Virginia Tech - Wake Forest University School of Biomedical Engineering & Sciences
VTech Works (Virginia Tech)Not a member yet
122049 research outputs found
Sort by
UAV-Enabled Wireless Communications: Deployment, Optimization, and Analysis
No full textUnmanned aerial vehicles (UAVs), known as drones, are a promising solution, as aerial base stations (BSs) or relays, in wireless communications systems. Due to their high likelihood of line-of-sight (LoS) links and ease of deployment, they play a crucial role in providing faster and better wireless network access and service where extra network resources are needed short term, like sports events, or to those emerging services that require high-capacity communications. Moreover, they can help extend wireless coverage to locations deprived of end-to-end wireless communications services in remote/rural areas due to natural disasters or being distant from the conventional terrestrial BSs. However, utilizing this new technology comes with its own novel challenges. In this dissertation, we focus on unprecedented challenges in UAV communications and networks, considering some unique features of UAV networks, such as their optimal placement and wireless backhaul links.
First, we focus on provisioning wireless coverage to those emerging services, like extended reality, demanding high-capacity communications. High frequencies, i.e., millimeter-wave (mmWave) and, terahertz frequency bands offer the substantial bandwidth required for such services. These high-frequency communications, however, depend critically on maintaining LoS connections to user terminals. In practical scenarios, users distributed in three-dimensional space often experience severely limited visibility due to environmental obstructions like buildings and foliage. We study the problem of finding an optimal 3D placement and antenna orientation for mmWave-equipped UAVs to minimize the number of required UAVs while maximizing the signal-to-noise ratios (SNRs) to all users. Our approach formulates this as an integer linear programming (ILP) optimization problem, establishes its computational intractability (NP-hardness), and develops a computationally efficient geometric algorithm that consistently achieves near-complete LoS coverage across diverse simulation scenarios.
Our second research thrust targets wireless connectivity in remote rural environments—such as agricultural Internet of Things (IoT) deployments—where conventional terrestrial infrastructure is limited or absent. A fundamental challenge in such UAV-assisted networks is determining the minimal UAV deployment that simultaneously achieves two objectives: complete ground user coverage and reliable wireless backhaul connectivity linking all UAVs to terrestrial BSs. We formulate this joint optimization—termed the Backhaul-and-coverage-aware Drone Deployment (BoaRD) problem—as an ILP problem and prove its NP-hardness. Our solution approach employs a graph-theoretic algorithm that efficiently solves the problem with provable performance bounds. Comparative analysis using ILP solvers demonstrates that our algorithm achieves near-optimal performance for smaller problem instances. For large-scale scenarios with extensive coverage areas and numerous users, comprehensive simulations show our algorithm substantially outperforms baseline algorithms while guaranteeing complete user coverage and end-to-end connectivity.
Finally, building upon these deployment optimization contributions, our third research thrust develops a comprehensive analytical framework for multi-hop UAV-assisted cellular networks. While the previous work provides deterministic algorithms for specific deployments, understanding system-wide performance requires statistical modeling of networks with random spatial distributions. We develop a comprehensive stochastic geometry framework for analyzing multi-hop UAV-assisted cellular networks that addresses fundamental gaps in existing analytical approaches. Traditional stochastic geometry techniques for terrestrial networks are insufficient for characterizing the complex 3D spatial relationships, interference patterns, and unique propagation characteristics inherent in multi-hop UAV deployments. We extend existing mathematical frameworks to accommodate the distinctive features of aerial networks, including realistic 3D spatial distributions of UAVs across multiple operational altitudes, probabilistic air-to-ground channel models that distinguish between LoS and NLoS conditions, and the intricate interference correlations that arise in multi-hop communication paths. Our framework derives novel mathematical constructs and probability distributions that enable precise characterization of multi-hop network behavior under random spatial deployments in the 3D space. We provide comprehensive closed-form expressions for coverage probability analysis covering both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols, accounting for the hybrid communication scheme where UEs can connect either directly to serving BSs or through the multi-hop UAV network based on received signal quality. Additionally, we introduce optimal relay selection strategies that maximize end-to-end SINR by jointly considering all link qualities in the formed multi-UAV network and accounting for the complex interdependencies between sequential links in the presence of interference. Through extensive theoretical analysis and simulation validation, our results demonstrate that well-designed multi-hop UAV networks can significantly enhance coverage probability and network reliability compared to single-hop architectures, particularly in challenging environments where direct links between UAVs and terrestrial BSs are weak or unavailable due to distance or environmental obstructions.Doctor of PhilosophyAs wireless communication demands continue to grow, drone-based networks are emerging as a powerful solution to extend cellular coverage and provide high-speed internet access in areas where traditional cell towers are impractical or unavailable. This dissertation addresses three critical challenges in deploying effective drone communication networks.
