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Description
The growing urban heat island (UHI) phenomenon is having detrimental effects on urban populations and the environment, and therefore, must be addressed. The purpose of this research is to investigate possible strategies that could be utilized to reduce the effects of the urban heat island for the city of Phoenix. Current strategies, case studies, and the ENVI-Met modeling software were used to finalize conclusions and suggestions to further progress Phoenix's goals in combating its urban heat island. Results from the studies found that there is much potential in reducing daytime and evening temperatures through improving infrastructure by means of increased vegetation in the forms of green roofs and walls, reducing anthropogenic heat release, improving artificial surface coverage, and implementing lasting policies for further development. Results from the ENVI-met microclimate program shows areas for further research in urban heat island mitigation strategies.
ContributorsShqalsi, Ema (Author) / Pijawka, David (Thesis director) / Middel, Ariane (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Historically, studies of condition-dependent signals in animals have been male-centric, but recent work suggests that female ornaments can also communicate individual quality (e.g., disease state, fecundity). There has been a surge of interest in how urbanization alters signaling traits, but we know little about if and how cities affect signal expression in female animals. We measured carotenoid-based plumage coloration and coccidian (Isospora spp) parasite burden in desert and city populations of house finches to examine urban impacts on male and female health and attractiveness. In earlier work, we showed that male house finches are less colorful and more parasitized in the city, and we again detected that pattern in this study for males. However, though city females are also less colorful than their rural counterparts, we found that rural females were more parasitized. Also, regardless of sex and unlike rural birds, more colorful birds in the city were more heavily infected with coccidia. These results show that urban environments can disrupt signal honesty in female animals and highlight the need for more studies on how cities affect disease and condition-dependent traits in both male and female animals.
ContributorsSykes, Brooke Emma (Author) / McGraw, Kevin (Thesis director) / Sweazea, Karen (Committee member) / Hutton, Pierce (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
There are two electrophysiological states of sleep in birds (rapid-eye-movement sleep [REM] and slow-wave sleep [SWS]), which have different functions and costs. REM improves memory consolidation, while SWS is neuro-restorative but also exposes the animal to more risk during this deep-sleep phase. Birds who sleep in more exposed microsites are known to invest proportionally less in SWS (presumably to ensure proper vigilance), but otherwise little else is known about the ecological or behavioral predictors of how much time birds devote to REM v. SWS sleep. In this comparative analysis, we examine how proportional time spent in SWS v. REM is related to brain mass and duration of the incubation period in adults. Brain mass and incubation period were chosen as predictors of sleep state investment because brain mass is positively correlated with body size (and may show a relationship between physical development and sleep) and incubation period can be a link used to show similarities and differences between birds and mammals (using mammalian gestation period). We hypothesized that (1) species with larger brains (relative to body size and also while controlling for phylogeny) would have higher demands for information processing, and possibly proportionally outweigh neuro-repair, and thus devote more time to REM and that (2) species with longer incubation periods would have proportionally more REM due to the extended time required for overnight predator vigilance (and not falling into deep sleep) while on the nest. We found, using neurophysiological data from literature on 27 bird species, that adults from species with longer incubation periods spent proportionally more time in REM sleep, but that relative brain size was not significantly associated with relative time spent in REM or SWS. We therefore provide evidence that mammalian and avian REM in response to incubation/gestation period have convergently evolved. Our results suggest that overnight environmental conditions (e.g. sleep site exposure) might have a greater effect on sleep parameters than gross morphological attributes.
ContributorsRaiffe, Joshua Sapell (Author) / McGraw, Kevin (Thesis director) / Deviche, Pierre (Committee member) / Hutton, Pierce (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Humans have greatly altered the night-time photic environment via the production of artificial light at night (ALAN; e.g. street lights, car traffic, billboards, lit buildings). ALAN is problematic because it may significantly alter the seasonal/daily physiological rhythms or behaviors of animals. There has been considerable interest in the impacts of ALAN on health in humans and lab animals, but most such work has centered on adults and we know comparatively little about effects on young animals. We exposed 3-week-old king quail (Excalfactoria chinensis) to a constant overnight blue-light regime for 6 weeks and assessed weekly bactericidal activity of plasma against Escherichia coli - a commonly employed metric of innate immunity in animals. We found that chronic ALAN exposure significantly increased immune function, and that this elevation in immune performance manifested at different developmental time points in males and females. These results counter the pervasive notion that overnight light exposure is universally physiologically harmful to diurnal organisms and indicate that ALAN can provide sex-specific, short-term immunological boosts to developing animals.
ContributorsSaini, Chandan (Author) / McGraw, Kevin (Thesis director) / Hutton, Pierce (Committee member) / Sweazea, Karen (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.
