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“Raise Your Keffiyeh:” Headdress as a Lens for Understanding the Arab Revolt in Mandatory Palestine, 1936-1939
Get PDFIn the fall of 1938, approaching the apex of the most intensive period of violence during the Arab Revolt against the British government in Mandatory Palestine (1936-1939), a seemingly unassuming change occurred for Arab men in cities throughout the region: they donned a new headdress. Sartorial shifts in the early post-Ottoman period were not unique to Palestine. During the Interwar period, changes in male headgear occurred throughout the greater Middle East in Turkey, Afghanistan, Iran, Syria and Iraq, to name a few. These transformations of dress signaled a shift in something either societal or political and oftentimes both. I argue that the headdress introduced to townsmen in 1938 Mandatory Palestine, the keffiyeh, acts as a new lens for understanding Arab male expressions of nationalism, resistance and class consciousness during the Revolt. I aim to accomplish this by examining how historians have understood the Revolt, modernity and nationalism and the relationship between clothing and nationalist identity in order to establish a framework for how we might begin to view these sartorial shifts. Furthermore, I seek to trace the fragmented history of male headgear as expressions of modernity and nationalism in the greater Middle East during the Interwar era to demonstrate the interconnected nature of culture and thought in the region
Qualitative and Quantitative Analysis of New Psychoactive Substances and Related Metabolites Using Liquid Chromatography-Ion Mobility-Mass Spectrometry (LC-IM-MS)
Get PDFThe increasing prevalence of novel psychoactive substances (NPS) in illicit drug markets has posed significant challenges for forensic and clinical toxicology, primarily due to the structural similarity and diversity among these compounds. This dissertation investigates the application of advanced liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS/MS) techniques, using the high-resolution Structures for Lossless Ion Manipulations (SLIM) platform and the drift tube ion mobility spectrometry (DT-IMS), for the qualitative and quantitative analysis of various types of synthetic opioids, synthetic cannabinoids, psychedelics and xylazine. By combining IMS separations with mass spectrometry and targeted chemical derivatization, this work enhances the ability to distinguish and characterize structural isomers and metabolites, overcoming limitations in conventional analytical methods.
Key findings include the novel use of metal ion adducts to improve mobility separations of fentanyl isomers, the application of dansyl chloride derivatization for enhanced resolution of cannabinoid and xylazine metabolites and the identification of protonation site isomers in fentanyl analogs and other classes of NPS using mobility-aligned fragmentation and adducts. These methodologies demonstrate high sensitivity, resolving power and reproducibility, with significant benefits for improving NPS characterization workflows in forensic, clinical and pharmaceutical settings. This work contributes to the growing field of multidimensional separations, addressing critical public health needs by providing tools for the rapid and accurate identification of dangerous substances in complex matrices
The Quest for Kindergarten Readiness: A Study of One District’s Early Implementation of the Pyramid Model For Promoting Social-Emotional Competence
Get PDFParticipation in high-quality preschool programs can help prepare young children for Kindergarten, and children demonstrating Kindergarten readiness are more likely to achieve positive outcomes later in life. With this in mind, Oakwood School District (OSD) set a strategic goal to improve the Kindergarten readiness levels of students participating in its 4K programs from 18% in 2021 to 70% by 2025. With research suggesting that school readiness outcomes are dependent on preschool program quality variables such as student-teacher relationships and emotional competencies, the Pyramid Model for Promoting Social-Emotional Competence in Infants and Young Children was implemented in OSD’s 4K program sites during the 2022-2023 school year. With the use of improvement science tools, this study sought to examine the potential impact of Pyramid Model practices on Kindergarten readiness in a group of 245 students. Classroom observations were conducted using the Teaching Pyramid Observation Tool to reflect the level of Pyramid Model practices demonstrated in the 4K setting in the Spring of the 2022-2023 school year. These scores were compared to students’ subsequent performance on the Kindergarten Readiness Assessment (KRA) at the beginning of the 2023-2024 school year. While KRA scores of students participating in the district’s 4K programs did improve overall from 30.3% to 45.5%, this study found no significant relationship between the level of Pyramid Model practices in the 4K classroom and KRA test performance. While these initial findings were not significant, it is important to note that Pyramid Model implementation is a multi-year process. This study included a review of implementation artifacts that identified logistical planning and the need for practice-based coaching as recommendations for OSD and other districts seeking to utilize the Pyramid Model framework. Educational entities are encouraged to continue to explore ways to improve preschool program quality, increase Kindergarten readiness, and utilize improvement science tools to solve problems of practice similar to those in this study
Countering Deficit Narratives Through a BlackCrit Lens by Examining Case Studies of Black College Mathematics Students’ Classroom Experiences
No full textThis dissertation examines the lived experiences of 11 Black college mathematics students at their predominantly white institution (PWI) through the lens of Black Critical Theory (BlackCrit) to counter deficit narratives about the racial achievement gap (RAG) in mathematics education courses. Deficit narratives often attribute disparities between Black and white students’ mathematical performance to assumed deficiencies in Black students’ abilities rather than systemic inequities, historical marginalization, and ongoing anti-Blackness in educational settings (Cobb & Russell, 2015; Kress, 2021). Using multiple case studies, this study explores how anti-Blackness manifests in mathematics classrooms, how students navigate tensions between multiculturalism, neoliberal educational policies, and Black progress, and how mathematics education can create liberatory spaces that support Black student success (Dumas & ross, 2016).
