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Enhancing Reliability, Throughput, and Energy Efficiency in UWB-based Applications
No full textUltra-wideband (UWB) radios are becoming increasingly popular among researchers due to their unique physical layer characteristics, including high data rates, low power consumption, and precise localization. Despite their potential, the efficiency of UWB networks remains a significant challenge, preventing the widespread adoption of this technology. As the number of users increases, issues such as low link reliability and reduced network throughput degrade the performance of UWB-based applications. Additionally, UWB-equipped nodes experience high energy consumption when discovering other nodes in large networks. Many UWB-based solutions have adapted conventional techniques from other wireless technologies to enhance network efficiency. However, these approaches have not fully addressed the existing challenges. UWB applications use Collision Avoidance (CA) mechanisms to improve link reliability and throughput. However, these methods are not entirely compatible with the UWB radio standard. Channel hopping for higher throughput may not be feasible in UWB networks that include nodes from different vendors. To reduce energy consumption, UWB applications have relied on low-power radios, such as Bluetooth Low Energy (BLE), for neighbor discovery, which requires additional radio interfaces on all UWB nodes. Recent research has also focused on leveraging UWB-specific signal characteristics to enhance efficiency. By analyzing UWB signal properties and receiver behavior, researchers have proposed solutions to improve the throughput of UWB applications through overlapping signals, also known as concurrent transmission. However, these solutions do not yield consistent results across all UWB systems. To improve network efficiency, this work presents solutions to (1) enhance link reliability, (2) increase throughput, and (3) reduce energy consumption in UWB networks. We designed our solutions based on UWB standards (IEEE 802.15.4z and IEEE 802.15.4a), ensuring compatibility with most UWB radio devices. Additionally, our solution is application-agnostic, making it adaptable for a wide range of UWB applications without requiring modifications to the underlying protocol
Ozone Precursor Sources and Box Modeling of Ozone in Mexico City Under Altered Emission Conditions
No full textThis dissertation investigated ozone (O3) precursor sources and their impact on O3 formation in Mexico City Metropolitan Area (MCMA) under altered emission condition for March-May, 2016. Since the O3 formation regime in the MCMA has transitioned to VOC-limitation, the identification of key VOCs with highest O3 formation potential (OFP) and their precise source identification is essential. In the first task, initial VOC concentrations (IC-VOCs) were calculated for both day and night from measured VOCs (MC-VOCs). The fraction reacting before reaching the receptor site, contributing to O₃ formation, is termed consumed VOCs (C-VOCs). During rush hour times, the top C-VOCs were trans-2-butene (1.12 ppb), cis-2-butene (0.60 ppb), trans-2-pentene (0.43 ppb), propylene (0.33 ppb), ethylene (0.24 ppb), and isoprene (0.16 ppb). Despite trans-2-butene’s highest consumption rate, m,p-xylene was the top VOC for O3 formation due to its high atmospheric abundance, linked to industrial and vehicular emissions. In the second task, a modified positive matrix factorization (PMF) with Fpeak rotation (0.3 for MC-PMF and 0.5 for IC-PMF) was utilized to identify VOC emission sources. Similar eight main sources were found, albeit with differing contributions from MC-PMF and IC-PMF. While vehicular emissions (29.28%) remain the dominant source, biogenic emissions, initially ranked 6th, emerged as the 2nd largest C-VOC contributor, increasing by 0.41% in IC-PMF. Therefore, traditional PMF underestimates biogenic sources, highlighting the need for refined methods for source apportionment. Our approach distinguishes primary emissions from the reactive portion of VOCs driving secondary pollution. In the third task, the O3 production P(O3) was studied using a zero-dimensional box model for a severe O3 episode (12-15 March, 2016) to determine whether O3 formation in this region is VOC or NOx limited and implemented an updated strategy for VOC emission reduction. A combination of P(O₃) isopleths, VOC/NOx throughout the day, a satellite-retrieved HCHO/NO2 during the O3 episode at midday confirmed MCMA as VOC-limited regime for O3 formation. Unlike previous studies suggesting reduction of liquefied petroleum gas emissions, reductions of traffic emissions prior to 14:00 might be an essential step in lowering in-situ O3 production, as this time is in particular sensitive for VOC induced O3 formation
From Friction to Decarbonation: Unraveling Carbonate Rock Dynamics Under Seismic Velocity
No full textSlip at seismic velocities in carbonate rocks may lead to decarbonation of dolomite, calcite, and siderite due to frictional heating (~600ºC). Key reactions, such as CaCO3 ↔ CaO + CO2, produce carbon dioxide in gaseous or supercritical fluid forms, drastically reducing friction along fault planes and controlling the mechanical behavior of seismogenic faults. This dissertation investigates these thermomechanical processes using microstructural analysis and rock magnetism, with focus on three examples: the Heart Mountain Slide (HMS) in Wyoming (~49 Ma), the Hebgen Lake Fault in Montana and the Venere Fault in the Apennines. The Heart Mountain Slide is the largest terrestrial landslide (~3,500 km²), formed by near-horizontal detachment of Paleozoic-Eocene cover sliding on shallow slopes (<2°). At the White Mountain locality (HMS), frictional heating caused the breakdown of iron sulfides (~250ºC) and carbonates (~400ºC), resulting in magnetite formation in the ultracataclasite and a significant drop in friction. Anisotropy of magnetic susceptibility (AMS) analysis of 274 samples reveals a consistent AMS fabric controlled by magnetite. Thermomagnetic experiments suggest the magnetic fabric began forming around ~250ºC. Interestingly, AMS data indicate a primary slip direction of ~N033°, challenging the previously accepted NNW-SSE movement direction. These findings, validated through 3D shape orientation and micro X-ray scanning, may reflect local synkinematic block rotation or require re-evaluation of large-scale slide dynamics. This work demonstrates the effectiveness of magnetic methods for unraveling deformation processes in carbonate rocks during high-strain-rate events.
