62588 research outputs found
Sort by
The Impact of COVID-19 on Up-to-Date Breast and Cervical Cancer Screenings Among Latina Women: A Comparative Analysis Using the National Health Interview Survey Data (2019 & 2021)
No full text{"value":"Breast and cervical cancers remain leading causes of death among women, with early detection critical to reducing mortality. Latina women face persistent barriers to screenings, and the COVID-19 pandemic further widened these disparities. While previous studies reported the overall drop-in cancer screening rate during the pandemic. Latina women’s screening rate before and after the pandemic remained unclearThis study examines how the COVID-19 pandemic impacted up-to-date breast and cervical cancer screening rates among Latina women, with attention to socioeconomic, cultural, and systemic influences on access.
Secondary data from the 2019 and 2021 National Health Interview Survey (NHIS) were analyzed using descriptive statistics, chi-square tests, and logistic regression. Up-to-date screening rates before and after the pandemic were compared, with estimates age-standardized to the 2000 U.S. Standard Population.
Among all women, up-to-date breast cancer screening rates declined from 80.6% in 2019 to 79.2% in 2021, and up-to-date cervical cancer screenings fell from 84.9% to 83.4%. Among Latina women, the declines were greater: breast cancer screening dropped from 83.1% to 78.4%, and cervical cancer screening from 87.6% to 86.4%. The steepest declines occurred among uninsured and lower-income Latina women. Logistic regression confirmed that insurance status, education, and income were significant predictors of up-to-date screening.
The COVID-19 pandemic exacerbated disparities in cancer screenings among Latina women. Addressing these gaps requires targeted interventions, including mobile screening units, bilingual patient navigators, expanded insurance access, and culturally tailored outreach strategies. ","attr0":"abstract"
Reducing Core Idling in Concurrent Data Structures
No full textThis dissertation examines the problem of reducing CPU core idling in concurrent data structures. This is achieved by addressing the two primary causes of such idling: blocking caused by concurrency control and cache misses. The document presents a survey of relevant concurrent programming techniques including spin locks, sequence locks, lock ordering, read-modify-write operations, hazard pointers, and transactional memory. The importance of reducing cache misses is emphasized by explaining the memory hierarchy, the C++ memory model, and cache coherency protocols. Tools for analyzing concurrent correctness are presented as well, including progress guarantees and linearizability.The dissertation presents three original research projects. The first is the skip vector, a novel high-performance concurrent data structure based on the skip list. By utilizing locality in both the index layer and data layer, the number of cache misses per operation is cut to a fraction of what a traditional skip list would incur. The use of sequence locks allows read-only operations to interleave, and the use of hazard pointers allows for strict memory reclamation.The second project consists of three original algorithms, superior to two-phase locking, for performing mutating bulk operations on a concurrent data structure. These three algorithms are generic and suitable for use with any concurrent data structure which can be divided into partitions. By varying the location and granularity of concurrency control metadata, the three algorithms specialize in different workloads.The final project is the skip hash, a novel high-performance data structure made by composing a skip list with a hash table. The skip list makes it possible to efficiently implement range operations. The hash table serves as an index into the skip list, achieving an asymptotic reduction in runtime from O(log n) to O(1) for most elemental operations. The skip hash avoids the use of complex concurrency control by relying on fast, modern software transactional memory. A fast-path/slow-path strategy prevents starvation of long-running range queries. Together, these projects demonstrate the effectiveness of designing high-performance concurrent data structures by utilizing techniques for reducing false waiting in conjunction with synergistic techniques for reducing cache misses.</p
Supercapacitive Swing Adsorption of Carbon Dioxide: Bipolar Stacks Scaling and Direct Air Capture application
No full text{"value":"This thesis explores the application and scaling of Supercapacitive Swing Adsorption (SSA) technology for carbon dioxide (CO2) capture. The first part focuses on the testing of a scaling strategy for SSA using bipolar electrodes. The second part explores the suitability of SSA for Direct Air Capture (DAC). The study addresses the growing global concern regarding CO2 emissions and climate change, with an emphasis on mitigating CO2 emissions through SSA as an innovative carbon capture technique. The introductory chapter 1 provides an overview of historical trends in CO2 emissions, emphasizing the urgent need for effective carbon capture solutions. Carbon capture and storage (CCS) technologies are introduced, which form the basis for the exploration of SSA. A comprehensive review of existing CO2 capture technologies is presented, ranging from absorption and adsorption processes to membrane separation and electrochemical methods. Each technology is evaluated for its merits, energy efficiency, and