This study draws from qualitative data, including surveys, interviews, and artifacts, to critically analyze how structural inequities and classroom dynamics shape Black students’ mathematical experiences (Jett & Terry, 2023; Martin, 2019). Findings capture that Black students experience cryptic exclusionary practices, limited cultural representation in course materials, and implicit biases that routinely affect their engagement in their mathematics courses. Students emphasize the need for inclusive instruction, representation of Black mathematicians, and classroom spaces that affirm their mathematical identities. These findings highlight the need for equitable mathematics courses layered with complimentary instruction and systemic reforms that challenge neoliberal multicultural policies and deficit-based narratives (Lubienski & Gutierrez, 2008; Ortiz, 2023).
This study critiques education policies, such as A Nation at Risk (ANAR), for framing Black students as at risk in math, leading to reforms that continue to negatively impact classrooms today, and calls for a paradigm shift toward culturally sustaining pedagogies (Dumas & ross, 2016; Robinson & Bell, 2023). The research provides critical inputs from Black student participants. Limitations include an exclusion of faculty perspectives, a need for further study of Black students at Historically Black Colleges and Universities (HBCUs), community colleges, students with disabilities, and multiple race students (e.g. one who is Black and white, or Black and Latinx, and more).
Through the utilization of BlackCrit, this dissertation extends the important critical conversation about unfairness in mathematics education courses and the misplaced focus in multiple RAG narratives. It calls for creating mathematics spaces that truly support and empower Black learners, offering a vision of learning that is both inclusive and freeing
The Effect of Nuclear Isomers on s-Process Nucleosynthesis
Get PDFs-Process nucleosynthesis is a process in which stars produce elements of mass range A = 57 to 210. Since the days of B2FH, immense work has gone into quantifying and computing s-process yields and pathways. We expand upon said work along two fronts. The first front sets up the framework for proper treatment of nuclear isomers in network calculations. We apply the framework to study 85Kr, which is a pivotal isotope in the s-process chain that affects the abundance yields of Strontium and Rubidium isotopes. In particular, we are interested in the ratio of 88Sr/86Sr and 87Rb which are important for pre-solar grain analysis and cosmochronometry respectively. The second front is characterizes the density of neutron exposures, following up the work done by the late Prof. Clayton. Additionally, we introduce two computational packages, a restructure of one that handles sparse matrix solving, and an in-house open-source highly modular Python package that can handle quantum levels data which contains features with future expansions planned
A Systemic Approach to Maximize Heterogeneous System Performance
Get PDFContinuous increases in high performance computing (HPC) throughput have served as catalysts for industry and scientific advancement in countless manners that have fundamentally shaped our modern world. Our demands on compute resources continue to scale, but the limitations of Ahmdal’s law and Dennard scaling have proven increasingly difficult to overcome when approached solely through hardware or software design. Furthermore, many HPC applications fail to utilize the collective system’s performance, even on the most advanced supercomputers.
However, the resurgence of AI in the industry has promoted an explosion of hardware and software codesign that have fueled massive improvements in GPU design and novel ASICs. These performance improvements are maximized on myriad heterogeneous systems by specially tuning applications. Mimicking these developments across the whole of computing will require similarly holistic approaches combining specialty hardware, software that caters its design to the greatest hardware strengths, and fine-tuning on individual systems to maximize performance.
