliness at age 6. Participants included a diverse sample of 796 4-year old children, about half of whom were male. At age 4, temperament was assessed with the Rothbart Child Behavior Questionnaire and three inhibitory control tasks, and attachment security was assessed with the Attachment Q-Sort. At age 5, the Social Skills Rating Scale was used to assess social competence, and, at age 6, loneliness was assessed with the Loneliness and Social Dissatisfaction Questionnaire. Results of hierarchical regression analyses indicated that lower levels of effortful control and inhibitory control at age 4 significantly predicted higher levels of loneliness at age 6. Also, lower levels of negative affect and higher levels of effortful control and attachment security at age 4 significantly predicted higher levels of social competence at age 5. However, social competence at age 5 did not predict loneliness at age 6. There was no evidence that social competence at age 5 mediated the relation between age 4 temperament, attachment security and age 6 loneliness. These findings reveal that early self-regulation is associated with later child-reported loneliness and that intervention for children who struggle with cognitive regulation may be effective in decreasing risk for later loneliness.
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Title: Inviscid Shock Propagation within a Variable-Geometry Scramjet Inlet
Creator: Grybko, Maciej
Date: 2021
Description: The study concerns the propagation of shockwaves within an inlet of a scramjet engine and effect of inlet geometry variation on performance. A...
Show moreThe study concerns the propagation of shockwaves within an inlet of a scramjet engine and effect of inlet geometry variation on performance. A Python code was developed to simulate and visualize a flowfield within a scramjet inlet, based on inviscid oblique shock theory. The program was validated against NASA Shock software, and the results differed only by round-off error (0.05%). Subsequently a geometric sensitivity study was conducted, showing that throughout acceleration from Mach 5 to Mach 20 parameters like inlet height could be varied to ensure constant number of shocks within an inlet (preventing discontinuous changes of flowfield), whereas lower wedge angle could control compression required for optimal combustion. Correspondingly, a trajectory was determined with a constraint on static pressure entering combustion chamber (100 kPa). For an arbitrary baseline inlet geometry, it was established that beyond Mach 10 the scramjet would exceed structural load limit, despite delivering sufficient conditions for rapid combustion. Nevertheless, below Mach 10 it would operate efficiently, proving that hydrocarbon-fueled scramjets can have a fixed geometry. For higher speeds, a variable geometry is a necessity.
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Title: ARE SUPPORTIVE FOSTER CAREGIVERS ASSOCIATED WITH IMPROVED FOSTER CARE ALUMNI OUTCOMES? A LONGITUDINAL EXAMINATION OF THE EFFECT OF SUPPORTIVE FOSTER CAREGIVERS ON MENTAL HEALTH OUTCOMES IN A NATIONALLY REPRESENTATIVE SAMPLE
Creator: Dunn, Megan Reeves
Date: 2021
Description: Foster youth are a vulnerable population associated with poor health outcomes, but relatively little research has identified factors that may...
Show moreFoster youth are a vulnerable population associated with poor health outcomes, but relatively little research has identified factors that may mitigate adverse outcomes for these youth. The present study augments previous research by utilizing a nationally representative, longitudinal study (The National Longitudinal Study of Adolescent to Adult Health or Add Health) to investigate whether foster youth in the United States face significantly different mental and behavioral health outcomes compared with same-age peers, and second, whether presence of a supportive foster caregiver may predict better mental and behavioral health outcomes in the foster youth subsample. Using data from Waves III and IV of the Add Health study (N = 12,288 participants, of which n = 282 were foster youth), analyses examined whether foster status and higher caregiver support was related to rates of depression symptoms, suicidal ideation, marijuana use, and alcohol use. Surprisingly, there were few differences between those with and without a foster history; higher frequency of marijuana use among foster youth was the only significant difference. However, analyses in the foster youth subsample indicated that the presence of a supportive caregiver was associated with lower rates of depression symptoms and lower endorsement of suicidal ideation, demonstrating caregiver support as a possible protective factor for foster youth. Future research must continue to explore potential benefits of caregiver support, as it may inform policy that can improve long-term outcomes for foster youth.
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Title: THE EFFECTS OF MODIFIED SURFACES ON INSULIN CRYSTALLIZATION
Creator: Hammadi, Okba Tahar
Date: 2021
Description: Engineered nucleation features (ENFs) were designed with the hope to improve the efficiency of protein crystallization and increase...
