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Description
Based on James Marcia's theory, identity development in youth is the degree to which one has explored and committed to a vocation [1], [2]. During the path to an engineering identity, students will experience a crisis, when one's values and choices are examined and reevaluated, and a commitment, when the

Based on James Marcia's theory, identity development in youth is the degree to which one has explored and committed to a vocation [1], [2]. During the path to an engineering identity, students will experience a crisis, when one's values and choices are examined and reevaluated, and a commitment, when the outcome of the crisis leads the student to commit to becoming an engineer. During the crisis phase, students are offered a multitude of experiences to shape their values and choices to influence commitment to becoming an engineering student. Student's identities in engineering are fostered through mentoring from industry, alumni, and peer coaching [3], [4]; experiences that emphasize awareness of the importance of professional interactions [5]; and experiences that show creativity, collaboration, and communication as crucial components to engineering. Further strategies to increase students' persistence include support in their transition to becoming an engineering student, education about professional engineers and the workplace [6], and engagement in engineering activities beyond the classroom. Though these strategies are applied to all students, there are challenges students face in confronting their current identity and beliefs before they can understand their value to society and achieve personal satisfaction. To understand student's progression in developing their engineering identity, first year engineering students were surveyed at the beginning and end of their first semester. Students were asked to rate their level of agreement with 22 statements about their engineering experience. Data included 840 cases. Items with factor loading less than 0.6 suggesting no sufficient explanation were removed in successive factor analysis to identify the four factors. Factor analysis indicated that 60.69% of the total variance was explained by the successive factors. Survey questions were categorized into three factors: engineering identity as defined by sense of belonging and self-efficacy, doubts about becoming an engineer, and exploring engineering. Statements in exploring engineering indicated student awareness, interest and enjoyment within engineering. Students were asked to think about whether they spent time learning what engineers do and participating in engineering activities. Statements about doubts about engineering to engineering indicated whether students had formed opinions about their engineering experience and had understanding about their environment. Engineering identity required thought in belonging and self-efficacy. Belonging statements called for thought about one's opinion in the importance of being an engineer, the meaning of engineering, an attachment to engineering, and self-identification as an engineer. Statements about self-efficacy required students to contemplate their personal judgement of whether they would be able to succeed and their ability to become an engineer. Effort in engineering indicated student willingness to invest time and effort and their choices and effort in their engineering discipline.
ContributorsNguyen, Amanda (Author) / Ganesh, Tirupalavanam (Thesis director) / Robinson, Carrie (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and

Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Smart contrast agents allow for noninvasive study of specific events or tissue conditions inside of a patient's body using Magnetic Resonance Imaging (MRI). This research aims to develop and characterize novel smart contrast agents for MRI that respond to temperature changes in tissue microenvironments. Transmission Electron Microscopy, Nuclear Magnetic Resonance,

Smart contrast agents allow for noninvasive study of specific events or tissue conditions inside of a patient's body using Magnetic Resonance Imaging (MRI). This research aims to develop and characterize novel smart contrast agents for MRI that respond to temperature changes in tissue microenvironments. Transmission Electron Microscopy, Nuclear Magnetic Resonance, and cell culture growth assays were used to characterize the physical, magnetic, and cytotoxic properties of candidate nanoprobes. The nanoprobes displayed thermosensitve MR properties with decreasing relaxivity with temperature. Future work will be focused on generating and characterizing photo-active analogues of the nanoprobes that could be used for both treatment of tissues and assessment of therapy.
ContributorsHussain, Khateeb Hyder (Author) / Kodibagkar, Vikram (Thesis director) / Stabenfeldt, Sarah (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
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Description
Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique

Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Description
In epilepsy, malformations that cause seizures often require surgery. The purpose of this research is to join forces with the Multi-Center Epilepsy Lesion Detection (MELD) project at University College London (UCL) in order to improve the process of detecting lesions in patients with drug-resistant epilepsy. This, in turn, will improve