Seismic rupture in carbonate rocks influences fault friction behavior through thermal evolution and mineral reactions. Focusing on the 1959 Mw 7.2 Hebgen Lake event in western Yellowstone, Montana, the largest earthquake on a normal fault in the United States, we analyze fault rock microstructures and mineralogical changes to constrain frictional heating on the fault plane. We combine thermal maturity of organic matter, magnetic fabric, and thermomagnetic methods with scanning electron microscopy to unravel variations in peak frictional temperature along the fault slip surface. The mineral changes caused by coseismic heating (e.g., nanocalcite formation or goethite to hematite reaction) occur in patches along the fault mirror, hence reflecting considerable differences in frictional heat. While coseismic thermal heterogeneities have been reported in other rock types, this is the first time they are documented and quantified specifically in carbonates. Furthermore, these results provide new mineralogical criteria to quantify coseismic frictional heat in natural faults at temperatures lower than that of decarbonation and highlight the need to consider coseismic friction processes at a scale larger than most deformation experiments. For example, we document the critical role played by fault plane attitude (dip) at the scale of a few tens of centimeters in production of frictional heat. Our results emphasize that while coseismic decarbonation dynamically weakens carbonate-hosted faults, it may generally not occur along an entire fault plane.
Finally, the Mw 7.0 Avezzano earthquake on January 13, 1915, claimed ~33,000 lives, making it one of the worst disasters in modern Italian history. Ruptures occurred at about 15 km depth along multiple normal faults along the Eastern margin of the Fucino Basin. The main segment, the Venere Fault, cuts carbonate rocks and presents a bedrock fault scarp produced by a prominent surface rupture. This fault scarp strikes NW-SE, dips moderately to the SW, and is well exposed in a quarry. It is a smooth, locally shiny, or powdery surface forming a fault mirror with extensive downdip striations, slickensides, and local reddish iron-oxide stains. The powdered material immediately above and below the mirror comprises a carbonate ultracataclasite. Recent deformation experiments indicate carbonate fault mirrors form through two distinct synkinematic processes: i) intense frictional heating causing decarbonation or ii) runaway grain-size reduction during slip at seismic velocities. In either case, friction drops substantially after some initial displacement, but the first process also leads to fault pressurization and a drastic drop in normal stress along the fault plane. Despite significant advances in the past twenty years in our understanding of seismic deformation in carbonates through deformation experiments, the transition from high-friction / low slip velocity to low-friction / high slip velocity conditions in natural carbonate faults is still not fully understood. We selected the Venere Fault, along which friction at seismic slip velocity is proven, to understand the nature and extent of dynamic weakening processes acting during the 1915 earthquake. More specifically, we investigate if decarbonation along the fault surface was patchy or uniform and if iron oxides on the mirrors preserve evidence for seismic slip. Our investigations take advantage of the high sensitivity of iron oxide assemblages and their magnetic remanence to heating to assess frictional heat. Our main results show that while the fault mirror experienced some frictional heating during the 0.8 m slip event, this displacement was insufficient to reach decarbonation conditions. We constrain the peak coseismic temperature along the fault plane to 400ºC through demagnetization experiments and 1D heat diffusion modeling
Understanding Psychosocial Support for Adult Patients and Survivors of Cancer through a Self-Report Research Design
No full textBackground: Over 1.2 million Americans develop cancer each year, with breast and prostate cancer most prevalent among people assigned female and male at birth, respectively. Reports estimate that 30-60 percent of the cancer population has unmet psychosocial support needs. Studies describe that psychological well-being has a positive effect on cancer treatment and quality of life, but the interplay between psychological distress and psychosocial support is still emerging. Additionally, understanding the impact gender and race have on psychosocial support is an important characteristic for tailoring future interventions. To fully support patients with and survivors of cancer, we biopsychosocial model as a framework, the present study examined the relationship between psychosocial support to depression and anxiety severity scores (psychological distress) among adult cancer populations during the peak of the COVID-19 pandemic through three aims: 1) describe characteristics of psychosocial supports and psychosocial utilization; 2) examine the psychosocial support quantity and quality by gender and race; and 3) investigate the relationship between the quantity and quality of psychosocial supports and psychological distress by gender and race. Methods: Data for this study (N = 143) was drawn from a self-reported, cross-sectional