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Evaluation of Fin Geometry and VT-Variant on Single-Event Effects in 7nm, 5nm, and 3nm Bulk FinFET Technologies
No full textTechnology Computer-Aided Design (TCAD) simulations are used to clarify the underlying mechanisms affecting single-event upset results at 7nm, 5nm and 3nm bulk FinFET technologies using hard-biased, inverter, and latch configurations. The parameters varied for irradiation tests and simulations are threshold voltage (VT) and fin geometry. Results show that
estimated changes in geometry and process parameters across these technology generations have minimal effects on collected charge, whereas circuit-level parameters strongly influence collected charge, single-event transient (SET) pulse widths, and, subsequently, single-event upset (SEU) cross-sections
Enhancing Exit Tickets to Improve Students’ Monitoring Ability
No full textMonitoring accuracy is crucial for self-regulated learning (SRL), yet students often struggle with self-monitoring, leading to overconfidence or underconfidence. This study examined a classroom intervention using confidence ratings, self-reflection, and feedback to improve monitoring accuracy.
Study 1 involved 32 students. The intervention reduced monitoring bias in ninth graders (d = 0.627) but had small impact on eighth graders. It did not improve motivation, and self-efficacy declined, possibly due to performance awareness. A high (36.6%) exit ticket incompletion rate may have limited effectiveness.
Study 2 refined the intervention by adding structured multiple-choice reflection prompts, explicit calibration reflection, and a “next step” planning component. Among five ninth graders, engagement improved (86.7% reflection completion vs. 63.4% in Study 1). However, unit test and post-survey data were not collected due to instructional constraints.
Findings suggest confidence calibration can reduce monitoring bias but may not enhance motivation. Future research should explore digital tools for real-time feedback and improve interventions for diverse learners
Design, Modeling, and Control of Collaborative Robotics for Subretinal Injection and Mechanisms for Micro-Motion
No full textRobotic systems have been used for manipulation augmentation over the past three decades. Examples include systems that address physiological limits by offering tremor filtration and motion scaling. Robots for computer-aided surgery have been used to alleviate perception and motor control limitations by enabling milligram force sensing and micro-scale motion in surgical tools. Of the two control frameworks of robotics in surgery, telemanipulation and cooperative (hand-on-hand) control, there is an emphasis on the latter over the past three decades for surgery as well as in manufacturing.
The introduction of collaborative robotics to the medical field has led to new surgical techniques (including less invasive access) and to otherwise physiologically impossible surgical procedures in retinal microsurgery. The crux of this proposed research aims to address the limitations of prior art within the two broad areas of microsurgical robots and collaborative control of steerable devices. Specifically, this work aims to explore opportunities for sensory-guided control and adaptive virtual fixtures for retinal microsurgery. We also aim to address the financial challenges associated with high-motion resolution mechanisms via easily manufactured mechanical imaging aids and actuators employing components with minimal manufacturing specification.
This dissertation aims to provide contribution to two general categories. First, we explore low-cost considerations for micro-scale motion with mechanisms to improve the image quality of retinal Optical Coherence Tomography (OCT) images and utilizing Twisted Wire Actuators (TWA) for enabling micro-scale motion in parallel manipulators. The second category explores assistive cooperative robotics on a cooperative robotic system with a variable admittance control scheme informed by B-Mode OCT designed for retinal injections.
We believe our contributions to the field of robotic ophthalmic surgery as well as the design, modeling and control of low-cost micro-motion mechanisms will improve the outcome of vitreoretinal therapeutic interventions and lower the barrier to access of devices for higher diagnostic fidelity and multi-scale manipulation robots
How Chinese People Experienced the Sino-Albanian Alliance
No full textHistory Department Honors ThesisCollege of Arts and ScienceDepartment of Histor
Rooted in Us: Black SEL at The Ferguson School
No full textLeadership and Learning in Organizations capstone projectThe Ferguson School (TFS) is a Black-led microschool serving K–5 students in Decatur, Georgia, with a mission to grow the hearts, minds, and faith of young learners using culturally responsive practices. This exploratory inquiry examined how TFS's practices align with the Black Social-Emotional Learning (Black SEL) framework and identified opportunities for deeper racial identity development. Using semi-structured interviews, classroom observations, and artifact analysis, the research team investigated how SEL is understood, enacted, and supported across the school and broader community. Findings revealed the presence of all six Black SEL pillars at TFS while also uncovering opportunities for Black Self-Concept to be more racially explicit and student-driven
Three Essays on Inequalities in Education Policy
No full textEducation policies often adopt broad, one-size-fits-all approaches that fail to address the unique challenges faced by multilingual learners classified as English Learners (ML-ELs) and students living in extreme poverty. This dissertation investigates how three education policies—grade retention, school funding, and online tutoring—shape the academic outcomes and learning opportunities of these vulnerable student populations through three empirical studies.
