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XAPID: An Explainable AI Framework for Behavior-based Malware Detection via Windows API Calls
No full textAs the online threat of malware continues to become more complex and pervasive, novel detection strategies are always being developed and expanded upon. In particular, behavior-based detection via analysis of Windows Application Programming Interface (API) calls has sparked considerable debate and development over the past decade. By examining the Windows API calls made by an executable throughout its runtime, researchers can gain insight into behavioral patterns that are characteristic of malicious or benign operations. Current research and detection solutions perform this analysis using artificial intelligence, feeding the API call sequences into various machine learning models to classify executables as malicious or benign. Although these systems can perform classification with high accuracy, researchers have identified a substantial need for Explainable AI (XAI) systems within malware detection. As these AI solutions tend to create black-box systems, in which users cannot be sure exactly what metrics are determining the final classification result, there is a natural lack of trust and an inability to understand the meaning behind the classification. Which API calls and sequences suggest malicious behavior, and what meaning can we extrapolate from the context of those sequences to better understand the malware's behavior as users? In this study, we propose the Explainable API-based Detection (XAPID) framework. This framework provides a method for performing behavior-based malware detection using Windows API calls, implementing explainable AI solutions to help human users derive meaningful behavioral patterns from API call sequences
Modern Political Murder in El Salvador: Patterns of Partisan Targeting of Public Figures
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Fragile Flesh
No full textThrough ceramics, leather, wool, fur, paper, wax, and other found objects, this exhibition questions internal and external structures of the flesh, the ways it can be depicted in both the abstract and the realistic, and the contexts both personal and universal that inform our own maintenance and upkeep. Starting from the cellular, to organs, and organ systems, Fragile Flesh exists in part, as a series of vignettes, or explorations of my own personal fascinations and observations of the world and the people around me. This show is an investigation the ways I can depict the biological forms we are made up of, as well as the spaces where we are most aware of our flesh. Be it the utilitarian sterility of a bathroom or the comforts of a family dining room. We move throughout the world thanks to these bodies we have, fueled by the beating of our hearts, the pumping of our blood, firing of neurons, or the shedding of skin. Fragile Flesh spans the gap between my personal motivations and interests in the interconnectedness of art and biological science, as well as highlighting the significance of the process and materials to the work's conceptual relativity. Structured around themes of patten, beauty, the abject, sexuality, as well as interior and utilitarian spaces under the larger context of body art and early feminism.Fragile Flesh explores the body, and more specifically a dissected view of flesh and bodily anatomy as a lens through which we can begin to view the complexity of our existence as a beautiful yet uncanny collection of organic systems that we inhabit. Moving throughout the world, developing personalities, identities, and experiences. Fragile Flesh looks at the unique structures of the biological forms that we are made up of in order the rewild the body, the flesh. Imagining it not as an identifiable human; made up of concrete parts like arms, legs, hands, a face, etc., but one that strips us down to our basic animality and biology. Making us uncanny, fascinating, and unknown once again. In the thesis exhibition, Fragile Flesh, human biology is taken and blended with aspects of the natural world to more easily understand the parallels that we share between ourselves, and other organisms. The ways in which our structures may be similar, our behaviors, and our place within the natural order. Through historical and contemporary examples as well as personal artwork references Fragile Flesh demonstrates how art can be a tool to grapple with our biological reality. The fragility and beauty of the flesh that we inhabit, the complexities contained within our skin, and our interconnectedness with the natural world. Visualized through a material-based practice that explores the potential of ceramic, fiber, and other natural mediums
Comparison of "One Health" Curriculum Integration into Nevada Health Professions Programs vs. U.S. Veterinary Colleges
No full textAdvancing Large-Scale Traffic Safety Analysis with Sociodemographic and High-Resolution Probe Data
No full textTraffic safety is a fundamental research theme in transportation engineering, involving influences and interactions among infrastructure, users, as well as transportation policy and management, which can be particularly complex from a perspective of large-scale transportation systems. In recent years, there has been an increased emphasis on adopting comprehensive and integrated approaches to traffic safety improvements, driven by growing evidence that crash risks disproportionately affect specific sociodemographic groups. Despite these advances, current methodologies for assessing disparities in traffic safety remain limited, due primarily to the reliance on historical crash data, which typically provide aggregated incident counts and classification without sufficient granularity and comprehensive temporal-spatial data availability. Leveraging emerging data sources provides a promising opportunity to facilitate current traffic safety improvement practices. Open-source sociodemographic data, such as income level, race, ethnicity, age distribution, and socioeconomic status, have become a critical component in traffic safety studies for understanding community-specific factors influencing traffic safety risks. The advent of high-resolution probe data (HRPD) offers extensive spatial coverage and detailed vehicle trajectory information, allowing for the identification of risky driving behaviors beyond what historical crash data alone can provide. This dissertation aims to explore the application of HRPD and detailed sociodemographic data in the development of quantitative metrics to assess and address the disproportionate distribution of crash risks across diverse communities.
