scholarly journals A unique computational algorithm to simulate probabilistic multi-factor interaction model complex material point behavior

2009 ◽  
Author(s):  
C. C. Chamis ◽  
G. H. Abumeri
Keyword(s):  
Computational Algorithm ◽  
Interaction Model ◽  
Material Point ◽  
Complex Material ◽  
Model Complex ◽  
Factor Interaction

scholarly journals Higher-order clinical risk factor interaction analysis for overall mortality in maintenance hemodialysis patients

2020 ◽  
Vol 11 ◽  
pp. 204062232094906
Author(s):  
Cheng-Hong Yang ◽  
Sin-Hua Moi ◽  
Li-Yeh Chuang ◽  
Jin-Bor Chen
Keyword(s):  
Interaction Analysis ◽  
Interaction Model ◽  
Higher Order ◽  
Survival Outcome ◽  
Maintenance Hemodialysis ◽  
Order Interaction ◽  
Statistical Approaches ◽  
The Impact ◽  
Factor Interaction ◽  
Overall Mortality

Background and Aims: In Taiwan, approximately 90% of patients with end-stage renal disease receive maintenance hemodialysis. Although studies have reported the survival predictability of multiclinical factors, the higher-order interactions among these factors have rarely been discussed. Conventional statistical approaches such as regression analysis are inadequate for detecting higher-order interactions. Therefore, this study integrated receiver operating characteristic, logistic regression, and balancing functions for adjusting the ratio in risk classes and classification errors for imbalanced cases and controls using multifactor-dimensionality reduction (MDR-ER) analyses to examine the impact of interaction effects between multiclinical factors on overall mortality in patients on maintenance hemodialysis. Meterials and Methods: In total, 781 patients who received outpatient hemodialysis dialysis three times per week before 1 January 2009 were included; their baseline clinical factor and mortality outcome data were retrospectively collected using an approved data protocol (201800595B0). Results: Consistent with conventional statistical approaches, the higher-order interaction model could indicate the impact of potential risk combination unique to patients on maintenance hemodialysis on the survival outcome, as described previously. Moreover, the MDR-based higher-order interaction model facilitated higher-order interaction effect detection among multiclinical factors and could determine more detailed mortality risk characteristics combinations. Conclusion: Therefore, higher-order clinical risk interaction analysis is a reasonable strategy for detecting non-traditional risk factor interaction effects on survival outcome unique to patients on maintenance hemodialysis and thus clinically achieving whole-scale patient care.

A Novel Material Point Method Based Needle-Tissue Interaction Model

2019 ◽  
Author(s):  
Murong Li ◽  
Yong Lei
Keyword(s):  
Material Point Method ◽  
Interaction Model ◽  
Needle Insertion ◽  
Friction Model ◽  
Material Point ◽  
Contact Forces ◽  
Point Method ◽  
Virtual Surgery ◽  
Tissue Interaction ◽  
Novel Material

Abstract Needle-tissue interaction model plays an important role in virtual surgery training, pre-intervention planning and intra-intervention guidance. Traditionally, finite element methods (FEM) had been a primary and popular way for simulation modeling. However, FEM, as a mesh-based numerical calculations, is likely to encounter numerical difficulties due to mesh distortion as needle insertion process includes damage, fracture and penetration. In this work, a novel material point method (MPM) based needle-tissue interaction model is proposed, which combines the advantages of Lagrangian and Euler methods. A simplified contact algorithm and friction model are integrated to calculate contact forces as well as the resultant tissue deformations. Both preliminary contact forces and deformation results are compared with test experiments, which show that the maximum and mean displacement errors are 0.9768mm and 0.5134mm, respectively while the mean relative errors of force is 14%. This preliminary result demonstrates that MPM has great potential in needle-tissue interaction modeling.

scholarly journals Genetic polymorphisms of key enzymes in folate metabolism affect the efficacy of folate therapy in patients with hyperhomocysteinaemia

2018 ◽  
Vol 119 (8) ◽  
pp. 887-895 ◽  
Author(s):  
Binghui Du ◽  
Huizi Tian ◽  
Dandan Tian ◽  
Chengda Zhang ◽  
Wenhua Wang ◽  
...  
Keyword(s):  
Folic Acid ◽  
Interaction Model ◽  
Folate Metabolism ◽  
Efficacy Rate ◽  
Environment Interaction ◽  
Optimal Model ◽  
Acid Therapy ◽  
Gene Environment ◽  
History Of ◽  
Factor Interaction