The first study estimates the effects of test-based grade retention on ML-ELs in Texas using a regression discontinuity design. It finds that retention and supplemental reading services improve math and reading proficiency and increase the likelihood of reclassification. However, these benefits do not extend to long-term outcomes such as post-secondary enrollment or earnings in young adulthood. Furthermore, the effects of retention are more pronounced in schools with higher expenditures on retained students or bilingual education, highlighting the importance of school resources.
In the second study, I analyze spending progressivity for ML-ELs in a U.S. district that uses student-based budgeting (SBB). Under SBB, districts allocate funds to schools based on student needs using weighted formulas and give principals more control over the budget. I compare average per-pupil spending for ML-ELs and non-ELs across six financial metrics, including general funds, Title I, and direct instruction. The findings indicate that general fund spending is, on average, equal for ML-ELs and non-ELs, while spending on direct instruction is progressive. However, in schools with a higher concentration of ML-EL, funding tends to be neutral or less progressive.
The third study evaluates a virtual tutoring program implemented in Buenaventura, Colombia, in 2021. Although the program incorporated best practices in tutoring design, it did not yield significant academic gains. The limited impact may have been driven by technological barriers, such as limited access to laptops or smartphones, which may have hindered student engagement and learning. This paper highlights the challenges of implementing virtual tutoring in contexts of extreme poverty.
Collectively, these studies underscore the importance of analyzing how education policies designed with all students in mind affect vulnerable students, and therefore, whether they address inequalities in opportunities and outcomes
A Comprehensive Study on Vision Foundation Models in Remote Sensing
No full textArtificial Intelligence (AI) technologies have profoundly transformed the field of remote sensing, revolutionizing data collection, processing, and analysis. Traditionally reliant on manual interpretation and task-specific models, remote sensing research has been significantly enhanced by the advent of foundation models—large-scale, pre-trained AI models capable of performing a wide array of tasks with unprecedented accuracy and efficiency. This paper provides a comprehensive survey of foundation models in the remote sensing domain. We categorize these models based on their architectures, pre-training datasets, and methodologies. Through detailed performance comparisons, we highlight emerging trends and the significant advancements achieved by those foundation models. Additionally, we discuss technical challenges, practical implications, and future research directions, addressing the need for high-quality data, computational resources, and improved model generalization. Our research also finds that pre-training methods, particularly self-supervised learning techniques like contrastive learning and masked autoencoders, remarkably enhance the performance and robustness of foundation models. This survey aims to serve as a resource for researchers and practitioners by providing a panorama of advances and promising pathways for continued development and application of foundation models in remote sensing
Genotype-Specific Effects of Clonal Hematopoiesis of Indeterminate Potential (CHIP) on Breast Cancer
No full textClonal hematopoiesis of indeterminate potential (CHIP) is characterized by expanded blood cell clones containing somatic mutations in leukemia-associated genes in patients without hematologic malignancies. A growing body of research indicates that CHIP is associated with aberrant inflammatory signaling, and studies have identified high rates of CHIP in patients with solid tumors. CHIP has been associated with adverse outcomes in some solid tumor settings, but its impact on breast cancer remains unclear. This dissertation leverages orthogonal approaches with clinical data and mouse models to investigate the impact of CHIP on breast cancer progression and the breast tumor microenvironment. We identified a retrospective cohort of 125 patients presenting with primary breast cancer and used targeted sequencing on peripheral blood to identify CHIP. Metastatic outcomes were curated via chart review, and distant metastasis-free survival probability was analyzed. In parallel, we used bone marrow transplantation to develop novel chimeric mouse models of CHIP. Sublethally irradiated mice received mixtures of wildtype cells and CHIP-mutant hematopoietic cells representing the two most common CHIP genotypes observed in patients (Dnmt3a and Tet2). After engraftment, CHIP and control mice were injected with syngeneic breast cancer cells into the mammary fat pad. Tumor growth was measured regularly, and at tumor endpoint, peripheral blood and breast tumors were harvested for analysis of immune cell abundance via mass cytometry. Patients with high-burden CHIP (variant allele frequency > 10%) and non-DNMT3A CHIP had significantly shorter distant metastasis-free survival. In vivo, mice with Tet2-CHIP developed larger primary tumors and were more likely to experience lung metastasis, while Dnmt3a-CHIP did not differ from controls. The general immune subsets observed in both CHIP models were similar, but immunophenotyping revealed clonal expansion and immune cell subset skewing specific to the Tet2-CHIP model. This work demonstrates a genotype-specific impact of CHIP on breast cancer across human and mouse data. Further, the chimeric models described offer a clinically relevant tool to study solid tumors in a CHIP background. These results underscore the need for further functional studies and personalized risk assessment to clearly define the impact of various CHIP genotypes on solid tumor
Electrochemical Investigation of Neurotransmitters for Environmental Toxins and Drug Development
No full textNeurotransmitters are signaling molecules released by neurons, essential for neurological and psychological functions. They serve as biomarkers for predicting neurodegenerative disease progression and assessing drug efficacy and toxicity. Comprehensive electrochemical neurotransmitter detection can reveal insights into neuronal transmission and metabolic disruptions from toxicants. However, simultaneous detection and monitoring of multiple neurotransmitters remain challenging for electrochemical biosensors.
