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Advancing Combat Casualty Care: The Development of a Compact Suction Device for Battlefield and Prehospital Medicine
No full textThe full text of this item is not available at this time because the author has placed this item under an embargo until August 26, 2026.Airway obstruction remains a leading cause of preventable death on the battlefield and in prehospital trauma care. Current portable suction solutions are often limited by excessive weight, inconsistent performance, or dependence on manual operation. This study introduces the Suction Capability for Emergencies – Portable Technology for Responders (SCEPTRE), a compact, lightweight suction device specifically designed to meet the operational needs of military and emergency field medicine. Weighing less than 0.3 kg and small enough to fit in a cargo pocket, SCEPTRE aims to provide sufficient liquid evacuation for blood, vomit, and other fluids encountered in trauma scenarios. Its design was shaped by 106 end-user interviews conducted through the NSF I-Corps™ program and SBIR Phase I funding.
SCEPTRE was evaluated under standardized laboratory conditions for vacuum pressure, air flowrate, and liquid flowrate using three simulated fluids (water, blood analog, and vomit simulant), and benchmarked against two commercial comparators: the manually operated Laerdal V-VAC and the battery-powered SSCOR Quickdraw. A novel contribution of this study is the introduction of normalized performance metrics—suction performance relative to device weight and volume—which offer a more practical and field-relevant evaluation framework. Results naturally showed that while SCEPTRE did not match the peak output of larger powered systems, it offered consistent and efficient suction, particularly when considering normalized performance. Additionally, a modified catheter with an enlarged inlet improved liquid evacuation. These findings support SCEPTRE as a promising solution for portable airway management, balancing simplicity, portability, and operational effectiveness in austere care settings.Mechanical Engineerin
Counterfactual AI Reveals Effectiveness of Mitigation Strategies in Protecting Groundwater Ecosystems
Get PDFThis poster was presented at the 2025 Postdoctoral Appreciation Week event.Groundwater systems are critical for ensuring food and water security while supporting vital ecosystem functions. However, the depletion of aquifers worldwide raises pressing concerns about the sustainability of groundwater withdrawals and environmental flows. Despite ongoing mitigation efforts, a significant gap remains in quantifying their effectiveness. This study focuses on the karstic Edwards Aquifer system in Texas, evaluating the impact of current mitigation strategies on maintaining groundwater levels and spring flows, which are essential for biodiversity and water security. By employing counterfactual artificial intelligence, we address the pivotal question: “What would have occurred, and what might occur, in the absence of these mitigation measures?†This innovative approach provides valuable insights into historical impacts and future scenarios under intermediate- and high-emission climate pathways. By simulating scenarios without mitigation, our analysis highlights the tangible benefits of groundwater management strategies, demonstrating their critical role in enhancing climate resilience and ensuring the sustainability of aquifers.Civil and Environmental Engineering, and Construction Managemen
Synthesis and Modification of Azide-Conjugated BO-264 Derivatives for Targeted Cancer Therapy
Get PDFChemotherapy remains a cornerstone in the treatment of advanced cancer progression following hormone therapy failure. However, systemic toxicity often constrains therapeutic dosing and is a very common challenge in drug development. To overcome this limitation, we investigated a tumor-selective prodrug strategy leveraging the elevated oxidative stress characteristic of cancerous tissues. Specifically, we utilized a biorthogonal approach in which aryl azide-conjugated prodrugs are selectively activated by endogenous acrolein, a reactive aldehyde upregulated in the tumor microenvironment but scarce in normal tissues. This project evaluated the efficacy of an aryl azide conjugate of BO-264, a