To achieve this objective, the dissertation comprises three interconnected research efforts:
The first study introduces an innovative approach to crash disparity metrics development, which integrates historical crash data, sociodemographic characteristics, and various measures of traffic exposure. A Crash Gini index (CGI) and Theil Index of Crash (TIC) are developed to indicate the level of traffic safety disparity. This approach facilitates standardized comparisons of crash risk disparities across extensive geographical regions, thereby supporting data-driven policy decisions and enabling the evaluation of interventions for transportation systems.
The subsequent two studies emphasize the integration of HRPD into large-scale traffic safety analyses. Specifically, the second study establishes connections between HRPD-derived driving behaviors and sociodemographic factors, highlighting variations in risky driving behaviors across communities. The third study implements an advanced geospatial analysis to demonstrate how HRPD can effectively function as a surrogate for current crash data in identifying and predicting traffic safety risks.
Collectively, insights from these three studies contribute to a deeper understanding of the relationship between sociodemographic factors and traffic safety. Moreover, the dissertation showcases how HRPD can complement current traffic safety evaluation practices and methodologies, guiding policymakers and transportation professionals toward more comprehensive, effective, and user-driven safety strategies.
Message Framing, Source, and Personality in Older Adults' Perceptions and Behavioral Intentions with AI-driven Healthcare Treatment Recommendations
No full textAs artificial intelligence (AI) continues to shape healthcare delivery, older adults represent a group with much to gain—but also much to lose—depending on how these technologies are introduced and implemented. Adoption remains uneven, often hindered by concerns about trust, privacy, and a lack of familiarity with AI-based technology. This study examined the impact of message framing (gain vs. loss), message source (AI, human provider, or a combination of the two), and personality traits on older adults’ trust in AI-driven healthcare recommendations and their predicted adherence to treatment plans. Grounded in prospect theory and personality research, a 2x3 experimental design tested how different message presentations interacted with individual differences to shape attitudes toward AI-based healthcare. The study also examined how healthcare and technological experience shaped perceptions of AI-generated recommendations. Results from the quantitative and qualitative analyses show that the source of the recommendation consistently shaped how comfortable and trusting respondents felt, with many expressing a preference for having a human involved in the process. Conscientiousness, in particular, played a role in how likely respondents said they would follow the treatment advice depending on who provided it. Comments in the open-ended responses pointed to a common trade-off: while AI was often seen as efficient and practical, many felt it lacked the personal touch they value in healthcare. `By integrating message features and individual traits, this study offers insight into how AI-based systems can be designed and communicated in ways that are more trustworthy, effective, and inclusive for older adults
Processing parameters and kinetics of phosphate-based dechlorination for electrorefiner salt waste
No full textPyroprocessing generates a salt waste stream of fission products dissolved in alkali chloride salts. Iron phosphate (FePs) glasses have been identified as candidate materials due to the high waste loading, good chemical durability, and lower processing temperatures. Phosphate-based dechlorination has been used to produce intermediate phosphate products before the addition of iron to create the chemically durable final waste form. Using this method, mixing salt with a phosphoric acid and heating to T < 600˚C leads to the evolution of HCl(g) and H2O(g) with concurrent formation of an alkali metaphosphate glass. Dechlorination in air environments was achieved at temperatures as low as 300°C in air, but full dechlorination was achieved in both air and argon between 500-600°C.This work aimed to reduce the thermal demands of the phosphate-based dechlorination process by investigating the structural evolution of dechlorinated phosphate products at previously investigated terminal temperatures and evaluating the effect of processing parameters on dechlorination at 300°C.
Studies were conducted to investigate the relationship between dechlorination, structural evolution, and reaction kinetics under varying heating rates in both air and argon atmospheres. Through Raman analysis, it was found that at T ≥ 300°C, in quasi-static conditions, metaphosphate Q1 and Q2 units are formed in both air and argon. Following these findings, materials were processed to 300˚C under low gas flow conditions (0.1-0.2 LPM) at heating rates of 1, 5, and 10°C min-1. Dechlorination behavior and structural evolution were characterized using ICP-MS and Raman analysis.
