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Title: IMPACT OF MULTITASKING AND PHYSICAL CONTEXT ON SELF-REPORTED TRANSFER OF E-LEARNING
Creator: Brown, Anna Kirsten
Date: 2015, 2015-05
Description: The growth of e-learning is increasing in todays organizations; however the research to support its application is slow to catch up. Previous...
Show moreThe growth of e-learning is increasing in todays organizations; however the research to support its application is slow to catch up. Previous research has focused on the factors relating to training and transfer of training, there appears to be a dearth on what trainees are actually engaging in during e-learning itself. This study focused on the relationship between di erent types of multitasking on transfer of e-learning and the interrelation of physical distractors in the training environment. Archival data was utilized in the study with 399 participants. The ndings indicate that the number of additional tasks engaged in during training negatively relate to reported transfer of e-learning. Temperature also related to transfer of e-learning. Participants who reported training in a room where they considered the temperature comfortable also noted higher levels of transfer of e-learning. Limitations and suggestions for future research are presented.
M.S. in Psychology, May 2015
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Title: MINIMIZING SALMONELLA CONTAMINATION IN SPROUTS BY CONTROLLING THE GERMINATION TEMPERATURE
Creator: Zhang, Hanshuai
Date: 2013, 2013-12
Description: Since 1990, contaminated sprouts have been linked to at least 46 outbreaks and over 2,500 cases of illness in the US [13]. Unlike other ready...
Show moreSince 1990, contaminated sprouts have been linked to at least 46 outbreaks and over 2,500 cases of illness in the US [13]. Unlike other ready-to-eat produce, sprouts pose a particular concern as the conditions that promote germination of their seeds also facilitate the growth of pathogens [6]. To address sprout’s propensity to microbial contamination, the U.S. Food and Drug Administration (FDA) has recommended that seeds destined for sprout production be disinfected with chemical sanitizers such as 20,000 ppm of calcium hypochlorite, Ca(OCl)2 [29]. However, this disinfectant often cannot completely eliminate pathogen that may be present in seeds [4, 23]; in which case, the surviving bacteria can re-grow to significant numbers during germination and cause severe illness upon consumption [45]. Therefore, maintaining control of the germination conditions to present the proliferation of pathogens is a crucial step in the overall approach to reduce microbial hazards in finished sprouts. This study examines the effects of temperature on the proliferation of Salmonella during germination, and how this temperature effect is influenced by factors such as pathogen load, seed-lot, and the presence or absence of chemical treatment with Ca(OCl)2 was also evaluated. Alfalfa seeds artificially inoculated with ~3 log CFU/g of Salmonella were used as the contaminated seeds. They were mixed at different levels (0.01, 0.1, 1.0, or 10.0% by weight) with 200g of non-contaminated seeds and then were allowed to germinate in glass jars for 3 or 5 days at 10, 20, or 30°C. The same experiment was repeated for the spiking seeds that were treated with 20,000 ppm Ca(ClO)2 for 15 min prior to sprouting. Sprout samples were taken from each jar daily and analyzed for the level of Salmonella ix by either plating on XLD plates or the three-tube most probable number method as described in the FDA BAM. The level of Salmonella increased during sprouting at all three temperatures and reached the highest level at 48h. Sprouting at 10°C yielded the least number of Salmonella when all other factors were controlled. At all spiking levels, or the percentage of seeds contaminated before sprouting, level of Salmonella increased during sprouting, and at 20°C and 30°C, the level of Salmonella reached to a similar level of 5 log CFU/g and 7 log CFU/g respectively. At 1.0% spiking level, the level of Salmonella increased by approximately 1.5, 4.0, and 6.0 log CFU/g in sprouts grown at 10, 20, and 30°C respectively. Difference in the level of microflora background between different seed lots did not appear to affect Salmonella proliferation during sprouting. Treatments with 20,000 ppm free chlorine in some cases lowered the levels of Salmonella to undetectable levels, while in other cases, it caused an approx. 3 log reduction in Salmonella count on seeds. The surviving ones could still proliferate during sprouting although with a delay and a much slower rate, and did not reach the maximal level at 48 h of sprouting. However, Ca(OCl)2 did not prevent the re-growth of Salmonella during germination. In conclusion, these results showed that sprouting temperatures do affect Salmonella proliferations. We recommend lowering the sprouting temperature in conjunction with chemical treatment of prior to sprouting seeds to reduce microbial hazards in sprouts.
M.S. in Food Safety and Technology, December 2013
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Title: APPROACHES TO QUANTIFY AND COMPARE THE THERMAL STABILITY OF FOOD ALLERGENS
Creator: Meng Xu
Date: 2013-04-24, 2013-05
Description: Stability to heat or other food processing conditions has been suggested as one of the characteristics of food allergens, however there is in...
Show moreStability to heat or other food processing conditions has been suggested as one of the characteristics of food allergens, however there is in general a lack of standardized approach to determine or compare the thermal stabilities of food allergens. This study evaluated the use of several analytical tools including the BCA total protein assay, Far-UV Circular Dichroism Spectroscopy, Differential Scanning Calorimetry, and inhibition ELISA assays to study the changes in the structural and immunological properties of major allergens as a result of heat treatments, and identified parameters that can be used to quantify and compare the thermal stability of food allergens. Purified allergens from milk, egg, and almond were subjected to moist-heat or dry-heat treatments and changes in protein solubility, IC50 values and thermodynamic properties of each protein were determined. It was found that high transition temperature (Tm) was closely related to a greater resistance to changes in immunological properties after heat treatments, suggesting that it can be a good parameter to quantify and compare the thermal stability of different food allergens.
