Matching Items (112)
Description
Thousands of human lives are lost every day due to chronic diseases, some more preventable than others. For years, the gold standard for diagnosing and monitoring these diseases has been through traditional methods such as individualized doctor-patient clinical evaluations, usually involving laboratory tests. These methods, though effective, can be costly, time-consuming, and fail to encompass an overarching perspective of the health profile of the larger population. Wastewater-based epidemiology (WBE) has successfully been employed for decades as a population-level data source informing on the consumption of licit and illicit substance use. It also is showing promise for its use as a community-wide diagnostic tool for broader public health measurements. This literature review constitutes a theoretical evaluation of the potential use of WBE for monitoring the top two deadly diseases in the United States; cardiovascular disease (CVD) and cancer. Literature-reported metabolites indicative of these diseases were evaluated to determine if they were capable of being identified and monitored in wastewater. Potential analytes include cardiac-specific troponin, α-fenotroin, and inositol. Results obtained within suggest WBE could be used as a viable and economical tool to track and monitor the top deadly diseases in human populations. This methodology could be implemented in tandem with current practices in order to provide a more holistic understanding of prevalence and risk for CVD and cancer.
ContributorsAmin, Vivek (Author) / Halden, Rolf (Thesis director) / Niebuhr, Robert (Committee member) / Bowes, Devin (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Microplastics are defined as small pieces of plastics that are less than five millimeters in size. These microplastics can vary in their appearance, are known to be harmful to aquatic life and can threaten life cycles of marine organisms because of their chemical make-up and the toxic additives used in their manufacture. Although small in size, it is hypothesized that microplastics can serve as an example of how human activities can alter ecosystems near and far. To investigate the implications and determine the potential impact of microplastics on a protected atoll’s ecosystems, red-footed booby (Sula sula) guano samples from six locations on Palmyra Atoll were acquired from North Carolina State University via The Nature Conservancy and were inspected for the presence of microplastics. Each of the guano samples were weighed and prepared via wet oxidation. Microplastic fibers were detected via stereoscope microscopy and analyzed for chemical composition via Raman spectroscopy. All six sampling locations within Palmyra Atoll contained microplastic fibers identified as polyethylene terephthalate, with North-South Causeway and Eastern Island having the highest average number of microplastic fibers found per gram of guano sample (n = 0.611). These data provide evidence that seabirds can serve as vectors for the spread of microplastic pollution. This research lends context to the widespread impact of plastic pollution and states possible implications of its presence in delicate ecosystems.
ContributorsAnderson, Alyssa Cerise (Author) / Lisenbee, Cayle (Thesis director) / Halden, Rolf (Committee member) / Rolsky, Charles (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Current methods measuring the consumption of prescription and illicit drugs are often hampered by innate limitations, the data is slow and often restricted, which can impact the relevance and robustness of the associated data. Here, wastewater-based epidemiology (WBE) was applied as an alternative metric to measure trends in the consumption of twelve narcotics within a collegiate setting from January 2018 to May 2018 at a Southwestern U.S. university. The present follow-up study was designed to identify potential changes in the consumption patterns of prescription and illicit drugs as the academic year progressed. Samples were collected from two sites that capture nearly 100% of campus-generated wastewater. Seven consecutive 24-hour composite raw wastewater samples were collected each month (n = 68) from both locations. The study identified the average consumption of select narcotics, in units of mg/day/1000 persons in the following order: cocaine (528 ± 266), heroin (404 ± 315), methylphenidate (343 ± 396), amphetamine (308 ±105), ecstasy (MDMA; 114 ± 198), oxycodone (57 ± 28), methadone (58 ± 73), and codeine (84 ± 40). The consumption of oxycodone, methadone, heroin, and cocaine were identified as statistically lower in the Spring 2018 semester compared to the Fall 2017. Universities may need to increase drug education for the fall semester to lower the consumption of drugs in that semester. Data from this research encompasses both human health and the built environment by evaluating public health through collection of municipal wastewater, allowing public health officials rapid and robust narcotic consumption data while maintaining the anonymity of the students, faculty, and staff.