biologic targeting the mitotic spindle protein TACC3. Upon acrolein-mediated activation, BO-264 demonstrated potent cytotoxicity in prostate cancer cells, indicating enhanced tumor activity. This acrolein-triggered strategy offers a promising alternative to antibody-drug conjugates, particularly for immunologically cold tumors like prostate cancer. Our findings support the potential of aryl azide-based prodrugs as a broadly applicable platform for improving the therapeutic index of anticancer agents through tumor-selective activation. One more approach is being investigated by attaching the aryl azide on a hydroxy analog of BO-264, in theory providing more efficient drug release.Chemistr
Co-designing 2.5D Silicon Photonic Accelerators for Distributed Transformer at the Edge
Get PDFThe efficient execution of attention-based transformers and large language models on traditional CPUs and GPUs presents significant challenges related to performance and energy efficiency. While innovative solutions like ASICs, FPGAs, and ReRAMs have been explored, the field of silicon photonics has emerged as a promising avenue for developing energy-efficient accelerators for deep AI models. Notably, existing endeavors in silicon photonics have predominantly concentrated on inference for deep AI algorithms, leaving a limited number of initiatives focused on creating comprehensive deep learning accelerators capable of real-time training for transformer-like algorithms. This paper utilizes the superior merits of silicon photonics to realize a full-fledged transformer accelerator equipped for both inference and training. Introducing PHOTRAN, an AI analog photonics accelerator, we harness silicon microdisk-based convolution, photonic phase-change memory-based cache, and dense-wavelength-division-multiplexing to achieve energy-efficient and ultrafast transformer acceleration. Through evaluations using a commercial CAD framework on benchmark models, including Vision Transformers and Large Language models, our results showcase the superior performance of PHOTRAN. This work underscores the significant potential of photonic computing for on-chip training of large deep AI models.Electrical and Computer Engineerin
Bayesian Methods for Joint Modeling, Variable Selection, and Robust Hypothesis Testing
Get PDFBayesian approaches to joint modeling and hypothesis testing have attracted considerable attention in recent years due to their ability to offer a coherent probabilistic framework for scientific inference. These methods align closely with the way researchers and practitioners intuitively reason about uncertainty in real-world situations.
In this dissertation, we first develop a new Bayesian framework for the joint modeling of quantitative and qualitative (QQ) outcomes. This work is motivated by the fact that, in many industrial and engineering settings, response data often contain a mix of heterogeneous outcome types--such as continuous, binary, and count responses--together with predictors obtained from designed experiments. To enable simultaneous parameter estimation and variable selection in QQ models, we introduce a computationally efficient Gibbs sampling algorithm in which all full conditional distributions belong to known families. Simulation studies demonstrate the efficiency and accuracy of the proposed Bayesian framework under different scenarios, and its practical utility is further illustrated through a real-data application.
The second project develops an objective Bayes factor-based method for hypothesis testing in one-way random-effects models. It is well known that using improper priors can render Bayes factors undefined due to arbitrary normalizing constants. To overcome this issue, we introduce the consecutive Bayes factor (CBF), which employs a consecutive minimum training sample size approach. The proposed CBF provides a closed-form expression that is computationally efficient and easy to implement, making it accessible to practitioners. Moreover, it allows researchers to compute consecutive posterior probabilities to quantify evidence against the null hypothesis objectively. Extensive simulation studies are conducted to assess the performance of the proposed method across a range of scenarios. Finally, several real data applications are provided for illustrative purposes.