ContributorsMiddel, Ariane (Author) / Vanos, Jennifer K. (Author) / Hondula, David M. (Author) / Kaloush, Kamil (Author) / Sailor, David (Author) / Medina, Jose R. (Jose Roberto) (Author) / Schneider, Florian (Author) / Ortiz, Johny Cordova (Author) / Campbell, Bill (Author) / Epel, Erin (Contributor) / Rice, Brendan (Contributor) / Garcia, Ruth (Contributor) / Phoenix (Ariz.). Street Transportation Department (Contributor) / City of Phoenix (Funder) / Industrial Development Authority of the County of Maricopa (Funder) / Julie Ann Wrigley Global Institute of Sustainability (Funder) / Arizona State University. Healthy Urban Environments Program (Contributor)
Created2021-09
Description
The imaging and detection of specific cell types deep in biological tissue is critical for the diagnosis of cancer and the study of biological phenomena. Current high-resolution optical imaging techniques are depth limited due to the high degree of optical scattering that occurs in tissues. To address these limitations, photoacoustic (PA) techniques have emerged as noninvasive methods for the imaging and detection of specific biological structures at extended depths in vivo. In addition, near-infrared (NIR) contrast agents have further increased the depth at which PA imaging can be achieved in biological tissues. The goal of this research is to combine novel PA imaging and NIR labeling strategies for the diagnosis of disease and for the detection of neuronal subtypes. Central Hypothesis: Utilizing custom-designed PA systems and NIR labeling techniques will enable the detection of specific cell types in vitro and in mammalian brain slices. Work presented in this dissertation addresses the following: (Chapter 2): The custom photoacoustic flow cytometry system combined with NIR absorbing copper sulfide nanoparticles for the detection of ovarian circulating tumor cells (CTCs) at physiologically relevant concentrations. Results obtained from this Chapter provide a unique tool for the future detection of ovarian CTCs in patient samples at the point of care. (Chapter 3): The custom photoacoustic microscopy (PAM) system can detect genetically encoded near-infrared fluorescent proteins (iRFPs) in cells in vitro. Results obtained from this Chapter can significantly increase the depth at which neurons and cellular processes can be targeted and imaged in vitro. (Chapter 4): Utilizing the Cre/lox recombination system with AAV vectors will enable selective tagging of dopaminergic neurons with iRFP for detection in brain slices using PAM. Thus, providing a new means of increasing the depth at which neuronal subtypes can be imaged and detected in the mammalian brain. Significance: Knowledge gained from this research could have significant impacts on the PA detection of ovarian cancer and extend the depth at which neuronal subtypes are imaged in the mammalian brain.
ContributorsLusk, Joel F. (Author) / Smith, Barbara S. (Thesis advisor) / Halden, Rolf (Committee member) / Anderson, Trent (Committee member) / Arizona State University (Publisher)
Created2022
Description
Infrastructure systems are facing non-stationary challenges that stem from climate change and the increasingly complex interactions between the social, ecological, and technological systems (SETSs). It is crucial for transportation infrastructures—which enable residents to access opportunities and foster prosperity, quality of life, and social connections—to be resilient under these non-stationary challenges. Vulnerability assessment (VA) examines the potential consequences a system is likely to experience due to exposure to perturbation or stressors and lack of the capacity to adapt. Post-fire debris flow and heat represent particularly challenging problems for infrastructure and users in the arid U.S. West. Post-fire debris flow, which is manifested with heat and drought, produces powerful runoff threatening physical transportation infrastructures. And heat waves have devastating health effects on transportation infrastructure users, including increased mortality rates. VA anticipates the potential consequences of these perturbations and enables infrastructure stakeholders to improve the system's resilience. The current transportation climate VA—which only considers a single direct climate stressor on the infrastructure—falls short of addressing the wildfire and heat challenges. This work proposes advanced transportation climate VA methods to address the complex and multiple climate stressors and the vulnerability of infrastructure users. Two specific regions were chosen to carry out the progressive transportation climate VA: 1) the California transportation networks’ vulnerability to post-fire debris flows, and 2) the transportation infrastructure user’s vulnerability to heat exposure in Phoenix.