feasibility, with a special focus on the limitations and potential enhancements required to make them economically viable. The development of SSA technology is detailed, focusing on the concept of using capacitive charging and discharging of activated carbon electrodes to reversibly adsorb and desorb CO2. This approach relies on the electrostatic forces generated by capacitors, thereby enhancing the efficiency of CO2 capture. The chapter explains the design of early SSA prototypes and their evolution. Chapter 2 covers the fundamental principles of various electrochemical characterization techniques employed to investigate and compare the properties of different electrochemical cells. These techniques are essential for assessing the capacitance, resistance and other energetic metrics evaluated in SSA. Chapter 3 describes the scalability potential of SSA. A novel design using bipolar electrode stacks is introduced with detailed descriptions of the materials and operational conditions used in experiments, to enable the scale-up of SSA technology. The experimental findings demonstrate that scaling the SSA module to allows for processing proportionally larger CO2 volumes. Secondly, it discusses the energetic benefits associated with this scaling strategy. In chapter 4, the application of SSA in Direct Air Capture (DAC) is explored, demonstrating its capability to effectively capture CO2 from a gas mixture contains 400 ppm CO2 with balanced N2. The final chapter summarizes the contributions of the research, emphasizing the potential of SSA as an effective and scalable CO2 capture solution. Future research directions are also outlined, include the investigation of underlying mechanisms using in-situ techniques, the removal of expensive gas diffusion layers by imprinting gas flow channels with structures that ensure low pressure drop, and the integration of SSA modules into energy shuttling systems for enhanced operational efficiency. These efforts aim to improve the cost-effectiveness, scalability, and overall performance of supercapacitive swing adsorption technology for carbon capture.
","attr0":"abstract"
Longitudinal Pathways to Maternal Psychological Control Towards Preadolescents in Conflict Conversations: The Roles of Economic, Maternal, and Child Risk Factors
No full textThe goal of this longitudinal study was to examine both the direct and indirect relations between economic pressure and maternal guilt and shame inductions, as well as to explore the potential mediating roles of family conflict, maternal depression, and children’s aggressive behaviors. Participants included 436 children (49% girls, 51% boys) and their mothers from a diverse sample of low-income European American (N = 148), African American (N = 144), and U.S. Mexican (N = 136) families who were followed from age 2 to fifth grade. Mothers reported economic pressure, family conflict, maternal depression and children’s aggressive behaviors. Maternal guilt and shame inductions were coded from conflict conversations with their pre-adolescent children. Results showed that economic pressure at age 2 was positively associated with family conflict at age 3 as well as with maternal depression and children’s aggressive behaviors by pre-kindergarten. Family conflict was further linked to both maternal depression and aggressive behaviors. Children’s aggressive behaviors were related to higher levels of maternal guilt and shame inductions, whereas maternal depression was associated only with shame inductions by fifth grade. Economic pressure had indirect links to maternal guilt inductions through family conflict and aggressive behaviors. These patterns remained consistent across ethno-racial groups. The findings largely support the Family Stress Model and extend its relevance to low-income African American and U.S. Mexican families. The results also emphasize the role of children in shaping parenting practices, particularly in relation to maternal psychological control. The distinct pathways underlying maternal guilt and shame inductions show the importance of conceptualizing psychological control as a multidimensional construct rather than a unidimensional one.</p
Landscape response to active deformation in the Ecuadorian Forearc
No full text{"value":"This study examines long-term forearc deformation in the northern Ecuadorian margin, an erosive subduction zone influenced by the subduction of the Nazca Plate and collision of the
Carnegie Ridge. We apply a suite of geomorphic metrics—normalized channel steepness index
(Ksn), χ-analysis, and drainage basin asymmetry—across 89 watersheds using high-resolution
ALOS World 3D topography and TopoToolbox in MATLAB. Longitudinal profiles and automated
knickpoint detection reveal spatial clustering of knickpoints in association with fault structures
and lithologic boundaries. Ksn values highlight zones of localized uplift along the Coastal and
Chongón Colonche Cordilleras, with domal structures inferred from radial drainage patterns. χ
based divide migration metrics indicate a regional tendency for eastward migration of the Coastal
Cordillera drainage divide toward a long-wavelength filtered topographic divide, except in its
southern extent where localized westward migration is inferred. Gilbert metrics generally
corroborate these patterns, though some segments suggest divide stability. Integration of
geomorphic observations with Vp isovelocity contours from seismic tomography reveals
correlations between surface deformation, basement highs, and subsurface low-velocity zones.
