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Title: Tanner, Robert, Oral History Interview, 2011
Creator: Tanner, Robert, Walker, Dale, Kuruna, Daniel
Date: 2011-05-01
Description: Video interview with Robert (Bob) Tanner, who received a BS in Photography from the Institute of Design in 1959. Tanner recounts his...
Show moreVideo interview with Robert (Bob) Tanner, who received a BS in Photography from the Institute of Design in 1959. Tanner recounts his experience as an undergraduate student under Harry Callahan and Aaron Siskind, and how ID impacted his professional work in film. Running time is 10:15 minutes.
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Collection: Institute of Design Photography Oral History Project, 2011

Title: Learning Stochastic Governing Laws from Noisy Data Using Normalizing Flows
Creator: McClure, William Jacob
Date: 2021
Description: With the increasing availability of massive collections of data, researchers in all sciences need tools to synthesize useful and pertinent...
Show moreWith the increasing availability of massive collections of data, researchers in all sciences need tools to synthesize useful and pertinent descriptors of the systems they study. Perhaps the most fundamental knowledge of a dynamical system is its governing laws, which describe its evolution through time and can be lever-aged for a number of analyses about its behavior. We present a novel technique for learning the infinitesimal generator of a Markovian stochastic process from large, noisy datasets generated by a stochastic system. Knowledge of the generator in turn allows us to find the governing laws for the process. This technique relies on normalizing flows, neural networks that estimate probability densities, to learn the density of time-dependent stochastic processes. We establish the efficacy of this technique on multiple systems with Brownian noise, and use our learned governing laws to perform analysis on one system by solving for its mean exit time. Our approach also allows us to learn other dynamical behaviors such as escape probability and most probable pathways in a system. The potential impact of this technique is far-reaching, since most stochastic processes in various fields are assumed to be Markovian, and the only restriction for applying our method is available data from a time near the beginning of an experiment or recording.
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Title: SPECIFICITY OF DEFICITS IN EXECUTIVE FUNCTIONING IN YOUTH WITH NONVERBAL LEARNING DISABILITY, ATTENTION DEFICIT HYPERACTIVITY DISORDER AND READING DISORDER
Creator: McCue, Kimberly Ann
Date: 2021
Description: Nonverbal Learning Disability (NLD) has been the focus of four decades of neuropsychological research. However, it has yet to be included as a...
Show moreNonverbal Learning Disability (NLD) has been the focus of four decades of neuropsychological research. However, it has yet to be included as a diagnostic category in the Diagnostic and Statistical Manual of Mental Disorders (i.e., currently in its fifth edition, DSM-5, American Psychiatric Association, 2013). Many of the characteristics associated with Nonverbal Learning Disorder (NLD) are similar to those found in other more established disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD), Specific Learning Disorders (SLD), and Autism Spectrum Disorder (ASD). Recent research in neuropsychology and other fields has contributed to a greater understanding of the cognitive profiles of NLD, ADHD, and Reading Disorder (RD). However, the neurological underpinnings of deficits in executive functioning specific to NLD versus ADHD and RD have yet to be fully elucidated. Ongoing research has failed to distinguish NLD from other childhood disorders, including ADHD, based on specific structural or functional neurological deficits. The current study examined the specificity of deficits in executive functioning in youth with nonverbal learning disability, attention deficit hyperactivity disorder and reading disorder. In addition, the study examined the degree to which the Rey Complex Figure Test subscales and Processing Speed Index (PSI) and Working Memory Index (WMI) scores (WISC-IV or WISC-III) could discriminate between the NLD group from ADHD and RD groups. Data for the present study were collected from a population served by the Pediatric Neuropsychological Service at The University of Chicago Medicine. Children who had been referred for neuropsychological assessment and whose comprehensive battery included a WISC measure (WISC-III or WISC-IV) and RCFT measurements were included. All data were archival, i.e., gleaned from the Service database; data from 202 participants was retrieved, including youth who underwent neuropsychological evaluation between 2003 and 2016. The present study hypothesized differences between NLD, ADHD, and RD diagnostic groups on visuo-spatial planning/organization, visuo-spatial working memory, long-term visuo-spatial recall, visuo-spatial recognition, verbal working memory, and processing speed. In summary, of the six executive function domains examined, two domains showed significant underperformance for the NLD group, two domains showed a non-significant trend of underperformance for the NLD group and two domains did not show significant differences between diagnostic groups.
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Title: MODELING AND CONTROL OF A GASOLINE-FUELED COMPRESSION IGNITION ENGINE
Creator: Pamminger, Michael
Date: 2021
Description: This work investigates a novel combustion concept, Gasoline Compression Ignition, that derives its superiority from the high compression ratio...