M.S. in Food Safety and Technology, May 2013
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Title: THERMAL PROCESSING TO MITIGATE ARSENIC CONTENT IN NORTH AMERICAN RICE: TOTAL, SPECIATED ARSENIC AND NUTRIENT EVALUATION
Creator: Zhao, Pengyi
Date: 2015, 2015-05
Description: Arsenic in the food supply has been a concern since public news reports in 2011 of the detection of arsenic in apple juice. Food and Drug...
Show moreArsenic in the food supply has been a concern since public news reports in 2011 of the detection of arsenic in apple juice. Food and Drug Administration (FDA) work on this issue has proposed a guidance for no more than 10 ppb of inorganic arsenic in apple juice. More recently rice harvested from the southern states of the United States is of concern of the arsenic content. Arsenic levels in rice have been attributed to the natural levels of arsenic in the soil and the farming practices used to grow rice. FDA released data that showed inorganic arsenic amounts in long grain white rice between 70 and 150 ppb. This work presents a process through washing/ rinsing to reduce the arsenic levels in prepared/cooked rice. Four different rice materials were obtained from Mississippi, Arkansas, Texas and Louisiana. Different processing methods such as common cooking, washing and cooking, excess water cooking, were used to prepare the rice. The common cooking method cooked the rice in a 2:1 (water : rice) ratio. The washing and cooking method rinsed a batch of rice with a 2:1 (water : rice) ratio at first, and then poured off wash water and added new water to cook rice in a 2:1 (water : rice) ratio. The excess water cooking method cooked the rice in excess water of a ratio of 4:1 (water : rice) and the excess water was removed after cooking. Controls of raw rice samples were also evaluated. The common cooked rice showed variable to no difference (-13.9% to 14.9%) from the raw control in arsenic retention. The washed and cooked rice showed a 9.8% to 36.8% reduction of arsenic from the control. The excess water cooked rice showed the greatest reduction of arsenic from 39.1% to 65.5% compared to the control. The species of arsenic mimic the total arsenic loss. There is a visible trend for reduction of arsenic content by washing, but the most reduction was achieved by cooking rice with an excess volume of water.
M.S. in Food Safety and Technology, May 2015
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Title: PIEZO-BARKHAUSEN PULSE SIGNAL ANALYSES (BPSA) AND DETERMINATION OF THE FATIGUE LIFE OF AISI-1018 STEEL NEAR THE ENDURANCE LIMIT
Creator: Nunez-moreno, Federico Alejandro
Date: 2014, 2014-05
Description: A series of fatigue tests were performed on two different types of steels named Steel A (annealed and decarbed AISI-1018 steel), and Steel B ...
Show moreA series of fatigue tests were performed on two different types of steels named Steel A (annealed and decarbed AISI-1018 steel), and Steel B (annealed and polished AISI-1018 steel), carried out to separation or to a maximum of 10,000,000 cycles (which was taken to be equivalent to infinite life). Strain levels ranging from 0.0014 in/in (0.0014mm/mm) down to 0.0008in/in (0.0008mm/mm) were used to execute all experimental load tests at a stress ratio R=-1 (complete reversal). An MTS machine was used for these trials. At the same time, magnetic fields and piezo-Barkhausen pulses were recorded by means of a flux gate magnetometer and a copper coil connected to a series of signal filters and amplifiers. Results were used to construct the classical S-N Whöler curve for both steels, as well as in exhibiting the behavior of the magnetic parameters (magnetic excursions, dominant frequencies of the magnetic signals) coupled to the fatigue lives of the samples tested. To describe such couplings, a set of correlations were introduced among the monitored variables as functions of testing time and applied strain. Also, a fractography analysis of the crack patterns using a scanning electron microscope was performed to represent statistically the geometry of “dimples” and fatigue striations from the inception of the crack, until the formation of a shear lip at the final stages of the crack. It was found that the magnitude of the mean amplitude of the piezo-Barkhausen pulses at early stages of the test is correlated to a mid-level energy of cracking, and thus explains the geometry of fatigue striations near the initiation of the crack at higher strain levels, compared to the geometry of the fatigue striations at lower strain levels. x xvi A joint analysis of the amplitudes of the magnetic excursions recorded in time, and the dominant frequencies of the magnetic signals were found to be discriminators of the elastic and plastic behavior of both types of steel. Furthermore the observed magnetic parameter variations determined in a clear way the endurance limit for each type of steel; these values also are in agreement with the strain level for which fatigue lives were greater than 10,000,000 cycles. Based on these results a “bell analogy” for interpreting the fatigue behavior is introduced. Bridge engineering applications and further research is also discussed.