The third project extends framework in the second project to develop a robust CBF procedure for hypothesis testing in one-way unbalanced fixed-effects Analysis of Variance (ANOVA) models with spherically symmetric errors by Maruyama and Strawderman, (2014). This broader class includes the normal and Student-t distributions as special cases, enabling robustness to outliers and heavy-tailed data. The proposed approach thus provides a more flexible and reliable Bayesian hypothesis testing framework applicable to complex and non-Gaussian data structures.Management Science and Statistic
Extracting Causal Relational Rules for Medical Question-Answering Tasks using Large Language Models
Get PDFLarge Language Models (LLMs) have demonstrated remarkable capabilities in understanding, summarizing, and extracting various topics from free-form text. However, most domain-specific extraction using LLMs still relies on an annotated corpus that is often expensive to achieve. We propose a prompting-based framework to extract causal relational rules from medical question-answering text without annotation. Our framework also integrates a self-judging workflow to enhance the quality of extracted rules. We also present a pilot study that evaluates the quality of the extracted rules based on human labels. The results demonstrate the efficacy of our framework in extracting high-quality rules that can enhance the performance of downstream LLMs-driven QA tasks. We have made the framework and dataset with enhanced rules available as open-source to encourage a wide range of applications.Computer Scienc
Does Inflammatory Rhetoric Boost Support for Political Violence? Considering the Role of Geographic Context
Get PDFThere has been significant speculation about the role that inflammatory elite rhetoric has played in sparking support for political violence in the United States. However, the extent to which uncivil and intolerant rhetoric contributes to support for political violence remains unclear. Similarly, the impact of racial/ethnic context on attitudes towards political violence is unclear. We report on the results from three experiments that included various measures of uncivil/intolerant rhetoric, geographic context, and political violence. Across our diverse set of experiments, we find that local racial heterogeneity is strongly associated with increased support for political violence. However, we find little evidence that inflammatory rhetoric, directly or indirectly, bolsters support for partisan violence. While our results cast doubt on the claim that inflammatory rhetoric from elites is responsible for bolstering broad support for partisan violence among Americans, they do suggest that increased heterogeneity may bolster support for political violence regardless of rhetoric elites adopt.Political Science and Geograph
New Circuits for Simultaneously Initiating Two Different Quantum Superpositions
Get PDFThis article presents, for the first time, a new approach to building quantum circuits for the initialization of two multi-qubit superpositions, namely, two different superpositions in one circuit, not in two separate circuits. For this, we introduce the concept of the discrete two signal-induced heap transformation (D2siHT). This transformation is generated by two signals, or vectors, which we call generators. The quantum analogue of the D2siHT is described. It allows us to build a quantum circuit to transform two superpositions <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mi mathvariant="bold-italic">x</mi></mrow></mfenced></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mi mathvariant="bold-italic">y</mi></mrow></mfenced></mrow></semantics></math></inline-formula> into the first conventual basis states <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mn>000</mn><mo>&hellip;</mo><mn>0</mn></mrow></mfenced></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mn>010</mn><mo>&hellip;</mo><mn>0</mn></mrow></mfenced></mrow></semantics></math></inline-formula>, respectively. Therefore, we can build a single quantum circuit to initiate two multi-qubit superpositions <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mi mathvariant="bold-italic">x</mi></mrow></mfenced></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mi mathvariant="bold-italic">y</mi></mrow></mfenced></mrow></semantics></math></inline-formula> from the basis states <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mn>000</mn><mo>&hellip;</mo><mn>0</mn></mrow></mfenced></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mfenced open="" close="&#10217;" separators="|"><mrow><mn>010</mn><mo>&hellip;</mo><mn>0</mn></mrow></mfenced></mrow></semantics></math></inline-formula>, respectively. Examples with quantum circuits for the preparation and transformation of two 2- and 3-qubit superpositions are described in detail. The results of circuit simulation using Qiskit are also presented. The main characteristic of the D2siHT is its path of processing the data of two generators and input qubits. We consider different paths to effectively compute the D2siHT. Such paths can reduce, for instance, the depth of the resulting quantum circuits, which can lead to a reduction in execution times and susceptibility to decoherence and noise. Multi-qubit superpositions are considered with real amplitudes, but the presented approach can be extended to initiate two such superpositions with complex amplitudes, as well
ENERGY HARVESTING IN TRANSPORTATION INFRASTRUCTURE: PERFORMANCE OF MAINTENANCE-FREE SOLAR PANELS ON HORIZONTAL AND VERTICAL SURFACES
No full textThe full text of this item is not available at this time because the author has placed this item under an embargo until December 11, 2027.This dissertation evaluates the feasibility, performance, and durability of photovoltaic (PV) technologies integrated into urban infrastructure—including sidewalks, vertical residential surfaces, and pavement systems—to expand renewable energy generation in constrained environments. Three year-long experimental studies were conducted using real-time cloud-based monitoring to measure energy output, climate effects, and mechanical loading conditions under actual pedestrian and vehicular activity.