Show moreThis work investigates a novel combustion concept, Gasoline Compression Ignition, that derives its superiority from the high compression ratio of a compression ignition engine as well as the properties of gasoline fuel, such as longer ignition delay and higher volatility compared to diesel fuel. Gasoline Compression Ignition was experimentally tested on a 12.4L truck engine and the acquired data were leveraged to develop a physics-based 0-dimensional combustion model for an engine operating with a low-reactivity fuel. The proposed 0-dimensional combustion model was developed to account for the different stages in combustion caused by the fuel stratification of various injection events and fuel mass fractions. As the ignition delay model is an integral part of the entire combustion process and significantly affects the predictionaccuracy, special attention was paid to local phenomena influencing ignition delay. A 1-dimensional spray model by Musculus and Kattke was employed in conjunction with a Lagrangian tracking approach in order to estimate the local fuel-air ratio within the spray tip, as a proxy for reactivity. The local fuel-air ratio, in-cylinder temperature and pressure were used in an integral fashion to estimate the ignition delay. Heat release rates were modeled by using first-order non-linear differential equations. Model prediction errors in combustion phasing of less than 1 crank angle degree across most conditions were achieved. Modeling results of other combustion metrics such as combustion duration and indicated mean effective pressure are also suitably accurate. Also, the model has been shown to be capable of estimating the ringing intensity for most conditions. While the performance of the proposed model was very satisfactory, the high computational time made it unsuitable for simulations. The high computational cost was mostly caused by the 1-dimensional spray model which described the fuelstratifcation in the spray tip as a function of crank angle for multiple injection events. Insights obtained from the 1-dimensional spray model were leveraged and applied to a 0-dimensional model to reduce the computation time. With the reduced order model, the simulation time decreased by three orders of magnitude for an entire engine cycle over the combustion model with the 1-dimensional spray model. Capturing only the basic features of the spray propagation did not show a substantial increase in prediction error compared to the initially proposed model. In order for this model to reflect a virtual engine, the influence of changes in actuator settings on intake manifold dynamics was modeled with first-order transfer functions. The intake manifold dynamics in turn influence intake valve closure conditions and further the entire combustion process. The proposed model provides information about in-cylinder metrics such as combustion phasing and indicated mean effective pressure. By taking into account the losses due to gas-exchange and friction, the brake mean effective pressure was modeled. The model was also augmented to capture cycle-to-cycle variations, thereby ensuring a faithful representation of real engine behavior. The Gasoline Compression Ignition combustion model, the intake dynamics and gas-exchange and friction model as well as the cycle-to-cycle variations model were combined to create a full engine model. This Gasoline Compression Ignition engine model was used as the plant in a control system and implemented in Matlab/Simulink.The Gasoline Compression Ignition engine model was then leveraged to investigate control actions and engine behavior with and without limiting in-cylinder peak pressure as well as combustion noise. Controlling combustion noise is of particular interest for injection strategies where fuel introduction happens early in the cycle. State estimation was performed by means of a Kalman filter which feeds into a model predictive controller. The model predictive controller chooses control actions based on a predefined cost function under consideration of bounds reflecting physical constraints. The Gasoline Compression Ignition engine model was also utilized to establish a state-space model that serves the Kalman filter and model predictive controller for estimation and prediction. In addition, the proposed control architecture was investigated at two different levels of cycle-to-cycle variations. Disturbance rejection was implemented to reduce state fluctuations and control efforts when high cycle-to-cycle variations are present. The control algorithm is able to maintain the desired references for brake mean effective pressure and combustion phasing while controlling peak in-cylinder pressure and combustion noise.
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Title: POTENTIAL EXPOSURE TO SUBSTANCES IN POLYMER COMPOSITES USED AS FOOD PACKAGING MATERIALS
Creator: Shah, Saloni S.
Date: 2021
Description: In the food manufacturing, preservation, supply, and distribution chain, packaging plays a critical role. The fundamental goal of any...
Show moreIn the food manufacturing, preservation, supply, and distribution chain, packaging plays a critical role. The fundamental goal of any packaging method is to keep food contained and protected. There is an increasing demand for natural and "fresh-like" foods that are less processed and have a longer shelf life, necessitating a variety of packing strategies. With increasing demand, the biggest developments in the field of packaging technology have been innovative food packaging approaches, such as active packaging, intelligent packaging, and bioactive packaging, which include deliberate contact with the food or its surroundings and its effect on consumer health. Several research studies in the past few years have shown that nanocomposite materials have significant improvement in the strength, barrier characteristics, antimicrobial capabilities, and heat and cold stability of food packaging materials, but various studies have reported that these composites might be a source of engineered nanomaterials in the human diet or environment. It has also been reported in numerous studies that nanocomposites can migrate into the food during long-term storage. These studies use food simulants like acetic acid and water to mimic the food matrix. However, they raise issues regarding how ingredients in real foods could affect exposure. This research focuses on the migration of silver (Ag) ions into food matrix-like commercial beverages and demonstrating if the ingredients present in commercial food and beverages influence the migration process. For the study, polymer composites films and dogbones were made. Polymer composite films with 0.2%, 1%, and 5% of silver zeolite concentration in polylactic acid (PLA) were produced, and different media like water, Domino sugar, and Squirt were stored in packages manufactured from this material under accelerated room-temperature conditions. Polymer composite dogbones were made with low-density polyethylene (LDPE) and polypropylene (PP) with 1.25% and 2.51% of graphene and graphite. Further, these materials were characterized with the help of Thermogravimetric analysis (TGA), Fourier Transform Infrared Spectroscopy-Attenuated Total Reflection (FTIR-ATR), and inductively coupled plasma mass spectrometry (ICPMS). This hypothesis of this study was that, when polymer composites are employed in packaging applications, food and beverage components may impact dietary exposure to these particles, and the use of food simulants may underpredict the quantity of the migration in some cases
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Title: AUTOMATION OF ULTRASONIC FLAW DETECTION APPLICATIONS USING DEEP LEARNING ALGORITHMS
Creator: Virupakshappa, Kushal
Date: 2021
Description: The Industrial Revolution-4.0 promises to integrate multiple technologies including but not limited to automation, cloud computing, robotics,...