study (PI: Danielle H. Llaneza) conducted among a diverse sample of patients with and survivors of cancer. Questions about sociodemographic variables, psychosocial support quantity and quality, barriers to Form measured the quantity and quality of psychosocial support (predictor variables); the must understand their psychosocial supports and needs. Purpose: With the support, and psychological distress were used. The Social Support Questionnaire-Short Hospital Anxiety and Depression Scale measured psychological distress (dependent variable). Investigator-developed questions measured additional information about psychosocial support and relevant barriers. Descriptive statistics summarized the variables of interest. T-tests determined the relationship between psychosocial supports quantity and quality, race, and gender. Multiple hierarchical linear regressions with gender and race as moderators identified whether psychosocial supports quantity and quality were associated with psychological distress. Results: The study’s population was predominantly White women with breast cancer, who identified as current patients with or survivors of cancer in their 30s. The sample reported moderate levels of depression and anxiety. The results indicated that gender did not moderate the relationship between psychosocial support quantity and depression. However, gender moderated the relationship between depression and psychosocial support quality. Regarding anxiety, gender moderated the relationship between anxiety and psychosocial support quantity. As well, gender moderated the relationship between anxiety and psychosocial support quality. Next, race moderated the relationship between anxiety and psychosocial support quality. Finally, race did not moderate the relationship between anxiety and psychosocial support quantity. Conclusion: Findings represent an important step in understanding the quantity and quality of current psychosocial supports in a sample of the cancer population, and the relationships gender and race have with psychosocial support. Clinicians and researchers should continue to evaluate and enhance psychosocial supports for patients and survivors throughout their cancer treatment to reduce psychological distress
Identifying the Immunostimulatory and Anti-Cancer Properties of Calocybe indica (Edible Milky White Mushroom) for Adjuvant Therapy Applications
No full textCalocybe indica (C. indica) is a commercially grown tropical edible fungus producing nutritionally rich milky white mushrooms. While recent studies have highlighted its therapeutic properties, limited information exists on how its compounds modulate immunity and inhibit cancer progression. This study investigates the immunomodulatory and anti-cancer properties of C. indica revealing its potential as a multi-functional therapeutic agent. Polysaccharide extracts of C. indica (CIP) demonstrated significant in vitro immunomodulatory effects, activating T cells and B cells, increasing plasma cell differentiation and enhancing antibody and cytokine secretion. RNA-seq analysis identified the activation of critical pathways in immune cell revealing the underlying mechanisms of CIP immunomodulatory effects. Structural analysis via sugar composition profiling and size-exclusion chromatography revealed that CIP primarily consists of low-molecular weight α-1,3 glucans, along with α-1,6 glucans, high-molecular-weight α-1,4 glucans, medium-molecular weight β-glucans and α-mannans, all of which are recognized for their bioactivity. In vivo studies in mice demonstrated that CIP exhibited robust adjuvant capabilities by significantly enhancing anti-OVA-specific immune responses. This effect was likely mediated through multiple immune cell types and promotion of B cell differentiation into plasma cells. Metabolomic analysis of C. indica identified a diverse array of metabolites, several of which have putative anti-cancer properties. Ethanol extract of C. Indica (CIEE) inhibited the proliferation of human breast cancer lines (MCF7 and MDA-MB231) in vitro, while sparing C57BL/6J mouse primary spleen cells, indicating selective cytotoxicity. CIEE induced apoptosis in breast cancer cells, accompanied by morphological changes indicative of cell death. RNA-seq analysis further revealed that CIEE activated multiple biological pathways consistent with anti-cancer mechanism including apoptosis and inhibition of proliferation. In summary, C. indica exhibit therapeutic potential: polysaccharides that confer immunostimulatory and adjuvant properties, and metabolites that exert direct tumoricidal effects. Future research aimed at purifying and characterizing its key bioactive molecules could lead to the development of novel therapeutics, offering potential for clinical trials and cost-effective treatment options
Temporal Variations of Saturn’s Radiant Energy Budget and Zonal Winds
No full textThis dissertation's primary objectives are to investigate the temporal variations of Saturn's radiant energy budget and zonal winds using data collected by the spacecraft Cassini from 2004 to 2017. Various instruments on board the Cassini spacecraft, including the Composite Infrared Spectrometer (CIRS), Imaging Science Subsystem (ISS), and Visual and Infrared Mapping Spectrometer (VIMS), are utilized for this study.
