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Title: Planets
Creator: Lerner, Nathan, 1913-1997
Date: 1939
Description: Photograph is mounted on cardstock. Signature and date inscribed on recto of cardstock, title and date notated on verso. Photograph is...
Show morePhotograph is mounted on cardstock. Signature and date inscribed on recto of cardstock, title and date notated on verso. Photograph is numbered 3560 and 755 on verso.
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Collection: Nathan Lerner photographs, 1935-1980

Title: Closed Eye
Creator: Lerner, Nathan, 1913-1997
Date: 1940
Description: Photograph mounted on cardstock. Signature and date inscribed on recto of cardstock, title and date notated on verso. Photograph numbered 3557...
Show morePhotograph mounted on cardstock. Signature and date inscribed on recto of cardstock, title and date notated on verso. Photograph numbered 3557 and 758 on verso. This photograph is sometimes titled Eye and Finger in other sources.
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Collection: Nathan Lerner photographs, 1935-1980

Title: Plaster Hand and Screen
Creator: Lerner, Nathan, 1913-1997
Date: 1940
Description: Photograph mounted on cardstock. Signature and date inscribed on recto of cardstock, title and date notated on verso. Photograph is numbered...
Show morePhotograph mounted on cardstock. Signature and date inscribed on recto of cardstock, title and date notated on verso. Photograph is numbered 3562 and 754 on verso. Photograph is sometimes titled Screen and Hand or Hand and Screen in other sources.
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Collection: Nathan Lerner photographs, 1935-1980

Title: Focused view for camera: Brown's Face (detail)
Creator: Lerner, Nathan, 1913-1997
Date: ca. 1939
Collection: Institute of Design records, 1937-ca. 1962

Title: Untitled
Creator: Lerner, Nathan, 1913-1997
Date: 1937-1938
Description: Untitled photograph by Nathan Lerner, with notation on verso indicating that it is from his second semester at the New Bauhaus. Date of...
Show moreUntitled photograph by Nathan Lerner, with notation on verso indicating that it is from his second semester at the New Bauhaus. Date of photograph unknown. Date listed is approximate.
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Collection: Institute of Design records, 1937-ca. 1962

Title: Benjamin de Brie Taylor with banner in Hermann Hall, Illinois Institute of Technology, Chicago, IL, ca. 1987
Date: 1987
Description: Photograph of Benjamin de Brie Taylor in front of a banner he designed hung in Hermann Hall. Taylor was Director of the Institute of Design at...
Show morePhotograph of Benjamin de Brie Taylor in front of a banner he designed hung in Hermann Hall. Taylor was Director of the Institute of Design at IIT from 1973 to 1975, and remained on the faculty at ID until 1987. Date of photograph is unknown. Date listed is approximate.
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Collection: Office of Communications and Marketing photographs, 1905-1999

Title: Students in The Bog, Illinois Institute of Technology, Chicago, Illinois, ca. 1972
Date: 1970-1974
Description: Photograph of students in The Bog, Illinois Tech's student recreation and dining venue located on the lower level of Hermann Hall....
Show morePhotograph of students in The Bog, Illinois Tech's student recreation and dining venue located on the lower level of Hermann Hall. Photographer unknown. Date of photograph unknown. Date range listed is approximate.
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Collection: Office of Communications and Marketing photographs, 1905-1999

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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