Together, these results demonstrate that geomorphic metrics provide a valuable framework for
identifying and interpreting active deformation in complex erosional forearc settings.","attr0":"abstract"
Interagency Training to Promote Culturally Responsive, Family-Centered Home Visiting and Pediatric Service Integration
No full textEarly childhood is a critical period of rapid cognitive, language, and social-emotional development, which influences long-term health and educational outcomes (Shonkoff et al., 2009). However, poverty can hinder development during these formative years (Morris et al., 2017), making it essential for agencies serving infants and toddlers to promote positive outcomes for at-risk populations. Two key service systems—home visiting and pediatric primary care—share the goal of providing culturally responsive, family-centered care. Despite this shared goal, coordinated care between these systems is lacking. One potential solution for achieving coordination is interagency training, where professionals from both systems engage in joint training to improve communication and understanding of each other’s roles. The current study followed the Participatory Intervention Model (Nastasi et al., 2000) to design and pilot Linking for Little Ones (LLO), an interactive interagency training for Early Head Start (EHS) home visitors and pediatric primary care residents. The training aimed to enhance mutual understanding of service systems and promote sustained collaboration between systems. LLO included four components: Interactive Instruction, Collaborative Case Study, Dual Discussion of Families, and a Reflective Debriefing session. A total of 10 EHS home visitors and 41 pediatric primary care residents participated. Results indicated that home visitors reported small gains in comfort and competence in guiding families on health topics and engaging in interprofessional collaborations with pediatricians. Effect sizes ranged from small to large across timepoints. Pediatric residents showed improvements in knowledge of EHS, family-centered care, and ideas for continued collaboration with home visitors. These results suggest that LLO offers meaningful benefits and warrants further exploration through a full-scale study. Limitations and future research directions are discussed.</p
On Heterogeneous Systems and Data Repositories
No full textData repositories are software systems that store, retrieve, and analyze data. They are the backbone of computing infrastructure and rely on various core components, including concurrency controls and data structures. Improving their performance is essential to supporting ever-increasing computational demand.With recent trends in computer architecture, it is becoming increasingly important to consider specialized processors and how they are interconnected and can cooperate. The design of these heterogeneous systems for data repositories and their algorithmic components is the primary focus of this dissertation. More specifically, we consider utilizing central processing units (CPUs) with graphics processing units (GPUs) as co-processors and designing our systems and components with these processors in mind. Our methodology is to approach data repositories through the lens of instruction set architecture affinity (ISA affinity), or how well our algorithms and tasks map to specific processor architectures. We further consider the interconnection between processors and the additional latency and performance of moving data between co-processors. The contributions of this dissertation include the design of two systems: a cooperative CPU-GPU key-value store and a transactional system with support for heterogeneous workloads, including hybrid transactional-analytical processing through first-class support for heterogeneous architectures. We also provide an approach to semantic transactional processing through cooperative CPU-GPU processing, an architecture-agnostic framework for coalescing memory accesses in data structures for high performance, and a mapping data structure supporting linearizable point operations and range queries.</p
Direct Investigation of the Impact of Rheology Modifiers on Internal Microstructure of Drying Coatings
No full textIn the 1970\u27s, due to environmental and health concerns, the coatings market wentthrough a major shift from solvent-borne coatings to waterborne coatings. This presented new
challenges and new opportunities for coatings formulators due to complex interactions between
constituents resulting in various final barrier, adhesion, and optical properties. These challenges
required formulators to focus on the development of new rheology modifiers to target optimal
properties for manufacturing, storage, and application. Benchtop experiments are commonly used
to predict the final coating properties, but they provide little detail of how the constituents interact
throughout drying. There is often a separation between the predicted film based on the formulation
and the final applied film properties.