Show moreThe Industrial Revolution-4.0 promises to integrate multiple technologies including but not limited to automation, cloud computing, robotics, and Artificial Intelligence. The non-Destructive Testing (NDT) industry has been shifting towards automation as well. For ultrasound-based NDT, these technological advancements facilitate smart systems hosting complex signal processing algorithms. Therefore, this thesis introduces the effective use of AI algorithms in challenging NDT scenarios. The first objective is to investigate and evaluate the performance of both supervised and unsupervised machine learning algorithms and optimize them for ultrasonic flaw detection utilizing Amplitude-scan (A-scan) data. Several inferences and optimization algorithms have been evaluated. It has been observed that proper choice of features for specific inference algorithms leads to accurate flaw detection. The second objective of this study is the hardware realization of the ultrasonic flaw detection algorithms on embedded systems. Support Vector Machine algorithm has been implemented on a Tegra K1 GPU platform and Supervised Machine Learning algorithms have been implemented on a Zynq FPGA for a comparative study. The third main objective is to introduce new deep learning architectures for more complex flaw detection applications including classification of flaw types and robust detection of multiple flaws in B-scan data. The proposed Deep Learning pipeline combines a novel grid-based localization architecture with meta-learning. This provides a generalized flaw detection solution wherein additional flaw types can be used for inference without retraining or changing the deep learning architecture. Results show that the proposed algorithm performs well in more complex scenarios with high clutter noise and the results are comparable with traditional CNN and achieve the goal of generality and robustness.
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Title: Alignment of Science-Themed Trade Books to the Next Generation Science Standards
Creator: Shepard, Kelly Marie
Date: 2021
Description: Elementary teachers often integrate science-themed trade books into their science and reading lessons. This study examines the alignment of...
Show moreElementary teachers often integrate science-themed trade books into their science and reading lessons. This study examines the alignment of science-themed trade books written for readers in Kindergarten through fifth-grade to the Next Generation Science Standards Disciplinary Core Ideas (NGSS DCI). The goal of this research is to analyze the scientific concepts presented in the text of the trade books recommended by professional organizations dedicated to science and science education. Research finds that integrated science and reading are valuable for elementary students’ understandings of science. This study addresses two problems: 1) elementary teachers have limited scientific knowledge and 2) there is a dearth of research that examines the expression of NGSS DCI in science-themed trade books for K-5th grades. The sample is selected from booklists compiled by professional organizations devoted to science and science education. A deductive content analysis methodology is used to identify the presence of NGSS DCI in trade books. Descriptive statistics and qualitative data analyses are used to reveal the themes in the collected data. A large majority of the sample is aligned to the NGSS DCI for K-5th grade. Most trade books express NGSS DCI at the grade levels for which they are recommended. The study is limited and does not examine the readability of trade books, scientific vocabulary, or images. This study contributes to the research on the intersection between science and reading for elementary grade levels.
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Title: DEVELOPMENT OF BIOMARKERS OF SMALL VESSEL DISEASE IN AGING
Creator: Makkinejad, Nazanin
Date: 2021
Description: Age-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and...
Show moreAge-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and development of dementia. Designing methodologies for early prediction of these diseases are much needed. Since multiple pathologies commonly coexist in brains of older adults, clinical diagnosis lacks the specificity to isolate the pathology of interest, and gold standard is determined only at autopsy. Magnetic resonance imaging (MRI) provides a non-invasive tool to study abnormalities in brain characteristics that is unique to each pathology. Utilizing ex-vivo MRI for brain imaging proves to be useful as it eliminates two important biases of in-vivo MRI. First, no additional pathology would develop between imaging and pathologic examination, and second, frail older adults would not be excluded from MRI.Hence, the aims of this dissertation were two-fold: to study brain correlates of age- related neuropathologies, and to develop and validate classifiers of small vessel diseases by combining ex-vivo MRI and pathology in a large community cohort of older adults. The structure of the project is as follows.First, the association of amygdala volume and shape with transactive response DNA-binding protein 43 (TDP-43) pathology was investigated. Using a regularized regression technique, higher TDP-43 was associated with lower amygdala volume. Also, shape analysis of amygdala showed unique patterns of spatial atrophy associated with TDP-43 independent of other pathologies. Lastly, using linear mixed effect models, amygdala volume was shown to explain an additional portion of variance in cognitive decline above and beyond what was explained by the neuropathologies and demographics.Second, the previous study was extended to analyze other subcortical regions including the hippocampus, thalamus, nucleus accumbens, caudate, and putamen, and was also conducted in a larger dataset. The results showed unique contribution of TDP-43, neurofibrillary tangles (hallmark characteristic of Alzheimer’s disease pathology), and atherosclerosis (a cerebrovascular pathology) to atrophy on the surface of subcortical structures. Understanding the independent effects of each pathology on volume and shape of different brain regions can form a basis for the development of classifiers of age-related neuropathologies.Third, an in-vivo classifier of arteriolosclerosis was developed and validated. Arteriolosclerosis is one of the main pathologies of small vessel disease, is associated with cognitive decline and dementia, and currently has no standard biomarker available. In this work, the classifier was developed ex-vivo using machine learning (ML) techniques and was then translated to in-vivo. The in-vivo classifier was packaged as a software called ARTS, which outputs a score that is the likelihood of arteriolosclerosis when the required input is given to the software. It was tested and validated in various cohorts and showed to have high performance in predicting the pathology. It was also shown that higher ARTS score was associated with greater cognitive decline in domains that are specific to small vessel disease.Fourth, motivated by current trends and superiority of deep learning (DL) techniques in classification tasks in computer vision and medical imaging, a preliminary study was designed to use DL for training an ex-vivo classifier of arteriolosclerosis. Specifically, convolutional neural networks (CNNs) were applied on 3 Tesla ex-vivo MR images directly without providing prior information of brain correlates of arteriolosclerosis. One interesting aspect of the results was that the network learnt that white matter hyperintense lesions contributed the most to classification of arteriolosclerosis. These results were encouraging, and more future work will exploit the capability of DL techniques alongside the traditional ML approaches for more automation and possibly better performance.Finally, a preliminary classifier of arteriolosclerosis and small vessel atherosclerosis was developed since the existence of both pathologies in brain have devastating effects on cognition. The methodology was similar to the one used for development of arteriolosclerosis classifier with minor differences. The classifier showed a good performance in-vivo, although the testing needs to be assessed in more cohorts.The comprehensive study of age-related neuropathologies and their contribution to abnormalities of subcortical brain structures offers a great potential to develop a biomarker of each pathology. Also, the finding that the MR-based classifier of arteriolosclerosis showed high performance in-vivo demonstrate the potential of ex-vivo studies for development of biomarkers that are precise (because they are based on autopsy, which is the gold standard) and are expected to work well in-vivo. The implications of this study include development of biomarkers that could potentially be used in refined participant selection and enhanced monitoring of the treatment response in clinical drug and prevention trials.