Show moreEngineered nucleation features (ENFs) were designed with the hope to improve the efficiency of protein crystallization and increase reproducibility both in quality and quantity. These ENFs were tested with human insulin as the protein of choice since it has flexible parameters, only one cofactor, and a large amount of commercially available crystal ready protein. Insulin crystallization on the ENFs will produce more crystals while also having a reduced crystallization on-set time compared to the control glass surface. The ENFs were compared to control surfaces under similar conditions and observed over time to record both onset-times and end times. The ENFs performed markedly better in on-set times, having an overall 87%-time reduction when compared to the control drops. The drops placed on the ENF produced more than 2.5x the number of crystals in the control drops.
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Title: THE EFFECTS OF COMMUNICATION MODALITY ON PRESENCE, COGNITIVE LOAD AND RETENTION IN SECOND LIFE
Creator: WILKES, STEPHANY FILIMON
Date: 2009-12
Description: This thesis reports findings from a study (N = 60) of the impact of three communication modalities (voice only, text only, and voice and text...
Show moreThis thesis reports findings from a study (N = 60) of the impact of three communication modalities (voice only, text only, and voice and text simultaneously) on cognitive load, as measured by subjective reports of mental effort; on learning, as measured by tests of recall and retention; and on perceptions of presence as measured by a Presence Questionnaire (Witmer & Singer, 2005). Based on the results of prior empirical research, it is hypothesized that retention scores will be higher for voice participants and voice-and-text participants than for text-only participants; that cognitive load will be lower for voice participants and higher for text conditions; that voice will contribute to greater perceptions to presence; and that higher perceptions of presence will not correlate with deeper learning. Study results indicate that communication modality significantly effected cognitive load (F(2, 54) = 4.58, p = .01) and retention (F(2, 54) = 3.53, p = .04), and that experience with and time spent in the virtual environment had significant effects on measures of cognitive load, retention, and presence: Significant between-subjects effects were found for cognitive load and time (p = .23), for retention and time (p = .21), and for retention and experience (p — .03).
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Title: From Critical to Transformative Pedagogy in Architectural Education
Creator: Jones, Kristin
Date: 2019, 2019
Publisher: Association of Collegiate Schools of Architecture, Washington, DC
Collection: 2019 ACSA/EAAE Teachers Conference Proceeding

Title: QUANTIFYING UNCERTAINTY IN RANDOM ALGEBRAIC OBJECTS USING DISCRETE METHODS
Creator: Wilburne, Dane
Date: 2018, 2018-05
Description: This thesis consists of two parts. Part 1 is concerned with the study of random algebraic objects and Part 2 deals with statistical modeling...
Show moreThis thesis consists of two parts. Part 1 is concerned with the study of random algebraic objects and Part 2 deals with statistical modeling for networks. Part 1 begins with the study of random monomial ideals. We define several models for generating random monomial ideals, illustrate their connection with models of random simplicial complexes, and study the behavior of various algebraic invariants of interest (e.g., Krull dimension and first Betti numbers) in the ER-type model. Next we consider a model for random numerical semigroups. In order to understand their properties, we introduce a family of simplicial complexes whose algebraic and combinatorial properties encode probabilistic information about random semigroups from the model. In Part 2, we introduce two exponential random graph models. The first is the shell distribution model. The sufficient statistics of this model are related to the k-cores of a network, which is a graph-theoretic concept designed to capture connectivity information in a more refined way than node degrees. We study the theoretical properties of the shell distribution model, develop an MCMC algorithm for sampling from the model, give an algorithm for sampling from the space of graphs with a fixed shell distribution, and present several simulation studies. The second model is the edge-degeneracy model, whose sufficient statistics are related to the density of edges in the graph. For this model, we prove several theoretical results concerning the model polytope and how it governs the asymptotic behavior of the model as the parameters diverge along infinite rays.
Ph.D. in Applied Mathematics, May 2018
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Title: Quantification of Vascular Permeability in the Retina Using Fluorescein Videoangiography Data as a Biomarker for Early Diabetic Retinopathy
Creator: Kayaalp Nalbant, Elif
Date: 2023
Description: Diabetic retinopathy, which is the most common reason for blindness in the working-age population, affects over one-third of those who have...
