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Ultra-Low-Overhead Arbitrary-Waveform Generation as a Circuit Macro: Augmenting the Characterization of Radiation-Induced Transient Effects in Highly Scaled Integrated Circuits
No full textArbitrary waveform generators (AWGs) are not typically feasible as subsystems on integrated circuits due to their size and complexity, but they are versatile circuits that are broadly useful. The purpose of this work is to show that by prioritizing minimal overhead and designing for targeted performance, as necessary for the application, it is possible to create a reusable on-chip AWG circuit macro in a small form factor. To support this claim, details and results are provided for a proof-of-concept implementation in a 45nm partially depleted silicon-on-insulator process. The presented design is able to achieve a small size by eliminating the complicated calibration and filtering circuitry commonly used in contemporary designs, instead relying on intrinsic accuracy of the base circuits. The reliability and accuracy of the AWG are driven by careful design down to the layout level, including the development of a variant of the traditional common-centroid layout technique called distributed-centroid layouts (DCL), which addresses the importance of bias circuitry in mitigating process-induced mismatch. A custom simulation workflow was developed to investigate the effectiveness of this technique at the circuit level as compared to other designs from the literature. The proof-of-concept circuit was designed to improve the characterization of radiation-induced transient effects in highly scaled integrated circuits by providing built-in self-test and hardware-emulation capabilities to a custom photocurrent measurement circuit (PMC). Details of this specific application are explored in detail, along with experimental measurements made using flash x-ray and pulsed laser sources. Alternative AWG designs that might benefit a broader application space beyond radiation effects are also provided
Missouri Department of Higher Education and Workforce Development: An Evaluation of CORE 42’s Impact in Missouri
No full textLeadership Policy and Organizations Department capstone projectStatewide articulation agreements are a burgeoning initiative in higher education, designed to increase graduation rates and lower costs for college students. In response to Senate Bill 997, the 2016 Missouri Transfer Curriculum Act charged the Missouri Coordinating Board for Higher Education (CBHE) with developing a standard general education core transfer curriculum for the state’s 2-year and 4-year public higher education institutions and any independent institutions electing to participate. Previous research on the efficacy of statewide articulation agreements is mixed. The researchers use convergent parallel design to understand the degree to which CORE 42 has satisfied the state’s goal of supporting transfer student persistence toward graduation. Quantitative findings reveal a decline in overall transfer student enrollment after CORE 42’s implementation but showed a positive relationship between Pell Grant eligibility and perception of CORE 42 on persistence to graduation. Qualitative findings reveal institutions’ initial perceptions of CORE 42 vary by institution type, that the implementation has required increased effort on institutional personnel, and a faculty perception of tension between CORE 42 and academic freedom. Based on these findings, researchers present recommendations for the Missouri Department of Higher Education and Workforce Development.Peabody College of Education and Human DevelopmentDepartment of Leadership Policy and Organization
From Phonics to Fluency: Mapping Early Literacy in Mountain View Whisman School District
No full textLeadership Policy and Organizations Department capstone projectMountain View Whisman School District (MVWSD) noted a decline in early literacy
achievement for students in the aftermath of the Covid-19 pandemic, especially among students
of color. This study explores the initial stage of the district’s response to declining achievement
in early literacy; MVWSD’s pilot of the science of reading-based Orton–Gillingham curriculum
in Tier 2 intervention classrooms. Using a mixed-methods approach, the research team examined
achievement data, conducted surveys, and observed classrooms to assess the implementation of
the science of reading curriculum. Researchers also investigated the role of parental involvement
in literacy practices, and the extent to which literacy practices are culturally relevant.Vanderbilt University, Mountain View Whisman Elementary School DistrictPeabody College of Education and Human DevelopmentDepartment of Leadership Policy and Organization
Overcoming Challenges with Real World Data and Clinical Restrictions in Pharmacokinetic Analyses
No full textReal world observational pharmacokinetic (PK) data, e.g., from Electronic Health Records or measurements collected during routine care, require additional analysis considerations relative to traditional PK trials. These data are more likely to be sparse, imbalanced, or error-prone, and the practical limitations must be considered to implement methods in a clinical setting. In this dissertation, we developed and investigated methodologies to improve studies conducted using real world PK data. First, we developed a natural language processing algorithm medExtractR which targets the extraction of dose information from free-text clinical notes for a specific medication of interest. Contrasted with existing general-purpose medication extraction algorithms, medExtractR was able to achieve better entity-level extraction, and maintained high performance on an external validation set with tuning and customization. Next, we examined an approximate Bayesian model for individualized PK estimation via a simulation study with opportunistic concentration measurements. The intended for therapeutic drug monitoring necessitated approximation methods that were both accurate and computationally efficient. We evaluated the accuracy of uncertainty estimates and implemented the methods into easy-to-use web interface. Finally, we addressed the issue of bias in estimation as a result of time recording errors (TREs) in PK data by evaluating various modifications to study design and data collection. We considered pragmatic strategies minimally invasive to a clinical workflow that could be implemented in an opportunistic data setting. Mitigation strategies included delaying timing of blood draws to non-infusion periods, selecting future draw times based on minimizing bias from simulated errors, and identifying patients whose existing measurements were most sensitive to TREs. For an intravenously infused drug, we found that these strategies reduced bias in estimation of a pharmacodynamic endpoint more for dosing schedules with rapid infusions than those with slower infusions