PH.D in Civil Engineering, May 2014
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Title: MAXIMIZING THE ANTI-INFLAMMATORY EFFECTS OF STRAWBERRY ANTHOCYANINS: UNDERSTANDING THE INFLUENCE OF CONSUMPTION TIMING VARIABLE
Creator: Huang, Yancui
Date: 2015, 2015-05
Description: Chronic low-grade inflammation is an emerging risk factor for chronic disease development and complication. Strawberries, rich in anthocyanins...
Show moreChronic low-grade inflammation is an emerging risk factor for chronic disease development and complication. Strawberries, rich in anthocyanins, attenuate meal-induced postprandial increases in inflammation and oxidative stress as well as improved post-meal insulin responses. Anthocyanins are considered to be responsible in part, for their health benefits. The bioavailability of anthocyanins is low and short-lived. The relationship between strawberry intake timing of consumption relative to a meal and the metabolic-, inflammatory- and oxidative stress responses that ensue are not known. Therefore, this study aimed to determine if the strawberry consumption timing would influence meal-induced oxidative-immuno-metabolic outcomes. Fourteen overweight (BMI 26 ± 2 kg/m2) healthy adults (aged 25 ± 4 years) participated in a 3-arm, placebo-controlled, crossover clinical trial. Subjects came to the research clinical on 3 different occasions for 10 hours (h) and received 3 study drinks: 2 hours before a meal, with the meal, and 2 hours after the meal. A strawberry drink was given at 1 of the 3 time points and control drinks at the alternative time points. Plasma analytes of glucose, insulin and triglycerides were measured over the 10 h along with oxidized low density lipoprotein, a marker of oxidative damage, and interleukin-6, a marker of inflammation. Results were compared between strawberry “timing” groups and with a demographically matched reference group (n=10, BMI 27 ± 2 kg/m2and aged 27 ± 4 years) that was provided only control drinks (no strawberry). Study result showed a significant reduction in postprandial blood glucose when strawberry was consumed before the meal compared to having the strawberry drink with or after the meal, p < 0.05. Compared to the reference group, eating strawberries, regardless of the consumption time, attenuated postprandial blood glucose without additional insulin, suggesting improved sensitivity. Interleukin-6was significantly lower after consuming the strawberry drink before the meal (p=0.048) and modestly lower after consuming the strawberry drink with (p=0.116) or after the meal (p=0.098) compared to the reference group. This study provides data suggesting that strawberries have a role in glycemic control and attenuating the pro-inflammatory effect of a modern diet. There may be particular advantages when consumed before a meal.
M.S. in Food Safety and Technology, May 2015
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Title: A NOVEL METHOD FOR THE IMPLEMENTATION OF STRUCTURAL CONTACT IN FINITE ELEMENT METHODS OFFERING SIMPLIFIED TREATMENT OF ENERGY DISSIPATION
Creator: Grudzinski, James John
Date: 2012-04-24, 2012-05
Description: A novel method for implementing contact/impact in an implicit nite element formulation is presented. The method uses the ideas of buoyancy to...
Show moreA novel method for implementing contact/impact in an implicit nite element formulation is presented. The method uses the ideas of buoyancy to enforce the normal contact constraint and a velocity dependent force to model energy dissipation. Upon contact (penetration) a normal force equal to the depth of penetration times a target weight density (di erent and much larger than the actual material weight density) creates a normal pressure on the contacting body. In addition to the buoyancy force, the penetrating surface area is subjected to a drag-like force that acts in a direction opposite the velocity vector of the penetrating node of the contacting body . This rate dependence is broken up into components tangential and normal to the target surface. The normal component of the drag performs two functions. First it provides for an energy absorbing mechanism similar to a coe cient of restitution for modeling non-conservative systems. Secondly, it can provide damping (analogous to mathematical damping) which can aid in solution convergence. The tangential component of the damping force serves the function of modeling friction in a simpli ed manner. The method applies contact forces in the manner of external forces and as such lends itself well to simpli ed contact detection schemes which rely on functional representation of bodies. The method is described and demonstrated through several examples including a comparison to experimental data.
Ph.D. in Mechanical and Aerospace Engineering, May 2012
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Title: TEMPERATURE PROFILES THROUGH THE SHELL IN EGGS HEATED BY INFRARED ENERGY
Creator: Guo, Jingxin
Date: 2012-07-30, 2012-07
Description: Infrared heating is an effective method for surface pasteurization of shell eggs. As the external temperature reaches the inactivation...
Show moreInfrared heating is an effective method for surface pasteurization of shell eggs. As the external temperature reaches the inactivation temperature, internal temperatures could become great enough to denature albumen. However, the internal temperature of albumen at the shell cannot be measured directly. The purpose of this study is to use experimental data to understand the response of the albumen temperature at the shell to infrared radiation impinging at its outer surface. Fresh eggs were obtained from a local producer and refrigerated until needed. They were prepared for each experiment by overnight equilibration with ambient conditions. Each egg was placed on a metal stage over which an infrared lamp was positioned. The stage allowed a K-type thermocouple to be inserted through a small hole in the shell opposite of the shell area facing the lamp. The thermocouple was pushed into the egg such that the tip was against the inner surface of the shell just underneath the exposed area. The external temperature of this area was measured by an infrared pyrometer. Variables for these experiments were temperature of the IR lamp (277°C, 329°C, 391°C and 452°C), distance between shell egg and IR lamp (3.13 cm – 15.83 cm), and treatment time. All experiments share the same initial lag around 30s, suggested that the initial lag did not vary with changing of lamp-egg distances and lamp temperatures. After the initial lag, internal and external temperatures were found to increase at the same rate regardless of experimental parameters, indicating and equilibrium between the infrared energy impinging on the surface and its dissipation in the interior of the egg. The difference of temperature distributes between 10°C to 20°C. However, lowering lamp temperatures or increasing distances did not change this difference significantly. Moreover, the temperature gap sustains the same temperature after initial lag. The results showed that the internal temperature could be inferred via measuring external temperature. This is valuable in processing to maximize external surface temperature while protecting heat sensitive albumen. Future work will involve modeling the heating phenomenon to determine if knowing only the lamp temperature and distance is sufficient for predicting internal temperature.
