scholarly journals Generalization of the Lighthill problem for the viscous fluid filled tubes with complicated wall rheology

2020 ◽  
pp. 67-70
Author(s):  
N. Kizilova ◽  
I. Maiko
Keyword(s):  
Plane Waves ◽  
Relaxation Times ◽  
Computation Time ◽  
Numerical Calculations ◽  
Wall Material ◽  
Circulation System ◽  
Model Parameters ◽  
Cross Sectional ◽  
Rheological Relation ◽  
Complex Models

A generalization of the Lighthill model of the plane waves propagation along fluid-filled viscoelastic tubes is proposed. The rheological relation of the wall has two relaxation times for strains and stresses. The equations of the generalized model for the averaged pressure, velocity and the cross-sectional area of the tube are obtained. The solution of the equations in the form of the running waves and the dispersion relation are obtained and compared to those for the Lighthill and Shapiro problems, and the viscoelastic Kelvin-Voigt model for the wall material. Numerical calculations for the model parameters corresponded to human circulation system have been carried out. It is shown, the complicated properties of the material allow accounting for both Young and Lame wave modes, and stabilization the modes that were unstable in the case of simpler rheology. The developed model is helpful in performing the numerical calculations on complex models of arterial vasculatures at lower computation time and resources.

Correlated personality change across time and age

2021 ◽  
pp. 089020702110140
Author(s):  
Gabriel Olaru ◽  
Mathias Allemand
Keyword(s):  
Structural Equation ◽  
Rank Order ◽  
Personality Development ◽  
The United States ◽  
Change Score ◽  
Personality Change ◽  
Equation Modeling ◽  
Model Parameters ◽  
Cross Sectional ◽  
Adult Lifespan

The goal of this study was to examine differential and correlated change in personality across the adult lifespan. Studying differential and correlated change can help understand whether intraindividual trait change trajectories deviate from the norm and how these trajectories are coupled with each other. We used data from two large longitudinal panel studies from the United States that covered a total age range of 20 to 95 years on the first measurement occasion. We used correlated factor models and bivariate latent change score models to examine the rank-order stability and correlations between change across three measurement waves covering 18 years ( N = 3250) and four measurement waves covering 12 years ( N = 4145). We examined the moderation effects of continuous age on these model parameters using local structural equation modeling. The results suggest that the test–retest correlations decrease with increasing time between measurements but are unaffected by participants’ age. We found that change processes in Extraversion, Openness, Agreeableness, and Conscientiousness were strongly related, particularly in late adulthood. Correlated change patterns were highly stable across time intervals and similar to the initial cross-sectional Big Five correlations. We discuss potential mechanisms and implications for personality development research.

scholarly journals A flexible framework for sequential estimation of model parameters in computational hemodynamics

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Christopher J. Arthurs ◽  
Nan Xiao ◽  
Philippe Moireau ◽  
Tobias Schaeffter ◽  
C. Alberto Figueroa
Keyword(s):  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Sequential Estimation ◽  
Wall Material ◽  
Patient Specific ◽  
Model Parameters ◽  
Computational Framework ◽  
Lumped Parameter ◽  
Estimation Of Model Parameters

AbstractA major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A “Netlist” implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.

scholarly journals Medial knee joint contact force in the intact limb during walking in recently ambulatory service members with unilateral limb loss: a cross-sectional study

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e2960 ◽  
Author(s):  
Ross H. Miller ◽  
Rebecca L. Krupenevich ◽  
Alison L. Pruziner ◽  
Erik J. Wolf ◽  
Barri L. Schnall
Keyword(s):  
Knee Joint ◽  
Limb Loss ◽  
Service Members ◽  
Model Parameters ◽  
Joint Loading ◽  
Cross Sectional ◽  
Medial Knee ◽  
Knee Oa ◽  
Joint Contact ◽  
Intact Limb

BackgroundIndividuals with unilateral lower limb amputation have a high risk of developing knee osteoarthritis (OA) in their intact limb as they age. This risk may be related to joint loading experienced earlier in life. We hypothesized that loading during walking would be greater in the intact limb of young US military service members with limb loss than in controls with no limb loss.MethodsCross-sectional instrumented gait analysis at self-selected walking speeds with a limb loss group (N = 10, age 27 ± 5 years, 170 ± 36 days since last surgery) including five service members with transtibial limb loss and five with transfemoral limb loss, all walking independently with their first prosthesis for approximately two months. Controls (N = 10, age 30 ± 4 years) were service members with no overt demographical risk factors for knee OA. 3D inverse dynamics modeling was performed to calculate joint moments and medial knee joint contact forces (JCF) were calculated using a reduction-based musculoskeletal modeling method and expressed relative to body weight (BW).ResultsPeak JCF and maximum JCF loading rate were significantly greater in limb loss (184% BW, 2,469% BW/s) vs. controls (157% BW, 1,985% BW/s), with large effect sizes. Results were robust to probabilistic perturbations to the knee model parameters.DiscussionAssuming these data are reflective of joint loading experienced in daily life, they support a “mechanical overloading” hypothesis for the risk of developing knee OA in the intact limb of limb loss subjects. Examination of the evolution of gait mechanics, joint loading, and joint health over time, as well as interventions to reduce load or strengthen the ability of the joint to withstand loads, is warranted.

