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An Ultrasonic Transceiver for Non-Invasive Intracranial Pressure Sensing
No full textThis work presents a 9-mW ultrasonic through-transmission transceiver (TRX) designed for portable, non-invasive intracranial pressure (ICP) sensing. The system employs two ultrasound transducers placed at the temporal bone windows to measure changes in ultrasonic time-of-flight (ToF), from which skull expansion and the corresponding ICP waveform are derived. Key components include a high-efficiency Class-DE power amplifier (PA) with 95% efficiency and a 15.8 VPP output swing, as well as a successive approximation register (SAR) delay-locked loop (DLL)-based time-to-digital converter (TDC) featuring 29.8 ps resolution and a 122 ns range. In addition to electrical characterization, the sensor is validated through two demonstrations: a water tank setup and a human head phantom setup. The system shows a high correlation (R² = 0.93) with a medical-grade invasive ICP sensor. The proposed system offers high accuracy, low power consumption, and reliable performance, making it a promising solution for real-time, portable, non-invasive ICP monitoring in various clinical settings
Low-cost Screening and Diagnostic Imaging Systems and Algorithms for the Early Detection of Oral Cancer
No full textEarly diagnosis of oral cancer is key to improving patient prognosis and reducing morbidity and mortality. Visual examination and palpation are the standard detection practices and the gold standard for diagnosis is biopsy followed by histopathologic analysis. Following confirmatory diagnosis, treatment typically involves surgery, where surgical margins are also assessed using visual and tactile cues. The methods applied for the screening, diagnosis, and surgical treatment of oral cancer are highly subjective and highly dependent on clinician expertise, so the development of objective tools is imperative for improving oral cancer care, especially in regions with limited or poor access to oral cancer specialists. The goal of this thesis is to improve the early detection of oral cancer and facilitate better patient outcomes through the development of low-cost imaging systems and algorithms to detect precancer and early cancer. This thesis describes the innovation of three optical imaging aids, targeting different stages of cancer care, to achieve this goal. First, this thesis describes the development and validation of a screening aid to improve the early detection of oral precancer and cancer through referral management, and triage which patients need to see an oral cancer specialist for diagnosis. A smartphone imaging system and mobile app were designed and built to support effective oral cancer screening by non-expert clinicians. This imaging tool was used to collect data in a study conducted in a low-prevalence, low-risk population from a general population and in a study conducted in a high-prevalence, at-risk population from a specialist clinic and tertiary cancer center. This data was used to develop a referral recommendation algorithm for this mobile system and was found to have 93.9% sensitivity and 79.3% specificity for the classification of patients requiring further evaluation by an oral cancer specialist. Data from a target low-prevalence, at-risk population was incorporated into the algorithm and validated in a target test population from a dental care clinic setting with a sensitivity of 60.0% and a specificity of 88.0%. Second, this thesis describes the improvements to a multiscale imaging system and diagnostic aid that combines widefield imaging with high-resolution imaging to facilitate decision-making on where to biopsy, especially in patients with heterogeneous lesions, to enable a timely and accurate diagnosis. An optimized diagnostic algorithm was developed for the multiscale imaging system and an analysis approach combining multiple imaging modalities for biopsy guidance was assessed. Performance of the multiscale approach was found to have an AUC of 0.848, with a sensitivity of 87.0% and a specificity of 69.0%. Lastly, this thesis describes the development of an intraoperative margin assessment aid to provide real-time feedback on epithelial margins during surgery, enabling the complete removal of tumor tissue to improve treatment outcomes. The multiscale approach described above was adapted to facilitate margin assessment during surgical treatment of oral cancer. A margin imaging workflow and analysis is described and assessed in a pilot study. Results in two highlighted patient cases demonstrate the promising potential of this multiscale approach for margin assessment. Taken together, the development of these three optical imaging aids shows promise to enable effective oral cancer screening, improve the early diagnosis of oral cancers, and facilitate real-time margin assessment during treatment, thus helping to reduce the incidence and mortality of oral cancers. Furthermore, the work described here provides an important foundation for the hardware, software, and analysis approaches to enable clinical translation of these screening, diagnostic, and surgical margin assessment imaging tools. Upon further validation, these optical imaging systems and approaches can be implemented to improve oral cancer screening, diagnostic, and treatment outcomes in resource-constrained settings
Computational Imaging Through Aberrations: From Adaptive Optics to Learning-Based Turbulence Mitigation
No full textOptical imaging systems often suffer from wavefront distortions introduced by aberrations, which degrade image quality and limit performance in fields such as astronomy, microscopy, and long-range imaging. Traditional wavefront sensing methods require dedicated hardware or controlled illumination conditions, posing challenges for deployment in dynamic or resource-constrained environments. This thesis presents two computational imaging frameworks that enable high-quality imaging through unknown aberrations using learning-based techniques, without requiring guidestars, paired training data, or specialized sensors.