M.S. in Food Processing Engineering, July 2012
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Title: CONSTRUCTIONS IN NON-ADAPTIVE GROUP TESTING STEINER SYSTEMS AND LATIN SQUARES
Creator: Balint, Gergely `greg' T.
Date: 2014, 2014-05
Description: This thesis explores and introduces new constructions for non-adaptive group testing which are particulary important for the parameter range...
Show moreThis thesis explores and introduces new constructions for non-adaptive group testing which are particulary important for the parameter range we encounter in real life problems. After a summary of existing results, the rst part of this thesis introduces our own constructions, the Latin Square Construction and the Column Augmented Concatenation. Both of these constructions take existing good group testing matrices to create test matrices of larger dimensions. These new matrices are easy to nd for the practical small parameter range we are most interested in. We also address and prove asymptotic results of our Latin Square Construction. In case of the Column Augmented Concatenation the asymptotic results depend greatly on the codes used for the construction. The second part of our work is to address possible ways of augmentation of the Latin Square Construction. Here we explore the di erence in augmentation based on the properties of the starting matrix. In the appendices we give tables of best matrices coming from our constructions with xed, small column weights. We also give a list of the known best 2-disjunct matrices for small row numbers.
PH.D in Applied Mathematics, May 2014
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Title: NEURAL ADAPTIVE CONTROL STRATEGY FOR HYBRID ELECTRIC VEHICLES WITH PARALLEL POWERTRAIN
Creator: Gurkaynak, Yusuf
Date: 2011-04-20, 2011-05
Description: In a hybrid electric vehicle (HEV) with parallel powertrain, the system can be controlled by splitting the required power between the electric...
Show moreIn a hybrid electric vehicle (HEV) with parallel powertrain, the system can be controlled by splitting the required power between the electric propulsion machine and internal combustion engine (ICE) to meet specific goals related to fuel consumption, efficiency, performance, and/or emissions. This power splitting scenario, which is of great hybridization importance, is in fact the control strategy or energy management of the hybrid vehicle. Performance of the system depends on the control strategy, which needs to be robust, stable, reliable, and independent from uncertainties. This Ph.D. research is focused on model based control strategies, which are proposed for parallel hybrid powertrains, showing significant advantages in performance and fuel economy. If a model based control strategy is used to develop the hybrid power management algorithm, the accuracy of the model data needs to be high for proper control. Therefore, this type of management method is parameter sensitive. Implementing system identification features into this algorithm reduces the effect. As a result, the proposed controller algorithm learns the existing component parameters while operating. Furthermore, combining the base controller with an online tuner, which simultaneously optimizes the controller for current conditions, will improve the performance of the power management. In addition, this Ph.D. thesis presents a novel neural adaptive equivalent consumption minimization strategy (ECMS) and applies it to a hybrid representative sport utility vehicle (SUV) with parallel powertrain. The ECMS is a model based optimal control strategy and is based on the minimization of both fuel consumption and battery charge usage by introducing the equivalent coefficient between them. Proper operation of the controller depends on the accuracy of the model. It also depends on the correct selection of the equivalent coefficient. In this Ph.D. thesis, specific neural network structures are proposed for both coefficient selections by drive cycle recognition and for precise model building by system identification. This thesis also presents a novel fast solution method of ECMS algorithm for real time applications.
Ph.D. in Electrical Engineering, May 2011
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Title: GROWTH, INACTIVATION, AND SURVIVAL OF SALMONELLA ON SESAME SEEDS DURING TAHINI PROCESSING AND REFRIGERATED STORAGE OF TAHINI
Creator: Zhang, Yangjunna
Date: 2016, 2016-05
Description: Salmonella can survive for long period of time in low-moisture foods and cause human illness after consumption of contaminated foods. Recently...