Show moreDiabetic retinopathy, which is the most common reason for blindness in the working-age population, affects over one-third of those who have had diabetes for over ten years. High blood sugar level (hyperglycemia) in the blood damages blood vessels and tight junction at the blood-retinal barrier (BRB). Chronic inflammation leads to changes in vascular health, and over time blood vessels tend to get damaged and exhibit higher “leakage” or permeability. In the late stage of DR, hemorrhages can occur, leading to irreversible damage of neuronal tissue in the retina and vision loss. In the clinic, there are some biomarkers and imaging modalities used to diagnose DR based on some of the more severe products of DR (e.g., hemorrhage), but there is no non-invasive, highly sensitive method to detect diabetic retinopathy before clinical signs occur, when mitigating therapies could be more effective. In this thesis, indicator dilution theory was explored to modeling the temporal dynamics of fluorescein in the retina after intravenous injection, with an aim to quantitatively map subtle changes in retinal blood flow and vascular permeability that could preempt subsequent irreversible damage. Specifically, a simplified version of indicator dilution theory—namely the “adiabatic approximation in tissue homogeneity” (AATH) model—was used to estimate physiological parameters such as the blood flow (F) and the extraction fraction (E: a parameter coupled with vascular permeability) from retinal fluorescein videoangiography data. The AATH fitting protocol was optimized through simulations using a more complex model (the AATH-vascular heterogeneity model, AATH-VH). It was determined that a two-step least square fitting method was more sensitive than a single-step least square fitting of AATH to simulated data to evaluate vascular permeability in early diabetic retinopathy. The optimized data analysis protocol was then evaluated in an initial clinical study comparing healthy control subjects to those with moderate non-proliferative DR. Volumetric blood flow and retinal vascular permeability maps were compared between patient groups with clear increases in extraction fraction observed in the mild NPDR patients compared to control. These promising early data have been the foundation to an ongoing 5 year study tracking 100 Diabetic patients with no DR so see if early changes in vascular permeability can predict which patients are more likely to progress to DR.
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Title: Efficient management of uncertain data
Creator: Feng, Su
Date: 2023
Description: Uncertainty arises naturally in many application domains. It can be caused by an uncertain data source (sensor errors, noise, etc.). Data...
Show moreUncertainty arises naturally in many application domains. It can be caused by an uncertain data source (sensor errors, noise, etc.). Data preprocessing techniques (data curation, data integration, etc.) can also results in uncertainty to the data. Analyzing uncertain data without accounting for its uncertainty can create hard to trace errors, with severe real world implications. Certain answers are a principled method for coping with the uncertainty that arises in many practical data management tasks. Unfortunately, this method is expensive and may exclude useful (if uncertain) answers. Other techniques from incomplete database record and propagate more detailed uncertainty information. However, most of these approaches are either too expensive to be practical, or only focus on a narrow class of queries and only work for a specific representation. In this thesis, we investigate models and query semantics for uncertain data management and present a framework that is general and practically efficient, backed up by fundamental theoretical foundations and with formally proven correctness guarantees. We first propose Uncertainty Annotated Databases (UA-DB), which combine an under- and over-approximation of certain answers to combine the reliability of certain answers with the performance of a classical database system. We then introduce attribute-annotated uncertain databases (AU-DB), which extend the UA-DB model with attribute-level annotations that record bounds on the values of an attribute across all possible worlds. AU-DB extends UA-DBs to encode a compact over-approximation of possible answers which is necessary to support non-monotone queries including aggregation and set difference. With a further extension to AU-DB that supports ranking and windowed aggregation queries using native implementation on modern DBMS, our approaches scale to complex queries and large datasets, and produces accurate results. Furthermore, they significantly outperforms alternative methods for uncertain data management.
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Title: High School Mathematics Teachers’ Conceptions of Nature of Mathematics (NOM) and How Prior Learning Environments Affect These Conceptions
Creator: Elefteriou, Katherine
Date: 2023
Description: Literature shows that the Nature of Mathematics Knowledge (NOMK) dates back to the era of Plato and Aristotle (Dossey, 1992). It suggests that...
Show moreLiterature shows that the Nature of Mathematics Knowledge (NOMK) dates back to the era of Plato and Aristotle (Dossey, 1992). It suggests that mathematics teachers’ beliefs, views, conceptions, and preferences about NOM influence the way in which they teach mathematics. It is important to understand how these conceptions are formed, which may evolve consciously or unconsciously from their experiences. Teachers’ experiences as students of mathematics, their family, school environment, cultural, and social experiences influence their behavior including their decisions, actions, class organization, learning activities, and students’ achievement (Beswick, 2012; Ernest, 2008; Thompson1984). Yet, there is no NCTM standard on NOM (Gfeller, 1999).The purpose of the present study was to assess high school mathematics teachers’ NOMK conceptions, and to explore how these conceptions have been influenced by their personal and educational experiences as students in learning mathematics. Another objective of this study was to explore whether the teachers’ years of mathematics teaching experience, and their level of education have any influence on their NOMK beliefs. The sample consisted of 52 high school mathematics teachers, who were certified to teach secondary mathematics, and who had at least three years of mathematics teaching experience. Two instruments were used to collect the data, 1) the VNOM D instrument to assess the teachers’ beliefs regarding the NOMK aspects, and 2) the demographics instrument to collect information on the teachers’ demographics, and on their experiences as students of mathematics. Interviews were also used to enhance the findings. Results showed that participants had strong beliefs regarding their NOMK, and that their years of experience, and level of education influenced their NOMK beliefs.