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Title: HIGH SURFACE AREA CARBONS FOR ENERGY STORAGE TECHNOLOGIES
Creator: Lee, Youngjin
Date: 2021
Description: Energy storage systems play a pivotal role in harvesting energy from various sources and converting it to the energy forms required for...
Show moreEnergy storage systems play a pivotal role in harvesting energy from various sources and converting it to the energy forms required for applications in several sectors, such as utility, industry, building and transportation. The outstanding growth of portable electronic devices and electric vehicle/hybrid electric vehicles (EVs/HEVs) has promoted the urgent and increasing demand for high‐power energy resources. The most common electrical energy‐storage device is the battery due to the large amount of energy stored in a relatively small volume and weight while providing suitable levels of power for many applications and requirements of everyday life. These days, lithium-sulfur batteries (LSBs) have been drawing attention with their potential to provide 3-5 times more energy than that of current lithium-ion batteries (LIBs) at lower cost. Thus, realization of a practical Li-S technology can move the U.S. rapidly toward a more sustainable transportation future. The electrochemical double-layer capacitor (EDLC) is also an emerging technology, which really plays a key part in fulfilling the demands of electronic devices and systems, for present and future. The EDLC technology strongly depends on the properties of electrode materials. Activated carbons play an important role in developing new electrodes for both LSB and supercapacitor technologies. For example, carbon electrode-based supercapacitors require very high specific surface area and superior pore size distribution for easy accessibility of ions. Thus, the primary objective of this study is to develop a new high surface area carbon material and assess its applicability for both LSB and supercapacitor technologies. In this thesis work, we have designed and synthesized several active carbon materials. One of them displayed very high surface area (1,832 m2/g) and excellent pore diameter (3.6 nm). We investigated the applicability of this carbon material for supercapacitor electrodes. We have also modified this carbon material with a nickel-rich phosphide in order to make it suitable for LSB cathode applications.
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Title: ENERGY METABOLISM OF CHLAMYDIA PNEUMONIAE
Creator: McMillan, B. Julia
Date: 2021
Description: Chlamydia pneumoniae is a gram-negative bacterium that infects the humanrespiratory tract. It causes acute pneumonia and has been linked to...
Show moreChlamydia pneumoniae is a gram-negative bacterium that infects the humanrespiratory tract. It causes acute pneumonia and has been linked to several chronic diseases including cardiovascular disease, asthma, and some neurological diseases. C. pneumoniae primarily exists in two forms, the elementary body (EB) and the reticulate body (RB). The EB infects host cells and the RB replicates inside them. In order to survive in and out of the host, it was thought that C. pneumoniae RBs obtain host ATP to use for energy, making it an “energy parasite.” However, genomic analysis indicated that it was also possible for C. pneumoniae to create ATP from its own respiratory chain using the Na + pump NADH Ubiquinone Oxidoreductase (Na + -NQR). Neither the details of the energy parasite theory nor the possibility of C. pneumoniae creating its own energy had been experimentally explored. This project used a pharmacological approach to explore C. pneumoniae host energy consumption at various developmental stages, examine a mechanism that the bacterium could use to produce its own energy, and assess the importance of a balanced Na + /H + gradient for energy production and maintaining homeostasis. Based on the genomic analysis, it was thought that C. pneumoniae would rely heavily on host ATP in the EB form but not the RB form, that inhibiting Na + -NQR would slow bacterial growth, particularly in RBs, and that disrupting the Na + /H + gradient would significantly reduce RB infection. The results indicate that in the EB form, C. pneumoniae relies on host ATP and requires a balanced Na + /H + gradient, but disrupting Na + -NQR does not hinder its growth. In the RB form, C. pneumoniae is not dependent on host ATP, nor on its own respiratory chain ATP, and is not impacted by an unbalanced Na + /H + gradient. Therefore, the energy parasite hypothesis appears to apply to C. pneumoniae EBs but not RBs. Furthermore, established C. pneumoniae infections are excellent at compensating for various environmental conditions and sources of energy, which proves challenging for drug design against C. pneumoniae.