Show moreSalmonella can survive for long period of time in low-moisture foods and cause human illness after consumption of contaminated foods. Recently, sesame seeds and tahini (sesame seeds pasta), have been identified as unusual sources of salmonellosis. Controlling specific steps during tahini processing and storage of tahini may minimize the risk of Salmonella contamination. This study examined the fate of Salmonella in different steps of tahini processing and refrigerated storage of tahini. A four serovar cocktail of Salmonella was used for inoculation of sesame seeds and tahini. Bacterial populations were determined by aerobic plate counts on both selective and non-selective media. Water activity of samples was determined during processing and storage. For the soaking step during tahini processing, unhulled dry sesame seeds with aw of 0.1 were inoculated with Salmonella, held 24 h, and then soaked in water at ambient temperature. Populations were monitored at 0, 18, 22 and 24 h. Salmonella decreased by 2 - 3-log CFU/g during drying and then increased by 5 log CFU/g after rehydration. Separately, inoculated de-hulled seeds with two different initial aw were roasted at three different temperatures (95, 110, and 130 ºC) for 90 min. Both the Salmonella populations and aw were determined at 10 min intervals during roasting. Finally, inoculated sesame seeds were processed into tahini. As a comparison, the same quantity of uninoculated roasted sesame seeds were processed into tahini, and then inoculated post-processing. Tahini was stored at 4 ºC for 17 weeks. Approximately 8 log CFU/g of Salmonella was detected initially in the sesame seeds prior to roasting with a 1-log CFU/g reduction after 20 min at 95 ºC when the aw of seeds decreased quickly. For different roasting temperatures, the aw declined much faster and stopped decreasing during roasting, while populations continue decreasing throughout the whole roasting. To investigate survival of Salmonella during refrigerated storage of tahini, approximately 9 log CFU/g of Salmonella was inoculated onto sesame seeds or into processed tahini without significant reduction throughout 17 weeks (p > 0.05). These results suggest that Salmonella contamination can be an issue at any step of tahini manufacture.
M.S. in Food Safety and Technology, May 2016
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Title: EFFICIENT SCORING AND RANKING OF EXPLANATION FOR DATA EXCHANGE ERRORS IN VAGABOND
Creator: Wang, Zhen
Date: 2014, 2014-05
Description: Data exchange has been widely used in big data era. One challenge for data exchange is to identify the true cause of data errors during the...
Show moreData exchange has been widely used in big data era. One challenge for data exchange is to identify the true cause of data errors during the schema translation. The huge amount of data and schemas make it nearly impossible to find “the” correct solution. Vagabond system is developed to address this problem and use best-effort methods to rank data exchange error explanations base on the likelihood that they are the correct solutions. Ranking done on scoring functions that model some aspects of explanation sets. Examples of these properties include complexity(size of explana- tion), and side effect size(number of correct data values that will be affected by the changes). The thesis introduced three new scoring functions to increase the applicability of Vagabond under various data exchange scenarios. We prove that the monotonicity property required by Vagabond may not hold for some of the new scoring functions, so a new generic ranker is also introduced to efficiently rank error explanations for these new scoring functions as well as for future scoring functions that have boundary property. We can efficiently compute upper or lower bounds on the score of partial solutions. We also completed some performance experiments on the new scoring functions and the new ranker. The experiment result proves that the new scoring functions introduced in this thesis have a scalable performance.
M.S. in Computer Science, May 2014
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Title: IMPACT OF INOCULUM LEVEL ON THE TRANSFER OF SALMONELLA SEROVARS FROM CONTAMINATED ALMOND BUTTER TO FOOD CONTACT MATERIALS
Creator: Zheng, Yue
Date: 2012-11-19, 2012-12
Description: Outbreaks of salmonellosis associated with nut butter have raised public concerns of sanitation issues in nut butter processing. The high fat,...
Show moreOutbreaks of salmonellosis associated with nut butter have raised public concerns of sanitation issues in nut butter processing. The high fat, low-moisture characteristics of nut butters significantly affect the efficiency of regular cleaning and sanitizing programs, allowing cross-contamination issues to persist on processing equipment. Besides organic matter in food soil, microbial load could also be a factor affecting efficacy of chemical sanitizers. The FDA Food Code (2005) require a 5-log bacterial reduction in testing the efficacy of a chemical sanitation method. As a result, evaluation of microbial transfer is essential for establishing methods for equipment sanitation. The first study of this thesis (Section 4.1) evaluated the survival of Salmonella serovars in almond butter at 25 ± 2 oC. This was achieved by investigating the survival of Salmonella Tennessee and Salmonella Oranienburg in inoculated almond butter sample for up to two weeks. These Salmonella serovars were inoculated into creamy almond butter separately and stored at 25 ± 2 oC. Results showed that Salmonella populations decreased slowly and could survive in almond butter for at least two weeks. This study also investigated the effect of initial inoculum level, contact time, food-contact material and bacterial serovar on the subsequent potential for transfer of bacteria to equipment surfaces (Section 4.2). Almond butter inoculated with Salmonella Oranienburg and Tennessee at different inoculums levels (~3, 6, 9 log CFU/g) were spread on 16 cm2 coupons made of polyethylene, polyurethane, Delrin and stainless steel. Microbial analysis was conducted after physically removing all visible nut butter with laboratory wipes. Results for S. Oranienburg and Tennessee followed similar trends of microbial transfer with regards to inoculum level and food-contact surface. The amount x of Salmonella transferred to a food-contact surface was dependent on initial inoculation levels. An average of 0.88 ± 0.22, 1.53 ± 0.15, and 4.59 ± 0.06 log CFU S. Tennessee per 16 cm2 were transferred to the four different food-contact surface types for low, medium, and high inoculum level, respectively. An average of 1.25 ± 0.24, 2.08 ± 0.08, and 4.55 ± 0.35 log CFU S. Oranienburg per 16 cm2 were transferred to the same four different foodcontact surfaces for low, medium, and high inoculum levels, respectively. The third part of this study (Section 4.3) determined the transfer of Salmonella from contaminated food-contact coupon surfaces to almond butter. Uninoculated almond butter was applied on the surface of previously contaminated food-contact coupon surfaces. More than 5 log CFU/16 cm2 Salmonella could transfer to clean almond butter after immediate contact (within 5 min) with the contaminated area. These findings help advance our understanding of factors affecting microbial transfer between nut butters and processing equipment surfaces. This research can be used to support future cleaning and sanitation studies for nut butter processing equipment.
