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Long-Range Water Municipality Planning in the Face of Climate Change in Oklahoma and Texas
Get PDFThe climate is warming as anthropogenic climate change continues to alter the planet and its atmosphere. Water infrastructure is a part of the human-built environment, and this system deals with disasters due to its construction. These disasters are inevitable, especially as the planet changes. The only way to deal with this chaos is through adaptation and mitigation strategies. In the water industry, these adaptations often fall on individual municipalities, as larger-scale change only happens through repeated and consistent large-scale actions. Due to the stressed environment of water workforces in the United States, specifically at the single-municipality level, adaptation efforts can be troublesome. Research efforts to promote adaptation at a more efficient level, meaning the water industry is using and providing water to its fullest extent with minimal losses, can lend assistance in the water realm in the U.S. This research project does so through a survey of water managers in Oklahoma and Texas, a region generally known as the Southern Plains, to analyze how climate change, infrastructure, and department obstacles are felt modernly. By uncovering what water managers go through on a day-to-day basis, this will help better shape policy and adaptation efforts to prepare future generations for a water-scarce environment. Major findings of this project show that most of the surveyed managers believe water is an underpriced resource, many utilities experience a myriad of vulnerabilities as the climate changes, and the majority of respondents do not incorporate climate data in their current long-range plans. Further findings illustrate that water sector workforce and pressure add hindrances to adaptation. In general, this project solidifies that many water systems in the U.S. need investment and organization to adapt. Future research should highlight the need for climatic data information in water municipality risk planning and continue to assess the water manager’s perspective, but also the point of view of the consumer
Evolution of Biomass Burning Aerosol Properties During Transport in the Southeast Atlantic Region
Get PDFBiomass burning (BB) is a major source of absorbing aerosols globally and accounts for about 40% of black carbon in the atmosphere. The Southern African region contributes approximately 35% of the planet’s BB aerosol emissions. During the austral winter and spring, smoke is transported westward towards the southeast Atlantic Ocean, where it overlies and interacts with a quasi-permanent stratocumulus (Sc) cloud deck. Aerosol-cloud-climate interactions contribute the largest uncertainty to model estimates of anthropogenic forcing. The SEA region thus exhibits a large model-to-model divergence of climate forcing due to aerosols. This makes studies in the region particularly valuable for understanding these interactions. Previous studies focusing on Southern Africa BB have explored the distribution of aerosol loading. However, changes in aerosol optical properties during transport are not well documented.
This study aims to use remotely sensed observations to investigate the evolution of BB aerosol optical properties after emission within continental Africa, during transport over land, and over the Atlantic Ocean. Measurements taken from a collection of remote-sensing instruments during the ORACLES campaign are combined with results from two regional models, the WRF-AAM and WRF-CAM5, to explore the changes in the optical properties of smoke plumes as they age. The aerosol age is modeled using tracers from the WRF-AAM configured over the region’s spatial domain (14 ºN – 41 ºS, 34 ºW – 51 ºE). The study conducted an analysis of extinction, single scattering albedo (SSA), and extinction Angstrom exponent (EAE) in relation to aerosol age. Additionally, observations from airborne 4STAR, ground-based AERONET were compared with model results using WRF-CAM5.
The analysis revealed that aerosol age varied distinctly with longitude and the physical and chemical processes associated with the transport drive changes in the optical properties. The aerosols sampled closest to the source exhibited lower SSA values relative to particles sampled along the coastline. Along the coastline, free tropospheric SSA peaked at about 5-6 days, before gradually decreasing over the ocean, with a minimum value observed after approximately 12 days. SSA was underestimated by WRF-CAM5, and the modeled values are constrained to a narrower range than observations highlighting the importance of improving the representation of mass absorption and extinction in regional climate models
A Geometry Modeling and Optimization Pipeline for the Atrioventricular Heart Valves
Get PDFThis research aims to develop a pipeline for modeling the tricuspid heart valve that can be used as an adaptable tool for furthering research in the field, including treatment options for heart valve disease such as functional tricuspid regurgitation. We first gathered data from micro-computed tomography scans of porcine heart valves to extract the valve shape and identify the annulus. The data were transformed and sent to a CAD modeling software in a streamlined process. We then combined the initial shape of the valve with a set of input parameters to define a leaflet surface and chordae tendineae using non-uniform rational B-splines (NURBS). The resulting model was used to represent the valve's shape, which we provide examples of using multiple patient data sets. We also combined the model with a nonlinear isotropic constitutive model for the leaflets to directly use isogeometric analysis (IGA) to evaluate the closure of the valve. This valve model creation, using only a set of initial data and input parameters, was combined with a genetic algorithm search pattern to demonstrate optimization capabilities of the modeling pipeline. The pipeline was used to minimize an objective function for the coaptation area of the valve model, which affects the quality of the valve's closure and reduces chances of tricuspid regurgitation. The presented modeling pipeline provides the next step in streamlining the process from data acquisition to improving biomechanical understanding of the tricuspid valve, bridging the research gap currently present with the tricuspid valve
Exploring the potential of dynamic mode decomposition in wireless communication and neuroscience applications
Get PDFThe exponential growth of available experimental, simulation, and historical data from modern systems, including those typically considered divergent (e.g., Neuroscience procedures and wireless networks), has created a persistent need for effective data mining and analysis techniques. Most systems can be characterized as high-dimensional, dynamical, exhibiting rich multiscale phenomena in both space and time. Engineering studies of complex linear and non-linear dynamical systems are especially challenging, as the behavior of the system is often unknown and complex. Studying this problem of interest necessitates discovering and modeling the underlying evolving dynamics. In such cases, a simplified, predictive model of the flow evolution profile must be developed based on observations/measurements collected from the system. Consequently, data-driven algorithms have become an essential tool for modeling and analyzing complex systems characterized by high nonlinearity and dimensionality.
