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- Language: English
- Creators: Ira A. Fulton Schools of Engineering
Description
Eigenvalues of the 3D critical point equation (∇u)ν = λν are normally computed numerically. In the letter, we present analytic solutions for 3D swirling strength in both compressible and incompressible flows. The solutions expose functional dependencies that cannot be seen in numerical solutions. To illustrate, we study the difference between using fluctuating and total velocity gradient tensors for vortex identification. Results show that mean shear influences vortex detection and that distortion can occur, depending on the strength of mean shear relative to the vorticity at the vortex center.
ContributorsChen, Huai (Author) / Adrian, Ronald (Author) / Zhong, Qiang (Author) / Wang, Xingkui (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-08-01
Description
The flexural behavior of epoxies was investigated by performing mechanical tests and applying statistical Weibull theory and analytical methods to the results. The effects of loading systems and environmental conditions were also considered. Three kinds of epoxies were studied: Epon E863, PRI 2002, and PR520. In total, 53 three-point-bending (3PB) Epon E863 samples and 26 3PB PR520 were tested immediately after curing, together with 26 four-point-bending (4PB) PRI2002 samples stored at 60°C and 90% Rh for 48 weeks. The Weibull parameters were estimated using both linear regression and the moments method. The statistical character of the Weibull model leads to uncertainty in the evaluated parameters, even for a large number of experiments. This study analyzed the ratio of flexural strength to tensile strength in bulk epoxy resin polymers. An analytical method previously developed by the authors to study the relationship between uniaxial tension/compression stress-strain curves and flexural load-deflection response was used to obtain the ratio. The results show that the Weibull model overpredicted the aforementioned ratio in different load arrangements.
ContributorsYekani Fard, Masoud (Author) / Raji, B. (Author) / Chattopadhyay, Aditi (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-12-01
Description
Identification of early damage in polymer composites is of great importance. We have incorporated cyclobutane-containing cross-linked polymers into an epoxy matrix, studied the effect on thermal and mechanical properties, and, more importantly, demonstrated early damage detection through mechanically induced fluorescence generation. Two cinnamate derivatives, 1,1,1-tris(cinnamoyloxymethyl) ethane (TCE) and poly(vinyl cinnamate) (PVCi), were photoirradiated to produce cyclobutane-containing polymer. The effects on the thermal and mechanical properties with the addition of cyclobutane-containing polymer into epoxy matrix were investigated. The emergence of cracks was detected by fluorescence at a strain level just beyond the yield point of the polymer blends, and the fluorescence intensified with accumulation of strain. Overall, the results show that damage can be detected through fluorescence generation along crack propagation.
ContributorsZou, Jin (Author) / Liu, Yingtao (Author) / Shan, Bohan (Author) / Chattopadhyay, Aditi (Author) / Dai, Lenore (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-09-01
Description
The impact of increasing penetration of converter control-based generators (CCBGs) in a large-scale power system is assessed through a model based small signal stability analysis. Three test bed cases for the years 2010, 2020, and 2022 of the Western Electricity Coordinating Council (WECC) in the United States are used for the analysis. Increasing penetration of wind-based Type 3 and wind-based Type 4 and PV Solar CCBGs is used in the tests. The participation and interaction of CCBGs and synchronous generators in traditional electromechanical interarea modes is analyzed. Two new types of modes dominated by CCBGs are identified. The characteristics of these new modes are described and compared to electromechanical modes in the frequency domain. An examination of the mechanism of the interaction between the CCBG control states and the synchronous generator control states is presented and validated through dynamic simulations. Actual system and forecast load data are used throughout.
ContributorsQuintero, Jaime (Author) / Vittal, Vijay (Author) / Heydt, Gerald (Author) / Zhang, Hui (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2014-09-01
Description
The Physics and Chemistry of Surfaces and Interfaces conference has maintained a focus on the interfacial and surface properties of materials since its initiation in 1974. The conference continues to be a major force in this field, bringing together scientists from a variety of disciplines to focus upon the science of interfaces and surfaces. Here, a historical view of the development of the conference and a discussion of some of the themes that have been focal points for many years are presented.
ContributorsFerry, David (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2013
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Psychologists report effect sizes in randomized controlled trials to facilitate interpretation and inform clinical or policy guidance. Since commonly used effect size measures (e.g., standardized mean difference) are not sensitive to heterogeneous treatment effects, methodologists have suggested the use of an alternative effect size δ, a between-subjects causal parameter describing the probability that the outcome of a random participant in the treatment group is better than the outcome of another random participant in the control group. Although this effect size is useful, researchers could mistakenly use δ to describe its within-subject analogue, ψ, the probability that an individual will do better under the treatment than the control. Hand’s paradox describes the situation where ψ and δ are on opposing sides of 0.5: δ may imply most are helped whereas the (unknown) underlying ψ indicates that most are harmed by the treatment. The current study used Monte Carlo simulations to investigate plausible situations under which Hand’s paradox does and does not occur, tracked the magnitude of the discrepancy between ψ and δ, and explored whether the size of the discrepancy could be reduced with a relevant covariate. The findings suggested that although the paradox should not occur under bivariate normal data conditions in the population, there could be sample cases with the paradox. The magnitude of the discrepancy between ψ and δ depended on both the size of the average treatment effect and the underlying correlation between the potential outcomes, ρ. Smaller effects led to larger discrepancies when ρ < 0 and ρ = 1, whereas larger effects led to larger discrepancies when 0 < ρ < 1. It was useful to consider a relevant covariate when calculating ψ and δ. Although ψ and δ were still discrepant within covariate levels, results indicated that conditioning upon relevant covariates is still useful in describing heterogeneous treatment effects.
