Matching Items (294)
Description
Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action.
ContributorsWolf, Tanja (Author) / Chuang, Wen-Ching (Author) / McGregor, Glenn (Author) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-10-23
Description
The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a probabilistic analysis to describe the variation between replicates of the experimental process, and analyze reliability of a structural system based on that model. In order to help design the EDP software to perform the full analysis, the probabilistic and regression modeling aspects of this analysis have been explored. The focus has been on creating and analyzing probabilistic models for the data, adding multivariate and nonparametric fits to raw data, and developing computational techniques that allow for these methods to be properly implemented within EDP. For creating a probabilistic model of replicate data, the normal, lognormal, gamma, Weibull, and generalized exponential distributions have been explored. Goodness-of-fit tests, including the chi-squared, Anderson-Darling, and Kolmogorov-Smirnoff tests, have been used in order to analyze the effectiveness of any of these probabilistic models in describing the variation of parameters between replicates of an experimental test. An example using Young's modulus data for a Kevlar-49 Swath stress-strain test was used in order to demonstrate how this analysis is performed within EDP. In order to implement the distributions, numerical solutions for the gamma, beta, and hypergeometric functions were implemented, along with an arbitrary precision library to store numbers that exceed the maximum size of double-precision floating point digits. To create a multivariate fit, the multilinear solution was created as the simplest solution to the multivariate regression problem. This solution was then extended to solve nonlinear problems that can be linearized into multiple separable terms. These problems were solved analytically with the closed-form solution for the multilinear regression, and then by using a QR decomposition to solve numerically while avoiding numerical instabilities associated with matrix inversion. For nonparametric regression, or smoothing, the loess method was developed as a robust technique for filtering noise while maintaining the general structure of the data points. The loess solution was created by addressing concerns associated with simpler smoothing methods, including the running mean, running line, and kernel smoothing techniques, and combining the ability of each of these methods to resolve those issues. The loess smoothing method involves weighting each point in a partition of the data set, and then adding either a line or a polynomial fit within that partition. Both linear and quadratic methods were applied to a carbon fiber compression test, showing that the quadratic model was more accurate but the linear model had a shape that was more effective for analyzing the experimental data. Finally, the EDP program itself was explored to consider its current functionalities for processing data, as described by shear tests on carbon fiber data, and the future functionalities to be developed. The probabilistic and raw data processing capabilities were demonstrated within EDP, and the multivariate and loess analysis was demonstrated using R. As the functionality and relevant considerations for these methods have been developed, the immediate goal is to finish implementing and integrating these additional features into a version of EDP that performs a full streamlined structural analysis on experimental data.
ContributorsMarkov, Elan Richard (Author) / Rajan, Subramaniam (Thesis director) / Khaled, Bilal (Committee member) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Agrobacterium tumefaciens has the ability to transfer its tumor inducing (Ti) plasmid into plant cells. In the last decade, agroinfiltration of Nicotiana benthamiana plants has shown promising results for recombinant protein production. However, A. tumefaciens produce endotoxins in the form of lipopolysaccharides (LPS), a component of their outer membrane that can induce organ failure and septic shock. Therefore, we aimed to detoxify A. tumefaciens by modifying their Lipid A structure, the toxic region of LPS, via mutating the genes for lipid A biosynthesis. Two mutant strains of A. tumefaciens were infiltrated into N. benthamiana stems to test for tumor formation to ensure that the detoxifying process did not compromise the ability of gene transfer. Our results demonstrated that A. tumefaciens with both single and double mutations retained the ability to form tumors. Thus, these mutants can be utilized to generate engineered A. tumefaciens strains for the production of plant-based pharmaceuticals with low endotoxicity.
ContributorsHaseefa, Fathima (Author) / Chen, Qiang (Thesis director) / Mason, Hugh (Committee member) / Hurtado, Jonathan (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Skin elasticity, a key indicator of skin health, is influenced by various factors including diet and body composition. This study, led by Myka Williams as part of her Barrett, The Honors College Thesis Project at Arizona State University under the guidance of Dr. Carol Johnston and Dr. Sandy Mayol-Kreiser, investigates the relationship between diet—specifically vegetarian and omnivorous patterns—and skin elasticity. Utilizing the ElastiMeter from Delfin Technologies, we assessed the skin elasticity of 38 individuals from the ASU community. Our findings revealed no significant difference in skin elasticity between the dietary groups. However, intriguing correlations emerged between participants' Body Mass Index (BMI) and skin elasticity. These initial findings suggest the potential influence of body composition on skin health, warranting further research with additional parameters to strengthen and expand upon these observations.
ContributorsWilliams, Myka (Author) / Johnston, Carol (Thesis director) / Mayol-Kreiser, Sandy (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2024-05