The field of data-driven modeling and analysis of complex systems is rapidly advancing. Associated investigations are poised to revolutionize the engineering, biomedical, and physical sciences. By applying modeling techniques, a complex system can be simplified using low-dimensional models with spatial-temporal structures described using system measurements. Such techniques enable complex system modeling without requiring knowledge of dynamic equations governing the system's operation.
The primary objective of the work detailed in this dissertation was characterizing, identifying, and predicting the behavior of systems under analysis. In particular, characterization and identification entailed finding patterns embedded in system data; prediction required evaluating system dynamics. The thesis of this work proposes the implementation of dynamic mode decomposition (DMD), which is a fully data-driven technique, to characterize dynamical systems from extracted measurements. DMD employs singular value decomposition (SVD), which reduces high-dimensional measurements collected from a system and computes eigenvalues and eigenvectors of a linear approximated model. In other words, by rather estimating the underlying dynamics within a system, DMD serves as a powerful tool for system characterization without requiring knowledge of the governing dynamical equations.
Overall, the work presented herein demonstrates the potential of DMD for analyzing and modeling complex systems in the emerging, synthesized field of wireless communication (i.e., wireless technology identification) and neuroscience (i.e., chemotherapy-induced peripheral neuropathy [CIPN] identification for cancer patients). In the former, a novel technique based on DMD was initially developed for wireless coexistence analysis. The scheme can differentiate various wireless technologies, including GSM and LTE signals in the cellular domain and IEEE802.11n, ac, and ax in the Wi-Fi domain, as well as Bluetooth and Zigbee in the personal wireless domain. By capturing embedded periodic features transmitted within the signal, the proposed DMD-based technique can identify a signal’s time domain signature. With regard to cancer neuroscience, a DMD-based scheme was developed to capture the pattern of plantar pressure variability due to the development of neuropathy resulting from neurotoxic chemotherapy treatment. The developed technique modeled gait pressure variations across multiple steps at three plantar regions, which characterized the development of CIPN in patients with uterine cancer.
Obtained results demonstrated that DMD can effectively model various systems and characterize system dynamics. Given the advantages of fast data processing, minimal required data preprocessing, and minimal required signal observation time intervals, DMD has proven to be a powerful tool for system analysis and modeling
Establishing Three-Dimensional Super-Resolution Microscopy Methods For Quantifying Intracellular Nanoparticle Distribution
Get PDFThe systemic administration of nanomedicine formulations has been described as a promising treatment option for solid tumors at both preclinical and clinical stages. However, these treatments are currently limited to improved safety over the administration of free drugs, while improvements to efficacy have been limited by a noted low accumulation of nanoparticles in cancer cells. The mechanisms for nanoparticle delivery across tumor blood vessels into the tumor microenvironment are not fully understood as a result of the physical limitations of the current standard methods of visualizing nanoparticle accumulation and intracellular transport in cancer cells. Most intracellular vesicles typically involved with the transport of nanoparticles across tumor blood vessels are sized smaller than the spatial resolution limit of light microscopy (~200 nm laterally), whereas electron microscopes, which provide sufficient lateral resolutions for visualizing these vesicles, are typically limited to thin biological samples, making it difficult to acquire three-dimensional (3D) visualizations of cells. To address these challenges, in this dissertation, quantitative 3D super-resolution light microscopy methods were applied to study the intracellular distribution of metallic and organic nanoparticle formulations in cultured cancer cells. We employed a method known as expansion microscopy, which involves embedding cell samples within swellable hydrogels to physically enlarge the sample >10X their original size for super-resolution imaging. Intracellular label-free metallic nanoparticles were visualized with light scattering imaging, while organic nanoparticles were visualized with internalized fluorescent tags. Since expansion microscopy is compatible with the labeling of intracellular features, this method enables the determination of the precise location of nanoparticles within cells, which can be used for studying intracellular nanoparticle trafficking with high spatial resolution in 3D. The successful application of this method will empower new research in nanomedicine for the development of safer and more effective treatments
Design of smart tool organizer