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Title: Effects of Microstructure Engineering on Laser Powder Bed Fusion Processed Superalloy IN718 through Inoculant Addition
Creator: Ho, I-Ting
Date: 2023
Description: Additive manufacturing (AM) techniques can now be utilized as innovative tools that provide unlimited design flexibility for the fabrication...
Show moreAdditive manufacturing (AM) techniques can now be utilized as innovative tools that provide unlimited design flexibility for the fabrication of geometrically complex metallic structures. For production of Ni-base superalloy components used in advanced gas turbine engines, laser powder bed fusion (L-PBF), which is one of the AM techniques, is frequently used as it allows good metallurgical bonding of powder feedstock and simultaneously enables development of ultra-efficient power systems for aerospace propulsion, space exploration and power generation. One of the major challenges associated with additively manufactured Ni-base superalloy components is that the extreme temperature gradients encountered during processing negatively impact the underlying microstructure and mechanical properties of the material. Although the macroscopic shape and chemistry of the additively fabricated part may be identical to the conventionally manufactured part, the resulting properties are usually compromised. In an effort to make Ni-base superalloys more amenable for processing via additive manufacturing, varying levels of benign inoculants that promote may heterogeneously grain nucleation were blended into Inconel 718 (IN718) powder feedstock and used for processing via L-PBF to characterize the microstructural evolution. In the first study, 0.2 wt. % of micron-sized CoAl2O4 flakes was found to effectively change the grain morphology during the L-PBF process leading to significant reduction in crystallographic texture and thus resulting elastic anisotropy. Dispersion of nano-oxides resulting from the reduction of CoAl2O4 particles also contributed to improved tensile strength and steady creep strain rate. It should be noted, however, that, the multiple iterations of remelting as the result of deposition of new layers dissolved the Co-rich particles reduced from CoAl2O4 inoculants. Instead of having nucleation events contributed by elemental Co, the oxide agglomerates as a result of Marangoni convection seemed to be the major contribution to facilitating grain refinement by inhibiting the heat transfer in the surroundings. On the other hand, addition CoAl2O4 particles appeared to generally reduce the melt pool width while increase the melt pool depth by inhibiting the degree of heat transfer and Marangoni flow. The changes in melt pool dimension aided in improving the relative density and surface roughness of the bulk samples by generating better metallurgical bonding to the subsequent layers. As the trade-off, however, the changes in melt pool physics also enhanced the tendency for epitaxial growth and hence retarded the columnar-to-equiaxed transition unless oxide agglomerates are present. In addition to CoAl2O4, candidates including Co, TaCr2, TiB2, and CeO2 particles were also considered to be blended with the powder feedstock of IN718. After the L-PBF process, different degree of microstructural evolution was characterized with the addition of Co, TaCr2, TiB2, or CeO2 particles. It was found that the physical presence of inoculants may change the melt pool geometries that accounted for a comparatively more columnar-grained structure with <101> texture in samples containing Co and TaCr2 particles while a relatively equiaxed-grained structure with <001> texture in samples containing TiB2. The comparison between samples containing TiB2 and CeO2 further indicates that the phase transformation induced agglomeration will also reduce the effectiveness of inoculants due to decreasing nuclei density. Findings from this investigation demonstrate the resulting grain structure upon L-PBF can be profoundly impacted by both chemistry and physical properties of the inoculants. These effects may potentially be harnessed to effectively engineer the microstructure and optimize the properties of L-PBF processed Ni-base superalloys.
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Title: High-integrity modeling of non-stationary Kalman Filter input error processes and application to aircraft navigation
Creator: Gallon, Elisa
Date: 2023
Description: Most navigation applications nowadays rely heavily on Global Navigation Satellite Systems (GNSSs) and inertial sensors. Both of these systems...