We use three distinct perspectives to address scalable system performance holistically. We analyze the impacts of liquid immersion cooling technologies on sustained application performance and energy efficiency. Next, we present a case study where intentional algorithmic redesign for GPU acceleration permits robust performance improvements that endure through multiple generations of hardware. We find that memory latency forms a primary bottleneck for GPU-accelerated performance and demonstrate how algorithm-specific optimizations can significantly improve performance over multiple architecture generations. Finally, we tie these concepts together through performance optimization techniques that respect software- and hardware-based performance constraints. We improve the re-usability of performance insights with novel transfer learning techniques that make performance optimization costs more predictable and more successful in the short term. Our insights demonstrate the necessity of systemic approaches for performance tuning in HPC
Decomposition and Coordination for Multiobjective Optimization: A Framework and Methodology
Get PDFIn this work, we consider finding Pareto efficient solutions for complex multiobjective optimization problems (MOPs). Complex MOPs are unique in the literature because they have many more objective functions than is typically considered. In fact, such complex MOPs will have 30+ objective functions. This large problem size presents computational and coginitive difficulties. Computationally, standard techniques for solving MOPs are often ineffective and cognitively it is difficult for a decision maker (DM) to handle all of the information provided in such a large problem. To address these challenges, we develop a decomposition and coordination framework. This framework will allow us to decompose the complex MOP into a set of subproblems, each of which are multiobjective but with fewer objective functions. Given efficient solutions to these subproblems, efficient solutions for the original complex MOP may be constructed. We develop this approach in four ways.
First, we make theoretical extensions to Achievement Scalarizing Functions, a well-established technique for transforming an MOP into a single-objective optimization problem, which uses a predetermined reference point that represents the DM\u27s aspirations. Our extension, which we call Bivariate Achievement Scalarizing Functions (BASFs), allow the reference point to itself be an optimization variable. In so doing, we take into account the DM\u27s uncertainty in her aspirations. This development is used to great effect in this work.
Secondly, we describe two decomposition and coordination methodologies. The first considers the case of a complex MOP with global and local variables. The second considers a complex MOP with global, quasi-global, and local variables. In the global, quasi-global, and local variables case, during the decomposition phase, we present results on constructing efficient solutions for the complex MOP given an efficient solution to a subproblem. However, the coordination stage ensures that the subproblems may work together to construct an efficient solution for the complex MOP. In particular, we use BASFs to define subproblem tradeoffs, which allows a DM to directly measure the conflict between entire subproblems, a feature that is not currently available in the literature. Using these subproblems, we construct three types of coordination. First, autonomous, which is independent of the DM\u27s involvement; second, hierarchical coordination, which is entirely dependent on the DM ordering subproblems, selecting anchor points, and defining relaxations; third, hybrid coordination, which combines autonomous and hierarchical coordinations to create a robust decision making tool. We demonstrate these results on a case study of delivering humanitarian aid in the event of a natural disaster.
Thirdly, we focus our attention on the problem of actually finding efficient solutions of a subproblem MOP. We consider the case of a biobjective mixed-integer problem (BOMIP) and develop an algorithm, Pareto Leap, which exactly identifies all slices of the outcome set which contribute to the Pareto set. It is recognized in the literature that the problem of identifying Pareto slices is a difficult problem. Nonetheless, Pareto Leap is able to find all Pareto slices using tabu constraints and computationally it is only restrained by access to a sufficiently powerful solver that can handle integer variables and the underlying continuous problem. We provide the requisite theoretical results, present the algorithm, and test it on problems from the literature.
Finally, we consider the problem of coordinating a DM\u27s preferences between efficient solutions of a complex MOP. We note that this is precisely equivalent to the problem of aggregating the preferences of a committee into a single group preference. We formulate this problem of group preference aggregation as a multiobjective optimization problem over binary relations. We further provide an initial result which shows that dictatorships provide Pareto efficient solutions to the group preference aggregation problem. This leads us to conjecture that efficient solutions to the group preference aggregation problem may be written as a convex combination of each individual\u27s preferences. We conclude by discussing an example which demonstrates this conjecture
Spatial Variaiton in Host-Associated Microbiota