The first challenge involves positioning drones equipped with high-frequency millimeter-wave antennas, which can provide extremely fast internet speeds but require precise line-of-sight connections to users. We developed algorithms that determine the optimal 3D placement and antenna orientation for these drones, ensuring reliable coverage even when users have limited visibility due to surrounding buildings, trees, or other obstacles. Our approach guarantees connectivity to nearly 100% of users in various scenarios, significantly outperforming traditional methods.
The second challenge focuses on designing efficient multi-drone networks that minimize costs while ensuring complete coverage. When deploying multiple drones to serve a large area, each drone must not only cover ground users but also maintain wireless connections to other drones, creating a "backhaul" network that connects to existing cellular infrastructure. We formulated this as an optimization problem and developed a practical algorithm that reduces the number of required drones by up to 95% compared to random deployment strategies, while guaranteeing both user coverage and drone-to-drone connectivity.
The third challenge involves creating mathematical models to analyze and predict the performance of complex multi-hop drone networks, where data may travel through several drones before reaching its destination. Traditional network analysis methods, designed for ground-based systems, are inadequate for three-dimensional drone deployments. We developed a comprehensive analytical framework using advanced mathematical techniques that accounts for the unique characteristics of aerial networks, including 3D spatial distributions, air-to-ground communication channels, and interference between multiple communication paths. This framework enables network designers to evaluate different deployment strategies and optimize system performance before actual implementation.
Together, these contributions provide a complete foundation for designing, deploying, and analyzing drone-assisted cellular networks. The research has practical applications in emergency response scenarios, rural connectivity initiatives, temporary event coverage, and next-generation wireless systems. By addressing challenges from individual drone placement to network-wide optimization and theoretical modeling, this work advances the integration of drone technology into modern communication infrastructure, potentially bringing high-speed wireless access to underserved areas and improving network resilience in challenging environments
Sustainability
No full textA two-parameter environmental (measured in CO2eq—CO2 is used in this paper to represent the carbon dioxide molecule as opposed to the chemical formula CO2 as is common practice in LCA studies; CO2eq is an abbreviation for CO2 equivalent and may be written as CO2e in the literature) and economic (measured in USD) analysis using life cycle analysis (LCA) and techno-economic analysis (TEA) of repurposed wind turbine blades for structural use in recreational trail bridges (e.g., on hiking trails and golf courses) is described in this paper. The US Department of Energy’s TECHTEST TEA/LCA software (v1.0) platform was used to compare three commercially available trail bridges (a steel truss bridge, an FRP pultruded truss bridge, and a glulam stringer bridge) with a bridge made from retired wind turbine blades (known as a BladeBridge). All bridges had a 50 ft (15.24 m) long by 6 ft (1.83 m) wide deck and were designed for a 90 psf (4.3 kN/m2) live load. The LCA functional unit was the assembled bridge, which was made ready to be shipped from the fabricator. Cradle-to-gate (A1–A3, i.e., raw material extraction, transportation, and manufacturing) system boundaries were used. For the BladeBridge, no embodied carbon was attributed to the blade itself (cut-off system allocation). For the TEA, a USD 660/tonne credit was attributed to the blade. The raw materials for each bridge were determined from detailed construction documents. Manufacturing and transportation energy were determined based on the equipment used for fabrication and geographical location. Direct labor for fabrication was calculated based on a weighted average of salaries taken from the US Bureau of Labor Statistics. The results indicate that raw materials had the biggest effect on embodied CO2eq and that labor had the largest impact on cost for all bridges. The results indicate that the BladeBridge is significantly less expensive to produce and releases less CO2eq into the environment (less Global Warming Potential (GWP)) than the three commercially available bridges. Additional TEA metrics for the BladeBridge, including Technology Readiness Level (TRL) and future market potential, were also evaluated and found to be positive for the BladeBridge technology.Published versio