Sidewalk-embedded PV panels were evaluated over two years (October 2023–November 2025), capturing extensive climate data and 200,770 pedestrian movements. Results showed strong seasonal dependence, with solar radiation, temperature, dew point, and UV index driving energy yield. The larger PV II panel consistently outperformed PV I, producing higher efficiency, greater annual energy generation, and a lower LCOE (0.45 vs. 1.004 $/kWh), along with substantially higher CO₂ mitigation.
Vertical residential PV integration using CIGS thin-film modules demonstrated that roof-mounted systems delivered the highest productivity and environmental benefit, while wall and fence installations offered resilient and space-efficient alternatives for urban environments. Temperature was the dominant performance driver across all configurations.
Pavement-integrated PV systems were tested under controlled parking-lot and roadway traffic. While both PV modules generated measurable energy, only the semi-rigid AHONY panel maintained structural integrity; the flexible SUNBEAM laminate failed due to wheel loading, thermal expansion mismatch, and surface fatigue.
Collectively, the findings confirm that PV can be effectively integrated into sidewalks, vertical structures, and pavement surfaces, but long-term viability depends on material robustness, installation context, and thermal–mechanical resilience. The results provide practical guidance for scalable urban solar deployment and highlight pathways for durable, infrastructure-integrated renewable energy systems.Civil and Environmental Engineerin
The Curious Case of RT Vir: Developing New Tools for Dusty Modeling, Motivated by a Stellar Outlier
Get PDFThe precise nature of cosmic dust is critical to understanding many important astronomical environments. InfraRed (IR) astronomy has shown that dust contributes to the physics of star and planet formation, mass loss from evolved stars, interstellar gas heating and the formation of molecules. In addition to its effect on the dynamics of cosmic environments, dust plays a major role in light extinction in the galaxy, so dust also plays an important role in understanding observations in multiple wavelengths. One of the most important dust-forming environments is around Asymptotic Giant Branch (AGB) stars. As AGB stars lose their mass in their stellar wind, dust grains are forming and evolving. As that dust drifts away from the AGB star it is slowly returned to the interstellar medium (ISM).
This dissertation aims to enhance our set of tools for modeling IR emission spectra of dusty environments and apply them to an enigmatic AGB star. We discuss the RT modeling of the O-rich AGB star RT Virginis (RT Vir). We use the RT modeling software DUSTY and several custom Python software ’wrappers’ to model the 1-D dust emission spectrum, fit to IRAS and ISO SWS data. This investigation characterizes RT Vir’s envelope as optically thin, large and cool with features indicative of the presence of both amorphous alumina grains alongside silicates and Fe in a warmer, inner-shell and crystalline aluminas with elongated morphologies in a colder, outer- shell. We find an innermost dust temperature T = 330 K, with an inner radius of∼150 AU and outer radius of∼10,950 AU. Our models may be indicative of two distinct periods of mass-loss from RT Vir, and a potential decrease of C/O ratio over time.
Herein we also present the first results from a custom python ’wrapper’ code that adjust DUSTY calculations of surface brightness into 2-D spatially resolved (spatial resolution in the radial direction only) model spectra. This software is made to model the 2-D spatially resolved spectra from the Michelle imager-spectrometer formerly mounted at the Gemini-North telescope. We apply this 1.5-D modeling method to RT Vir, and demonstrate satisfactory fits to certain regions
around the star. This analysis highlights the axisymmetry of the RT-Vir system, and the evolution of the 10 and 13 µm features with distance from the central star. This software is a proof-of con- cept for a novel method of radiative transfer modeling spatially resolved spectroscopy. This is especially prescient due to the increasing prevalence of integral field units, slitscanning and other methods to provide spatially resolved spectroscopy. We show that this method can be used to show the distinct properties of dust in regions around an AGB star, demonstrating the utility of this new
analysis method. We plan to include the capability to provide spatially resolved RT modeling for the footprints of other instruments or for other applications.Physics and Astronom