Matching Items (114)
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
This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment.
ContributorsDavis, Vanessa Brooke (Co-author) / Bucklin, Lindsay (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This thesis examines Care Not Cash, a welfare reform measure that replaced traditional cash General Assistance program payments for homeless persons in San Francisco with in-kind social services. Unlike most welfare reform measures, proponents framed Care Not Cash as a progressive policy, aimed at expanding social services and government care for this vulnerable population. Drawing on primary and secondary documents, as well as interviews with homelessness policy experts, this thesis examines the historical and political success of Care Not Cash, and explores the potential need for implementation of a similar program in Phoenix, Arizona.
ContributorsMcCutcheon, Zachary Ryan (Author) / Lucio, Joanna (Thesis director) / Williams, David (Committee member) / Bretts-Jamison, Jake (Committee member) / School of Public Affairs (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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
Patterning technologies for micro/nano-structures have been essentially used in a variety of discipline research areas, including electronics, optics, material science, and biotechnology. Therefore their importance has dramatically increased over the past decades. This dissertation presents various advanced patterning processes utilizing cross-discipline technologies, e.g., photochemical deposition, transfer printing (TP), and nanoimprint lithography (NIL), to demonstrate inexpensive, high throughput, and scalable manufacturing for advanced optical applications.
The polymer-assisted photochemical deposition (PPD) method is employed in the form of additive manufacturing (AM) to print ultra-thin (< 5 nm) and continuous film in micro-scaled (> 6.5 μm) resolution. The PPD film acts as a lossy material in the Fabry-Pérot cavity structures and generates vivid colored images with a micro-scaled resolution by inducing large modulation of reflectance. This PPD-based structural color printing performs without photolithography and vacuum deposition in ambient and room-temperature conditions, which enables an accessible and inexpensive process (Chapter 1).
In the TP process, germanium (Ge) is used as the nucleation layer of noble metallic thin films to prevent structural distortion and improve surface morphology. The developed Ge-assisted transfer printing (GTP) demonstrates its feasibility transferring sub-100 nm features with up to 50 nm thickness in a centimeter scale. The GTP is also capable of transferring arbitrary metallic nano-apertures with minimal pattern distortion, providing relatively less expensive, simpler, and scalable manufacturing (Chapter 2).
NIL is employed to fabricate the double-layered chiral metasurface for polarimetric imaging applications. The developed NIL process provides multi-functionalities with a single NIL, i.e., spacing layer, planarized surface, and formation of dielectric gratings, respectively, which significantly reduces fabrication processing time and potential cost by eliminating several steps in the conventional fabrication process. During the integration of two metasurfaces, the Moiré fringe based alignment method is employed to accomplish the alignment accuracy of less than 200 nm in both x- and y-directions, which is superior to conventional photolithography. The dramatically improved optical performance, e.g., highly improved circular polarization extinction ratio (CPER), is also achieved with the developed NIL process (Chapter 3).
ContributorsChoi, Shinhyuk (Author) / Wang, Chao (Thesis advisor) / Yu, Hongbin (Committee member) / Holman, Zachary (Committee member) / Hwa, Yoon (Committee member) / Arizona State University (Publisher)
Created2023
Description
High throughput transcriptome data analysis like Single-cell Ribonucleic Acid sequencing (scRNA-seq) and Circular Ribonucleic Acid (circRNA) data have made significant breakthroughs, especially in cancer genomics. Analysis of transcriptome time series data is core in identifying time point(s) where drastic changes in gene transcription are associated with homeostatic to non-homeostatic cellular transition (tipping points). In Chapter 2 of this dissertation, I present a novel cell-type specific and co-expression-based tipping point detection method to identify target gene (TG) versus transcription factor (TF) pairs whose differential co-expression across time points drive biological changes in different cell types and the time point when these changes are observed. This method was applied to scRNA-seq data sets from a SARS-CoV-2 study (18 time points), a human cerebellum development study (9 time points), and a lung injury study (18 time points). Similarly, leveraging transcriptome data across treatment time points, I developed methodologies to identify treatment-induced and cell-type specific differentially co-expressed pairs (DCEPs). In part one of Chapter 3, I presented a pipeline that used a series of statistical tests to detect DCEPs. This method was applied to scRNA-seq data of patients with non-small cell lung cancer (NSCLC) sequenced across cancer treatment times. However, this pipeline does not account for correlations among multiple single cells from the same sample and correlations among multiple samples from the same patient. In Part 2 of Chapter 3, I presented a solution to this problem using a mixed-effect model. In Chapter 4, I present a summary of my work that focused on the cross-species analysis of circRNA transcriptome time series data. I compared circRNA profiles in neonatal pig and mouse hearts, identified orthologous circRNAs, and discussed regulation mechanisms of cardiomyocyte proliferation and myocardial regeneration conserved between mouse and pig at different time points.
ContributorsNyarige, Verah Mocheche (Author) / Liu, Li (Thesis advisor) / Wang, Junwen (Thesis advisor) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (positron emission tomography (PET)). And one of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research projects focuses in the AD pathophysiological progress.
In this dissertation, I proposed three novel machine learning and statistical models to examine subtle aspects of the hippocampal morphometry from MRI that are associated with Aβ /tau burden in the brain, measured using PET images. The first model is a novel unsupervised feature reduction model to generate a low-dimensional representation of hippocampal morphometry for each individual subject, which has superior performance in predicting Aβ/tau burden in the brain. The second one is an efficient federated group lasso model to identify the hippocampal subregions where atrophy is strongly associated with abnormal Aβ/Tau. The last one is a federated model for imaging genetics, which can identify genetic and transcriptomic influences on hippocampal morphometry. Finally, I stated the results of these three models that have been published or submitted to peer-reviewed conferences and journals.
ContributorsWu, Jianfeng (Author) / Wang, Yalin (Thesis advisor) / Li, Baoxin (Committee member) / Liang, Jianming (Committee member) / Wang, Junwen (Committee member) / Wu, Teresa (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
Current methods for quantifying microplastics via LC-MS/MS analysis have been adapted from environmental monitoring protocols and are often inadequate for sampling within complex matrices. This study explores the application of liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the detection of microplastics. The initial phase of this research utilized pork kidney samples to establish a baseline for background and efficacy of sample processing. These findings underscore the complexity of developing a sensitive and specific analytical technique for microplastics in tissues. The observed discrepancies in contamination and replicability between samples emphasize the need for continual method optimization.
ContributorsBabbrah, Ayesha (Author) / Halden, Rolf (Thesis director) / Newell, Melanie (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2023-12
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