ContributorsLi, Rui (Author) / Chester, Mikhail V. (Thesis advisor) / Middel, Ariane (Committee member) / Hondula, David M. (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2022
Description
Wastewater-based epidemiology (WBE) has emerged as a powerful tool for community health assessment, using wastewater-borne biological and chemical markers as analytical targets. This study investigates the critical influence of sampling frequency on the resultant estimates of opioid consumption and the prevalence of SARS-CoV-2 infections at the neighborhood level using common WBE biomarkers including fentanyl, norfentanyl, and the SARS-CoV-2 N1 gene as targets. The goal was to assess sampling methodologies that include the impact of the day of the week and of the sampling frequency. Wastewater samples were collected two or three times per week over the course of five months (n=525) and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) or reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) for target chemical or molecular indicators of interest. Results showed no statistically significant differences for days of the week (i.e., Tuesday vs. Thursday vs. Saturday) for 24-hour composite samples analyzed for fentanyl or SARS-CoV-2; however, concentrations of the human metabolite of fentanyl, norfentanyl, were statistically different between Tuesday and Saturday (p < 0.05). When data were aggregated either by Tuesday/Thursday or Tuesday/Thursday/Saturday to examine sensitivity to sampling frequency, data were not statistically different except for the Tuesday/Thursday weekly average and Saturday for norfentanyl (p < 0.05). These results highlight how sample collection and data handling methodologies can impact wastewater-derived public health assessments. Care should be taken when selecting an approach to the sampling frequency based on the public health concerns under investigation.
ContributorsAJDINI, ARIANNA (Author) / Halden, Rolf (Thesis advisor) / Driver, Erin (Committee member) / Conroy-Ben, Otakuye (Committee member) / Arizona State University (Publisher)
Created2023
Description
This dissertation focused on studying risks associated with emerging drinking water contaminants and tradeoffs related to water management interventions. The built environment impacts health, as humans on average spend ~90% of their time indoors. Federal regulations generally focus on drinking water at the water treatment plant and within the distribution system as opposed to when it enters buildings after crossing the property line. If drinking water is not properly managed in buildings, it can be a source or amplifier of microbial and chemical contaminants. Unlike regulations for chemical contaminants that are risk-based, for pathogens, regulations are either based on recommended treatment technologies or designated as zero, which is not achievable in practice. Practice-based judgments are typically made at the building level to maintain water quality. This research focuses on two drinking water opportunistic pathogens of public health concern, Legionella pneumophila and Mycobacterium avium complex (MAC). Multiple aspects of drinking water quality in two green buildings were monitored in tandem with water management interventions. Additionally, a quantitative microbial risk assessment framework was used to predict risk-based critical concentrations of MAC for drinking water-related exposures in the indoor environment corresponding to a 1 in 10,000 annual infection target risk benchmark. The overall goal of this work was to inform the development of water management plans and guidelines for buildings that will improve water quality in the built environment and promote better public health. It was determined that a whole building water softening system with ion exchange softening resin and expansion tanks were unexplored reservoirs for the colonization of L. pneumophila. Furthermore, it was observed that typical water management interventions such as flushing and thermal disinfection did not always mitigate water quality issues. Thus, there was a need to implement several atypical interventions such as equipment replacement to improve the building water quality. This work has contributed comprehensive field studies and models that have highlighted the need for additional niches, facility management challenges, and risk tradeoffs for focus in water safety plans. The work also informs additional risk-based water quality policy approaches for reducing drinking water risks.
ContributorsJoshi, Sayalee (Author) / Hamilton, Kerry A (Thesis advisor) / Abbaszadegan, Morteza (Committee member) / Conroy-Ben, Otakuye (Committee member) / Halden, Rolf (Committee member) / Arizona State University (Publisher)
Created2023
Description
Machine learning (ML) and deep learning (DL) has become an intrinsic part of multiple fields. The ability to solve complex problems makes machine learning a panacea. In the last few years, there has been an explosion of data generation, which has greatly improvised machine learning models. But this comes with a cost of high computation, which invariably increases power usage and cost of the hardware. In this thesis we explore applications of ML techniques, applied to two completely different fields - arts, media and theater and urban climate research using low-cost and low-powered edge devices. The multi-modal chatbot uses different machine learning techniques: natural language processing (NLP) and computer vision (CV) to understand inputs of the user and accordingly perform in the play and interact with the audience. This system is also equipped with other interactive hardware setups like movable LED systems, together they provide an experiential theatrical play tailored to each user. I will discuss how I used edge devices to achieve this AI system which has created a new genre in theatrical play. I will then discuss MaRTiny, which is an AI-based bio-meteorological system that calculates mean radiant temperature (MRT), which is an important parameter for urban climate research. It is also equipped with a vision system that performs different machine learning tasks like pedestrian and shade detection. The entire system costs around $200 which can potentially replace the existing setup worth $20,000. I will further discuss how I overcame the inaccuracies in MRT value caused by the system, using machine learning methods. These projects although belonging to two very different fields, are implemented using edge devices and use similar ML techniques. In this thesis I will detail out different techniques that are shared between these two projects and how they can be used in several other applications using edge devices.
ContributorsKulkarni, Karthik Kashinath (Author) / Jayasuriya, Suren (Thesis advisor) / Middel, Ariane (Thesis advisor) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2021