M.S. in Food Safety and Technology, December 2012
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Title: EXPERIMENTAL EFFECTS OF SOCIAL MEDIA ON BODY DISSATISFACTION AND EATING PATHOLOGY: UPWARD VERSUS DOWNWARD COMPARISONS
Creator: Badillo, Krystal Elizabeth
Date: 2019
Description: Research has been limited in assessing the different impacts of social media platforms on body dissatisfaction, apart from Facebook. In...
Show moreResearch has been limited in assessing the different impacts of social media platforms on body dissatisfaction, apart from Facebook. In addition, most studies have measured social media use by only assessing time. This study aimed to test experimental effects of social comparison on body dissatisfaction (BD) and desire to engage in eating behaviors. In addition, a mediation model was tested of the association between social media use and BD via social comparison. Participants viewed one of two live public Instagram profiles and were asked questions that facilitated individuals comparing their appearance to the Instagram profile. A total of 74 women completed questionnaires regarding social media use, body image, and eating disorder psychopathology. It was found that regardless of condition, desire to eat decreased after profile views, but there was no change in BD. The mediation model suggests that there was a significant indirect effect of increased BD and importance of Instagram through social comparison. Results suggest that, contrary to earlier work, overall social media use may not negatively impact BD as previously thought. Rather, it appears that trait level factors such as social comparison negatively influence BD while using social media.
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Title: Developing Novel Optimization Algorithms Applied To Building Energy Performance and Indoor Air Quality
Creator: Faramarzi, Afshin
Date: 2021
Description: Residential and commercial buildings account for 23% of global energy use. In the United States, space heating, cooling, and lighting energy...
Show moreResidential and commercial buildings account for 23% of global energy use. In the United States, space heating, cooling, and lighting energy use accounts for 38%, 9%, and 7% of building energy consumption, which results in 54% of the total energy consumption of the building. Energy efficiency improvements in buildings require consideration of optimal design, operation, and control of building components (e.g., mechanical and envelope systems). We can address this task by taking advantage of computational optimization methods throughout the design, operation, and control processes.Non-gradient metaheuristic optimization methods known as metaheuristics are some of the most popular and widely used optimization methods in Building Performance Optimization (BPO) problems. Conventional metaheuristics usually have simple mathematical models with low rate of convergence. On the other hand, high-performance metaheuristic optimizers are efficient and usually have a fast rate of convergence, but their mathematical models are hard to understand and implement. As such, researchers are usually not inclined to employ them in solving their problems. To this end, we aimed at developing optimization algorithms which borrow simplicity from conventional methods and efficiency from high-performance optimizers to solve problems fast and efficiently while being welcomed by users from throughout the world. Therefore, the overarching objective of this work is defined to first develop novel optimization algorithms which are simple in mathematical models and still efficient in solving optimization benchmark problems and then apply the methods to building energy performance and indoor air quality (IAQ) problems. In the first objective of this work, which is the development phase, two continuous optimization methods and one binary optimizer are developed and are separately described in three different tasks. The first method called Equilibrium Optimizer (EO) is a simple method inspired by the mass balance equation in a control volume. The second optimization method called Marine Predators Algorithm (MPA) is a more complicated method compared to EO and is inspired by widespread foraging strategies between marine predators in the ocean ecosystem. Finally, the third method is the binary version of an already developed equilibrium optimizer called Binary Equilibrium Optimizer (BEO). The second objective of the dissertation is the application phase which focuses on the application of the developed methods and other widely used methods in research and industry for solving the almost new BPO and IAQ problems. The results showed that the developed methods were able to either reach more energy-efficient solutions compared to the other methods or to show a considerably faster rate of convergence compared to other methods in the problems in which the optimal solutions are similarly obtained by different methods.
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Title: AI IN MEDICINE: ENABLING INTELLIGENT IMAGING, PROGNOSIS, AND MINIMALLY INVASIVE SURGERY
Creator: Getty, Neil
Date: 2022
Description: While an extremely rich research field, compared to other applications of AI such as natural language processing (NLP) and image processing...