The first contribution is a guidestar-free wavefront correction framework that leverages asymmetric apertures and two neural networks to estimate and correct phase aberrations from extended natural scenes. By exploiting the injective mapping properties of asymmetric apertures, such as triangles, the proposed method breaks conjugate flip ambiguities inherent in conventional phase retrieval. Experimental results show that this approach achieves over 9 dB improvement in PSNR compared to symmetric apertures and effectively corrects unknown isoplanatic aberrations.
The second contribution is NeRT, an unsupervised turbulence mitigation framework based on implicit neural representations. NeRT decomposes turbulence effects into spatially and temporally varying tilt and blur components, following a tilt-then-blur model. It jointly learns grid deformation, a coordinate-based image generator, and a shift-varying blur module to recover a clean image from distorted observations without ground truth supervision. NeRT demonstrates strong generalization across atmospheric and water turbulence datasets and outperforms existing supervised and unsupervised methods on both synthetic and real-world scenes.
Together, these contributions offer practical solutions for imaging through complex aberrations, pushing the boundarieses of adaptive optics and computational imaging in uncontrolled environments
Vernacular Structures holding the field
No full textThe inherent meaning of Vernacular architecture in contemporary architecture is shifting from Limitation to specification. This thesis using three contemporary vernacular typologies to discuss how is vernacular architecture, landscape and their composition to urban infrastructure and urbanization
Development of 3D constructs that enable vascularization and tissue integration for therapeutic macro-device implants
No full textBlood and lymphatic vessel vascularization are paramount in the field of tissue engineering and regeneration. Transplantation of cellular therapies for chronic disease management depends on vascularization of blood vessels for nutrient delivery and lymphangiogenesis for waste and fluid removal that are essential for long-term transplanted cellular therapies survival, therapeutic efficacy, and disease management. Here we investigate biomaterials, 3D fabrication approaches, pro-angiogenic and pro-lymphangiogenic approaches that enable regeneration of blood and lymphatic vessels for functional macro-device regenerative therapeutic implants for chronic diseases and conditions such as type 1 diabetes and lymphedema. Through vascular modeling at the bench top with 3D bioprinting, evaluation of 3D bioprinted constructs in vivo for vascularization and the utilization of bioprinted hydrogel constructs with pro-angiogenic peptides for diabetes, and the development and screening of alginate-based hydrogels that can be fabricated into 3D constructs and encapsulate pro-lymphangiogenic cell-based therapy, we have evaluated 3D fabrication techniques and biomaterials that can guide vascularization of blood and lymphatic vessels and allow encapsulation and transplantation of therapeutic cells for lymphatic regeneration and reversal of edema in lymphedema pre-clinical models
6.2 Accessible Biotech Education
Get PDFThis Entreaty emphasizes the necessary element of future education focusing on “Accessibility”. The Education session at the meeting ignited several key points that were discussed further during and after the meeting as narrated and listed below.This entreaty was created as part of The Spirit of Asilomar and the Future of Biotechnology summit (February 23-26, 2025) in Pacific Grove, CA.This Entreaty is developed in response to the discussion in “Essential education for the Biotechnologists of 2075” as part of “Framing Biotechnology’s Future” theme at the Spirit of Asilomar conference. This session is the only technical session with “Education” keyword ties to the secession name with 1 hour budgeted time. Even though the topic appeared much less frequent in the program, conversations centered on education had been touched as much as other topics during the meeting
Max-Cut QAOA Cost Hamiltonian Compilation for Unweighted Graphs Using Minimum Global Controls and Qubit Bit Flips
No full textWe study an operation compilation problem, associated with the hybrid quantum-classical algorithm, QAOA, for the max-cut problem on trapped-ion quantum computers. As opposed to the standard and gate compilation of the cost Hamiltonian for QAOA, here the goal is to compile it to global coupling operations and individual qubit bit flips. Rajakumar et al have proposed this compilation and showed such a compilation exists for any graph. To mitigate operation error a short sequence of operations is desired. In essence, the problem is a low-rank semi-discrete matrix decomposition for the adjacency matrix of a given graph. The lowest possible rank for this decomposition is known as the graph coupling number, , where is the input graph. They gave a combinatorial