Studying Saturn’s radiant energy budget (REB) can help us better understand Saturn’s evolution and climate behaviors. Based on the Cassini long-term multi-instrument observations, we provide the seasonal variation of Saturn’s energy budget for the first time. The new measurements not only help us to precisely determine some important parameters related to REB (e.g., Bond albedo = 0.41 ± 0.02) but also help us refine the internal heat (2.84±0.20 Wm-2). The new measurements significantly update previous estimates. More importantly, our measurements first reveal the energy imbalance of the energy budget at the seasonal scale, which has fluctuations with a magnitude of 16.0±4.2%. Therefore, current theories and models of Saturn should be revisited with this imbalance. Additionally, considering the seasonal variation of radiant energy components can help us re-examine the internal heat of other giant planets in our solar system, which is crucial to understanding planetary formation and evolution, both within and beyond our solar system.
The long-term multi-instrument observations not only help us better understand Saturn’s REB but also provide important information on its large-scale circulation, such as zonal winds. Our analysis of Cassini data reveals the global structure of zonal winds in Saturn’s upper troposphere (50–500 mbar). The zonal winds from 10°S to 10°N initially decrease with altitude and then increase. Zonal winds also are used to examine atmospheric stability. There are some unstable regions, which may have contributed to the development of the giant convective storm in 2010. Finally, the analysis of Cassini multi-instrument observations reveals different temporal behaviors of zonal winds in the vertical direction, which suggests that seasonally varying solar flux is one of the drivers of temporal variations in zonal winds
Baroque Meets Jazz: An Analysis Of Nikolai Kapustin’s Suite In The Old Style, Op. 28
No full textLike the bulk of Nikolai Kapustin’s compositions, his Suite in the Old Style, op. 28 for piano, represents a remarkable fusion of Baroque forms and jazz idioms. Composed in 1977, this suite marked Kapustin’s return to serious solo piano writing after a long break since his student years. The significance of this composition is further highlighted by Kapustin’s decision to record it on his second vinyl disc, Jazz Pieces for Piano, released in 1987. Over the years, interest in Kapustin’s music has increased dramatically, especially since the turn of the century. In addition to many performances of his music, there have been no fewer than fifteen theses devoted to his work, including Jonathan Edward Mann’s, “Red, White, and Blue Notes: The Symbiotic Music of Nikolai Kapustin” (2007), and Randall J. Creighton’s “A Man of Two Worlds: Classical and Jazz Influences in Nikolai Kapustin’s Twenty-Four Preludes, op. 53” (2009). Overshadowed especially by some of his other compositions, such as the Eight Concert Etudes, op. 40, and Twenty-Four Preludes in Jazz Style, op. 53, the Suite in the Old Style has not received the attention it deserves, either from scholars or performers. This essay accordingly attempts to address this lacuna by analyzing the music’s style and structure, comparing the piece to a Bach French Suite, and providing information related to performance practice and reception history
Nephroprotective Strategies to Attenuate Antibiotic-Associated Acute Kidney Injury
No full textInfections caused by multidrug-resistant (MDR) bacteria are increasing, presenting a major threat to global public health. Resistance to first-line antibiotics, such as carbapenems, is widespread and has rendered them ineffective treatment options. Glycopeptides, aminoglycosides, and polymyxins are three classes of antibiotics that have generally maintained in vitro activity against drug resistant bacteria. Unfortunately, the clinical usage of these antibiotics is hindered by dose-limiting nephrotoxicity. Attenuation of nephrotoxicity could allow the optimal clinical use of these antibiotics to treat difficult infections and provide timely solutions to the MDR bacteria crisis. The mechanism of antibiotic nephrotoxicity is well understood to involve accumulation in the kidney, subsequent oxidative stress, and renal cell death. Despite this, effective therapeutic strategies to interfere in antibiotic nephrotoxicity and reduce renal injury are less well understood.