ContributorsLiu, Xinran (Author) / Anderson, Samantha F (Thesis advisor) / McNeish, Daniel (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2023
Description
Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers can employ diverse strategies when studying individual differences in multiple mediation pathways, including individual fit measures and analysis of residuals. This dissertation investigates the use of individual residuals and fit measures to identify individual differences in multiple mediation pathways. More specifically, this study focuses on mediation model residuals in a heterogeneous population in which some people experience indirect effects through one mediator and others experience indirect effects through a different mediator. A simulation study investigates 162 conditions defined by effect size and sample size for three proposed methods: residual differences, delta z, and generalized Cook’s distance. Results indicate that analogs of Type 1 error rates are generally acceptable for the method of residual differences, but statistical power is limited. Likewise, neither delta z nor gCd could reliably distinguish between contrasts that had true effects and those that did not. The outcomes of this study reveal the potential for statistical measures of individual mediation. However, limitations related to unequal subpopulation variances, multiple dependent variables, the inherent relationship between direct effects and unestimated indirect effects, and minimal contrast effects require more research to develop a simple method that researchers can use on single data sets.
ContributorsSmyth, Heather Lynn (Author) / MacKinnon, David (Thesis advisor) / Tein, Jenn-Yun (Committee member) / McNeish, Daniel (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Food insecurity is an economic and social condition involving limited or uncertain access to food. The problem of food insecurity in communities is influenced by economic conditions, food deserts, and barriers to accessing healthy food. Individuals experiencing food insecurity often endure concurrent problems of financial instability, hunger, and poor mental and physical health. Public and non-profit services in the U.S., such as the federally supported Supplemental Nutrition Assistance Program (SNAP) and community food banks, provide food-related assistance to individuals who are at a high risk of experiencing food insecurity. Unfortunately, many individuals who qualify for these services still experience food insecurity due to barriers preventing them from accessing food, which may include inadequate finances, transportation, skills, and information. Effective approaches for removing barriers that prevent individuals from accessing food are needed to mitigate the increased risk of hunger, nutritional deficiencies, and chronic disease among vulnerable populations. This dissertation tested a novel food insecurity intervention using informational nudges to promote food security through the elimination of information barriers to accessing food. The intervention used in this mixed-methods feasibility study consisted of informational nudges in the form of weekly text messages that were sent to food pantry clients experiencing food insecurity. The study aims were to test the efficacy and acceptability of the intervention by examining whether the informational nudges could enhance food pantry utilization, increase SNAP registration, and promote food security. Quantitative study results showed a lower prevalence of food insecurity in the intervention group than the control group. Qualitative findings revealed how the intervention group found the text messages to be helpful and informative. These study findings can enhance future food insecurity interventions aiming to eliminate barriers that prevent individuals who are food insecure from accessing healthy food.
ContributorsRoyer, Michael F. (Author) / Wharton, Christopher (Thesis advisor) / Buman, Matthew (Committee member) / Der Ananian, Cheryl (Committee member) / MacKinnon, David (Committee member) / Ohri-Vachaspati, Punam (Committee member) / Arizona State University (Publisher)
Created2023
Description
Longitudinal recursive partitioning (LRP) is a tree-based method for longitudinal data. It takes a sample of individuals that were each measured repeatedly across time, and it splits them based on a set of covariates such that individuals with similar trajectories become grouped together into nodes. LRP does this by fitting a mixed-effects model to each node every time that it becomes partitioned and extracting the deviance, which is the measure of node purity. LRP is implemented using the classification and regression tree algorithm, which suffers from a variable selection bias and does not guarantee reaching a global optimum. Additionally, fitting mixed-effects models to each potential split only to extract the deviance and discard the rest of the information is a computationally intensive procedure. Therefore, in this dissertation, I address the high computational demand, variable selection bias, and local optimum solution. I propose three approximation methods that reduce the computational demand of LRP, and at the same time, allow for a straightforward extension to recursive partitioning algorithms that do not have a variable selection bias and can reach the global optimum solution. In the three proposed approximations, a mixed-effects model is fit to the full data, and the growth curve coefficients for each individual are extracted. Then, (1) a principal component analysis is fit to the set of coefficients and the principal component score is extracted for each individual, (2) a one-factor model is fit to the coefficients and the factor score is extracted, or (3) the coefficients are summed. The three methods result in each individual having a single score that represents the growth curve trajectory. Therefore, now that the outcome is a single score for each individual, any tree-based method may be used for partitioning the data and group the individuals together. Once the individuals are assigned to their final nodes, a mixed-effects model is fit to each terminal node with the individuals belonging to it.
I conduct a simulation study, where I show that the approximation methods achieve the goals proposed while maintaining a similar level of out-of-sample prediction accuracy as LRP. I then illustrate and compare the methods using an applied data.
I conduct a simulation study, where I show that the approximation methods achieve the goals proposed while maintaining a similar level of out-of-sample prediction accuracy as LRP. I then illustrate and compare the methods using an applied data.
ContributorsStegmann, Gabriela (Author) / Grimm, Kevin (Thesis advisor) / Edwards, Michael (Committee member) / MacKinnon, David (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2019