Browsing by Subject "predictive models"

Now showing 1 - 3 of 3
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    A Novel Framework for Predictive Modeling and Optimization of Powder Bed Fusion Process
    (MDPI, 2021-10) Marrey, Mallikharjun; Malekipour, Ehsan; El-Mounayri, Hazim; Faierson, Eric J.; Agarwal, Mangilal; Mechanical and Energy Engineering, School of Engineering and Technology
    Powder bed fusion (PBF) process is a metal additive manufacturing process which can build parts with any complexity from a wide range of metallic materials. PBF process research has predominantly focused on the impact of only a few parameters on product properties due to the lack of a systematic approach for optimizing a large set of process parameters simultaneously. The pivotal challenges regarding this process require a quantitative approach for mapping the material properties and process parameters onto the ultimate quality; this will then enable the optimization of those parameters. In this study, we propose a two-phase framework for optimizing the process parameters and developing a predictive model for 316L stainless steel material. We also discuss the correlation between process parameters -- i.e., laser specifications -- and mechanical properties and how to achieve parts with high density (> 98%) as well as better ultimate mechanical properties. In this paper, we introduce and test an innovative approach for developing AM predictive models, with a relatively low error percentage of 10.236% that are used to optimize process parameters in accordance with user or manufacturer requirements. These models use support vector regression, random forest regression, and neural network techniques. It is shown that the intelligent selection of process parameters using these models can achieve an optimized density of up to 99.31% with uniform microstructure, which improves hardness, impact strength, and other mechanical properties.
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    Diagnostic Modalities for Non-alcoholic Fatty Liver Disease (NAFLD), Non-alcoholic Steatohepatitis (NASH) and Associated Fibrosis
    (Wiley, 2018) Younossi, Zobair M.; Loomba, Rohit; Anstee, Quentin M.; Rinella, Mary E.; Bugianesi, Elisabetta; Marchesini, Giulio; Neuschwander-Tetri, Brent A.; Serfaty, Lawrence; Negro, Francesco; Caldwell, Stephen H.; Ratziu, Vlad; Corey, Kathleen E.; Friedman, Scott L.; Abdelmalek, Manal F.; Harrison, Stephen A.; Sanyal, Arun J.; Lavine, Joel E.; Mathurin, Philippe; Charlton, Michael R.; Goodman, Zachary D.; Chalasani, Naga P.; Kowdley, Kris V.; George, Jacob; Lindor, Keith; Medicine, School of Medicine
    NAFLD is a spectrum comprised of isolated steatosis, NASH, advanced fibrosis, and cirrhosis. The majority of NAFLD subjects do not have NASH and don't carry a significant risk for adverse outcomes (cirrhosis and mortality). Globally, the prevalence of NAFLD is approximately 25%. In Asia, a gradient of high prevalence rates to low rates are noted from urban to rural areas. Given the prevalence of NAFLD, the clinical and economic burden of NAFLD and NASH can be substantial. With increasing recognition as an important liver disease, the diagnosis of NASH still requires a liver biopsy which is suboptimal. Although liver biopsy is the most accurate modality to diagnose and stage the severity of NASH, it suffers from being invasive, costly, associated with potential complications, and plagued with interobserver variability of individual pathologic features. A number of non-invasive modalities to diagnose NASH and stage liver fibrosis are being developed. These include predictive models (NAFLD fibrosis score) and serum biomarkers such as Enhanced Liver Fibrosis, (ELF). Other tests are based on radiologic techniques such as transient or MR elastography (MRE) which are used to estimate liver stiffness as a potential surrogate of hepatic fibrosis. Although a dynamic field of research, most of these diagnostic modalities have AUROC between 0.76 to 0.90% with MRE having the best predictive performance. In summary, developing accurate, safe and easily accessible non-invasive modalities to accurately diagnose and monitor NASH and associated fibrosis is of utmost importance in clinical practice and clinical research. These tests are not only important to risk stratify subjects at the greatest risk for progressive liver disease but to serve as appropriate surrogate endpoints for therapeutic clinical trials of NASH.
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    The Discursive and Practical Influence of Spirituality on Civic Engagement
    (Wiley, 2022-06) Steensland, Brian; King, David P.; Duffy, Barbara J.; Sociology, School of Liberal Arts
    Religion has long been recognized as promoting civic engagement. Recent declines in organized religion and growing interest in spirituality raise the question of whether spirituality might also promote civic engagement. Using data from a new nationally representative survey, we assess the independent and joint influence of spirituality and religion on civic life. We find that 40% of respondents perceive spirituality as influencing their civic engagement. Spirituality's influence typically appears in tandem with religion, but when spirituality and religion are distinct, the influence of spirituality is greater and more prevalent. Using two distinct measures, we assess the influence of spirituality on civic engagementat both discursive and practical levels. We find positive associations for both. Spirituality is both a conscious influence and tacit resource in civic life. We close by briefly outlining an agenda for better understanding socially engaged spirituality.