No full textMany organisms rely upon the internal and/or external microbial communities they harbor. Microbial communities which depend upon other organisms for survival are known as host-associated (HA) microbial communities. HA microbial communities differ in diversity and composition from surrounding environmental microbiota and are generally less diverse than surrounding soil microbiomes. Although distinct bacterial profiles exist between host and environment, microbial scale dispersal often links the two. For this reason, host and environmental microbial communities can be correlated (e.g., dominant taxa in HA microbiota are dominant in the host microenvironment or vice versa). Eukaryotic hosts act as islands for HA microbiota. Unlike environmental microbial communities, HA microbiota are often maintained by a host organism and may undergo selection based upon host anatomy, physiology, and behavior. Said differently, hosts directly and indirectly curate their microbial communities, retaining the microbiota that are beneficial for survival, while becoming refractory to those that compromise it. Thus, HA microbiota experience evolutionary histories separate from environmental microbiota and are classified as distinct communities. Importantly, HA microbial communities are often subject to perturbation based on a plethora of factors, making beneficial microbes subject to extirpation on both individual host and host-population scales. Throughout this dissertation I investigate the effects of spatial variation on the variation of HA microbiota in wild populations of ectotherms. I begin first with a theoretical model where I interconnect variable host and microbe dynamics within a iii nested multiple-scale metapopulation system. This model incorporates dynamics across host and microbial scales in a spatially implicit framework to obtain a baseline understanding of how changes in colonization/extinction ratios at one scale impacts the other. Importantly, the newly developed theoretical model explicitly accounts for colonization and extinction dynamics at both the microbe and host scales. Explicit accounting of dynamics at both scales reveals complex interactions which significantly influenced persistence and stability within multiscale metapopulations. I then extend insights from my theoretical model into a small-scale spatially explicit system Green Salamander (Aneides aeneus) metapopulation across a relatively homogenous landscape with low environmental variation. My findings demonstrate that the spatial distribution of skin microbiota in green salamanders is not a mere reflection of the surrounding environmental microbial pool but is instead distinctly shaped by host metapopulation structure and dispersal limitation. Despite consistent alpha diversity across populations, I observed a clear pattern of distance-decay in HA but not environmental microbiota similarity with increasing spatial distances, underscoring the role of host dispersal limitations in shaping HA microbial community structure. Amphibian conservation implications of the observed variability in composition and distance-decay of HA microbiota include that putative Chytrid-inhibitory microbiota richness substantiality varied (twofold increase across populations). For my following investigation I once again consider a smaller spatial scale, but I incorporate substantial environmental heterogeneity and explicitly consider host iv relatedness using a species of Aphaenogaster ant found within a montane system which I argue should experience less dispersal limitation than my Green Salamanders. Similar to my Green Salamander system, genetic isolation by distance was detected between host and spatial distance. Interestingly, this correlation was even detected between host phylogeny and environmental dissimilarity. Compositional impacts on HA microbiota resulting from distance-decay of host phylogeny, host spatial distance, or host environmental dissimilarity were not detected. Instead, a well-known endosymbiotic member of the microbiota- Wolbachia- disproportionately dominated composition. Wolbachia relative abundance did covary with host phylogeny and environment. For my fifth chapter I expand upon my previous Green Salamander system to explore microbiome variation across a substantial proportion of the Green Salamander species range from Alabama to Virginia experiencing wide bioclimatic variation. Where my previous salamander study quantified differentiation over a small spatial scale (~40km), chapter five quantifies differentiation over a much larger scale (~500 km). My findings suggest that host microbiota differentiation across large spatial extents is chiefly influenced by spatial proximity of hosts. I observed that host phylogeny minimally impacted microbiota composition refuting the hypothesis that microbiota community assembly across a species range would be heavily influenced by evolutionary history. While microbiota profiles did differ by host clade, the differences did not recapitulate host phylogeny as expected by phylosymbiosis. Similar to the full microbiota, Chytridinhibitory community composition varied by host clade, but interestingly, richness did not
How a College Course Benefits Under-Resourced High Schoolers Interested in Veterinary Medicine
Get PDFThe Veterinary Perspectives Institute (VPI) was designed to address the challenges faced by underrepresented youth who are interested in veterinary medicine. This study examines the VPI, a tuition-free program that introduces students from under-resourced high schools to veterinary medicine and One Health through a hands-on, transdisciplinary approach. The VPI integrates One Health concepts by linking human, animal, and environmental health in the context of veterinary medicine. The program’s aim is to foster college readiness and career exploration in veterinary and biomedical fields, while also addressing barriers to diversity in veterinary medicine. Through hands-on learning and case studies in One Health, students gain exposure to STEM topics like anatomy, microbiology, and epidemiology. The program addresses systemic barriers such as limited animal exposure and lack of mentorship by pairing students with university mentors from diverse backgrounds who guide them in building academic portfolios and developing professional skills. The program also emphasizes financial literacy, mental health, and work-life balance, providing students with the tools to navigate future challenges. Daily “community circles” foster socio-emotional growth, resilience, and belonging, helping students confront impostor syndrome. Program outcomes, assessed through pre- and post-surveys, show increased awareness of educational pathways and One Health concepts. While some participants reconsidered careers in veterinary medicine, the program successfully cultivated a college-going mindset and interest in STEM careers. By combining mentorship, transdisciplinary learning, and community building, the VPI offers a replicable model to address diversity gaps in veterinary medicine and inspire a new generation of professionals grounded in the One Health framework