ContributorsCarlson, Alyssa Rose (Author) / Halden, Rolf (Thesis director) / Gushgari, Adam (Committee member) / School of Human Evolution & Social Change (Contributor) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The combined use of methamphetamine and opioids has been reported to be on the rise throughout the United States (U.S.). However, our knowledge of this phenomenon is largely based upon reported overdoses and overdose-related deaths, law enforcement seizures, and drug treatment records; data that are often slow, restricted, and only track a portion of the population participating in drug consumption activities. As an alternative, wastewater-based epidemiology (WBE) has the capability to track licit and illicit drug trends within an entire community, at a low cost and in near real-time, while providing anonymity to those contributing to the sewer shed. In this study, wastewater was collected from two Midwestern U.S. cities (2017-2019) and analyzed for the prevalence of methamphetamine and the opioids oxycodone, codeine, fentanyl, tramadol, hydrocodone, and hydromorphone. Monthly 24-hour time-weighted composite samples (n = 48) from each city were analyzed using isotope dilution liquid chromatography tandem mass spectrometry. Results showed that methamphetamine and total opioid consumption (milligram morphine equivalents) in City 1 were strongly correlated only in 2017 (Spearman rank order correlation coefficient, ρ = 0.78), the relationship driven by fentanyl, hydrocodone, and hydromorphone. For City 2, methamphetamine and total opioid consumption were strongly positively correlated during the entire study (ρ = 0.54), with the correlations driven by hydrocodone and hydromorphone. In both cities, hydrocodone and hydromorphone mass loads were highly correlated, suggesting a parent and metabolite relationship. WBE provides important insights into licit and illicit drug consumption patterns in near real-time as they evolve; important information for community stakeholders in municipalities across the U.S.
ContributorsClick, Kathleen Grace (Author) / Halden, Rolf (Thesis director) / Gushgari, Adam (Committee member) / Driver, Erin (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Alzheimer’s disease (AD) is a neurodegenerative disease resulting in loss of cognitive function and is not considered part of the typical aging process. Recently, research is being conducted to study environmental effects on AD because the exact molecular mechanisms behind AD are not known. The associations between various toxins and AD have been mixed and unclear. In order to better understand the role of the environment and toxic substances on AD, we conducted a literature review and geospatial analysis of environmental, specifically wastewater, contaminants that have biological plausibility for increasing risk of development or exacerbation of AD. This literature review assisted us in selecting 10 wastewater toxic substances that displayed a mixed or one-sided relationship with the symptoms or prevalence of Alzheimer’s for our data analysis. We utilized data of toxic substances in wastewater treatment plants and compared them to the crude rate of AD in the different Census regions of the United States to test for possible linear relationships. Using data from the Targeted National Sewage Sludge Survey (TNSSS) and the Centers for Disease Control and Prevention (CDC), we developed an application using R Shiny to allow users to interactively visualize both datasets as choropleths of the United States and understand the importance of this area of research. Pearson’s correlation coefficient was calculated resulting in arsenic and cadmium displaying positive linear correlations with AD. Other analytes from this statistical analysis demonstrated mixed correlations with AD. This application and data analysis serve as a model in the methodology for further geospatial analysis on AD. Further data analysis and visualization at a lower level in terms of scope is necessary for more accurate and reliable evidence of a causal relationship between the wastewater substance analytes and AD.
GitHub Repository: https://github.com/komal-agrawal/AD_GIS.git
GitHub Repository: https://github.com/komal-agrawal/AD_GIS.git
ContributorsAgrawal, Komal (Author) / Scotch, Matthew (Thesis director) / Halden, Rolf (Committee member) / College of Health Solutions (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
With a rapidly decreasing amount of resources for construction, wood and bamboo have been suggested as renewable materials for increased use in the future to attain sustainability. Through a literature review, bamboo and wood growth, manufacturing and structural attributes were compared and then scored in a weighted matrix to determine the option that shows the higher rate of sustainability. In regards to the growth phase, which includes water usage, land usage, growth time, bamboo and wood showed similar characteristics overall, with wood scoring 1.11% higher than bamboo. Manufacturing, which captures the extraction and milling processes, is experiencing use of wood at levels four times those of bamboo, as bamboo production has not reached the efficiency of wood within the United States. Structural use proved to display bamboo’s power, as it scored 30% higher than wood. Overall, bamboo received a score 15% greater than that of wood, identifying this fast growing plant as the comparatively more sustainable construction material.
ContributorsThies, Jett Martin (Author) / Ward, Kristen (Thesis director) / Halden, Rolf (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Civil, Environmental and Sustainable Eng Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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
Interdigitated back contact (IBC) solar cells have achieved the highest single junction silicon wafer-based solar cell power conversion efficiencies reported to date. This thesis is about the fabrication of a high-efficiency silicon heterojunction IBC solar cell for potential use as the bottom cell for a 3-terminal lattice-matched dilute-nitride Ga (In)NP(As)/Si monolithic tandem solar cell. An effective fabrication process has been developed and the process challenges related to open circuit voltage (Voc), series resistance (Rs), and fill factor (FF) are experimentally analyzed. While wet etching, the sample lost the initial passivation, and by changing the etchant solution and passivation process, the voltage at maximum power recovered to an initial value of over 710 mV before metallization. The factors reducing the series resistance loss in IBC cells were also studied. One of these factors was the Indium Tin Oxide (ITO) sputtering parameters, which impact the conductivity of the ITO layer and transport across the a-Si:H/ITO interface. For the standard recipe, the chamber pressure was 3.5 mTorr with no oxygen partial pressure, and the thickness of the ITO layer in contact with the a-Si:H layers, was optimized to 150 nm. The patterning method for the metal contacts and final annealing also change the contact resistance of the base and emitter stack layers. The final annealing step is necessary to recover the sputtering damage; however, the higher the annealing time the higher the final IBC series resistance. The best efficiency achieved was 19.3% (Jsc = 37 mA/cm2, Voc = 691 mV, FF = 71.7%) on 200 µm thick 1-15 Ω-cm n-type CZ C-Si with a designated area of 4 cm2.