Sustainable Timber Supply Chain Optimization
No full textThe U.S. timber supply chain faces mounting challenges related to capacity constraints, sustainability, and supply resilience at a time when federal policy calls for a rapid expansion of domestic timber production. Following the March 2025 executive order to reduce reliance on foreign timber imports, achieving near-term production targets requires a nationwide redesign of supply chain infrastructure under significant data and operational uncertainty. This study develops a data-driven optimization framework to support short-term, actionable planning for the U.S. timber supply chain. We propose a hybrid machine learning–mixed-integer linear programming (ML–MILP) model that captures the flow of timber from mills through distribution centers to demand points, with the objective of minimizing total transportation and facility-opening costs. U.S.–wide implementation is complicated by incomplete and fragmented data, particularly for mill counts, production levels, and facility locations. To address these gaps, we leverage machine learning models, including gradient boosting, ridge regression, and weighted K-Means clustering, to reconstruct a comprehensive national dataset and generate candidate distribution center locations informed by socioeconomic and environmental factors. The resulting MILP generates an infrastructure and flow plan and is evaluated through sensitivity and scenario-based analyses reflecting demand growth, transportation disruptions, and disaster impacts. Results highlight the dominant role of transportation costs, diminishing returns to capacity expansion, and heightened vulnerability in the South and West regions. Overall, the proposed framework provides policymakers and industry stakeholders with a scalable, sustainability-oriented decision-support tool for guiding domestic timber supply chain expansion under evolving policy objectives.Submitted versionYes, full paper (Peer reviewed?
Developing C–H bond Functionalization, Organocatalytic Hydrophosphination Reactions and Anti-Invasion Agents
No full textIn chapters 1-3, we will discuss the development of iron alkoxide complexes for C–H bond functionalization. Currently, methods for C–H bond functionalization rely on precious metal catalysts that present environmental and health concerns. Earth abundant metals have been explored as sustainable catalysts; however, these systems are difficult to develop because of their distinct chemical properties and reactivity patterns compared to 4d and 5d metals. Several reported monometallic iron imido MLMB species capable of nitrene group transfer do so by accessing high-spin states, although their instability limits their applications. Bimetallic species were proposed to improve stability, but these complexes are difficult to synthesize and appeared to be unreactive. Herein, we disclose the Lewis base enhanced C–H bond functionalization mediated by a diiron alkoxide species. Alkoxide ligands were employed to synthesize high-spin bimetallic species due to their weak field and π-donor character, and substituted pyridines were utilized as a handle for nuclearity and reactivity control. Sterically encumbered pyridines allowed access to asymmetric bimetallic complexes (2.5a and 2.6a) and electron rich pyridines resulted in the monometallic analogs (2.2a-2.4a). Electron withdrawing p-trifluoromethylpyridine selectively accessed both the asymmetric dinuclear and mononuclear species indicative of electronic and steric controls. Diiron imido species were isolated with and without pyridine via nitrene capture with aryl azides (3.2a, 3.2b, 3.6a, and 3.6b) and demonstrated Lewis based enhanced toluene amination through a bimetallic pathway.
