Matching Items (259)
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Description

This poster, first presented at the National Academy of Engineers Frontiers of Engineering Education workshop in Long Beach CA in Oct 2012, explains the necessity of developing engineering cognition, affection, and conation by completing the whole Kolb Learning Cycle. It emphasizes experience and reflection as essential, but overlooked, aspects engineering

This poster, first presented at the National Academy of Engineers Frontiers of Engineering Education workshop in Long Beach CA in Oct 2012, explains the necessity of developing engineering cognition, affection, and conation by completing the whole Kolb Learning Cycle. It emphasizes experience and reflection as essential, but overlooked, aspects engineering education with the potential to create transformation of the student.

ContributorsSeager, Thomas (Author) / Nies, Loring (Author) / Nagel, Robert (Author) / Yim, Mark (Author) / Canfield, Stephen (Author) / Kellar, J. J. (Jon J.) (Author)
Created2012-10-24
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ContributorsFraser, Andrew (Author) / Linke, Marcus (Author) / Reilly, Russ (Author) / Rosales, Justin (Author) / Rossman, Daniel (Author) / Staffnik, Abbey (Author) / Tarin, Mohammed (Author) / Seager, Thomas (Author)
Created2012-08-14
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ContributorsFraser, Andrew (Author) / Linke, Marcus (Author) / Reilly, Russ (Author) / Rosales, Justin (Author) / Staffnik, Abbey (Author) / Tarin, Mohammed (Author) / Tijerino, Berman (Author) / Wellman, Robert (Author) / Seager, Thomas (Teacher)
Created2012-08-10
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Description

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.

Objectives:

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.

Objectives: We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.

Methods: A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups’ findings.

Results: We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis.

Conclusions: We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts.

ContributorsMalloy, Timothy F. (Author) / Zaunbrecher, Virginia M. (Author) / Batteate, Christina M. (Author) / Blake, Ann (Author) / Carroll, William F. (Author) / Corbett, Charles J. (Author) / Hansen, Steffen Foss (Author) / Lempert, Robert J. (Author) / Linkov, Igor (Author) / McFadden, Roger (Author) / Moran, Kelly D. (Author) / Olivetti, Elsa (Author) / Ostrom, Nancy K. (Author) / Romero, Michelle (Author) / Schoenung, Julie M. (Author) / Seager, Thomas (Author) / Sinsheimer, Peter (Author) / Thayer, Kristina A. (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2017-06-13
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Description

Vegetarian diets are associated with factors that may not support bone health, such as low body mass and low intakes of protein; yet, these diets are alkaline, a factor that favors bone mineral density (BMD). This study compared the correlates of BMD in young, non-obese adults consuming meat-based (n =

Vegetarian diets are associated with factors that may not support bone health, such as low body mass and low intakes of protein; yet, these diets are alkaline, a factor that favors bone mineral density (BMD). This study compared the correlates of BMD in young, non-obese adults consuming meat-based (n = 27), lacto-ovo vegetarian (n = 27), or vegan (n = 28) diets for ≥1 year. A 24 h diet recall, whole body DXA scan, 24 h urine specimen, and fasting blood sample were collected from participants. BMD did not differ significantly between groups. Protein intake was reduced ~30% in individuals consuming lacto-ovo and vegan diets as compared to those consuming meat-based diets (68 ± 24, 69 ± 29, and 97 ± 47 g/day respectively, p = 0.006); yet dietary protein was only associated with BMD for those following vegan diets. Urinary pH was more alkaline in the lacto-ovo and vegan groups versus omnivores (6.5 ± 0.4, 6.7 ± 0.4, and 6.2 ± 0.4 respectively, p = 0.003); yet urinary pH was associated with BMD in omnivores only. These data suggest that plant-based diets are not detrimental to bone in young adults. Moreover, diet prescriptions for bone health may vary among diet groups: increased fruit and vegetable intake for individuals with high meat intakes and increased plant protein intake for individuals who follow a vegetarian diet plan.