AbstractThe aim of this study is to analyse the efficacy rate of folate for the treatment of hyperhomocysteinaemia (HHcy) and to explore how folate metabolism-related gene polymorphisms change its efficacy. This study also explored the effects of gene–gene and gene–environment interactions on the efficacy of folate. A prospective cohort study enrolling HHcy patients was performed. The subjects were treated with oral folate (5 mg/d) for 90 d. We analysed the efficacy rate of folate for the treatment of HHcy by measuring homocysteine (Hcy) levels after treatment. Unconditioned logistic regression was conducted to analyse the association between SNP and the efficacy of folic acid therapy for HHcy. The efficacy rate of folate therapy for HHcy was 56·41 %. The MTHFR rs1801133 CT genotype, TT genotype and T allele; the MTHFR rs1801131 AC genotype, CC genotype and C allele; the MTRR rs1801394 GA genotype, GG genotype and G allele; and the MTRR rs162036 AG genotype and AG+GG genotypes were associated with the efficacy of folic acid therapy for HHcy (P<0·05). No association was seen between other SNP and the efficacy of folic acid. The optimal model of gene–gene interactions was a two-factor interaction model including rs1801133 and rs1801394. The optimal model of gene–environment interaction was a three-factor interaction model including history of hypertension, history of CHD and rs1801133. Folate supplementation can effectively decrease Hcy level. However, almost half of HHcy patients failed to reach the normal range. The efficacy of folate therapy may be genetically regulated.

scholarly journals A glacier–ocean interaction model for tsunami genesis due to iceberg calving

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Joshuah Wolper ◽  
Ming Gao ◽  
Martin P. Lüthi ◽  
Valentin Heller ◽  
Andreas Vieli ◽  
...  
Keyword(s):  
Large Scale ◽  
Hybrid Approach ◽  
Interaction Model ◽  
Greenland Ice Sheet ◽  
Material Point ◽  
Mitigation Measures ◽  
Coastal Regions ◽  
Outlet Glacier ◽  
Subsequent Propagation ◽  
Fluid Interactions

AbstractGlaciers calving icebergs into the ocean significantly contribute to sea-level rise and can trigger tsunamis, posing severe hazards for coastal regions. Computational modeling of such multiphase processes is a great challenge involving complex solid–fluid interactions. Here, a new continuum damage Material Point Method has been developed to model dynamic glacier fracture under the combined effects of gravity and buoyancy, as well as the subsequent propagation of tsunami-like waves induced by released icebergs. We reproduce the main features of tsunamis obtained in laboratory experiments as well as calving characteristics, the iceberg size, tsunami amplitude and wave speed measured at Eqip Sermia, an ocean-terminating outlet glacier of the Greenland ice sheet. Our hybrid approach constitutes important progress towards the modeling of solid–fluid interactions, and has the potential to contribute to refining empirical calving laws used in large-scale earth-system models as well as to improve hazard assessments and mitigation measures in coastal regions, which is essential in the context of climate change.

scholarly journals Optimization of Bioinsecticides Overproduction by Bacillus thuringiensis subsp. kurstaki Using Linear Regression

2013 ◽  
Vol 62 (3) ◽  
pp. 287-293 ◽  
Author(s):  
KARIM ENNOURI ◽  
HANEN BEN HASSEN ◽  
NABIL ZOUARI
Keyword(s):  
Bacillus Thuringiensis ◽  
Linear Regression ◽  
Interaction Model ◽  
Inoculum Size ◽  
Order Model ◽  
First Order ◽  
Initial Ph ◽  
Proteolytic Activities ◽  
Factor Interaction ◽  
Significant Factors

A multiple linear regression analyses were performed to screen for the significant factors simultaneously influencing production of deltaendotoxin, proteolytic activities and spore formation by a Bacillus thuringiensis kurstaki strain. Investigated factors included: pH of the medium, available oxygen and inoculum size. It was observed that oxygen availability was the most influencing setting on both deltaendotoxins production and spores counts, followed by initial pH of the medium and inoculum size. On other hand, pH of medium was found to be the most significant parameter for proteolytic activity, followed by inoculum size and dissolved oxygen. Our results suggested that the first order with two-factor interaction model seemed to be more satisfactory than simple first order model for optimization of delta-endotoxin overproduction. The coefficients of determination (R') indicated a better adequacy of the second order models to justify the obtained data. Based on results, relationships between delta-endotoxins production, proteolytic activities and spores counts were established. Our results can help to balance delta-endotoxins production and its stability.

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