In chapter 5, we will discuss the phosphine-catalyzed regio- and stereoselective hydrophosphination of 1,3-diynes. Diynes are important scaffolds for synthesizing π-conjugated organic frameworks for applications in organic synthesis and materials. The selective functionalization of diynes allows researchers to control the chemical properties of highly conjugated compounds for applications in optic and data storage devices. Phosphines have been shown to enhance the photochemical properties of unsaturated frameworks because of their unique metal-like properties; however, the hydrophosphination of 1,3-diynes is scarcely reported and requires the use of precious metals, alkali metals, or prefunctionalized materials. In this dissertation, we describe a facile method to access previously unreported (E)-(1,4-diphenylbut-1-en-3-yn-2-yl)diphenylphosphanes via the organocatalytic hydrophosphination of 1,4-diphenylbuta-1,3-diynes. The reaction employs catalytic n-tributylphosphine, has a mild substrate scope, and proceeds in a regio- and stereoselective fashion.
In chapter 4, we will discuss the development of small molecule anti-invasion agents for the treatment of metastatic cancer. Metastasis remains the leading cause of anti-cancer treatment therapy and cancer-related death. The rapid spread and mutation of the cancerous cells complicates treatment and increases the chance of recurrence. Treatment options are limited because most anti-cancer agents inhibit tumor growth or cause apoptosis, but do not inhibit cancer spread, which is imperative for treating metastatic cancer. Recently, small molecule PDZ1i displayed anti-invasion activity and showed improved survival in multiple in vivo metastatic cancer mouse models. Inspired by PDZ1i, we conducted a structure activity relationship study of related small molecules with the aim of improving anti-invasion activity. Herein, we report a focused library of substituted 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives inspired by the anti-invasion and anti-metastatic agent, PDZ1i. Our studies revealed that 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives bearing 6-trifluoromethyl (4.3y) and 6-bromo (4.3aa) substituents display anti-invasion activity comparable to PDZ1i. The reported 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives serve as promising starting points for future investigations of small molecule anti-invasion agents with potential to prevent and treat metastatic cancers.Doctor of PhilosophyDesigning methods to selectively introduce non-carbon atoms into carbon frameworks is important for organic synthesis. First row transition metal complexes are desirable as sustainable catalysts for these transformations. There are numerous reports of monometallic iron MLMB complexes capable of this reactivity. However, none has progressed to commercial use because of stability issues. Bimetallic complexes have been proposed as an alternative due to their enhanced stability. Based on previous trends, we hypothesized that iron-alkoxide catalysts will access high spin states, dimerize, and facilitate C–H bond functionalization. Herein, we report the synthesis and characterization of iron alkoxide complexes and investigate the effects of Lewis bases on their chemical properties and reactivity.
Unsaturated carbon bonds are often used as a scaffold for the synthesis of complex electron rich compounds. These molecules have important roles in material design and incorporating heteroatoms allows researchers to tune the properties of these materials. Phosphine groups are desirable because they have demonstrated metal-like behavior that enhance optical properties. In this dissertation, we describe the phosphine-catalyzed selective hydrophosphination of 1,3-diynes to access previously unreported (E)-(1,4-diphenylbut-1-en-3-yn-2-yl)diphenylphosphanes.