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Title: The Public Stigma of Tourette Syndrome
Creator: Tooley, Anastasia Cherise
Date: 2021
Description: There is a dearth of quantitative research examining the public stigma of Tourette syndrome (TS), and no known studies assessing public...
Show moreThere is a dearth of quantitative research examining the public stigma of Tourette syndrome (TS), and no known studies assessing public perceptions of difference (how similar they are), disdain (how bad they are), and blame (how responsible they are) toward individuals with TS. The current study sought to understand the public stigma of TS as a visible and unconcealable condition. An internet sample of 450 adults were recruited through MTurk. Participants read four brief vignettes, each describing an adolescent with TS, obsessive-compulsive disorder (OCD), autism spectrum disorder (ASD), or a history of juvenile detention. Results showed TS to be associated with neutral or negative public perceptions across stigma facets. When compared to OCD and ASD, vignettes describing TS were viewed with similar difference, disdain, and blame. TS was least familiar to participants. Findings highlight differences in stigma for concealable versus visible stigmatized conditions which has implications for future research and anti-stigma interventions.
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Title: Examining Racial Differences in Body Dissatisfaction and Disordered Eating Following Media Exposure of a Curvaceous Body Ideal
Creator: Dorsaint, Talissa
Date: 2021
Description: Previous research has found that internalization of a thin body ideal contributes to negative cognitive and behavioral symptoms, such as body...
Show morePrevious research has found that internalization of a thin body ideal contributes to negative cognitive and behavioral symptoms, such as body dissatisfaction and disordered eating. However, studies supporting a sociocultural model have typically included mostly White samples. Research suggests that there may be racial differences in body dissatisfaction and disordered eating among Black and White women, specifically that Black women may be protected from body dissatisfaction via the buffering hypothesis. However, studies have found that differences in body dissatisfaction between Black and White women are smaller than previously thought. Additionally, Black women do not feel represented in the mainstream media on the basis of their physical appearance and ascribed ideals when exposed to thin ideals. Research is needed to examine the impact of other ideals (e.g., the curvaceous body ideal) on body dissatisfaction, as well as body dissatisfaction for Black women in Western culture. The present study used an experimental design to examine differences in body dissatisfaction and disordered eating behaviors in a community sample of Black and White self-identified women before and after exposure to a thin or curvaceous body ideal. Participants were randomized to a thin ideal or curvaceous ideal condition. All participants completed a demographic questionnaire, baseline measures of body dissatisfaction and disordered eating and Visual Analog Scales before and after viewing thin or curvaceous images. Findings indicated no racial differences in baseline body dissatisfaction and disordered eating. Additionally, associations between baseline body dissatisfaction and disordered eating were significant and align with previous research, but an effect of condition was found on body satisfaction change scores. No statistically significant interaction was found between race and body ideal condition for body dissatisfaction change scores. Finally, change scores of body dissatisfaction measures were not statistically different from pre- to post-exposure of either thin or curvy body ideal conditions. Findings have significant implications for the buffering hypothesis and add to studies that have found small racial differences in body dissatisfaction. Present findings also have implications for assessment and treatment in overall eating pathology as seen by the Sociocultural Model in Black women.
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Title: Computational study on the heme scavenging ability of Staphylococcus aureus IsdH receptor: Utilizing molecular dynamics to understand an unknown mechanism
Creator: Clayton, Joseph Alan
Date: 2021
Description: Methicillin-resistant Staphylococcus aureus (MRSA) has become an infamous pathogen with infection rates that have declined slowly in recent...
Show moreMethicillin-resistant Staphylococcus aureus (MRSA) has become an infamous pathogen with infection rates that have declined slowly in recent years. S. aureus requires iron as a metabolic nutrient during infection and obtains this nutrient through an iron-regulated surface-determinant (Isd) system that extracts iron from the host’s heme stored in hemoglobin (Hb) through near iron transporter (NEAT) domains. This work concentrates on studying the second and third NEAT domains of IsdH by utilizing atomistic molecular dynamics to probe the heme scavenging process; in collaboration with the Clubb Group at UCLA, we discover key functional regions of IsdH and describe fundamental interdomain dynamics. In addition, I investigate a conventional computational method to describe protein dynamics and propose an alternative that aims to alleviate computational effort by incorporating experimental data.
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Title: ADVANCING OPEN-SOURCE TOOLS FOR INDOOR ENVIRONMENTAL MONITORING AND BUILDING SYSTEMS CONTROLS USING WIRELESS SENSOR NETWORKS
Creator: Ali, Akram Syed
Date: 2021
Description: Incorporating data monitoring and visualization tools in buildings can provide a glimpse into their energy use, thermal performance, daily...
