Matching Items (119)
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This paper describes the research done to quantify the relationship between external air temperature and energy consumption and internal air temperature and energy consumption. The study was conducted on a LEED Gold certified building, College Avenue Commons, located on Arizona State University's Tempe campus. It includes information on the background

This paper describes the research done to quantify the relationship between external air temperature and energy consumption and internal air temperature and energy consumption. The study was conducted on a LEED Gold certified building, College Avenue Commons, located on Arizona State University's Tempe campus. It includes information on the background of previous studies in the area, some that agree with the research hypotheses and some that take a different path. Real-time data was collected hourly for energy consumption and external air temperature. Intermittent internal air temperature was collected by undergraduate researcher, Charles Banke. Regression analysis was used to prove two research hypotheses. The authors found no correlation between external air temperature and energy consumption, nor did they find a relationship between internal air temperature and energy consumption. This paper also includes recommendations for future work to improve the study.
ContributorsBanke, Charles Michael (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the

ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the abovementioned techniques were optimized. In addition, MALDI mass spectrometry based peptide synthesis characterization on semiconductor microchips was developed and novel applications of a CombiMatrix (CBMX) platform for electrochemically controlled synthesis were explored. We have investigated performance of 2-(2-nitrophenyl)propoxycarbonyl (NPPOC) derivatives as photo-labile protecting group. Specifically, influence of substituents on 4 and 5 positions of phenyl ring of NPPOC group on the rate of photolysis and the yield of the amine was investigated. The results indicated that substituents capable of forming a π-network with the nitro group enhanced the rate of photolysis and yield. Once such properly substituted NPPOC groups were used, the rate of photolysis/yield depended on the nature of protected amino group indicating that a different chemical step during the photo-cleavage process became the rate limiting step. We also focused on electrochemically-directed parallel synthesis of high-density peptide microarrays using the CBMX technology referred to above which uses electrochemically generated acids to perform patterned chemistry. Several issues related to peptide synthesis on the CBMX platform were studied and optimized, with emphasis placed on the reactions of electro-generated acids during the deprotection step of peptide synthesis. We have developed a MALDI mass spectrometry based method to determine the chemical composition of microarray synthesis, directly on the feature. This method utilizes non-diffusional chemical cleavage from the surface, thereby making the chemical characterization of high-density microarray features simple, accurate, and amenable to high-throughput. CBMX Corp. has developed a microarray reader which is based on electro-chemical detection of redox chemical species. Several parameters of the instrument were studied and optimized and novel redox applications of peptide microarrays on CBMX platform were also investigated using the instrument. These include (i) a search of metal binding catalytic peptides to reduce overpotential associated with water oxidation reaction and (ii) an immobilization of peptide microarrays using electro-polymerized polypyrrole.
ContributorsKumar, Pallav (Author) / Woodbury, Neal (Thesis advisor) / Allen, James (Committee member) / Johnston, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
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The Chinese Construction Industry has grown to be one of the largest construction markets in the world within the last 10 years. The size of the Chinese Construction Industry is on par with many developed nations, despite it being a developing country. Despite its rapid growth, the productivity and profitability

The Chinese Construction Industry has grown to be one of the largest construction markets in the world within the last 10 years. The size of the Chinese Construction Industry is on par with many developed nations, despite it being a developing country. Despite its rapid growth, the productivity and profitability of the Chinese Construction Industry is low compared to similar sized construction industries (United States, United Kingdom, etc.). In addition to the low efficiency of the Chinese Construction Industry, there is minimal documentation available showing the performance of the Chinese Construction Industry (projects completed on time, on budget, and customer satisfaction ratings).

The purpose of this research is to investigate potential solutions that could address the poor efficiency and performance of the Chinese Construction Industry. This research is divided into three phases; first, a literature review to identify countries that have similar construction industries to the Chinese Construction Industry. The second phase is to compare the risks and identify solutions that are proposed to increase the performance of similar construction industries and the Chinese Construction Industry. The third phase is to create a survey from the literature-based information to validate the concepts with the Chinese Construction Industry professionals and stakeholders.
ContributorsChen, Yutian (Author) / Chong, Oswald (Thesis advisor) / Kashiwagi, Dean T. (Committee member) / Badger, Willliam (Committee member) / Arizona State University (Publisher)
Created2020
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Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of

Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
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Evolution is a key feature of undergraduate biology education: the AmericanAssociation for the Advancement of Science (AAAS) has identified evolution as one of the five core concepts of biology, and it is relevant to a wide array of biology-related careers. If biology instructors want students to use evolution to address scientific challenges post-graduation,