Metastasis is defined as the spread of cancerous cells throughout the body. Progression to this stage is responsible for 90% of all cancer-related deaths. Anti-invasion agents are compounds that inhibit the spread of metastases; however, there are no FDA-approved anti-invasive agents for the treatment of metastatic cancers. Recently, a novel small molecule anti-invasion agent (PDZ1i) that demonstrated good activity in in vivo mouse models was reported. Herein, we discuss the structure-activity relationship of 1-(benzo[d]thiazol-2-yl)-3-phenylurea derivatives as anti-invasion agents inspired by the structure of PDZ1i
Organic Letters
No full textAccessing complex α,β-dehydroamino acids remains challenging due to the instability of the enamine product during N-terminal deprotection. We report a mild, organocatalytic method for the installation of primary amides on the α-carbon of alkynoates that avoids N-terminal deprotection. The PBu3 catalyst is key to umpolung reactivity and affords α,β-dehydroamino acids in good yield with excellent (Z)-selectivity. The utility of this reaction was demonstrated in the synthesis of two natural products: a 2,5-diketopiperazine and scutianene M.Published versio
Analysis of Trace Gas Heterogeneity using In-Situ and Remote Sensing Measurement Techniques
No full textDifferential Optical Absorption Spectroscopy (DOAS) is a remote sensing spectroscopic technique capable of retrieving vertical column densities of trace gases in the atmosphere. While the technique can be used to retrieve vertical profiles of trace gases this retrieval is not applicable to Mobile-DOAS measurements due to the lengthy measurement times. In addition, the requirement for rapid measurements for Mobile-DOAS application prevents a single instrument from retrieving information about the horizontal trace gas distributions around the instrument, in addition to the lack of vertical distribution information. However, with the addition of collocated in-situ measurements of surface concentration, as well as the use of Multi Axis DOAS (MAX-DOAS) measurements taken from multiple azimuth viewing directions, it is possible to estimate these distributions using a minimal amount of measurements, allowing this gap in mobile DOAS measurements to be filled.
The relationship between the vertical column density measured by Mobile Zenith-DOAS and in-situ surface concentration is first explored using measurements made during the first TRACER-AQ field campaign. This relationship, expressed as the column to surface ratio, is then used to identify trace gas plumes and other transport patterns that can be separated from local, vehicular emission based on this ratio during two case days, in order to determine the origin of the high Ozone event that was observed on both days. In addition, the effect of the trace gas vertical distribution on satellite-based DOAS measurements is also determined, where it is found that the column to surface ratio is proportional to worsening agreement between Mobile Zenith-DOAS and TROPOMI Satellite-Based DOAS, however the relationship is only somewhat correlated (r2=0.3), indicating that other factors are a greater influence on the ability of Ground-Based DOAS and Satellite-Based DOAS to agree.
During the second TRACER-AQ field campaign, the column to surface ratio was combined with analysis of MAX-DOAS measurements in order to determine both the vertical and horizontal distributions of trace gas around the instruments. This analysis of the horizontal distribution is expressed with the Horizontal Heterogeneity Index, which is a comparison between two MAX-DOAS azimuth viewing directions, behind and to the right of the moving vehicle, with the Zenith DOAS measurements each MAX-DOAS instrument is making. The analysis of both distributions is then used to pinpoint the potential sources giving rise to two more high Ozone events during two more case days during the second field campaign. In addition, the horizontal trace gas distribution was also compared to TROPOMI validation, and was found to correlate more strongly than the vertical distribution (r2=0.69), showing that while there are many issues with satellite validation, the horizontal distribution is most likely responsible for deviations between Ground-Based and Satellite-Based DOAS measurements.