Bias Instability, Radiation Effects, and Low-Frequency Noise in Semiconductor Devices
No full textAs microelectronic devices have become more integrated and compact over time, ensuring their reliability has become a critical challenge. This dissertation investigates the bias instability, radiation effects, and low-frequency 1/f noise (LFN) in semiconductor devices, specifically focusing on Ge pMOS FinFETs, GaAs pseudomorphic high-electron-mobility transistors (PHEMTs), and Si bipolar junction transistors (BJTs). In Ge pMOS FinFETs with high-K dielectrics, positive interface-trap generation is the dominant defect responsible for negative-bias-temperature stress (NBTS). The LFN measurements indicate that the defect energy distributions before and after NBTS are increasing toward midgap in these devices. Newly created and/or activated border traps after NBTS related to oxygen vacancies and their complexes with hydrogen. In contrast, GaAs PHEMTs demonstrate robust device performance under electrical stress. First-principles calculations and comparisons with previous work suggest that OAs impurity centers, other oxygen-related defects, isolated AsGa antisites, and dopant-based DX centers may contribute significantly to the LFN in these devices. We also evaluate the degradation and the nature of radiation-induced defects before and after Si ion irradiation of n-p-n Si BJTs through both deep-level transient spectroscopy (DLTS) and LFN measurements. The DLTS measurements identify three prominent classic defect levels in the bulk Si that are introduced by irradiation in the base-collector junction of these transistors. Additionally, a combination of contributions from oxygen vacancies and hydrogen complexes in the oxide that overlies the base-emitter junction is inferred from the temperature-dependent LFN measurements. Our work contributes to a broader understanding of the degradation mechanisms and reliability issues in semiconductor devices across different materials and device architectures. For future research, LFN measurement remains a valuable tool for enhancing our understanding of defect densities and energy distributions in microelectronic devices
Defective Mitochondrial and Peroxisomal Fission Dynamics Impair Neurogenesis
No full textMitochondrial and peroxisomal dynamics driven by DRP1 are integral to many cellular functions. Mutations in DRP1 lead to a devastating neurodevelopmental disease known as encephalopathy due to defective mitochondrial and peroxisomal fission (EMPF1), which presents with a spectrum of symptoms including developmental delay, seizures, and microcephaly. To interrogate the molecular mechanisms by which DRP1 mutations lead to developmental defects, we used induced pluripotent stem cell (iPSC)-derived models with patient mutations in different domains of DRP1. Given that EMPF1 patients present with a spectrum of neurodevelopmental abnormalities, we differentiated iPSCs into neural progenitor cells and neural organoids. DRP1 mutant neural progenitor cells express lower levels of critical identity transcription factors, such as PAX6 and TBR2. Intriguingly, neural organoids with mutations in the stalk domain of DRP1 take on a choroid plexus identity instead of following a cortical development trajectory. Our results show that EMPF1 associated DRP1 mutations lead to metabolic dysregulation, which may cause changes in neural cell fate during early corticogenesis. Understanding these mechanisms will give insight into the role of mitochondrial and peroxisome dynamics in neurodevelopment, as well as the mechanisms underlying the rare disease EMPF1
Learning Programs for Modeling Strategy Differences in Visuospatial Reasoning
No full textHumans have the ability to form strategies when faced with novel tasks, and different people often form different strategies for the same task. Most AI systems, on the other hand, do not exhibit this level of fluidity. Also, there is currently limited research on how to formally represent a space of strategies such that individual strategies can be systematically synthesized, scrutinized, and transferred. This limitation acts as a barrier to building AI systems that reason fluidly.
In this dissertation, I explored three ways in which strategies could be expressed in intelligent systems. First, I investigated how strategies could be expressed in information processing terms in intelligent systems that relied on visual imagery based representations. I built models to reason through problems on the Punched-hole Paper Folding Task, the Leiter International Intelligence Scale-Revised (Leiter-R), and the Block Design Task (BDT), all of which are non-verbal intelligence reasoning tasks.
Second, I investigated how AI systems could leverage techniques from program synthesis to generate their own strategies when faced with tasks. I created a domain specific language, called Visual Imagery Reasoning Language (VIMRL), with which I built AI systems that synthesized reasoning strategies for solving tasks on the Abstract Reasoning Corpus (an abstract reasoning benchmark for AI systems), and the Block Design Task.
Third, I contributed work towards automating of the measurement of human performance on the Block Design Task. This work led to the creation of innovative systems that produce detailed recordings of human performance on the block design task, for both in-person and web based online sessions. I additionally built tools to identify and visualize strategy variations in data collected from these systems.