Evolution is a key feature of undergraduate biology education: the AmericanAssociation for the Advancement of Science (AAAS) has identified evolution as one of the five core concepts of biology, and it is relevant to a wide array of biology-related careers. If biology instructors want students to use evolution to address scientific challenges post-graduation, students need to be able to apply evolutionary principles to real-life situations, and accept that the theory of evolution is the best scientific explanation for the unity and diversity of life on Earth. In order to help students progress on both fronts, biology education researchers need surveys that measure evolution acceptance and assessments that measure students’ ability to apply evolutionary concepts. This dissertation improves the measurement of student understanding and acceptance of evolution by (1) developing a novel Evolutionary Medicine Assessment that measures students’ ability to apply the core principles of Evolutionary Medicine to a variety of health-related scenarios, (2) reevaluating existing measures of student evolution acceptance by using student interviews to assess response process validity, and (3) correcting the validity issues identified on the most widely-used measure of evolution acceptance - the Measure of Acceptance of the Theory of Evolution (MATE) - by developing and validating a revised version of this survey: the MATE 2.0.
ContributorsMisheva, Anastasia Taya (Author) / Brownell, Sara (Thesis advisor) / Barnes, Elizabeth (Committee member) / Collins, James (Committee member) / Cooper, Katelyn (Committee member) / Sterner, Beckett (Committee member) / Arizona State University (Publisher)
Created2023
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Although Saudi Arabia is moving towards a sustainable future, Existing residential buildings in the country are extremely unsustainable. Therefore, there is a necessity for greening the existing residential building. Mostadam green rating systems was developed by the Saudi ministry of housing in 2019 to address the long-term sustainability vision in

Although Saudi Arabia is moving towards a sustainable future, Existing residential buildings in the country are extremely unsustainable. Therefore, there is a necessity for greening the existing residential building. Mostadam green rating systems was developed by the Saudi ministry of housing in 2019 to address the long-term sustainability vision in residential buildings in the country. By setting Mostadam requirements as an objective of the retrofit process, it will ensure that the building achieve sustainability. However, Mostadam is new and there is a lack of knowledge of implementing its requirements on existing buildings. The aim of this research is to develop a framework to green existing residential buildings in Saudi Arabia to achieve Mostadam energy and water minimum requirements. The framework was developed based on an extensive keyword-based search and an analysis of 92 relevant research. The process starts with assessing the building against the minimum requirements of energy and water of Mostadam. After that, optimization phase is conducted. Building information modelling is used in the optimization phase. Energy and water efficiency optimization measures are identified from the analysed literature. Revit is used in the base model authoring and Green building studio cloud is used to simulate the energy and water efficiency measures. Then, payback period is calculated for all the efficiency measured to assess the decision making. A case study of a villa in Riyadh, Saudi Arabia is provided. result shows that the implemented efficiency measures led to an increment of 37.5% in annual energy savings and 26.1% in the annual water savings. Results shows that the application of the proposed framework supports evaluating energy and water efficiency measures to implement it on the buildings to achieve Mostadam minimum energy and water requirements. Recommendations were made for future work to bridge the knowledge gap.
ContributorsMohamed, Sara Murad (Author) / Sullivan, Kenneth (Thesis advisor) / Chong, Oswald (Committee member) / Hurtado, Kristen (Committee member) / Arizona State University (Publisher)
Created2022
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As the construction industry in Saudi Arabia was on its way to thriving again. Their growth was due to the unprecedented volume of planned projects such as large-scale and unique projects. Suddenly, the world was faced with one of the most disrupting events in the last century which had a

As the construction industry in Saudi Arabia was on its way to thriving again. Their growth was due to the unprecedented volume of planned projects such as large-scale and unique projects. Suddenly, the world was faced with one of the most disrupting events in the last century which had a devastating impact on the construction industry specifically. This paper explores mainly the impact of the COVID-19 pandemic on construction projects in Saudi Arabia. Particularly, this paper explores how the pandemic and its related events contributed to the projects' schedule disturbances. This is because most of the projects rely on manpower and supply chains which were heavily disrupted due to the protective measures. For that, a study was conducted to evaluate the impact on the construction projects in Saudi Arabia, to what extent the schedule projects were affected, and what were the main reasons for the schedule delays. The research relied on a field survey and schedule analysis for 12 projects which resulted in identifying several causes of delays and the delayed durations that the projects in Saudi Arabia were facing. This research allows those in construction fields to identify the main causes of delays in order to avoid or minimize the impact of these issues on future projects.
ContributorsObeid, Muhammad Hasan Hani (Author) / Ariaratnam, Samuel (Thesis advisor) / El Asmar, Mounir (Committee member) / Chong, Oswald (Committee member) / Arizona State University (Publisher)
Created2021
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People with disabilities are underrepresented in the Science, Technology, Engineering, and Math (STEM) workforce (NSF, 2016). One way to increase representation of people with disabilities in STEM fields is by supporting students with disabilities (SWDs) at the undergraduate level. In undergraduate education in the United States, SWDs represent approximately 19%