Finally, analysis of trace gas distributions requires low uncertainty retrievals of Zenith DOAS VCD's. This is typically performed using radiative transfer simulations, but which require information of the aerosol scattering properties that are not retrievable from a mobile platform. In order to perform these simulations, a novel technique of averaging the aerosol conditions as measured by a network of six AERONET aerosol measuring instruments was investigated through a series of sensitivity studies. These studies analyzed the effect of potential errors in the aerosol properties on the resulting Air Mass Factor estimations, in order to determine how these errors effect Air Mass Factor uncertainty. The studies showed that the total error introduced into the model through potential errors in aerosol properties, as well as through errors in the assumption of an a priori trace gas profile used to retrieve the Air Mass Factors, was less than 20% for AMF retrievals in Visible light and 25% for UV retrievals, approximately the same level of uncertainty used for Zenith AMF retrievals in other studies, demonstrating that this averaging technique is capable of retrieving sufficiently low uncertainty AMF estimations.Doctor of PhilosophyDifferential Optical Absorption Spectroscopy (DOAS) is a remote sensing technique capable of measuring trace gas amounts in the atmosphere. However, DOAS measurements taken onboard vehicles have remained limited in scope due to the limited amount of time Mobile DOAS instruments spend in a measurement area. In order to expand the applications of Mobile DOAS, this dissertation combines Multi-Axis DOAS (MAX-DOAS) measurements with Zenith DOAS, or DOAS measurements taken directly vertical, with in-situ measurements of surface concentrations to analyze both the horizontal and vertical distributions of trace gases around the instruments. While this technique does not provide as much information as similar techniques for stationary DOAS instruments, the technique is used to analyze the sources contributing to multiple high Ozone events observed in Houston, Texas during the Tracking Aerosol Convection Experiment-Air Quality (TRACER-AQ) field campaigns held during 2021 and 2022. In addition, the effect of the vertical and horizontal trace gas distributions on Satellite-Based DOAS instruments is evaluated, in order to determine if the trace gas distribution is contributing to errors in Satellite-Based DOAS validation. Finally, due to the need for low uncertainty Zenith DOAS Vertical Column Densities, a novel technique of estimating Air Mass Factors radiative transfer simulations based on the mean aerosol conditions observed by six Aerosol Robotic Network (AERONET) is explored with a series of sensitivity studies. These studies isolate each potential source of error due to uncertain radiative transfer inputs, and are used to both determine how much uncertainty is introduced into the Air Mass Factor estimation due to errors in the aerosol properties, as well as prove that these uncertainties are sufficiently small that the estimated aerosol properties are valid inputs
BMC Research Notes
No full textObjective: Sub-Saharan Africa produces less than 4% of global scientific output, despite significant health and development challenges. This study evaluated the effectiveness of a pilot scientific writing workshop in Cameroon aimed at building writing skills and publication readiness of early career researchers. We conducted two workshops’ sessions in Yaoundé, Cameroon, in April and November 2023. A mixed-methods approach was used. Quantitative data were obtained via pre- and post-workshop questionnaires designed to capture participants’ self-assessed knowledge, skills, and confidence related to the workshop content. Qualitative data were gathered through in-depth interviews. Descriptive and inferential statistics were applied to the survey data, and thematic content analysis was used to assess qualitative responses.
Results: A total of 86 participants completed both the pre- and post-workshop surveys (response rate: 86.9%). The majority had never published scientific papers (62.8%) nor had they received formal writing training (61.6%). The quantitative results showed statistically significant improvements in participants’ overall understanding of scientific writing and publishing (mean difference = 0.93, p < 0.001) and confidence regarding writing skills (mean difference = 0.94, p < 0.001). Thematic analysis of the interviews revealed high satisfaction with the learning environment, perceived knowledge gains, and a strong demand for mentorship and sustained training opportunities.
Highlights: Most of the participants (61.6%) had never completed a scientific writing or publication course. Almost two thirds (62.8%) had never published a scientific paper before. Participants reported increased knowledge, skills and confidence in scientific communication. Junior researchers in Africa seek consistent mentorship and training opportunities.Published versio
Frontiers of Urban and Rural Planning