In this dissertation I mainly contribute the following: (1) a demonstration of the sufficiency of imagery as a viable representation for reasoning about the BDT, Leiter-R, and Paper Folding Task; (2) VIMRL, an imagery inspired domain specific language, and its associated program synthesis system that generates strategies for certain visual reasoning tasks; (3) a VIMRL based solver for the Abstract Reasoning Corpus that tied for 4th place on the 2022 international ARCATHON competition; (4) a demonstration of how reasoning strategies for simplified forms of the BDT could be synthesized and represented in VIMRL; (5) tools for recording, visualizing, and categorizing human performance and strategy on the Block Design Task
Model Based Design and Evaluation of Measurement Systems
No full textAs modern engineering challenges grow more complex, the demand for novel methods of sensing the world around us and more accurate models to explain that world grow in tandem. This dissertation seeks to advance the state of the art in radiation tolerant robotics, underwater imaging, and artificial hearts through both model-based design and sensor evaluation, with a particular emphasis on physics-based models in the design and evaluation of measurement systems. First, this work proposes a method to evaluate an encoder’s performance and failure modes in a high-radiation environment. This work is useful for designing robots that can withstand ionizing radiation with only minor compromises to cost and dexterity. Second, this research develops an acoustic model and a physical prototype of a novel short-range sonar system. A device based on this research would help a diver maintain vision in zero-visibility would dramatically improve the diver’s effectiveness, allowing for faster repairs and more complete inspections. Finally, this work develops a translation of a lumped parameter model of the human circulatory system into the physical domain. This “mock circulatory loop” supports the development of next-generation artificial hearts by providing a realistic dynamic load for prototypes. This work fills the gap between in-silico simulations and blood compatibility testing
A Human-Centered Approach to Improving Adolescent Real-Time Online Risk Detection Algorithms
No full textComputational risk detection holds promise for shielding particularly vulnerable groups from online harm. A thorough literature review on real-time computational risk detection methods revealed that most research defined 'real-time' as approaches that analyze content retrospectively as early as possible or as preventive approaches to prevent risks from reaching online environments. This review provided a research agenda to advance the field, highlighting key areas: employing ecologically valid datasets, basing models and features on human understanding, developing responsive models, and evaluating model performance through detection timing and human assessment. This dissertation embraces human-centric methods for both gaining empirical insights into young people's risk experiences online and developing a real-time risk detection system using a dataset of youth social media. By analyzing adolescent posts on an online peer support mental health forum through a mixed-methods approach, it was discovered that online risks faced by youth could be laden by other factors, like mental health issues, suggesting a multidimensional nature of these risks. Leveraging these insights, a statistical model was used to create profiles of youth based on their reported online and offline risks, which were then mapped with their actual online discussions. This empirical study uncovered that approximately 20% of youth fall into the highest risk category, necessitating immediate intervention. Building on this critical finding, the third study of this dissertation introduced a novel algorithmic framework aimed at the 'timely' identification of high-risk situations in youth online interactions. This framework prioritizes the riskiest interactions for high-risk evaluation, rather than uniformly assessing all youth discussions. A notable aspect of this study is the application of reinforcement learning for prioritizing conversations that need urgent attention. This innovative method uses decision-making processes to flag conversations as high or low priority. After training several deep learning models, the study identified Bi-Long Short-Term Memory (Bi-LSTM) networks as the most effective for categorizing conversation priority. The Bi-LSTM model's capability to retain information over long durations is crucial for ongoing online risk monitoring. This dissertation sheds light on crucial factors that enhance the capability to detect risks in real time within private conversations among youth
Ultra-Low-Overhead Arbitrary-Waveform Generation as a Circuit Macro: Augmenting the Characterization of Radiation-Induced Transient Effects in Highly Scaled Integrated Circuits
No full textArbitrary waveform generators (AWGs) are not typically feasible as subsystems on integrated circuits due to their size and complexity, but they are versatile circuits that are broadly useful. The purpose of this work is to show that by prioritizing minimal overhead and designing for targeted performance, as necessary for the application, it is possible to create a reusable on-chip AWG circuit macro in a small form factor. To support this claim, details and results are provided for a proof-of-concept implementation in a 45nm partially depleted silicon-on-insulator process. The presented design is able to achieve a small size by eliminating the complicated calibration and filtering circuitry commonly used in contemporary designs, instead relying on intrinsic accuracy of the base circuits. The reliability and accuracy of the AWG are driven by careful design down to the layout level, including the development of a variant of the traditional common-centroid layout technique called distributed-centroid layouts (DCL), which addresses the importance of bias circuitry in mitigating process-induced mismatch. A custom simulation workflow was developed to investigate the effectiveness of this technique at the circuit level as compared to other designs from the literature. The proof-of-concept circuit was designed to improve the characterization of radiation-induced transient effects in highly scaled integrated circuits by providing built-in self-test and hardware-emulation capabilities to a custom photocurrent measurement circuit (PMC). Details of this specific application are explored in detail, along with experimental measurements made using flash x-ray and pulsed laser sources. Alternative AWG designs that might benefit a broader application space beyond radiation effects are also provided