Under these low flow conditions, a quasi-static environment was still present, with the removal of off-gassed byproducts limited by diffusion rather than forceful convection from the surface of the melt. Therefore, as dechlorination proceeded with increasing temperature, water vapor accumulated over the melt, creating a saturated local environment that suppressed reactions leading to dechlorination. In the argon atmosphere, the conditions were comparable to those in previous studies, resulting in similar residual Cl contents in the intermediate product (~6-9 wt% compared to ~6-7 wt% previously). However, samples processed in air experienced a more water-rich environment in the current study, leading to significantly higher residual Cl content than previous studies having ~0-2 wt%, compared to this study, ~8-9 wt%.
Despite these quasi-static conditions, slower heating rates were found to enhance structural evolution in both air and argon atmospheres. Structural differences were observed in Raman spectra, with more bands associated with Q2 units prominent in samples processed at lower heating rates. However, the influence of the humid environment was apparent, as bands associated with H3PO4/Q0 units were present in all the samples. The humidity appeared to be greater in the air environment as Q2 units that were present in argon at all heating rates were only observed for air at the lower heating rates.
A higher flow rate (2 LPM) was analyzed as the quasi-static conditions initially limited off-gas collection. Analysis was conducted by analyzing the overall conversion of Cl for both air and argon. It was determined that argon had a higher conversion of Cl than air and samples processed with 1°C min-1 heating rates had a higher overall conversion. Ea from 100-300°C for the removal of Cl was quantitatively analyzed using the KAS integral isoconversional method for samples processed in both air and argon, although further testing is necessary to further elucidate Ea. It was determined that between 100-200°C and 200-300°C the behavior of Ea for air and argon were dissimilar. For air samples, it was suggested that for 100-200°C O2 may decrease the energy barrier necessary to dechlorinate, but from 200-300°C Ea sharply increases, indicating that Ea may be affected by a change in reaction mechanism potentially caused by a change in surface mediated processes. However, for argon environments Ea appeared to be thermally driven as the energy barrier decreases as the heating profile was followed.
Ultimately, reducing the thermal and atmospheric processing requirements could improve efficiency and advance the technological readiness of the FeP waste form
Protons and Potentials: How Neurotransmission Influences and is Influenced by pH Transients
No full textProtons, hydrogen ions, are essential to biological functions, contributing to energy metabolism, protein transport, protein modulation, and ion homeostasis. While usually tightly controlled by systemic and cellular processes, free hydrogen ions can overwhelm endogenous buffering during neurotransmission and can form transient increases or decreases in pH. These transients can modulate neuronal activity by altering neuronal excitability, either by inhibiting or potentiating ion channels or by acting on receptors. Changes in pH and their influence on activity are variable and context dependent, leaving ambiguity on what changes occur and how they may affect neurons. I examined pH transients and how they may affect activity using two preparations: the neuromuscular junctions of the levator auris longus muscle (NMJ) and the central synapses in acute hippocampal brain slices. To characterize transients at the NMJ, I utilized a virally delivered, genetically encoded, pH-sensitive fluorescent probe, pHusion-Ex, to identify a novel activity-dependent pH transient. This transient in the synaptic cleft alkalizes initially and acidifies with more strenuous stimulation. We found that the alkalinizing transient was caused by the activity of plasma membrane Ca2+ ATPases in the NMJ, buffering intracellular release of Ca2+ from the muscle. I also noticed pH changes induced by the neuron did not affect cleft pH, which was expected from prior reports. This led to the hypothesis that there is an additional level of pH regulation within the synaptic cleft, which may be affected in diseases like amyotrophic lateral sclerosis. I then pivoted to investigating how pH affects changes in neurotransmission, beginning by observing spreading depolarization (SD), a wave-like depolarization in the brain that lasts tens of seconds and is thought to be responsible for secondary injury after strokes. I found that extracellular and intracellular pH affect the duration and extent of the SD. I showed that extracellular acidic pH can slow or halt SD, suggesting acidification may be neuroprotective and could be induced clinically to limit SD occurrence following brain injury. This research demonstrates how various factors can alter pH transients, what mechanisms are or could be underlying these changes, and what impacts to neurotransmission may occur due to proton signaling