No full textAs cities evolve in increasingly complex ways, urban planners and researchers are focusing on creating long term and stable visions that are location-specific, sustainable, and inclusive. This visioning process often results in a fundamental question: Is there an underlying urban DNA, a foundational structure that shapes how urban areas grow, adapt, and transform? The idea of urban DNA, first articulated in the early 2000s, has gained renewed prominence since 2020, particularly in post-pandemic recovery strategies that emphasize local identity and place branding. Unlike the concept of urban identity and urban traits, which reflect external dynamics observable in a city and its performance, the concept of urban DNA focuses on the internal structures and mechanisms that shape urban identity, providing sustainable solutions over temporary remedies. Although numerous scholars have introduced conceptual frameworks for urban DNA, and many policy documents highlight cities’ interpretations of their distinctive urban DNA, these applications often lack a strong theoretical grounding. This limitation underscores the need for a more rigorous theoretical foundation that can both substantiate the concept of urban DNA and explain the sequence of urban evolutionary events, framing it as a structured process rather than a set of randomized events. This research develops the concept of urban DNA by identifying the core elements that constitute the genetic building blocks of cities and shape their emergence and evolution. Five interrelated elements, urban uniqueness, temporal variation, spatial variation, growth, and stability, form the basis of this framework. To ground these elements theoretically, 17 urban evolutionary theories were systematically assessed through a relevance matrix, comparing their conceptual alignment, explanatory power, and practical applicability to the urban DNA construct. The analysis highlights urban niche theory and French regulatory theory as particularly relevant for explaining urban DNA. Based on these insights, a grounded theoretical framework is proposed that offers urban planners and policymakers an operational tool to identify and leverage the urban DNA of their respective cities.Published versio
Scientific Reports
No full textThe Chesapeake Bay region (defined as longitudes − 78° to -74° and latitudes 36.5° to 40°) experiences the highest rates of relative sea-level rise (RSLR) on the Atlantic Coast. Regional land subsidence influences RSLR, however quantified rates of vertical land motions (VLM) are inconsistent in published solutions. For 5 years from 2019 to 2023, new Global Navigation Satellite System (GNSS) campaign data were collected at over 60 sites across the Chesapeake Bay region annually. These data were processed and combined with continuous GNSS data (120 stations) from the region covering the same time-period using GAMIT-GLOBK to produce 3D velocities and their associated uncertainties. We use the Robust Network Imaging algorithm to interpolate GNSS-derived VLM to produce a new regional VLM solution of the Chesapeake Bay region. We find that land subsidence is ubiquitous throughout the region with rates varying from − 2.97 to -0.40 mm/yr. In major cities across the Chesapeake Bay region, VLM rates are − 1.1 ± 1.6 mm/yr (1-sigma) for Washington DC, -0.8 ± 1.4 mm/yr for Baltimore, MD, -2.4 ± 0.5 mm/yr for Ocean City, MD, and − 2.3 ± 1.0 mm/yr for Hampton, VA. When we compare our VLM rates with a geodetic-based solution from 1974, we observe meaningful shifts in the locations and rates of maximum subsidence. The results of this work underscore that regular monitoring of VLM and can be used to improve projections of relative sea-level changes as well as the associated coastal hazards for communities in the Chesapeake Bay region.Published versio
Biomedicines
No full textHypertension has been traditionally known to be highlighted by mean blood pressure; however, emerging evidence exhibits that blood pressure variability (BPV), including short-term, day-to-day, and visit-to-visit fluctuations can have an implication across multiple body systems. Elevated BPV reflects repetitive hemodynamic stress, affecting the physiologic hemostasis contributing to vascular injury and end organ damage. This narrative review is a compilation of recent evidence on the prognostic value of BPV, explained by pathophysiology, various devices with its measurement approaches, and, essentially, the clinical implication of BPV and the use of such devices utilizing artificial intelligence. A comprehensive literature search across PubMed, Cochrane Library, Scopus, and Web of Science were conducted, focusing on observational studies, cohorts, randomized trials, and meta-analyses. Higher BPV has been associated with an increased risk of cardiovascular mortality, stroke, coronary events, and heart failure, the progression of chronic kidney disease, cognitive decline, and preeclampsia, among other end organ damage, despite mean blood pressure. The various pathophysiologic mechanisms include autonomic dysregulation, arterial stiffness, endothelial dysfunction, circadian rhythm alteration, and systemic inflammation, which result in vascular remodeling and multisystem damage. Antihypertensive medications such as calcium channel blockers and renin–angiotensin–aldosterone system inhibitors seem to reduce BPV; randomized trials have not specifically investigated their BPV-reducing effects. The aim of this review is to highlight that BPV is a dynamic marker of multisystem risk, and question how various AI-based devices can aid continuous BPV monitoring and patient specific risk stratification.Published versio