Show moreMost navigation applications nowadays rely heavily on Global Navigation Satellite Systems (GNSSs) and inertial sensors. Both of these systems are known to be complementary, and as such, their outputs are very often combined in an extended Kalman Filter (KF) to provide a continuous navigation solution, resistant to poor satellite geometry, as well as radio frequency interference. Additionally, recent development in safety critical applications (such as aviation) revealed the performance limitations of current algorithms (Advance Receiver Autonomous Integrity Monitoring - ARAIM) to vertical guidance down to 200 feet above the runway (LPV-200). When nominal constellations are depleted, LPV-200 can only sparsely be achieved. Exploiting satellite motion in ARAIM (for instance using a KF) could help alleviate those limitations, but would require adequate modeling of the errors, including the error's time correlation.Power Spectral Density (PSD) bounding is a methodology that provides high integrity, time correlated error models, but this approach is currently limited to stationary errors (which is rarely the case with real data), and has never been applied to navigation errors. More generally, no high integrity, time correlated error models have ever been derived for navigation errors.As a result, in the first part of this thesis, a methodology for high integrity modeling of time correlated errors is introduced. The PSD bounding methodology is extended to both stationary and non-stationary errors. In the second part of this thesis, these methodologies are applied to the 3 main error sources impacting iono-free GNSS measurements (orbit and clock errors, tropospheric errors and multipath), as well as to inertial errors.The methodology introduced in this dissertation provides high integrity time correlated error models and is applicable to any type of applications where high integrity is required (e.g. Differential GNSS - DGNSS, Aircaft Based Augmentation System - ABAS, Ground Based Augmentation System - GBAS, Space Based Augmentation System - SBAS, etc...). Additionally, the error models derived here are not only limited to high integrity applications, but could also be used in applications were the correlation over time of the errors plays an important role (such as any KF integration).In the last part of this dissertation, we focus on a specific safety critical application: aviation, and in particular ARAIM. The dissertation is concluded with an assessment of the performance improvements provided by recursive ARAIM, using those bounding dynamic error models, with respect to those models, used for baseline snapshot ARAIM. Additionally, a sensitivity analysis is performed on each of the error model parameters to assess which of them impacts the KF performance (i.e. covariance) the most.
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Title: A Novel CNFET SRAM-Based Computing-In-Memory Design and Low Power Techniques for AI Accelerator
Creator: Kim, Young Bae
Date: 2023
Description: Power consumption and data processing speed of integrated circuits (ICs) is an increasing concern in many emerging Artificial Intelligence (AI...
Show morePower consumption and data processing speed of integrated circuits (ICs) is an increasing concern in many emerging Artificial Intelligence (AI) applications, such as autonomous vehicles and Internet of Things (IoT). In addition, according to the 2020 International Technology Road map for Semiconductors (ITRS), the high power consumption trend of AI chips far exceeds the power requirements. As a result, power optimization techniques are highly regarded in nowadays AI chip designs. There are various low-power methodologies from the system level to the layout level, and we are focusing on transistor level and register transfer level (RTL) through this thesis. In this thesis, we propose a novel ultra-low power voltage-based computing-in- memory (CIM) design with a new SRAM bit cell structure for AI Accelerator. The basic working principle of CIM (Computing-in-memory) is to use the existing internal embedded memory array (e.g. SRAM) instead of external memory, and it reduces unnecessary access to external memory by calculating with internal embedded mem- ory. Since the proposed our SRAM bit cell uses a single bitline for CIM calculation with decoupled read and write operations, it supports much higher energy eciency. In addition, to separate read and write operations, the stack structure of the read unit minimizes leakage power consumption. Moreover, the proposed bit cell structure provides better read and write stability due to the isolated read path, write path and greater pull-up ratio. Compared to the state-of-the-art SRAM-CIM, our proposed SRAM-CIM does not require extra transistors for CIM vector-matrix multiplication. We implemented a 16k (128⇥128) bit cell array for the computation of 128x neurons, and used 64x binary inputs (0 or 1) and 64⇥128 binary weights (-1 or +1) values for the binary neural networks (BNNs). Each row of the bit cell array corresponding to a single neuron consists of a total of 128 cells, 64x cells for dot-product and 64x replicas cells for ADC reference. And 64x replicas cells consist of 32x cells for ADC reference and 32x cells for o↵set calibration. We used a row-by-row ADC for the quantized outputs of each neuron, which supports 1-7 bits of output for each neuron. The ADC uses the sweeping method using 32x duplicate bit cells, and the sweep cycle is set to 2N1 +1, where N is the number of output bits. The simulation is performed at room temperature (27C) using 32nm CNFET and 20nm FinFET technology via Synopsys Hspice, and all transistors in bitcells use the minimum size considering the area, power, and speed. The proposed SRAM-CIM has reduced power consumption for vector-matrix multiplication by 99.96% compared to the existing state-of-the-art SRAM-CIM. Moreover, because of the separated reading unit from an internal node of latch, there is no feedback from the read access circuit, which makes it read static noise margin (SNM) free. Furthermore, for the low power AI accelerator design, we propose a new AI accelerator design method that applies low power techniques such as bus specific clock gating (BSCG) and local explicit clock gating (LECG) at the register-transfer- level (RT-level). And evaluates them on the Xilinx ZCU-102 FPGA SoC hardware platform and 45nm technology for ASIC, respectively. It measures dynamic power using a commercial EDA tool, and chooses only a subset of FFs to be gated selectively based on their switching activities. We achieve up to a 53.21% power reduction in the ASIC implementation and saved 32.72% of the dynamic power dissipation in the FPGA implementation. This shows that our RTL low power schemes have a powerful possibility of dynamic power reduction when applied to the FPGA design flow and ASIC design flow for the implementation of the AI system.