ContributorsMoeini Rizi, Mansoure (Author) / Goodnick, Stephen (Thesis advisor) / Honsberg, Christina (Committee member) / Goryll, Michael (Committee member) / Smith, David (Committee member) / Bowden, Stuart (Committee member) / Arizona State University (Publisher)
Created2022
Description
The future will be replete with Artificial Intelligence (AI) based agents closely collaborating with humans. Although it is challenging to construct such systems for real-world conditions, the Intelligent Tutoring System (ITS) community has proposed several techniques to work closely with students. However, there is a need to extend these systems outside the controlled environment of the classroom. More recently, Human-Aware Planning (HAP) community has developed generalized AI techniques for collaborating with humans and providing personalized support or guidance to the collaborators. In this thesis, the take learning from the ITS community is extend to construct such human-aware systems for real-world domains and evaluate them with real stakeholders. First, the applicability of HAP to ITS is demonstrated, by modeling the behavior in a classroom and a state-of-the-art tutoring system called Dragoon. Then these techniques are extended to provide decision support to a human teammate and evaluate the effectiveness of the framework through ablation studies to support students in constructing their plan of study (\ipos). The results show that these techniques are helpful and can support users in their tasks. In the third section of the thesis, an ITS scenario of asking questions (or problems) in active environments is modeled by constructing questions to elicit a human teammate's model of understanding. The framework is evaluated through a user study, where the results show that the queries can be used for eliciting the human teammate's mental model.
ContributorsGrover, Sachin (Author) / Kambhampati, Subbarao (Thesis advisor) / Smith, David (Committee member) / Srivastava, Sidhharth (Committee member) / VanLehn, Kurt (Committee member) / Arizona State University (Publisher)
Created2022
Description
Written corrective feedback (WCF) has received considerable attention in secondlanguage (L2) writing research. The conducive role of WCF in developing L2 writing and
second language acquisition has been corroborated by a number of theoretical frameworks,
and the findings of empirical studies, meta-analyses, and research syntheses. WCF research
has predominantly addressed its effectiveness in improving learners’ syntactic, lexical, and
orthographic knowledge. This dissertation project extends the scope of this line of research
to formulaic aspects of language and investigates the relative effectiveness of WCF
targeting formulaic vs. non-formulaic constructions in L2 writing. The text-analytic
descriptive aspect of this research design aimed at investigating the extent of L2 learners’
non-target-like use of formulaic vs. non-formulaic forms in L2 writing and writing
teachers’ WCF treatment of non-target (non)formulaic language use. A total of 480 first
drafts of essays written by 33 advanced adult English-as-a-foreign language (EFL) learners
during one semester and 480 drafts of essays corrected through WCF by three EFL teachers
constituted the corpus in this study. Advancing the field of learner corpus research, the
findings demonstrated that whereas learners’ non-target formulaic forms outnumbered that
of non-formulaic ones in their writing assignments, all three teachers provided WCF more
often for erroneous use of non-formulaic forms. The quasi-experimental aspect of the
research design attempts to add new empirical evidence on the L2 learning potential of
accessing and processing WCF provided for formulaic vs. non-formulaic constructions in
L2 writing. To this end, a total of 66 EFL learners in a Test of English as a Foreign
Language preparation course participated in a pretest-posttest design, with 5 experimental groups (those who were provided with direct, indirect, direct plus metalinguistic, and
indirect plus metalinguistic WCF) and a control group (those who were not provided with
WCF). Maintaining a division between formulaic vs. non-formulaic forms, the findings
provide empirical evidence on the interactions between types of WCF, types of linguistic
targets, and the effectiveness of WCF in terms of enhancing L2 learners’ accuracy and
acquisition in their revised writing and new writings in the short and long term.
ContributorsGholami, Leila (Author) / Smith, David (Thesis advisor) / Matsuda, Paul K (Committee member) / James, Mark A (Committee member) / Arizona State University (Publisher)
Created2022