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ASSOCIATIONS OF COGNITIVE FUNCTION TRAJECTORIES AND OBJECTIVELY MEASURED PHYSICAL ACTIVITY: THE ARIC NEUROCOGNITIVE STUDY
Get PDFImportance: Declining cognitive ability may inhibit engaging in physical activity (PA) in late life, aggravating disease burden and functional decline.
Objective: Examine the association between cognitive decline trajectories and daily PA patterns in cognitively unimpaired older adults using retrospective data from the Atherosclerosis Risk in Communities Neurocognitive Study.
Methods: Participants underwent neuropsychological battery tests at each visit (Visits 5-9) over 12 years, for overall and domain-specific cognitions (language, memory, and executive function). Cognitive trajectories were derived using linear mixed-effects models. Participant-specific rates of cognitive decline were categorized into tertiles representing fast decline, slow decline, and stable groups. PA patterns were assessed using wrist-worn accelerometry collected at the latest visit (Visit 9, 2021-2022), including intensity, volume, fragmentation, and variability. Associations between cognitive trajectories and PA were analyzed using multivariable linear regression and estimated marginal means adjusted for demographic variables, lifestyle, genetic risk factors, health status, self-report PA and cognitive function.
Results: Among 2,071 cognitively unimpaired older adults (mean age 74.0 years [SD 4.5]; 59.9% female) followed for 8.2 years (median), the per-decade decline rate of overall cognition is 0.52 SD (IQR -0.68 to -0.35). Cognitive decline trajectories, rather than baseline functions, were associated with PA patterns. A 10% slower rate of overall cognitive decline was associated with increased total activity counts (β=0.035 SD [95% CI 0.022 to 0.049]), higher maximum activity counts per minute over 10 consecutive minutes (β=0.044 SD [0.037 to 0.063]), increased active-to-sedentary transition probability (β=-0.036 SD [-0.050 to -0.023]), and greater root mean square successive difference (RMSSD; β=0.050 SD [0.037 to 0.063]). RMSSD showed the strongest associations with overall and domain-specific cognitive decline, with additive effects among individuals classified in fast decline groups (four times versus zero: β=- 0.65 SD [-0.91 to -0.39], p for trend<0.001). Executive function decline affected most PA patterns more strongly than language or memory decline.
Conclusion: Cognitive decline trajectories, particularly in executive function, were most strongly associated with reduced activity variability, as well as lower volumes, lower intensity, and greater fragmentation, independent of baseline cognition. The findings suggest that objective PA monitoring could serve as an indicator of cognitive vulnerability in older adults
HIGH-SPEED HYPERSPECTRAL IMAGING OF ENERGETIC MATERIALS: A NEW ARCHITECTURE FOR DIFFUSE REACTION IMAGING
Get PDFHigh spectral and temporal resolution optical diagnostic methods for in situ energetic material analysis have recently grown in demand due to the increasing applications of reactive nanocomposites and metal fuels. A lack of feasible pyrometric and spectroscopic techniques has left much to be understood about the heterogeneous and diffuse reactions inherent to metal combustion. To meet these demands, a new design of the snapshot hyperspectral imager for emissions and reactions (SHEAR) is proposed – incorporating integral field spectroscopy to enable the analysis of diffuse combustion scenes – dubbed SHEAR-IFS. The justification for such a tool is given, as well as its optical design, calibration, and initial signal processing. Physical vapor deposited Al:Zr composite samples are ignited, and their burn evolution is recorded at a 5 kHz frame rate with simultaneous, co-registered imaging and spectral channels. This technology provides insight into the nature of the reaction wavefront, burn time, temperature, spectral emission, and emissivity of similar materials with flexibility in temporal, spatial, and spectral range and resolution
Highly Sensitive and Multiplexed Biomarker Detection in Infectious Disease Diagnostics
No full textAntimicrobial resistance (AMR) is a growing global crisis, rendering conventional antibiotic treatments ineffective and posing a significant threat to public health. AMR currently accounts for over a million deaths annually, with projections indicating an even greater burden in the coming decades. The main driver behind AMR is the misuse and overuse of antibiotics, which is caused by various factors including the difficulty in accurately distinguishing different infection types and the delay in performing antimicrobial susceptibility testing (AST) using existing diagnostic approaches. These factors lead to inappropriate antibiotic prescriptions and excessive reliance on empirical broad-spectrum antibiotic use, accelerating the spread of resistance.