ContributorsKnurick, Jessica (Author) / Johnston, Carol (Author) / Wherry, Sarah J. (Author) / Aguayo, Izayadeth (Author) / College of Health Solutions (Contributor)
Created2015-05-11
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Description

In spite of well-documented health benefits of vegetarian diets, less is known regarding the effects of these diets on athletic performance. In this cross-sectional study, we compared elite vegetarian and omnivore adult endurance athletes for maximal oxygen uptake (VO2 max) and strength. Twenty-seven vegetarian (VEG) and 43 omnivore (OMN) athletes

In spite of well-documented health benefits of vegetarian diets, less is known regarding the effects of these diets on athletic performance. In this cross-sectional study, we compared elite vegetarian and omnivore adult endurance athletes for maximal oxygen uptake (VO2 max) and strength. Twenty-seven vegetarian (VEG) and 43 omnivore (OMN) athletes were evaluated using VO2 max testing on the treadmill, and strength assessment using a dynamometer to determine peak torque for leg extensions. Dietary data were assessed using detailed seven-day food logs. Although total protein intake was lower among vegetarians in comparison to omnivores, protein intake as a function of body mass did not differ by group (1.2 ± 0.3 and 1.4 ± 0.5 g/kg body mass for VEG and OMN respectively, p = 0.220). VO2 max differed for females by diet group (53.0 ± 6.9 and 47.1 ± 8.6 mL/kg/min for VEG and OMN respectively, p < 0.05) but not for males (62.6 ± 15.4 and 55.7 ± 8.4 mL/kg/min respectively). Peak torque did not differ significantly between diet groups. Results from this study indicate that vegetarian endurance athletes’ cardiorespiratory fitness was greater than that for their omnivorous counterparts, but that peak torque did not differ between diet groups. These data suggest that vegetarian diets do not compromise performance outcomes and may facilitate aerobic capacity in athletes.

ContributorsLynch, Heidi (Author) / Wharton, Christopher (Author) / Johnston, Carol (Author) / College of Health Solutions (Contributor)
Created2016-11-15
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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

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
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Description

Resilient infrastructure research has produced a myriad of conflicting definitions and analytic frameworks, highlighting the difficulty of creating a foundational theory that informs disciplines as diverse as business, engineering, ecology, and disaster risk reduction. Nevertheless, there is growing agreement that resilience is a desirable property for infrastructure systems – i.e.,

Resilient infrastructure research has produced a myriad of conflicting definitions and analytic frameworks, highlighting the difficulty of creating a foundational theory that informs disciplines as diverse as business, engineering, ecology, and disaster risk reduction. Nevertheless, there is growing agreement that resilience is a desirable property for infrastructure systems – i.e., that more resilience is always better. Unfortunately, this view ignore that the fact that a single concept of resilience is insufficient to ensure effective performance under diverse and volatile stresses. Scholarship in resilience engineering has identified at least four irreducible resilience concepts, including: rebound, robustness, graceful extensibility, and sustained adaptability.

In this paper, we clarify the meaning of the word resilience and its use, explain the advantages of the pluralistic approach to advancing resilience theory, and clarify two of the four conceptual understandings: robustness and graceful extensibility. Furthermore, we draw upon examples in electric power, transportation, and water systems that illustrate positive and negative cases of resilience in infrastructure management and crisis response. The following conclusions result:

1. Robustness and graceful extensibility are different strategies for resilience that draw upon different system characteristics.
2. Neither robustness nor extensibility can prevent all hazards.
3. While systems can perform both strategies simultaneously, their drawbacks are different.

Robust infrastructure systems fail when policies and procedures become stale, or when faced with overwhelming surprise. Extensible systems fail when a lack of coordination or exhaustion of resources results from decompensation. Consequently, resilience is found neither only in robustness, nor only in extensibility, but in the capacity apply both and switch between them at will.

ContributorsEisenberg, Daniel A. (Author) / Seager, Thomas (Author) / Hinrichs, Margaret M. (Author) / Kim, Yeowon (Author) / Wender, Benjamin A. (Author) / Markolf, Samuel A. (Author) / Thomas, John E. (Author) / Chester, Mikhail Vin (Author) / Alderson, David L. (Author) / Park, Jeryang (Author) / Linkov, Igor (Author) / Clark, Susan Spierre (Author) / Woods, David (Author)
Created2017-07-17
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

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