This dissertation describes the development of electrochemical sensors utilizing enzymatic conversion to study neurochemical dysregulation from environmental toxins and their potential therapies. We characterized 8-channel and 3-channel screen-printed electrode arrays via an in-house developed microclinical analyzer (µCA). These multichannel designs allow simultaneous neurotransmitter detection without crosstalk interference. Enzyme immobilization and polymer deposition on the electrodes ensured sensitive and stable measurements along detection limits appropriate for neurochemical investigation. Additionally, m-phenylenediamine electrodeposition interference was demonstrated to effectively reduce electrochemical interference from the ascorbic acid and dopamine typically found in neuronal systems. Environmental toxins, particularly organophosphate pesticides such as chlorpyrifos (CPF) and its metabolite chlorpyrifos-oxon (CPO), disrupt neurotransmission and cause significant brain damage, raising public health concerns. CPF and CPO impair glutamate neurotransmission and inhibit acetylcholinesterase (AChE). Human iPSC-derived astrocytes were utilized to assess changes in glutamate uptake in response to CPF/CPO exposure. Acute exposure to high toxin concentrations caused marked dysregulation of glutamate uptake. AChE inhibition was confirmed using acetylcholine sensors. Beta-lactam antibiotics, such as ceftriaxone (CEF), showed potential in reducing CPF toxicity and mitigating glutamate uptake inhibition after 100 µM CPF exposure. However, CEF did not facilitate the restoration of AChE activity after acute exposure to CPO. This study highlights the effectiveness of electrochemical biosensing techniques in exploring the neurotoxic effects of environmental toxins on specific cell types and neurochemical pathways
Mending the Matrix: Piezo Initiates Transient Collagen IV Production During Basement Membrane Repair
No full textBasement membranes are specialized sheets of extracellular matrix that separate tissue layers and provide mechanical support to cells. Collagen IV (Col4) is the most abundant structural protein, and Col4 protomers are covalently crosslinked by Peroxidasin. Although Peroxidasin-mediated crosslinking may allow for the specialized mechanical roles of the basement membrane, the importance of this crosslinking has not been clear. We show that Peroxidasin establishes basement membrane stiffness during development and is required for both mouse and fly viability, and we also showed that continuing Peroxidasin function is essential for maintaining adult basement membranes. These findings were unexpected since Col4 is believed to be a long-lived molecule, and the covalent bond was thought to be stable and irreversible. However, our work suggests that either the covalent bond is not as stable as initially thought and needs to be replaced over time, or that Col4 is being turned over and is partially replaced requiring continual crosslinking by Peroxidasin.
Basement membranes are also subject to damage, but little is known about how they are repaired, including whether and how damage is detected, what cells repair the damage, and how repair is controlled to avoid fibrosis. Using the intestinal basement membrane of adult Drosophila as a model, we found that basement membrane damage is actively detected. Following damage, there is a sharp increase in enteroblasts transiently expressing Col4, termed “matrix mender” cells. Enteroblast-derived Col4 is specifically required for matrix repair. The increase in the matrix mender cells requires the mechanosensitive ion channel Piezo, which is expressed in intestinal stem cells. Further, we found that matrix menders are induced by the loss of matrix stiffness, as specifically inhibiting Col4 crosslinking is sufficient for Piezo-dependent induction of matrix mender cells. Therefore, our data suggests that epithelial stem cells control basement membrane integrity by monitoring stiffness