scholarly journals A Flow Stress Model of 300M Steel for Isothermal Tension

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 252
Author(s):  
Rongchuang Chen ◽  
Shiyang Zhang ◽  
Xianlong Liu ◽  
Fei Feng
Keyword(s):  
Flow Stress ◽  
Constitutive Model ◽  
Tensile Deformation ◽  
Flow Behavior ◽  
Tensile Tests ◽  
Uniaxial Tensile ◽  
Model Parameters ◽  
Average Deviation ◽  
Cross Sectional ◽  
300M Steel

To investigate the effect of hot working parameters on the flow behavior of 300M steel under tension, hot uniaxial tensile tests were implemented under different temperatures (950 °C, 1000 °C, 1050 °C, 1100 °C, 1150 °C) and strain rates (0.01 s−1, 0.1 s−1, 1 s−1, 10 s−1). Compared with uniaxial compression, the tensile flow stress was 29.1% higher because dynamic recrystallization softening was less sufficient in the tensile stress state. The ultimate elongation of 300M steel increased with the decrease of temperature and the increase of strain rate. To eliminate the influence of sample necking on stress-strain relationship, both the stress and the strain were calibrated using the cross-sectional area of the neck zone. A constitutive model for tensile deformation was established based on the modified Arrhenius model, in which the model parameters (n, α, Q, ln(A)) were described as a function of strain. The average deviation was 6.81 MPa (6.23%), showing good accuracy of the constitutive model.

Modelling Age Differences in Isometric Elbow Flexion Using Hill's Three-Element Visco-Elastic Model

1993 ◽  
Vol 37 (2) ◽  
pp. 202-205
Author(s):  
R. Darin Ellis ◽  
Kentaro Kotani
Keyword(s):  
Mechanical Properties ◽  
Steady State ◽  
Age Differences ◽  
Elbow Flexion ◽  
Model Parameters ◽  
Elastic Model ◽  
Tissue Elasticity ◽  
Age Related ◽  
Complex Models ◽  
State Force

A visco-elastic model of the mechanical properties of muscle was used to describe age-differences in the buildup of force in isometric elbow flexion. Given information from the literature on age-related physiological changes, such as decreasing connective-tissue elasticity, one would expect changes in the mechanical properties of skeletal muscle and their related model parameters. Force vs. time curves were obtained for 7 young (aged 21–27) and 7 old (aged 69–83) female subject. There were significant age group differences in steady-state force level and the best fitting model parameters. In particular, the viscous damping element of the model plays a large role in describing the increased time to reach steady-state force levels in the older subject group. Implications of this research include incorporating parameter differences into more complex models, such as crash impact models.

Abstract 273: New Reconstruction Technique for MRA to “Fly Through” the Lumen of the Cerebral Vasculature

2013 ◽  
Vol 33 (suppl_1) ◽  
Author(s):  
Mallikarjunarao Kasam ◽  
Siva S Ketha ◽  
Soumya Konduru
Keyword(s):  
Virtual Endoscopy ◽  
Statistical Parameter ◽  
Computation Time ◽  
Reconstruction Technique ◽  
Cross Sectional ◽  
Root Area ◽  
Contrast Enhanced ◽  
3.0 T ◽  
Area Product ◽  
Sectional Structure

Methods Patient exams were performed under an IRB-approved protocol. Two 3D SWIRLS [3] single phase contrast-enhanced angiographies with 1mm3 spatial resolution were used for this work. Clinical exams were acquired on 3.0 T scanners (GE, DVMR 20.1IB, Milwaukee, WI). Data analysis The angiogram was post-processed using tree analysis and virtual endoscopy modules of Analyze 11.0 software (Analyze 11.0; Biomedical Imaging Resource, Mayo Clinic, Rochester, MN) to fly through the artery. A statistical parameter called Brightness Area Product (BAP) was defined as the sum of the intensities above the sample minimum intensity/threshold set by the user. Results and Discussions Figures (I-IV) show the methodology to fly through the part of anterior carotid artery (ACA) and all statistics of part of the artery (Fig. IV) with angles from the “Root” to its different branches of A1 to G2 (Fig. III). Figure II shows the snap shot of the fly through/internal cross sectional structure of ACA of branch “E2”, at the location marked as “red dot”. Table (IV) represents different statistics including length, angle from the root, area of cross section and the BAP of the branches mentioned in Fig. III. The computation time for this method is < 5 minutes compared to the other reconstruction techniques (>~30 minutes). We proposed a simple and fast automated post-processing method to fly through the artery using Analyze 11.0 software. This technique can be extended to any arteries to monitor internal vasculature and to estimate the stenosis using the statistical parameter BAP, which generates a master profile/database of arteries. References 1 Shu Y, Bernstein MA, ISMRM 2009 p764.