Get PDFThe increasing demand for compact and energy efficient machines and mechanisms, led to the emergence of a series of scalable instruments and devices used for testing, storage, manufacturing, and prototyping. The emergence of these devices indeed provided the flexibility and low capital cost that were necessary for product development and personal use. Furthermore, the demand is expected to proliferate to all domestic and industrial sectors of the economy, which brings us to the subject of the current investigation. The main objective of the proposed project is the design and prototyping of a compact electromechanical smart tool organizer that is capable of storing, tracking personal use and availability of machine shop tools in the college of Mathematics and Science at the University of Central Oklahoma. The proposed design incorporates a micro-controlled electro-mechanical dispensing unit, an interactive digital interface with key activation and a database for data collection & tracking of tools and personnel users. The dispensing unit consists of a CNC machine, linear actuator and a 3D printed mechanical clamp which enables the unit to efficiently hold and move various tools to the desired location. The skeleton of the CNC machine is assembled using five stainless steel v-slots operating on a belt and pinion system. Pinons are fitted to NEMA 17 stepper motors to achieve 2D motion by converting rotational motion to linear motion using a belt driven actuator. The assembly of the CNC machine utilizes various gantry plates to hold v-slots in position along with providing mounts for stepper motors and linear actuator. The linear actuator acts as a third axis which allows the motion of the dispensing unit to operate in three directions. This provides mobility to the machine to precisely take the mechanical clamp to a predetermined position within the frame of the dispensing unit. The design of mechanical clamp includes assembly of the base of the clamp, rack and pinion system, two gripper arms and a servo motor. The pinion converts the rotational motion to linear motion of the racks enabling the grip to open and close as required. The final assembly of the mechanical clamp is mounted on the linear actuator using the 3D printed mount bracket on the base of the clamp. The electronics and controls of the smart tool organizer includes low and high voltage operating components such as Nema 17 stepper motors, MG996R servo, linear actuator, limit switches, buck converter, DS3231 RTC module, SD card module, L298N motor drive module, TB6600 motor drivers, a 7” touch screen LED display and an arduino mega. The firmware arduino IDE is used to program these electronic components and ASCII is used to program the Interactive GUI and HMI on the Nextion display which connect to arduino using serial port and synchronizes to achieve the goal of the smart tool organizer
Identifying latent diversity, equity, inclusion, and accessibility (DEIA) indicators for multimodal transportation systems
Get PDFTraditional transportation policies unfairly affect marginalized travelers and under-represented groups, limiting their access to social and economic opportunities and contributing to residential segregation. Even though there is growing acknowledgement among policymakers and planners about the need for fair and inclusive transport systems covering all modes, the empirical literature remains inconclusive and lacks sufficient intellectual tools, data sources, and standards to incorporate a system-level perspective and assess the diversity, equity, inclusion, and accessibility (DEIA) indicators for multi-modal transportation systems. Existing approaches rely on time-consuming, labor-intensive, expensive surveys that lack real-time capabilities. In contrast, this research utilizes alternative data sources such as large-scale, open-source social media and street network data to identify latent DEIA indicators for transportation systems using network science theories and advanced data-driven methods.
First, road network data from sources like OpenStreetMap or Google Maps offer a promising avenue to measure the accessibility of social opportunities for marginalized populations, such as bicycle users and transit dependents. This research aims to establish indicators of bike accessibility by utilizing open-source street network data from OpenStreetMap and extracting the bicycle network of 40 cities in the United States. Various macro network parameters (e.g., density, diameter, average path length, circuity, average degree) were calculated for the cities, along with demographic parameters obtained from the American Community Survey 2020 data (e.g., population size, per capita income, percentage of bike users). Statistical regression analysis revealed a significant relationship between accessibility score and certain network and demographic parameters. The regression model can assist planners in identifying the accessibility of the bike network in any given area using network data. The study also presents a systematic intervention method that utilizes the betweenness centrality measure to increase the accessibility of an existing network, with lower centrality nodes found to be more critical for interventions aimed at improving accessibility.