Show moreWhile an extremely rich research field, compared to other applications of AI such as natural language processing (NLP) and image processing/generation, AI in medicine has been much slower to be applied in real-world clinical settings. Often the stakes of failure are more dire, the access of private and proprietary data more costly, and the burden of proof required by expert clinicians is much higher. Beyond these barriers, the often typical data-driven approach towards validation is interrupted by a need for expertise to analyze results. Whereas the results of a trained Imagenet or machine translation model are easily verified by a computational researcher, analysis in medicine can be much more multi-disciplinary demanding. AI in medicine is motivated by a great demand for progress in health-care, but an even greater responsibility for high accuracy, model transparency, and expert validation.This thesis develops machine and deep learning techniques for medical image enhancement, patient outcome prognosis, and minimally invasive robotic surgery awareness and augmentation. Each of the works presented were undertaken in di- rect collaboration with medical domain experts, and the efforts could not have been completed without them. Pursuing medical image enhancement we worked with radiologists, neuroscientists and a neurosurgeon. In patient outcome prognosis we worked with clinical neuropsychologists and a cardiovascular surgeon. For robotic surgery we worked with surgical residents and a surgeon expert in minimally invasive surgery. Each of these collaborations guided priorities for problem and model design, analysis, and long-term objectives that ground this thesis as a concerted effort towards clinically actionable medical AI. The contributions of this thesis focus on three specific medical domains. (1) Deep learning for medical brain scans: developed processing pipelines and deep learn- ing models for image annotation, registration, segmentation and diagnosis in both traumatic brain injury (TBI) and brain tumor cohorts. A major focus of these works is on the efficacy of low-data methods, and techniques for validation of results without any ground truth annotations. (2) Outcome prognosis for TBI and risk prediction for Cardiovascular Disease (CVD): we developed feature extraction pipelines and models for TBI and CVD patient clinical outcome prognosis and risk assessment. We design risk prediction models for CVD patients using traditional Cox modeling, machine learning, and deep learning techniques. In this works we conduct exhaustive data and model ablation study, with a focus on feature saliency analysis, model transparency, and usage of multi-modal data. (3) AI for enhanced and automated robotic surgery: we developed computer vision and deep learning techniques for understanding and augmenting minimally invasive robotic surgery scenes. We’ve developed models to recognize surgical actions from vision and kinematic data. Beyond model and techniques, we also curated novel datasets and prediction benchmarks from simulated and real endoscopic surgeries. We show the potential for self-supervised techniques in surgery, as well as multi-input and multi-task models.
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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: Intelligent Job Scheduling on High Performance Computing Systems
Creator: Fan, Yuping
Date: 2021
Description: Job scheduler is a crucial component in high-performance computing (HPC) systems. It sorts and allocates jobs according to site policies and...
Show moreJob scheduler is a crucial component in high-performance computing (HPC) systems. It sorts and allocates jobs according to site policies and resource availability. It plays an important role in the efficient use of system resources and users satisfaction. Existing HPC job schedulers typically leverage simple heuristics to schedule jobs. However, the rapid growth in system infrastructure and the introduction of diverse workloads pose serious challenges to the traditional heuristic approaches. First, the current approaches concentrate on CPU footprint and ignore the performance of other resources. Second, the scheduling policies are manually designed and only consider some isolated job information, such as job size and runtime estimate. Such a manual design process prevents the schedulers from making informative decisions by extracting the abundant environment information (i.e., system and queue information). Moreover, they can hardly adapt to workload changes, leading to degraded scheduling performance. These challenges call for a new job scheduling framework that can extract useful information from diverse workloads and the increasingly complicated system environment, and finally make well-informed scheduling decisions in real time.In this work, we propose an intelligent HPC job scheduling framework to address these emerging challenges. Our research takes advantage of advanced machine learning and optimization methods to extract useful workload- and system-specific information and to further educate the framework to make efficient scheduling decisions under various system configurations and diverse workloads. The framework contains four major efforts. First, we focus on providing more accurate job runtime estimations. Estimated job runtime is one of the most important factors affecting scheduling decisions. However, user provided runtime estimates are highly inaccurate and existing solutions are prone to underestimation which causes jobs to be killed. We leverage and enhance a machine learning method called Tobit model to improve the accuracy of job runtime estimates at the same time reduce underestimation rate. More importantly, using TRIP’s improved job runtime estimates boosts scheduling performance by up to 45%. Second, we conduct research on multi-resource scheduling. HPC systems are undergoing significant changes in recent years. New hardware devices, such as GPU and burst buffer, have been integrated into production HPC systems, which significantly expands the schedulable resources. Unfortunately, the current production schedulers allocate jobs solely based on CPU footprint, which severely hurts system performance. In our work, we propose a framework taking all scalable resources into consideration by transforming this problem into multi-objective optimization (MOO) problem and rapid solving it via genetic algorithm. Next, we leverage reinforcement learning (RL) to automatically learn efficient workload- and system-specific scheduling policies. Existing HPC schedulers either use generalized and simple heuristics or optimization methods that ignore workload and system characteristics. To overcome this issue, we design a new scheduling agent DRAS to automatically learn efficient scheduling policies. DRAS leverages the advance in deep reinforcement learning and incorporates the key features of HPC scheduling in the form of a hierarchical neural network structure. We develop a three-phase training process to help DRAS effectively learn the scheduling environment (i.e., the system and its workloads) and to rapidly converge to an optimal policy. Finally, we explore the problem of scheduling mixed workloads, i.e., rigid, malleable and on-demand workloads, on a single HPC system. Traditionally, rigid jobs are the main tenants of HPC systems. In recent years, malleable applications, i.e., jobs that can change sizes before and during execution, are emerging on HPC systems. In addition, dedicated clusters were the main platforms to run on-demand jobs, i.e., jobs needed to be completed in the shortest time possible. As the sizes of on-demand jobs are growing, HPC systems become more cost-efficient platforms for on-demand jobs. However, existing studies do not consider the problem of scheduling all three types of workloads. In our work, we propose six mechanisms, which combine checkpointing, shrink, expansion techniques, to schedule the mixed workloads on one HPC system.