One reason for this separation in prediction and performance outcome is because small
additions of rheology modifiers can have a large impact on the paint\u27s flow properties and
constituent stability. Over the last few decades, better understanding the drying process of
coatings, and how different factors can affect the process, has become a topic of interest.
Scattering techniques such as small angle x-ray scattering (SAXS) and optical coherence
tomography (OCT) have been utilized to attempt to further our understanding of what occurs
inside the film while drying at very different scales. In contrast, spatially precise analysis enabled
by high speed laser scanning confocal microscopy can be utilized to directly image the film in the
80-150 μm adjacent to the substrate during drying. This technology can resolve individual
constituents larger than about 250 nm with high fidelity to measure microstructural evolution
during drying. Each of these techniques have limitations, such as resolving the relevant range of
length scales and limitations about opacity of the formulation, yet together they help to bridge the
wide gap of knowledge between formulation and final film performance.
This research focuses on using industry knowledge and background to guide academic
research focusing on materials of relevance. The primary focus is to understand the
role that additives play in the microstructural evolution on the drying process. Additionally, in
industry we commonly group the interactions and mechanisms seen between different rheology
modifiers as in categories of associative or non-associative additives. This tends to lack detail
about the colloidal interactions and the microstructure evolution that are taking place amongst
materials in the formulation. Focusing on bridging this gap between these industrial descriptions
and a fundamental understanding of these interactions is the main objective of my research.
Using high speed laser scanning confocal microscopy we directly image
microstructural rearrangement in situ throughout the entire drying process. Using particle
tracking algorithms, simulation level details of particle locations are generated throughout the entire drying process to resolve almost instantaneous, fully 3D maps of the microstructure. A model formulation is utilized in this research to mimic a simple paint formulation. The formulation contains 3 main materials to act as a surrogate for common ingredients found in architectural latex paints.
Polyethylene oxide (PEO) is used to represent water soluble polymers in solution. Silica (SiO2) microspheres act as a surrogate for latex particles or other pigments. Silica is used primarily due to refractive index issues seen with latex and it gives us the flexibility to change and control
surface properties resulting in consistent particle interactions. Lastly, commonly used rheology modifiers and their impact on stability and microstructure is investigated.
Using the x, y, z particle locations, we quantify the differences seen in raw confocal
images. One way we can measure the extent of aggregation in our formulations is the number of
neighbors in contact, Nc. The neighbors are found pair wise and determine the number of particles
that are in network with the particle of interest. Voronoi polyhedron volume, or free space is calculated, associated with each particle and use the evolution of the distribution in these volumes to fingerprint the microstructure evolution. The strength of particle association is directly seen in the distribution of Voronoi volumes where long tails and higher average volumes represent stronger
particle associations and shorter rates of assembly.
Using these techniques for collecting and analyzing data, we are able to quantify differences seen between different rheology modifiers used in coatings formulations on microstructure development. Cellulosic materials present weak associative interactions in low concentrations suggesting that these materials may alter the surface properties of the particles and as concentration increases depletion flocculation takes over resulting in significant aggregation and flocculation of the particles. Alkali swellable emulsions (ASE) also fall into the non-associative category but thicken through different types of interactions. This interaction is a true representation of the volume exclusion mechanism, resulting in a similar progression of microstructure regardless of the concentration of ASE. With non-associative materials, two different types of interactions were quantified thus suggesting that materials within a certain mechanism can have different evolutions of microstructure and these simple descriptions may not be the best to describe the mechanism of the rheology modifiers.