Next, social media data presents a cost-effective and real-time alternative for capturing public opinion on transportation issues, which can serve as an indicator of a transportation system's DEIA. The study leveraged approximately three months' worth of Twitter data (around 1.46 million tweets) from the state of New York to identify key transportation-related DEIA issues discussed by users. Natural language processing techniques were employed to extract transportation DEIA-relevant conversations, followed by the use of a Bidirectional Encoder Representations from Transformers (BERT) model for tweet classification. Socio-demographic information of users was detected using Random Forest machine learning algorithm. Major topics discussed by the users in the sample dataset were public transportation infrastructure, active transportation, ridesharing, accessibility, etc. Finally, a logistic regression model was developed to understand the relationship between users' demographic data and DEIA concerns. This model helps identify specific transportation DEIA issues raised by different marginalized groups, providing valuable insights for urban planners.
In conclusion, this research utilizes an innovative dataset and sophisticated data analysis techniques to introduce a unique method for assessing the diversity, equity, inclusion, and accessibility (DEIA) of transportation systems. This approach yields crucial insights for planners, pinpointing the specific locations and demographic segments most impacted by existing transportation inequities. Furthermore, the study presents a distinct strategy for systematically enhancing network accessibility. Collectively, these findings represent substantial advancements in our comprehension of, and ability to address, DEIA issues within transportation networks.
Keywords: transportation DEIA, OpenStreetMap, Graph Theory, Multiple Linear Regression model, Twitter, Machine Learning, Multinomial Logit Model, Econometric Modelin
Saturn's sphere : astrology, mythology, and the contemplatives in Dante's Paradiso 21-22
Get PDFIn the arrangement of souls in Dante's Paradiso, the poet places the most blessed category of souls, the contemplatives, in the sphere of Saturn, a planet generally considered to be "The Greater Infortune" in medieval astrology (Paradiso 21-22). This thesis asks and answers the question why this should be so. Scholarly literature on Dante has rarely dealt with this question in depth. Commentators since the fourteenth century have typically offered a brief explanation, and one often finds these explanations more or less expanded upon in the tradition of Lecturae Dantis. But to my knowledge, the only prolonged consideration of the nature of Saturn in Paradiso is the relevant chapter of Richard Kay's Dante's Christian Astrology, which tends to focus more on details than on the larger question. My thesis is that when fully examined the medieval associations of Saturn actually constitute an atmosphere peculiarly appropriate to contemplative hermits, and an understanding of this "Saturnine atmosphere" will enable us to read rightly both the two speaking figures of the cantos, Peter Damian and Benedict of Nursia, as well as the two lesser figures who are named as present but remain silent, Macarius and Romuald. In order to develop this thesis, I consider Dante's sources, both confirmed and surmised, in order to develop a portrait of Saturn as he was understood by the fourteenth century, employing contemporary definitions and etymologies of the appropriate terms. I look at Paradiso's intertextual relations with those authors, ancient, late antique, and medieval, in connection with the Saturnine associations they furnish. I use those results to demonstrate the nature of the Saturnine atmosphere developed in Paradiso 21-22, comparing the images and qualities of Saturn with the characterizations and images of Saturn's sphere in the Commedia. Then I consider the lives, writings, and depictions in the appropriate cantos of the four contemplatives that Dante identifies, demonstrating how they relate to the Saturnine atmosphere and associations and why the poet might have chosen each of them for inclusion in Saturn's sphere. Special attention is given to the identity of Macarius, as there are at least three possibilities and Dante does not specify in any way which one he is thinking of. I find that the medieval understanding of Saturn is truly integral to the atmosphere and events of Par. 21-22, and that there are many examples of this in the lives, writings, and role in the Commedia of the four souls in question. These findings significantly deepen our understanding of these cantos and their connection with the architectonics of Paradiso. Future research might focus in more depth on one of the four contemplatives, particularly the much neglected Macarius, consider to a greater degree the role of Saturnine allusions and imagery in other parts of the Commedia and perhaps even in Dante's lyrics, and treat more profound themes connected with Saturn and Paradiso in light of critical theory, such as the work of Walter Benjamin and Mikhail Bakhtin
As Seen from Bombay: An Iranian Zoroastrian Photo Album from the 1930s
Get PDFThis photo essay provides a visual archive of Parsi philanthropic efforts toward the Iranian Zoroastrian
communities of Yazd, Kerman, and Tehran during the 1930s. The essay reproduces a collection of
photographs from a photo album produced by the Iranian Zoroastrian Anjoman (est. 1918) for the benefit of Parsi audiences in Bombay. These photographs were taken and compiled by administrators of the
Parsi-funded charities in order to demonstrate to Bombay-based Parsi benefactors how their charity
efforts were being used inside Iran. The essay also discusses the importance of including visual archival
material as part of the social and cultural history of modern Iran, as well as the unique sets of challenges that such archival preservation represents.YesThe full photo album is available via SHAREOK: https://hdl.handle.net/11244/33521