To address these challenges, this thesis presents novel molecular diagnostic platforms designed for highly sensitive, multiplexed biomarker analysis to improve infectious disease management (Chapter 1). Key innovations include: (1) FluoMag-dPEA, a fluorescence-coded, magnetic bead-enhanced digital proximity extension assay enabling multiplexed protein biomarker detection (Chapter 2); (2) FluoMag-dREP, a fluorescence-coded, magnetic bead-enhanced digital reverse transcription-extension PCR assay for multiplexed mRNA biomarker detection (Chapter 3), allowing for multimodal analysis when integrated with FluoMag-dPEA (Chapter 4); and (3) a microfluidic dual-digital PCR approach for rapid AST of Neisseria gonorrhoeae to beta-lactam antibiotics, leveraging the observed bacterial lysis and DNA fragmentation upon antibiotic exposure (Chapter 5).
These platforms provide scalable, accessible, and high-sensitivity diagnostic solutions, potentially improving the differentiation of bacterial and viral infections while enabling rapid AST. By enhancing biomarker detection and reducing diagnostic turnaround times, this work contributes to global efforts in combating AMR and advancing antimicrobial stewardship
3D Self-Folding Shell Microfluidic Arrays (SMFAs) for Spatiotemporal Chemistry
No full textConventional microfluidic systems have traditionally been confined to planar, two-dimensional geometries, limiting their ability to generate complex chemical patterns in truly 3D contexts. This limitation becomes particularly significant when studying spherical biological models such as organoids, which have emerged as powerful tools for investigating developmental processes and disease mechanisms. To address this challenge, we have designed and fabricated biocompatible self-folding shell microfluidic arrays (SMFAs) with embedded microchannels that can encapsulate and interface with 3D spherical structures. Using conventional photolithography, we created gradient cross-linked SU8 films with embedded sacrificial fillers that dissolve to form self-folded microchannels around spherical objects. Through a combination of computational fluid dynamics simulations and experimental validation, we demonstrate the versatility of our system in generating chemical gradients, performing multi-chemical patterning, and facilitating complex chemical reactions within agarose gel beads. Moreover, we establish the biocompatibility of SMFAs and their potential for biological applications through successful spatiotemporal patterning of live stem cell-derived neural organoids. By enabling precise control over the 3D chemical microenvironment of spherical objects, this work provides a versatile platform for investigating fundamental questions in developmental biology, advancing tissue engineering approaches, and creating novel patchy particles with complex 3D chemical patterns
ANALYZING GREAT POWER COMPETITION USING THE SITE FRAMEWORK: GREAT POWER COMPETITION BETWEEN THE U.S. AND CHINA IN SOUTH AMERICA
Get PDFGreat power competition between the U.S. and China is often analyzed globally or in the Indo-Pacific region. Its dynamics in peripheral regions traditionally under the sphere of influence of one power are less understood but critically important. This study focuses on South America, a region historically linked closely with the U.S., no experiencing significant increases in Chinese engagement across multiple domains. Current U.S. strategy often frames the global dynamic as a struggle between the U.S.-led liberal order and a revisionist China seeking greater global influence. Yet the nature of this interaction within South America remains debated.
This research directly addresses this debate with the question: Is the competition between China and the U.S. within South America characterized as great power competition? The central hypothesis is that if competition between China and the U.S. in South America is characterized as great power competition, then there should be representation of competition in the following four domains: Security, Ideology, Technology, and Economy (SITE). The findings support the hypothesis: Great power competition between the U.S. and China is occurring in South America evidenced by significant competitive influence across the security, ideology, technology, and economy domains. However, this competition is characterized by strategic asymmetry with China prioritizing economic and technological influences over direct security challenges
COMPUTATIONAL CHEMO-FLUIDIC MODELING OF THROMBOSIS IN ANEURYSMS DUE TO FLOW DIVERTING STENTS
Get PDFIntracranial Aneurysms (IA) pose a significant risk of rupture, leading to subarachnoid
hemorrhage with high fatality rates. In the last decade, Flow Diverting Stents (FDS)
have emerged as a promising treatment. These stents are placed within the artery
to reduce blood flow into the aneurysm, inducing flow stagnation and triggering
thrombosis. The resulting thrombus restricts flow, preventing subsequent growth and
rupture. Additionally, the stent acts as a scaffold for endothelium reconstruction.