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Title: Growth Kinetics of Listeria monocytogenes and Salmonella enterica on Rehydrated Enoki and Wood Ear Mushrooms during Storage
Creator: George, Josephina
Date: 2023
Description: Plant foods, such as fruits and vegetables, that have been dehydrated do not support the growth of pathogenic microorganisms. Recent...
Show morePlant foods, such as fruits and vegetables, that have been dehydrated do not support the growth of pathogenic microorganisms. Recent listeriosis and salmonellosis outbreaks in the U.S. have been associated with imported specialty mushrooms. These mushrooms are commonly sold fresh or dehydrated. This study evaluated the survival and growth of two foodborne pathogens Listeria. monocytogenes and Salmonella. enterica on dehydrated mushrooms during both rehydration at 25 or 5℃ and storage at 5, 10, or 25℃. Fresh enoki and wood ear mushrooms were dehydrated for 24 h at 60°C. Dehydrated mushrooms were inoculated with a four-strain cocktail of S. enterica or L. monocytogenes at 4 log CFU/g. Mushrooms were dried for 1 h, followed by rehydration for 2 h with 5 or 25°C (water and air temperature). Rehydrated mushrooms were stored at 5, 10, or 25°C for up to 14 d. The pathogens were enumerated at 0, 1, 3, 6, 9 and 14 d. Three independent trials with triplicate samples at each time point were completed. Population differences were evaluated via Student’s t-test; p<0.05 was considered significant. The growth rates were determined by DMFit in Excel. Overall, the growth rates of L. monocytogenes and S. enterica on enoki mushrooms were significantly higher when the mushrooms were rehydrated at 25℃ and stored at 25℃ (P<0.05). The growth rates were 2.69 log CFU/g per day and 3.56 log CFU/g per day, for L. monocytogenes and S. enterica respectively. Since the growth of pathogens on wood ear mushrooms during rehydration and storage was considerably less and below the level of enumeration, enrichment of the pathogens was conducted. The pathogens could be suppressed during rehydration due to less nutrient contents and antimicrobial properties of wood ear. The result of this study outlines the importance of refrigerated storage temperature and time combination for safety during rehydration and subsequent storage of the mushrooms.
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Title: Characterization and Migration of Silver Nanoparticles from Electron-Beam Irradiated Low-Density Polyethylene
Creator: Donovan, Dylan
Date: 2023
Description: Polymer nanocomposites (PNCs) and engineered nanomaterials (ENMs) may find use in a wide range of commercial applications, including food and...
Show morePolymer nanocomposites (PNCs) and engineered nanomaterials (ENMs) may find use in a wide range of commercial applications, including food and medical product packaging. Migration of nanofillers from polymer nanocomposites into food matrices could be a source of human dietary exposure to ENMs. Electron beam (e-beam) irradiation is a processing method used for microbial inactivation as well as for modifying properties of polymer films, such as stretch resistance and shrink tension. Process treatment of nanotechnology-based packaging materials either for sterilization or for strengthening of the polymer films may have a significant effect on the migration of ENMs into food matrices. The primary objective of this study is to investigate the effect of e-beam irradiation treatments of LDPE containing silver nanoparticles (AgNPs) and the subsequent migration of AgNPs into a food simulant under intended use conditions. The study observes a correlation between e-beam irradiation dose quantity and the release of AgNPs into a food simulant.
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Title: Investigating The Impact of Tall Building Ordinances (TBOs) on the Evolution of Ultra-Tall Buildings Typology: Case Studies in Chicago and Dubai
Creator: Alkoud, Amjad
Date: 2023
Description: Zoning ordinances are instruments that tangibly and intangibly shape cities; control urban morphology, demography, and visual identity; and...