In epilepsy, malformations that cause seizures often require surgery. The purpose of this research is to join forces with the Multi-Center Epilepsy Lesion Detection (MELD) project at University College London (UCL) in order to improve the process of detecting lesions in patients with drug-resistant epilepsy. This, in turn, will improve surgical outcomes via more structured surgical planning. It is a global effort, with more than 20 sites across 5 continents. The targeted populations for this study include patients whose epilepsy stems from Focal Cortical Dysplasia. Focal Cortical Dysplasia is an abnormality of cortical development, and causes most of the drug-resistant epilepsy. Currently, the creators of MELD have developed a set of protocols which wrap various
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.
ContributorsHumphreys, Zachary William (Author) / Kodibagkar, Vikram (Thesis director) / Foldes, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
The International Dyslexia Association defines dyslexia as a learning disorder that is characterized by poor spelling, decoding, and word recognition abilities. There is still no known cause of dyslexia, although it is a very common disability that affects 1 in 10 people. Previous fMRI and MRI research in dyslexia has

The International Dyslexia Association defines dyslexia as a learning disorder that is characterized by poor spelling, decoding, and word recognition abilities. There is still no known cause of dyslexia, although it is a very common disability that affects 1 in 10 people. Previous fMRI and MRI research in dyslexia has explored the neural correlations of hemispheric lateralization and phonemic awareness in dyslexia. The present study investigated the underlying neurobiology of five adults with dyslexia compared to age- and sex-matched control subjects using structural and functional magnetic resonance imaging. All subjects completed a large battery of behavioral tasks as part of a larger study and underwent functional and structural MRI acquisition. This data was collected and preprocessed at the University of Washington. Analyses focused on examining the neural correlates of hemispheric lateralization, letter reversal mistakes, reduced processing speed, and phonemic awareness. There were no significant findings of hemispheric differences between subjects with dyslexia and controls. The subject making the largest amount of letter reversal errors had deactivation in their cerebellum during the fMRI language task. Cerebellar white matter volume and surface area of the premotor cortex was the largest in the individual with the slowest reaction time to tapping. Phonemic decoding efficiency had a high correlation with neural activation in the primary motor cortex during the fMRI motor task (r=0.6). Findings from the present study suggest that brain regions utilized during motor control, such as the cerebellum, premotor cortex, and primary motor cortex, may have a larger role in dyslexia then previously considered. Future studies are needed to further distinguish the role of the cerebellum and other motor regions in relation to motor control and language processing deficits related to dyslexia.
ContributorsHoulihan, Chloe Carissa Prince (Author) / Rogalsky, Corianne (Thesis director) / Peter, Beate (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
Octopus arms employ a complex three dimensional array of musculature, called a
muscular hydrostat, which allows for nearly infinite degrees of freedom of movement without
the structure of a skeletal system. This study employed Magnetic Resonance Imaging with a
Gadoteridol-based contrast agent to image the octopus arm and view the internal tissues. Muscle
layering

Octopus arms employ a complex three dimensional array of musculature, called a
muscular hydrostat, which allows for nearly infinite degrees of freedom of movement without
the structure of a skeletal system. This study employed Magnetic Resonance Imaging with a
Gadoteridol-based contrast agent to image the octopus arm and view the internal tissues. Muscle
layering was mapped and area was measured using AMIRA image processing and the trends in
these layers at the proximal, middle, and distal portions of the arms were analyzed. A total of 39
arms from 6 specimens were scanned to give 112 total imaged sections (38 proximal, 37 middle,
37 distal), from which to ascertain and study the possible differences in musculature. The
images revealed significant increases in the internal longitudinal muscle layer percentages
between the proximal and middle, proximal and distal, and middle and distal sections of the
arms. These structural differences are hypothesized to be used for rapid retraction of the distal
segment when encountering predators or noxious stimuli. In contrast, a significant decrease in
the transverse muscle layer was found when comparing the same sections. These structural
differences are hypothesized to be a result of bending behaviors during retraction. Additionally,
the internal longitudinal layer was separately studied orally, toward the sucker, and aborally,
away from the sucker. The significant differences in oral and aboral internal longitudinal
musculature in proximal, middle, and distal sections is hypothesized to support the pseudo-joint
functionality displayed in octopus fetching behaviors. The results indicate that individual
octopus arm morphology is more unique than previously thought and supports that internal
structural differences exist to support behavioral functionality.
ContributorsCummings, Sheldon Daniel (Author) / Fisher, Rebecca (Thesis director) / Marvi, Hamidreza (Committee member) / Cherry, Brian (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05