Despite these advancements, some IA cases still experience post-treatment rupture due
to poor thrombus quality. To address this, we propose a more precise analysis using
Computational Fluid Dynamics (CFD) modeling and simulation. In our approach,
the fluid dynamics is simulated using a sharp interface Immersed Boundary Method
(IBM) which enables us to address the complicated geometry associated with arteries
and aneurysms easily. The solver is augmented with a graph partitioning approach
to increase efficiency of IBM solver in internal flow. Seven scalars and five reactions
are introduced to model a simplified coagulation cascade as well as platelet (PLT)
activation. The first adopted approach to model thrombus growth is based on the
Bound PLT (BP) field. We also propose a second Thrombus Index (TI) approach
that might impose physical constraints and solve some problems associated with the
BP approach. The interaction between the clot and the fluid is modeled as a Darcy
term in the Navier-Stokes equation. Following previously published work, the FDS
is treated as a porous membrane with an inhomogeneous force model to account for
the deflection of the flow by the stent and the change in pressure across the stent
mesh. In a channel flow validation for the FDS force, our results show agreement
with previously published data. Based on a subject-specific geometry of a saccular
aneurysm, stents with different porosities are used in simulations of thrombosis in a
modeled aneurysm. The key findings of the study are
1. Fibrin (FI) contributes a nearly uniform thrombus region for TI, while BP
adds fluctuations inside, affecting its quality. This proves the practical findings
in previous works that it is important to know the PLT concentration in a
thrombus.
2. A thrombus is generated at a porosity of 65% and below. Thrombus coverage
decreases from 44% to 30% when increasing porosity from 60% to 65%. It
indicates that in the applications for a large-size aneurysm, it would be robust
to use at least 40% porosity.
3. The intraneurysmal thrombus grows in two steps: it starts at the corner, first
thickening locally; this initiates a secondary flow stasis region and thrombosis
behind it. The physical process implies the the local geometry and initiating
position of thrombosis could make a difference in clotting, and it might shed
some light on optimizing the placement or reveal some potential risks.
Overall, the research demonstrates the potential of in-silico models to predict FDS
driven thrombosis in patient-specific aneurysms
A Computational Framework To Reconstruct Dislocation Plasticity From Surface Measurement Data
No full textDislocations are fundamental to understanding the mechanical properties of crystalline materials, as they are the primary carriers of plastic deformation. The movement and interaction of dislocations under applied stress significantly influence material strength, ductility, and toughness. However, their microscale dimensions, complex three-dimensional distributions, and intermittent motion pose significant challenges for direct observation and characterization. Conventional techniques such as transmission electron microscopy, X-ray diffraction, and electron channeling contrast imaging provide valuable insights into dislocation structures. While these techniques can resolve the fine details of individual dislocations, they are limited in their ability to monitor dynamic dislocation evolution. Recent advancements in surface measurement techniques, including laser interferometry and acoustic emission sensing, offer high-frequency temporal resolution, making them promising candidates for studying dislocation dynamics. However, interpreting surface measurements into meaningful 3D dislocation microstructures remains a key challenge. This thesis develops a robust computational framework to reconstruct dislocation evolution from high-frequency surface measurement data, bridging the gap between surface responses and underlying dislocation activities.
At the core of this framework, an analytical solution for the three-dimensional elastodynamic field generated by dislocation motion is derived, demonstrating remarkable agreement between its predicted displacement and stress wave patterns and those obtained from molecular simulations. A scalable algorithm is designed to numerically implement this solution within dislocation dynamics simulations, enabling the computation of elastodynamic stress and displacement field at any point for evolving dislocations networks. To infer dislocation network evolution and reconstruct plastic strain localization, data assimilation techniques—including a total variation-regularized algorithm and the ensemble variational method—are employed. Rigorous assessments using simulation data demonstrate that the proposed approach achieves an accuracy exceeding 90% in three-dimensional reconstruction of plastic strain localization. The proposed computational framework advances the development of characterization techniques of crystalline materials and opens new avenues for understanding plastic deformation
Synthesis and Utilization of High-Entropy Alloy (HEA) supported on Metal Oxide for Ammonia Decomposition to Hydrogen
No full textAmmonia (NH₃) is increasingly recognized as a promising hydrogen carrier due
to its high hydrogen content, ease of storage and transportation, and compatibility with
existing infrastructure. Catalytic ammonia decomposition, which produces hydrogen
and nitrogen without CO₂ emissions, is a key reaction enabling the use of ammonia
as a clean fuel. In this study, a series of high-entropy alloy (HEA) catalysts supported
on metal oxides (MgO and γ-Al₂O₃) were synthesized via Wetness Impregnation
Thermalshock combined method and evaluated for their catalytic performance in NH₃
decomposition. The influence of transition metal composition, precursor types, support
materials, and Co/Mo ratio was systematically investigated in this study.
XRD and TEM characterizations confirmed the formation of FCC-structured
HEA nanoparticles with an average particle size of ~1 nm. EDS mapping revealed
homogeneous elemental distribution without detectable phase separation. Among
the catalysts tested, the Co₃₅Mo₃₅Fe₁₀Ni₁₀Mn₁₀/Al₂O₃ sample exhibited the highest
NH₃ conversion (91.71%) at 500 ℃. Kinetic studies showed an apparent activation
energy of 95.5 kJ/mol under low-conversion conditions, and stability testing
demonstrated consistent catalytic activity over 12 hours at 500 ℃.