Show moreZoning ordinances are instruments that tangibly and intangibly shape cities; control urban morphology, demography, and visual identity; and determine the inhabitants' life quality, well-being, and comfort. Tall building ordinances (TBOs), in turn, control the vertical growth of cities and the development of tall buildings as distinctive actors in the built environment today. With the recent proliferation of developing Ultra-tall buildings in cities around the world, ordinances should offer flexibility, adaptability, and responsiveness to the dynamic nature of emerging needs and technological potentials.This dissertation investigates the emergence of Ultra-tall buildings as a new typology in major metropolises and the interaction between the building ordinances and the construction of Ultra-tall. The work presented in this dissertation implements two primary research methods: cross-sectional surveys and longitudinal studies, documenting supertall buildings completed in two major cities, Chicago and Dubai. The discussions and findings are supported by structured interviews with architects and engineers actively involved in designing and constructing Ultra-tall buildings. The cross-sectional survey comprises all supertall buildings (i.e., buildings above 1000 feet in height) completed as of 2022 in Chicago, the cradle of the "modern" high-rise with 318 towers of 100-plus meters and eight supertall towers of 300-plus meters; and Dubai, the new experimental land of supertall construction with 298 towers of 100-plus meters and 28 towers of 300-plus meters height. The longitudinal case studies provide additional information and knowledge about selected examples in Chicago and Dubai, derived from personal structured interviews conducted in both cities. Several additional survey cases from China, NYC, and London were investigated for their importance and uniqueness in supporting the research discussions and findings. This research aims to bridge the gap between the building ordinance literature and Ultra-tall building design practices on the one hand. On the other hand, it sheds light on the necessity to realize Ultra-tall buildings as a distinct typology entitled to its particular set of ordinances.The research findings are intended to help architects, engineers, policymakers, and planning authorities ensure a sustainable socioeconomic future and mitigate the negative impact of Ultra-tall constructions in major cities. This goal is assumed to be achieved by developing a set of recommendations, strategies, and universal criteria to implement a more flexible and responsive approach toward emerging human needs and technologies.
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Title: Quantifying Localization Safety for State-of-the-Art Mobile Robot Estimation Algorithms
Creator: Abdul Hafez, Osama Mutie Fahad
Date: 2023
Description: In mobile robotics, localization safety is quantified using covariance matrix or particle spread.However, such methods are insufficient for...
Show moreIn mobile robotics, localization safety is quantified using covariance matrix or particle spread.However, such methods are insufficient for mission or life-critical applications, like Autonomous Vehicles (AVs), because they only reflect nominal sensor noise without considering sensor measurement faults. Sensor faults are unknown deterministic errors that cannot be modeled using a zero mean Gaussian distribution. Ignoring sensor faults, in such applications, might result in large localization errors, which in turn deceives other reliant systems, like the controller, leading to catastrophic consequences, such as traffic accidents for AVs. Thus, other techniques need to be used to conservatively quantify pose safety.This thesis builds upon previous research in aviation safety, or what is referred to as \textit{integrity monitoring}, to quantify localization safety for mobile robots that use state-of-the-art state estimators (as localizers).Specifically, this thesis utilizes the localization \textit{integrity risk} metric, as a measure of localization safety, which is defined as the probability of the robot's pose estimate error to lie outside pre-determined acceptable limits while an alarm is not triggered. Unlike open-sky aviation applications, where Global Navigation Satellite Systems (GNSS) signals are available, mobile robots operate in GNSS-denied, or in the best case GNSS-degraded, environments, which demands utilizing more complex set of sensors to guarantee an acceptable level of localization safety. This thesis provides a conservative measure of localization safety by rigorously upper-bounding the integrity risk while accounting for both nominal lidar noise and unmodeled lidar measurement faults.The contributions of this thesis include the design and analysis of practical integrity monitoring and failure detection procedures for mobile robots utilizing map-based particle filtering, a recursive integrity monitoring method for mobile robots utilizing map-based fixed lag smoothing for both solution-separation and chi-squared as failure detectors, the synthesis of an integrity monitoring procedure for mobile robots utilizing Extended Kalman Filter-based Simultaneous Localization And Mapping (EKF-based SLAM), and a Model Predictive Control (MPC) framework that is capable of planning mobile robot's trajectory to follow a predefined robot path while maintaining a predefined minimum level of mobile robot localization safety. The proposed methodologies are validated using both simulation and experimental results conducted in real-world urban university campus environments.
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Title: Designs and Optimizations of Oblivious Data Access for Mitigating Access Pattern Leakage
Creator: Che, Yuezhi
Date: 2023
Description: In today’s data-driven world, data outsourcing has grown, increasing the importance of data security and privacy. Data encryption, while...