Therefore, this project aimed to investigate various nephroprotective strategies (e.g., megalin inhibition, mitochondrial protection, antioxidant) and identify renal protective adjuvant compounds. To accomplish this, robust assays for the quantification of antibiotics and renal protectants were developed, in vitro studies were used to provide insights into renal cell protection, and in vivo studies were used to evaluate the renal protective efficacy/safety of the promising adjuvant, zileuton.
For the quantification assays, liquid chromatography tandem mass spectrometry (LCMS) assays were developed and validated for vancomycin and zileuton. These assays were used to assess renal cell accumulation of vancomycin and evaluate the serum/renal tissue pharmacokinetics of vancomycin/zileuton in rats. Renal cell protection against antibiotic nephrotoxicity was evaluated in vitro using imaging, molecular biology, and biochemical approaches. The efficacy of the most promising renal protective compound, zileuton, was assessed using a clinically relevant animal model. Clinical relevancy was established with pharmacokinetic studies demonstrating comparable antibiotic systemic exposure in animals and humans. Zileuton was found to reduce antibiotic-associated nephrotoxicity and was formulated for parenteral administration using a ternary cosolvent system. Zileuton stability, multidose safety, and pharmacokinetics were evaluated using this formulation.
Additional research is needed to fully understand the mechanism(s) of renal protection associated with zileuton. This would be an important finding to provide more effective and safe therapeutic options for combatting the MDR bacteria crisis
Conduct a Comprehensive Analysis of Internet User Data to Identify Patterns of Malicious Traffic Over an Extended Period of Time
No full textThe increasing prevalence of malicious activity over the Internet traffic at presently a growing challenge for ensuring secure and reliable services for the operators and business entities. This thesis presents a comprehensive analysis of recent Internet users data to identify patterns of malicious traffic over an extended period of time. The primary objective of this research is to design and develop a robust system which is capable of identifying both known and emerging threats in real-time through NetFlow traffic with a limited number of fields. The system utilizes advanced machine learning models to detect both known attacks and unknown threats, which offers a comprehensive protection against a wide range of internet data. In this approach, known threats are addressed through supervised models, while unsupervised models use to identify new attack patterns that does not have prior labels. By integrating both supervised and unsupervised learning techniques, the system is able to adapt to the constantly evolving threats. The second objective of this research is to provide an analogy for how attack vectors occurs over time, particularly for Internet users who primarily access the traffic via mobile devices over broadband networks. This analogy will help service providers, businesses, and even government entities to recognize threat patterns over time. This will enable proactive measures and more effective initiatives to counter these threats. For the supervised learning models XGBoost, CatBoost, and LightGBM are considered due to their proven effectiveness in structured data analysis \cite{odeh2023comparative} and the availability of labeled datasets. These models are designed to separate traffic data based on predefined labels, identifying patterns associated with malicious behavior. On the other hand, the presence of novel attacks that are not represented in training data necessitates the use of unsupervised models. Techniques such as K-Means clustering, Local Outlier Factor (LOF), and Isolation Forest are used to detect anomalous patterns and outliers in traffic that do not correspond to typical malicious attach, making them ideal for uncovering new and unknown attack. However, we consider K-Means as a final model as result shows the highest accuracy. The findings shows that integrating supervised and unsupervised learning models improves the capacity to identify malicious traffic in a variety of contexts, ranging from known attack patterns to new, undiscovered threats. This research not only contributes to the development of advanced security systems but also shows the path for future work in the field of anomaly detection and recent pattern on Internet traffic using machine learning techniques. By providing a holistic approach to malicious traffic detection and identifying the pattern in different time this thesis aims to improve the overall security posture of Internet services, enabling timely responses to emerging threats and ensuring a safer digital environment for users
Reliability-Aware Design of Flexible Hybrid Electronics
No full textFlexible Hybrid Electronics (FHE) integrates the flexibility of soft substrates along with conventional semiconductor devices to enable a wide spectrum of innovative solutions in areas like healthcare and defense. The popularity of FHE is evident from the NextFlex consortium, which includes various industry partners and the US Department of Defense. Despite the high interest, the reliability of FHE circuits remains a concern, which limits its widespread adoption. More specifically, FHE devices are susceptible to mechanical stress (due to bending/stretching). Repeated application of stress (e.g., due to multiple bending), can lead to cracks, delaminations, which can result in an unreliable device. Prior research has tried to address this problem by finding new materials and fabrication methods that result in higher reliability. However, optimizing system level design to reduce stress has remained relatively unexplored. In this work, we propose an automated system-level design space exploration method that -based on experimental results- finds FHE designs that experience less stress, despite that the same amount of force is applied