These results demonstrate that the synergistic tuning of HEA composition and
oxide supports can lead to enhanced catalytic activity and stability, offering a
promising pathway for the development of noble-metal-free ammonia cracking
catalysts for hydrogen production
Analysis of envelope diversity in simian immunodeficiency virus infected rhesus macaques during untreated infection
No full textHuman immunodeficiency virus (HIV) establishes lifelong infection by integrating into the host genome of CD4+ T cells, forming a persistent latent reservoir. This latent reservoir in resting memory CD4+ T cells is the major barrier to HIV cure and viral eradication, even with effective antiretroviral therapy (ART). Simian immunodeficiency virus (SIV) infection in Indian-origin rhesus macaques is a powerful model to study HIV pathogenesis and reservoir dynamics due to closely related immunological and virological characteristics, replication strategies, and disease progression. A key feature of both HIV and SIV is the extraordinary genetic diversity of the envelope (env) gene, which encodes the viral surface spike protein and plays a critical role in immune escape and persistence.
To understand the diversification of the viral envelope during untreated infection, we examined the intra-host evolution of the SIV env gene in eight Indian-origin rhesus macaques infected with the SIVmac251 swarm. Using single-genome sequencing (SGS) of plasma samples obtained at multiple (6-7) time points pre-ART, we generated 4,731 high quality env sequences, coupled with 2,443 on-ART proviral sequences that were already published (Fray et al., 2023).
The analysis reveals extensive within-host viral diversification following host-specific evolutionary patterns despite being infected with the same viral stock. We hypothesize that distinct dominant mutations present in the plasma virus of each animal at the same time reflect unique pathways of escape from the host’s neutralizing antibodies. Chao1 estimator predicted thousands of unique env variants were present in each animal. Longitudinal sampling of pre-ART plasma viruses and on-ART proviral sequences uncovered continuously new variants being sampled at different time points, and same variants were rarely found. Rarefaction analysis showed that the new variants discovered had different combinations of previously observed mutations. Amino acid substitution analysis suggests that only certain amino acid positions within gp120 subunit of the envelope tolerate a restricted set of amino acid changes. Together, this work demonstrates the evolutionary constraints that are necessary to maintain the structural integrity and functionality of the envelope. These results highlight that the significant animal-specific immune driven diversity within each host is bound by evolutionary limitations
DESIGN AND ANALYSIS OF ELECTROACTIVE DIELECTRIC BLENDS AND INTERFACES IN ORGANIC ELECTRONIC DEVICES FOR ENHANCED VAPOR SENSITIVITY AND PERFORMANCE
No full textOrganic electronic devices are promising candidates for a wide variety of applications including chemical vapor sensing and nonvolatile memory. Devices such as organic field-effect transistors (OFETs) and capacitors continue to attract increasing attention due to their flexibility, low cost, and ease of processability compared to traditionally employed inorganic materials. However, the lower degree of ordering and stability in organic materials relative to inorganic materials limits their performance, demanding the understanding of charge trapping and transport in organic electronic devices to increase their applicability.
In this work, OFETs are fabricated on flexible and high-surface area membrane gate dielectrics to enhance device charge carrier mobility and sensitivity to gaseous nitrogen dioxide (NO2), a widespread air pollutant. Thermal annealing studies are conducted on these devices up to 200°C to assess performance improvements and changes in device stability. Additional OFETs comprising novel aniline-functionalized semiconducting polymers are fabricated to enable sensitivity to less reactive volatile organic compounds such as acetone, which can indicate diabetic ketoacidosis when detected in the breath.
In addition to improving chemical vapor sensing of OFETs, polystyrene (PS)-based gate dielectrics were blended with the electroactive small molecule dibenzotetrathiafulvalene (DBTTF) to increase charge trapping and storage in pentacene OFETs. The structure-property relationship of these OFETs was analyzed and determined to be dependent on the concentration and morphology of the small, separated DBTTF crystallites in each dielectric material. Two-terminal measurements were performed as an additional characterization and revealed memristor activity in devices containing 7.5-10 wt.% DBTTF, indicating nonvolatile memory behavior that resembles the synaptic behavior of the human nervous system.
To further investigate the charge trapping behavior of electroactive dielectric blends, polymer capacitors were fabricated using PS, polycarbonate (PC), and poly(methyl methacrylate) (PMMA) as dielectric materials. Dilute concentrations of DBTTF and 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) were blended in to improve capacitor energy density, efficiency, and breakdown electric field strength. Lastly, dielectric spectroscopy was utilized to determine the frequency-dependent dielectric constant of thin films of tholin, a material analog of the aerosols found in Titan’s hazy atmosphere, with analytical models used to calculate low frequency dielectric constants that will support the Dragonfly probe mission