People with disabilities are underrepresented in the Science, Technology, Engineering, and Math (STEM) workforce (NSF, 2016). One way to increase representation of people with disabilities in STEM fields is by supporting students with disabilities (SWDs) at the undergraduate level. In undergraduate education in the United States, SWDs represent approximately 19% of the undergraduate community (U.S. Census Bureau, 2021). However, SWDs have lower graduation and retention rates. This is particularly true for STEM majors, where SWDs make up about 9% of the STEM community in higher education. The AAC&U has defined a list of High-Impact Practices (HIPs), which are active learning practices and experiences that encourage deep learning by promoting student engagement, and could ultimately support student retention (AAC&U). To date, student-centered disability research has not explored the extent to which SWDs participate in HIPs. We hypothesized that SWDs are less likely than students without disabilities to be involved in HIPs and that students who identify as having severe disabilities would participate in HIPs at lower rates. In this study, we conducted a national survey to examine involvement in HIPs for students with disabilities in STEM. We found that disability status significantly affects the probability of participation in undergraduate research, but is not a significant factor for participation in most other HIPs. We also found that self-reported severity of disability did not significantly impact participation in HIPs, though we observed trends that students reporting higher severity generally reported lower participation in HIPs. Our open-ended responses did indicate that SWDs still faced barriers to participation in HIPs.
ContributorsPais, Danielle (Author) / Brownell, Sara (Thesis director) / Cooper, Katelyn (Committee member) / Barrett, The Honors College (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor)
Created2022-05
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The fast pace of global urbanization makes cities the hotspots of population density and anthropogenic activities, leading to intensive emissions of heat and carbon dioxide (CO2), a primary greenhouse gas. Urban climate scientists have been actively seeking effective mitigation strategies over the past decades, aiming to improve the environmental quality

The fast pace of global urbanization makes cities the hotspots of population density and anthropogenic activities, leading to intensive emissions of heat and carbon dioxide (CO2), a primary greenhouse gas. Urban climate scientists have been actively seeking effective mitigation strategies over the past decades, aiming to improve the environmental quality for urban dwellers. Prior studies have identified the role of urban green spaces in the relief of urban heat stress. Yet little effort was devoted to quantify their contribution to local and regional CO2 budget. In fact, urban biogenic CO2 fluxes from photosynthesis and respiration are influenced by the microclimate in the built environment and are sensitive to anthropogenic disturbance. The high complexity of the urban ecosystem leads to an outstanding challenge for numerical urban models to disentangling and quantifying the interplay between heat and carbon dynamics.This dissertation aims to advance the simulation of thermal and carbon dynamics in urban land surface models, and to investigate the role of urban greening practices and urban system design in mitigating heat and CO2 emissions. The biogenic CO2 exchange in cities is parameterized by incorporating plant physiological functions into an advanced single-layer urban canopy model in the built environment. The simulation result replicates the microclimate and CO2 flux patterns measured from an eddy covariance system over a residential neighborhood in Phoenix, Arizona with satisfactory accuracy. Moreover, the model decomposes the total CO2 flux from observation and identifies the significant CO2 efflux from soil respiration. The model is then applied to quantify the impact of urban greening practices on heat and biogenic CO2 exchange over designed scenarios. The result shows the use of urban greenery is effective in mitigating both urban heat and carbon emissions, providing environmental co-benefit in cities. Furthermore, to seek the optimal urban system design in terms of thermal comfort and CO2 reduction, a multi-objective optimization algorithm is applied to the machine learning surrogates of the physical urban land surface model. There are manifest trade-offs among ameliorating diverse urban environmental indicators despite the co-benefit from urban greening. The findings of this dissertation, along with its implications on urban planning and landscaping management, would promote sustainable urban development strategies for achieving optimal environmental quality for policy makers, urban residents, and practitioners.
ContributorsLi, Peiyuan (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Myint, Soe (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2021
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There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and

There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and anxiety. No studies have examined the relationship between active learning and undergraduate depression. To address this gap in the literature, we conducted hour-long exploratory interviews with 29 students with depression who had taken active learning science courses across six U.S. institutions. We probed what aspects of active learning practices exacerbate or alleviate depressive symptoms and how students’ depression affects their experiences in active learning. We found that aspects of active learning practices exacerbate and alleviate students’ depressive symptoms, and depression negatively impacts students’ experiences in active learning. The underlying aspects of active learning practices that impact students’ depression fall into four overarching categories: inherently social, inherently engaging, opportunities to compare selves to others, and opportunities to validate or invalidate intelligence. We hope that by better understanding the experiences of undergraduates with depression in active learning courses we can create more inclusive learning environments for these students.

ContributorsAraghi, Tala (Author) / Cooper, Katelyn (Thesis director) / Brownell, Sara (Committee member) / Busch, Carly (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05