Show moreIn today’s data-driven world, data outsourcing has grown, increasing the importance of data security and privacy. Data encryption, while providing some protection, is insufficient against side-channel attacks such as access pattern leakage. This thesis focuses on designing and optimizing efficient oblivious access methods to enhance data security and privacy. Traditional solutions, like Oblivious RAM (ORAM), often impose significant overheads, limiting their market adoption. Our research proposes novel oblivious data access schemes tailored to specific applications, systems, and contexts. This approach enables us to identify critical vulnerabilities and performance bottlenecks, and balance performance, security, and other relevant parameters. In this thesis, I present four published works in Chapters 3 to 6, demonstrating the effectiveness of my proposed methods: (1) optimizing Ring ORAM for multi-channel memory systems, (2) introducing a multi-range supported ORAM for locality-aware applications, (3) proposing an oblivious data access solution for NVM hybrid memory systems, and (4) developing an oblivious access method for deep neural networks (DNNs), ensuring privacy without sacrificing performance. These contributions address unique challenges across application domains, enhancing data security and privacy in contemporary computing systems. This thesis provides a comprehensive investigation of targeted oblivious access methods, highlighting the benefits of the proposed designs, and contributing to more effective solutions for access pattern leakage mitigation, ultimately improving data security and privacy in contemporary computing systems.
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Title: Developing Adaptive and Predictive Modules for the Second Generation of Multivariable Insulin Delivery System for People with Type-1 Diabetes
Creator: Askari, Mohammad Reza
Date: 2023
Description: In this research, we are developing the second generation of multivariable automated insulin delivery system (mvAID) for people with Type 1...
Show moreIn this research, we are developing the second generation of multivariable automated insulin delivery system (mvAID) for people with Type 1 diabetes (T1D). AID system is improved by integrating missing data from sensors into the system, reconciling outliers in the data, and eliminating the effects of artifacts in signals from wearable devices. Behavioral patterns of individuals with T1D are captured by data-driven models. The model predictive control algorithm of the mvAID uses these patterns for making decisions and predicting glucose concentrations in the future more accurately. A pipeline algorithm is developed for removing noise and motion artifacts from wristband signals. Then, energy expenditure, physical activity, and acute psychological stress (APS) are estimated from wearable device signals to detect and quantify disturbances affecting the concentration of blood glucose concentration. Additionally, different modules were designed for predicting risky glycemic episodes and are used to build the second generation of the mvAID system. The techniques developed are tested with historical data sets from various clinical experiments and free-living data, and with simulations made by using our multivariable glucose, insulin and physiological variables simulator (mGIPsim).
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Title: Transdiagnostic Emotional Factors as Mediators of the Relation between Obsessive-Compulsive Symptoms and Tobacco Use and Dependence in a Large Community Sample of Adolescents
Creator: Chang, Weilynn Christine
Date: 2023
Description: This study investigated the associations between obsessive compulsive disorder symptoms (OCS) and tobacco use and tobacco dependence in a...
Show moreThis study investigated the associations between obsessive compulsive disorder symptoms (OCS) and tobacco use and tobacco dependence in a large community sample of adolescents. Specifically, transdiagnostic emotional vulnerability factors (i.e., anhedonia, distress tolerance and anxiety sensitivity) were explored as potential mediators of the relation between OCS and tobacco use/dependence. Weighted logistic regression models found that OCS was significantly positively associated with likelihood of tobacco use in the past six months (when suppressor variables were excluded). Similarly, zero-inflated negative binomial regression models found a significant positive relation between OCS and tobacco dependence (when suppressor variables were excluded). There was no significant weighted indirect effect via anhedonia for the OCS-Tobacco Use association, which suggests that anhedonia was not a significant mediator in this case. However, the indirect effect via anhedonia for the OCS-Tobacco Dependence association was significant at the p < .05 level, but not the adjusted p < .001 threshold (when suppressor variables were removed). The weighted indirect effect via distress tolerance for the OCS-Tobacco Use association was significant at the p < .05 level, but not the p < .001 threshold (when suppressor variables were removed). There was no significant indirect effect via distress tolerance for the OCS-Tobacco Dependence association. There was a significant weighted indirect effect via anxiety sensitivity for the OCS-Tobacco Use association (when suppressor variables were removed). There were no significant indirect effects via anxiety sensitivity for the OCS-Tobacco Dependence association. When overlapping variance was accounted for by including all three mediators simultaneously, anhedonia was still not a significant mediator of the OCS-Tobacco Use association; there were still significant indirect effects via distress tolerance and anxiety sensitivity, under specific model parameters. Our results also revealed that while Asian adolescents demonstrated lower likelihood of tobacco use compared to those who were Hispanic/Latinae, Asian youth demonstrated more severe tobacco dependence symptoms.
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