Continuing to move throughout the common materials that are all said to follow associative interactions were investigated as well. Hydrophobic modifications to common polymers are the driving mechanism to provided associative interactions amongst the particles and polymers. Hydrophobically modified hydroxy ethyl cellulose (HMHEC) and hydrophobically modified alkali swellable emulsion (HASE) materials are said to thicken through both volume exclusion and enhanced interactions. When using HMHEC, a network of polymer suspends the SiO2 particles resulting in a consistent drying profile regardless of concentration of HMHEC. HASE materials presented a combination of interactions, at low concentrations a more volume exclusion effect is seen and as concentration increases an apparent association results in aggregation. In contrast, hydrophobically modified ethoxylated urethane (HEUR) demonstrates the impact of a rheology modifier designed to have an associative interaction on particle microstructure during drying. A wide variety of interactions and materials are studied resulting in the generation of a toolbox of knowledge on the interactions that dominate the constituent interactions with rheology modifiers in formulations.
Lastly, research and product lines have emerged in the last few years focusing on the impact that temperature plays on the drying process of coatings. Increasing the working range of common coatings would give more time for contractors and consumers to paint ensuring they are in ideal conditions for good film formation and development. Preliminary investigations of the role the temperature plays on the microstructural evolution suggest a range of various impacts on microstructure. This imaging method provides a more comprehensive test for understanding the complex interactions of the constituents through these model paint systems. These studies could be useful in industry to understand the effects that different rheology modifiers play on the drying properties and how the dry film properties could be impacted. This research provides a new perspective to the way that we research coatings, combining industry knowledge to ensure that materials of relevance are tested to provide real world useful data to formulators and raw materials companies. Although there is much more work to be done upon pushing the formulation to a more realistic coatings formulation, this research could provide early stages of information on how rheology modifiers thicken and interact amongst constituents throughout the drying process.
</p
Advancing Spectral Koopman Methods: Challenges in Integrating Randomized Algorithms
No full textThis thesis investigates the potential enhancement of the Sparse-Grid-Based Adaptive SpectralKoopman (SASK) method through the integration of modern randomized algorithms. Specifi-
cally, this research examines the transition from MATLAB\u27s standard eig function to the more
efficient eigs implementation, followed by an attempted integration with the sketched Rayleigh-
Ritz (sRR) method. While the eigs implementation demonstrates substantial performance im-
provements—achieving up to 68 times faster computation while maintaining solution accuracy—the
integration of sRR reveals fundamental compatibility challenges due to eigenvalue classification re-
quirements in Koopman analysis. These findings provide crucial insights into the mathematical
constraints of enhancing Koopman operator methods with randomized algorithms, contributing to
the ongoing development of efficient numerical methods for high-dimensional dynamical systems.</p
Effects of a Dance/Movement Therapy-Informed Adaptation of the Strong Kids Curriculum on Social-Emotional-Behavioral Outcomes of Students with Autism Spectrum Disorder
No full textSocial-emotional learning (SEL) programs in schools provide students with opportunities to develop skills in self-awareness, self-management, social awareness, relationship skills, and responsible decision-making. Although prior research has demonstrated positive effects of school-based SEL programs for general student populations such as increased social-emotional competence and positive attitudes, less is known about the effects of SEL for students with emotional and behavioral disorders (EBD) or autism spectrum disorder (ASD). More research is needed to understand how SEL programs could be adapted to better fit the needs of students with disabilities to decrease off-task behavior and increase academic engagement during instruction. Dance/movement therapy (DMT), for example, offers students strategies to non-verbally identify emotions, communicate, and engage with peers with a focus on the mind-body connection. Preliminary research has shown that autistic students who participated in school-based DMT demonstrated increased self-awareness, engagement, and social competence. The current study utilized a DMT-informed adaptation of an SEL curriculum for elementary-aged autistic students receiving special education. Using a multiple-baseline design across student groups, students\u27 academic engagement and off-task behavior was observed during SEL lessons. Further assessment included student point sheet data, student mood ratings, teacher-report of social-emotional competencies, and student SEL knowledge, as well as procedural fidelity and intervention acceptability. Findings suggested that the DMT-informed adaptation of an SEL program generally decreased off-task behaviors and increased academic engagement with varying levels of effect. Students reported larger increases in mood during the DMT-informed SEL lessons compared to baselines, and most students demonstrated increases in SEL knowledge. Results were inconclusive for point sheet data and teacher-reported social-emotional competencies. Overall, results of the current study set the stage for further research to refine and improve implementation of DMT-informed adaptation of an SEL curriculum in school settings and continue to develop SEL programming for autistic students.</p