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Title: FACTORS INFLUENCING INDIVIDUALS’ PROVISION OF AUTONOMY SUPPORT TO THEIR PARTNERS WITH CHRONIC PAIN: A PATH ANALYSIS MODEL BASED ON SELF-DETERMINATION THEORY
Creator: Ivins-Lukse, Melissa N.
Date: 2021
Description: Receiving autonomy support from a relationship partner has been associated with increased physical activity among individuals with chronic...
Show moreReceiving autonomy support from a relationship partner has been associated with increased physical activity among individuals with chronic pain (ICP), but no studies have explored what factors may influence partners’ use of an autonomy supportive interpersonal style with an ICP. Self-determination theory (SDT) posits that contextual, perceptual, and individual factors influence how much individuals use an autonomy supportive interpersonal style through the mediators of basic psychological need satisfaction and autonomous motivation. The present study used path analysis to test a SDT model of the relationships between a contextual factor (autonomy support from health care provider), a perceptual factor (partner’s perception of ICP motivation for physical activity), an individual factor (partner catastrophizing about ICP’s pain), and the sequential mediators of relationship need satisfaction and autonomous motivation with respect to the dependent variable of partners’ use of an autonomy supportive interpersonal style. 176 partners of ICPs completed a cross-sectional survey including the Health Care Climate Questionnaire, partner-report revised Behavioral Regulation in Exercise Questionnaire, Pain Catastrophizing Scale – Significant Other version, Need Satisfaction Scale, Motivation to Help, and Interpersonal Behaviours Questionnaire-Self. The proposed model demonstrated poor fit to the data: χ2 (10) = 31.949, p < 0.001), RMSEA = 0.11 (90% CI = .07 to .16, p = 0.01), CFI = 0.81, and SRMR = .10. While the overall model was not supported, most individual pathways in the model were significant. Alternative analyses were conducted to identify a model with acceptable fit.
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Title: Numerical Analysis and Deep Learning Solver of the Non-local Fokker-Planck Equations
Creator: Jiang, Senbao
Date: 2022
Description: This thesis is divided into three mutually connected parts. ...
Show moreThis thesis is divided into three mutually connected parts. In the first part, we introduce and analyze arbitrarily high-order quadrature rules for evaluating the two-dimensional singular integrals of the forms \begin{align*} I_{i,j} = \int_{\mathbb{R}^2}\phi(x)\frac{x_ix_j}{|x|^{2+\alpha}} \d x, \quad 0< \alpha < 2 \end{align*} where $i,j\in\{1,2\}$ and $\phi\in C_c^N$ for $N\geq 2$. This type of singular integrals and its quadrature rule appear in the numerical discretization of fractional Laplacian in non-local Fokker-Planck Equations in 2D. The quadrature rules are trapezoidal rules equipped with correction weights for points around singularity. We prove the order of convergence is $2p+4-\alpha$, where $p\in\mathbb{N}_{0}$ is associated with total number of correction weights. We present numerical experiments to validate the order of convergence of the proposed modified quadrature rules. In the second part, we propose and analyze a general arbitrarily high-order modified trapezoidal rule for a class of weakly singular integrals of the forms $I = \int_{\R^n}\phi(x)s(x)\d x$ in $n$ dimensions, where $\phi$ and $s$ is the regular and singular part respectively. The admissible class requires $s$ satisfies three hypotheses and is large enough to contain singular kernel of the form $P(x)/|x|^r,\ r > 0$ where $P(x)$ is any monomial with degree strictly less than $r$. The modified trapezoidal rule is the singularity-punctured trapezoidal rule plus correction terms involving the correction weights for grid points around singularity. Correction weights are determined by enforcing the quadrature rule to exactly evaluate some monomials and solving corresponding linear systems. A long-standing difficulty of these types of methods is establishing the non-singularity of the linear system, despite strong numerical evidence. By using an algebraic-combinatorial argument, we show the non-singularity always holds and prove the general order of convergence of the modified quadrature rule. We present numerical experiments to validate the order of convergence. In the final part, we propose \emph{trapz-PiNN}, a physics-informed neural network incorporated with a modified trapezoidal rule and solve the space-fractional Fokker-Planck equations in 2D and 3D. We verify the modified trapezoidal rule has the second-order accuracy for evaluating the fractional laplacian. We demonstrate trapz-PiNNs have high expressive power through predicting solutions with low $\mathcal{L}^2$ relative error on a variety of numerical examples. We also use local metrics such as point-wise absolute and relative errors to analyze where could be further improved. We present an effective method for improving performance of trapz-PiNN on local metrics, provided that physical observations of high-fidelity simulation of the true solution are available. Besides the usual advantages of the deep learning solvers such as adaptivity and mesh-independence, the trapz-PiNN is able to solve PDEs with fractional laplacian with arbitrary $\alpha\in (0,2)$ and specializes on rectangular domains. It also has potential to be generalized into higher dimensions.
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