Show moreIncorporating data monitoring and visualization tools in buildings can provide a glimpse into their energy use, thermal performance, daily operation, and maintenance requirements. However, buildings have traditionally been monitored using hardware and software that are expensive, proprietary, and often limited in terms of ease of use and flexibility. Many existing buildings remain unmonitored or poorly monitored, leaving many opportunities for energy savings and improving indoor environmental conditions unaddressed. To this end, the goal of this research is to develop and demonstrate an open-source hardware and software platform for monitoring and controlling the performance of buildings and their systems, called Elemental. It is designed to provide real-time data on indoor environmental quality, energy usage, heating, ventilating, and air-conditioning (HVAC) operation, and other factors to its users, and provide easy development of building controls. It combines: (i) custom low power printed circuit boards (PCBs) with RF transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi with custom firmware acting as a backhaul, and (iii) custom software applications that manage data storage, device configuration and interface for querying and visualizing the data in real-time. The platform is built around the idea of a private, secure, and open technology for the built environment. Among its many applications, the platform allows occupants to investigate anomalies in energy usage, environmental quality, and thermal performance. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls. This proposal describes the development process of the hardware and software used in the Elemental platform along with three distinct applications including: (1) deployment in a research lab for long-term data collection and automated analysis, (2) use as a full-home energy and environmental monitoring solution, and (3) building heating system automation at the room-level with the development and deployment of a custom radiator control. Through these applications, this work demonstrates that the platform allows easy and virtually unlimited datalogging, monitoring, and analysis of real-time sensor data with low setup costs. Low-power sensor nodes placed in abundance in a building can also provide precise and immediate fault-detection, allowing for tuning equipment for more efficient operation and faster maintenance during the lifetime of the building.
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Title: A Reasoning System Architecture for Spectrum Decision-making
Creator: Das, Udayan D.
Date: 2021
Description: Spectrum is a public resource; yet understanding how spectrum is allocated and used is a daunting task. Usable spectrum is already fully...
Show moreSpectrum is a public resource; yet understanding how spectrum is allocated and used is a daunting task. Usable spectrum is already fully allocated, but the demand for spectrum continues to grow and there are opportunities for utilizing spectrum in more efficient ways. Understanding how spectrum is allocated and its utilization in time and space is necessary to take advantage of these emerging opportunities. A combination of fragmented information from varied information sources, a complex regulatory environment, variability of regulations and physics by band, real-time spectrum usage dynamics, and a status quo with knowledge concentration among a few, makes understanding spectrum a considerable challenge for all stakeholders including researchers, students, policymakers, and new telecom operators. After considerable study of spectrum, its allocation, regulation, and usage, we have developed a system architecture that is a significant step towards easing the burden of understanding spectrum information. Our system architecture connects information from disparate sources and leads to a richer understanding of spectrum usage, how it is governed, and its potential for future use. Classes of information are modeled as knowledge graphs, and the interplay of knowledge graphs produces a richer set of insight and can lead to more informed decision-making. Further, we show mechanisms for connecting spectrum information with real-time observations to get a comprehensive view of spectrum usage dynamics. While focused on the United States, this work should be applicable to other spectrum contexts worldwide. This work, of considerable technical value, also has democratic value in making complex information accessible and allowing the public to determine whether spectrum, a natural resource, is being used for the public good.
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Title: ELECTROCHEMICAL BEHAVIOR OF ADDITIVELY MANUFACTURED NON-SPHERICAL TI-6AL-4V POWDER IN 3.5 WT. % NACL SOLUTION
Creator: Bagi, Sourabh Dilip
Date: 2021
Description: In laser powder bed fusion (LPBF), also known as selective laser melting (SLM), the feedstock powder and processing parameters affect the...
Show moreIn laser powder bed fusion (LPBF), also known as selective laser melting (SLM), the feedstock powder and processing parameters affect the properties of additively manufactured parts. Limited research has been conducted on non-spherical Ti6Al4V feedstock powder prepared by Hydride-Dehydride process. Significant progress in metal powder additive manufacturing (AM) requires the inter-linking of multiple variables, which includes starting materials, process settings, and post-treatment to achieve desired resultant properties. Owing to the rapid emergence of metal 3D-printing, process-property relationships, and appropriate post-treatment conditions have not been as extensively characterized as for conventional materials, thus requiring significant attention. Over the years, spherical powders were used in powder bed AM machines and there have been various concerns related to powder as well as processing parameters leading to defects formation, poor part quality, and unsatisfactory performance. It is critical to keep the cost of manufacturing low for large-scale production which results in significant interest in low-cost powder, making it vital to understand the effect of microstructural defects on corrosion behavior. Recently, economical powder attracted attention in AM, thus, making it is necessary to understand the role of possible microstructural defects on corrosion behavior. In powder bed additive manufacturing, feedstock and processing affect final microstructure and properties of the 3D printed parts. While numerous studies have evaluated 3D-printing of spherical powder, very limited research has examined the processing of the non-spherical feedstock. In this research, parts are manufactured by SLM of hydride-dehydride (HDH) Ti6Al4V powder. heat treatment and hot isostatic pressing are applied on SLM parts. The microstructures, potentiodynamic curves, and electrochemical impedance spectroscopy are characterized for SLM processed, heat treated, and hot isostatically pressed HDH Ti6Al4V specimens. Results indicate although the as-built specimen has anisotropic microstructure (i.e., lamellar α + acicular α’ + β phases), the heat treatment and hot isostatic pressing result in homogenized grain structures and enhanced corrosion behavior. Results indicate that type of constituent phase, grain size, and morphology directly determine corrosion resistance. This research is beneficial for the manufacturing of low-cost titanium alloys. In the current research, we evaluate non-spherical powder processing by hydride-dehydride (HDH) method and selective laser melted in powder bed AM machine followed by heat treatment and hot isostatic pressing to alter microstructure and electrochemical behavior. If successful, the usage of non-spherical morphology in conjunction with the newer powder dispensing method of double smoothing will enable remarkable improvements in the quality and performance of additively manufactured products. This method will also cut down costs associated with a greener powder production method and enhance the fabrication rate. It is a well-established fact that corrosion behavior is drastically affected by heterogeneous microstructure and defects. Thus, it is paramount to conduct a systematic study on the role of processing parameters and post process heat treatment, which can enhance our understanding of possible defect formation in micro and macro scale and their impact on electrochemical behavior.