construction, named union of stars, with the rank of at most for any unweighted graph with n vertices. They gave an construction for weighted graphs as well. Here we focus solely on the unweighted graphs. We extract important theoretical properties of the problem. Utilizing these properties we prove the order-optimality of the union of stars algorithm for unweighted graphs by introducing a family of graphs with a lower bound of n - 1 on their gc number. Additionally, we decrease the theoretical upper bound from to for any unweighted graph with n vertices. For specific graph families like cliques, perfect matching graphs, paths, and cycles, we find tighter bounds. Additionally, we propose a compact mixed integer program (MIP) which is competitive against their MIP formulation which has exponential size in the input graph. We also discover a beautiful connection of the problem with the Hadamard matrices
In a Changed World: A Comparative Examination of Place, Health, and Care Experiences of Urban American Indians
No full textIn exchange for stolen land through the treaty and trust responsibility from the U.S. government, Native Americans received healthcare (Kruse et al. 2022; Warne and Frizzell 2014). As such, they are the only census designated racial/ethnic group with federally promised access to care through the Indian Health Services (IHS). Centering this legal premise, my dissertation examines the health and health care of American Indians/Alaska Natives living in urban areas, or Urban Indians. Despite mounting evidence of profound historical marginalization and deleterious health profiles, American Indians/Alaska Natives have seldom been the topic of focused sociological inquiry, especially those living in urban areas. Drawing on interview, participant observation, and archival data, I explore Urban Indians’ health and health-related experiences (e.g., life course events that shape health, healthcare access) in two case sites, Portland, Oregon, and Houston, Texas. Primarily, this project relies on interview data of 16 Houston Urban Indians and 21 Portland Urban Indians conducted between March 2023 and August 2024, and also incorporates participant observations at both sites. In Chapter 1, I introduce the social problem of American Indian/Alaska Native health and healthcare, describe respondent profiles, and provide an outline for proceeding chapters. Chapter 2 explores key differences in place that uniquely shape health for everyone, but specifically for Urban Indians in my companion sites. Chapter 3 examines the reality of navigating the promise of healthcare for Urban Indians, where I find Urban Indians often delay, forgo, or travel great distances to receive health care. Furthermore, this chapter also reveals how both identity and the state construct influence Urban Indian healthcare access. Chapter 4 details how Urban Indians make sense of their health and aging on the body by examining Indigenous mechanisms shaping their health. Finally, I conclude with a discussion of the theoretical ties across the substantive chapters and provide policy considerations within a broader conversation of Indigenous health
What’s Important to Workers and Changing Careers in the Greater Houston Area
No full textAccording to Randstad’s Workmonitor 2025, more workers worldwide value a work-life balance over job security or even a well-paying job. A December 2024 report from Pew Research Center also reported 1 in 4 U.S. workers said they were likely to look for a new job in the next 6 months. The continued development and evolution of the Greater Houston economy benefits from understanding its workforce, including what workers value in a job and steps people are taking toward changing careers. To this end, members of the Greater Houston Community Panel—a longitudinal panel study of nearly 10,000 adults in Fort Bend, Harris, and Montgomery counties— were asked to report on their job priorities, current work, and intentions to change careers. This report provides a snapshot of the findings
Who Remains ‘College, Career, and Military Ready’ in the Context of a Shifting Accountability Framework?
Get PDFThe Texas A-F Accountability System uses College, Career, and Military Readiness indicators as a key component in measuring how prepared students are for postsecondary success. What began in 2013 with a flexible graduation structure and reduced testing has evolved into a multifaceted rating system shaped by legislative directives, ongoing input from advisory committees, shifting workforce demands and a changing understanding of postsecondary success. While the system has been refined, its evolution has not been linear; it has faced disruptions such as the COVID-19 pandemic and misalignments between policy vision and implementation. Using a mixed-methods approach, this study investigates: 1) the development of the Texas framework, with specific attention to CCMR standards over time; 2) equity considerations during development; and 3) how changes affected CCMR rates across districts among different student groups