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Title: OPTIMUM WEIGHT STIFFNESS STRUCTURAL DESIGN
Creator: Barnett, Ralph L.
Date: 2021
Description: My adventures with flexible structures began on the IIT campus with an extracurricular undergraduate project to design an “Open House Exhibit”...
Show moreMy adventures with flexible structures began on the IIT campus with an extracurricular undergraduate project to design an “Open House Exhibit” for the Civil Engineering Department. I chose to display a reinforced concrete diving board together with a prestressed concrete diving board. Visitors enthusiastically pounced on the reinforced concrete structure whose rigid response disappointed one and all. Their indignation was transferred to the prestressed cantilever which thrust them upward from six to ten feet into the air. This unexpected response from a diving board became so dangerous that the Exhibit was unceremoniously closed. I still have the display sign, “More Bounce to the Ounce.”While still an undergraduate, I secured a part-time job at Armour Research Foundation where I responded to a bid request from Rock Island Arsenal to design the 26 foot Honest John Rocket Launcher Rail at minimum weight. This tactical weapon was transported by helicopter. I basked in the fantasy that I was Leonardo da Vinci without his artistic proclivity. Rocket launchers that droop during operation are similar in concept to a circular firing squad. So began my research into minimum weight beams based on deflection rather than strength. I searched for the shoulders of Giants. I found them in the form of mathematicians not structural engineers. I achieved a 26.5% weight savings in the 1126 pound rail by optimizing the geometry. When I developed an optimum prestressed and segmented Kentanium cermet rail, the weight savings became 89%. The right material provides a bigger bang for the buck. When my journey into optimum design began, I was armed only with analysis tools: strength, stability, and stiffness. This thesis begins with an outline of my present toolbox which contains eight design concepts: 1. Establish the Geometry, 2. Select a material from a finite number of candidates, 3. Prestress and Prestrain, 4. Statistical Screening (Proof Testing), 5. Manipulation of Boundary Conditions, 6. Energized Systems, 7. Counterweights, 8. Self-Healing and Self-Reinforcing. Four of these are used through this review which focuses on stiffness. Beginning with beams, deflection control examples are described where prestraining and prestressing techniques are used to produce both a zero-deflection beam and a method for pushing with a chain. The calculus of variations made it possible to establish optimum tapers for the flanges and webs of I-beams that minimize beam weight for a specified deflection or, because of reciprocity, minimize beam deflection for a specified beam weight. An anomaly is encountered that enables one to achieve an upward, downward, or zero deflection with a set of beams of vanishing weight. In addition, special circumstances are defined where a uniform strength design is identical to the minimum weight design based on a specific deflection. Closed form solutions are obtained for a variety of loading scenarios. One problem is presented for self-weight that leads to a nonlinear integral equation. The optimum stiffness-weight design of trusses is undertaken where the area distribution of the truss members is optimized using Lagrange’s method of undetermined multipliers. Once again, we obtain a degenerate case where upward, downward, and zero deflection conditions can be met with an infinite set of trusses of vanishing weight. We photograph a simply supported truss under a downward load that leads to an upward deflection at one of the joints. Special loading conditions are identified that lead to uniform stress designs that are identical to the minimum weight designs based on deflections. This study provides a Segway into the world of minimum weight strength design of trusses. The resulting Maxwell and Michell trusses sometimes display the optimum distribution of bar areas from the point of view of stiffness. Many practitioners are under the mistaken impression that Michell structures, when they exist, provide the optimum truss profile for stiffness. Unfortunately, the optimum array of truss joints based on deflection does not exist. For both trusses and beams the optimum distribution of mass is shown to be necessary and sufficient; the sufficiency is established using well-known inequalities. The role of stiffness in the design of columns is explored in our final chapter. This cringe-worthy history of column analysis begins our study as a warning to practitioners who use analysis as their basis for design and especially optimum design. Conventional elastic and inelastic buckling theories provide little insight into the design of columns. The fundamentals of minimum weight column design are presented to show the power of design theory in contrast to analysis. Both prismatic and tapered columns are studied with one surprise result; the optimum taper gives rise to a uniform bending stress (without axial stresses). It was fun to see that in 1733 Lagrange made a mistake in calculus of variations that led to the incorrect solution for the optimum tapered column. It took 78 years before Clausen obtained the correct solution. The problem has been revisited by William Prager and again by the author who used dynamic programming. Of course, we all got the same result which is a dreadful solid circular tapered column that is heavier than any ordinary waterpipe. The best of a class is not necessarily the best possible design. Under the heading, “Intuition is a good servant but a bad master,” we introduce the notions of tension members that buckle, columns constructed from spherical beads, optimum rigging of crane booms, and deflection reversal of beam-columns. In several places we observe that the weight of optimum columns is proportional to P^α where P is the axial load and α is less than unity. We fail to tell the reader that this implies that minimum weight columns require putting all your eggs in one basket; one column under load P is lighter than two columns each under load P/2. On the other hand, we expose the solid circular column as the least efficient shape among all regular polygons, the equilateral triangle is the best. Indeed, there is a family of rectangles that are superior to the circular cross-section. Finally, the author’s prestressed tubular column is introduced that is pressurized to eliminate local buckling. Euler’s buckling can always be eliminated with a thin-wall section of sufficient width without a weight penalty. The weight of the balloon-like member is proportional to (PL) which implies that at last we have a compressive member that meets the requirement of a Michell structure. Bundling of pressurized gas columns are possible without a weight penalty. Further, the column is insensitive to most imperfections. It is the lightest known column for small structural indices (P/L^2 ). When coupled with circulating cryogenic liquid as a prestressing system, a limiting column has a vanishing weight.
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Title: The Relation Between Executive Functions and Academic Performance in Clinically-Referred Adolescents
Creator: Coultis, Nora Plumb
Date: 2021
Description: The literature on executive functioning (EF) and academic performance has focused on early academic performance in young children (Best et al....
Show moreThe literature on executive functioning (EF) and academic performance has focused on early academic performance in young children (Best et al., 2011). Few studies have assessed the relation between EF abilities and academics in adolescents, which is particularly important because the demand on EF skills greatly increases in middle and high school (Best et al., 2011). Environmental factors, including completing multiple assignments, managing increased independent work, and changing classes, exacerbate the EF burden and reduce cognitive resources (Langberg et al., 2013; Samuels et al., 2016). Academic tasks also become more complex during middle and high school, for example, requiring solving algebraic problems, reading comprehension, and expository writing (Bull & Scerif, 2001; Sesma et al., 2009). Thus, complex academic tasks in adolescence likely require a higher demand on EF abilities compared to academic tasks in early childhood. The extant literature also has several limitations, such as focusing on only a couple of EF or academic domains and using parent- or teacher-report ratings rather than performance measures. Therefore, the aim of this study was to examine the relation between four domains of EF (i.e., working memory, inhibition, shifting, and planning) and three areas of academic performance (i.e., reading, writing, math) in a sample (N = 87) of clinically-referred middle and high school students. Contrary to expectation, results of hierarchical multiple regression analyses revealed that the measures of EF did not contribute significant additional variance to scores in reading and writing performance after controlling for IQ. It is notable that the EF variables did contribute a significant amount of additional variance to math scores after controlling for IQ and diagnosis. However, only working memory was significantly associated with math performance. This finding suggests that strategies designed to enhance working memory may be effective in improving math performance in students who are underperforming.
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Title: Assessment of Sleep Characteristics and Their Effects in People with Type 1 Diabetes for the Development of a Sleep Module for the Multivariable Artificial Pancreas System
Creator: Brandt, Rachel
Date: 2021
Description: his work is focused on the relationship between sleep and blood glucose control in people with Type 1 Diabetes and on the development of a...
Show morehis work is focused on the relationship between sleep and blood glucose control in people with Type 1 Diabetes and on the development of a sleep module incorporating new variables and rules for use in automated insulin delivery and advisory systems. Through this research, sleep effects were identified, quantified and incorporated into a multivariable artificial pancreas system (mvAP) that is currently being developed. The mvAP uses different physiological signals acquired through non-invasive wearable sensors along with a continuous glucose monitor (CGM) to detect the state of the user to predict future blood glucose values to aid in insulin dosing decisions. The overall objective of the research was to develop and add a module to further improve the successful mvAP by incorporating sleep related information while retaining the functionality and safety of the system and improving the effectiveness in maintaining good glycemic control. Two types of sleep effects were studied: effects of sleep characteristics and stages in real-time (during sleep) and effects of sleep on glucose metabolism the next day. It was found that poor sleep quality was related to higher glycemic variability overnight in adults with Type 1 Diabetes. However, in adults without diabetes, there were no consistent relationships found between sleep stages and changes in blood glucose levels overnight. For adults with Type 1 Diabetes, it was determined that Sleep Quality, Total Sleep Time, Wake After Sleep Onset (WASO), Number of Awakenings >5 minutes, and amount of Deep sleep could be used in conjunction with insulin on board and the amount of time that has passed since the user has woken up to predict how much more insulin may be needed at the first meal of the day. This Insulin Multiplier Algorithm was tested and validated in replay simulations. Finally, in order to incorporate these relationships into the mvAP, a sleep stage detection algorithm was developed using the Empatica E4 wristband.
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Title: BURNOUT AMONG SEXUAL MINORITIES: THE ROLE OF CONCEALMENT, RUMINATION, AND ORGANIZATIONAL NON-DISCRIMINATION POLICIES
Creator: Burke, Margaret
Date: 2021
Description: Employee burnout is detrimental to individuals (e.g., physical and mental health concerns), as well as to organizations (e.g., diminished...
Show moreEmployee burnout is detrimental to individuals (e.g., physical and mental health concerns), as well as to organizations (e.g., diminished performance). Although numerous studies have examined burnout across a variety of industries and populations, there are limited studies that have examined burnout specifically among sexual minority employees, referring to lesbian, gay, bisexual, transgender, and queer (LGBTQ) workers. This study integrated Meyer’s (2003) Minority Stress Model and Hatzenbuehler’s (2009) Psychological Mediation Framework to investigate the role of concealment, rumination, and non-discrimination organizational policies on burnout among 406 sexual minority employees working in a variety of industries (e.g., healthcare, retail, education, etc.). To test the relationships between these variables, a mediation model and a mediation with moderation model was tested using Hayes’ (2018) Process macro. Results indicated that concealing one’s sexual orientation at work was positively related to rumination, and in turn, was positively related to burnout. Contrary to one of the hypotheses, organizational non-discrimination policies that were inclusive of sexual minorities did not moderate the relationship between concealment and burnout. Previous research, implications, and limitations to this study are discussed in detail.
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