Epistemological Aspects of Simulation Models for Decision Support

2013 ◽  
Vol 5 (2) ◽  
pp. 55-77 ◽  
Author(s):  
Anthony H. Dekker
Keyword(s):  
Coupled Oscillators ◽  
True Belief ◽  
Simulation Models ◽  
Decision Makers ◽  
Kuramoto Model ◽  
Model Parameters ◽  
Theoretical Construct ◽  
Formal Definitions ◽  
Complex Models ◽  
The Kuramoto Model

In this paper, the author explores epistemological aspects of simulation with a particular focus on using simulations to provide recommendations to managers and other decision-makers. The author presents formal definitions of knowledge (as justified true belief) and of simulation. The author shows that a simple model, the Kuramoto model of coupled-oscillators, satisfies the simulation definition (and therefore generates knowledge) through a justified mapping from the real world. The author argues that, for more complex models, such a justified mapping requires three techniques: using an appropriate and justified theoretical construct; using appropriate and justified values for model parameters; and testing or other verification processes to ensure that the mapping is correctly defined. The author illustrates these three techniques with experiments and models from the literature, including the Long House Valley model of Axtell et al., the SAFTE model of sleep, and the Segregation model of Wilensky.

scholarly journals A graphical model for skewed matrix-variate non-randomly missing data

Biostatistics ◽  
2018 ◽  
Author(s):  
Lin Zhang ◽  
Dipankar Bandyopadhyay
Keyword(s):  
Mixed Model ◽  
Graphical Model ◽  
Linear Mixed Model ◽  
Disease Status ◽  
Epidemiological Studies ◽  
Model Parameters ◽  
Probit Regression ◽  
Pocket Depth ◽  
Cross Sectional ◽  
Missing Responses

SummaryEpidemiological studies on periodontal disease (PD) collect relevant bio-markers, such as the clinical attachment level (CAL) and the probed pocket depth (PPD), at pre-specified tooth sites clustered within a subject’s mouth, along with various other demographic and biological risk factors. Routine cross-sectional evaluation are conducted under a linear mixed model (LMM) framework with underlying normality assumptions on the random terms. However, a careful investigation reveals considerable non-normality manifested in those random terms, in the form of skewness and tail behavior. In addition, PD progression is hypothesized to be spatially-referenced, i.e. disease status at proximal tooth-sites may be different from distally located sites, and tooth missingness is non-random (or informative), given that the number and location of missing teeth informs about the periodontal health in that region. To mitigate these complexities, we consider a matrix-variate skew-$t$ formulation of the LMM with a Markov graphical embedding to handle the site-level spatial associations of the bivariate (PPD and CAL) responses. Within the same framework, the non-randomly missing responses are imputed via a latent probit regression of the missingness indicator over the responses. Our hierarchical Bayesian framework powered by relevant Markov chain Monte Carlo steps addresses the aforementioned complexities within an unified paradigm, and estimates model parameters with seamless sharing of information across various stages of the hierarchy. Using both synthetic and real clinical data assessing PD status, we demonstrate a significantly improved fit of our proposition over various other alternative models.

Perceived Sensitivity to Pain and Responsiveness to Non-noxious Sensation in Substance Use Disorder

Pain Medicine ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 1902-1912
Author(s):  
Naama Assayag ◽  
Yoram Bonneh ◽  
Shula Parush ◽  
Haim Mell ◽  
Ricky Kaplan Neeman ◽  
...  
Keyword(s):  
Substance Use ◽  
Logistic Regression ◽  
Substance Use Disorder ◽  
Pain Sensitivity ◽  
Pain Perception ◽  
Cross Sectional Study ◽  
Control Group ◽  
Model Parameters ◽  
Cross Sectional ◽  
Sensory Responsiveness

Abstract Objective This comparative cross-sectional study aimed to characterize individuals with substance use disorder (SUD) in self-perception of pain sensitivity, experimental auditory aversiveness, and non-noxious sensory responsiveness, as well as examine the associations with SUD. Methods Therapeutic community (TC) individuals with SUD (N = 63, male 88.9%) and healthy controls (N = 60, male 86.7%) completed the Pain Sensitivity Questionnaire (PSQ) and the Sensory Responsiveness Questionnaire–Intensity Scale (SRQ-IS), followed by a psychophysical auditory battery, the Battery of Averseness to Sounds (BAS)–Revised. Results The SUD group scored higher on the PSQ (P &lt; 0.0001), BAS-R aversiveness (P &lt; 0.0001), BAS-R-unpleasantness (P &lt; 0.0001), and on the aftersensation of auditory aversiveness (P &lt; 0.0001) and unpleasantness (P &lt; 0.000). Fifty-four percent of the SUD group vs 11.7% of the control group were identified as having sensory modulation dysfunction (SMD; P &lt; 0.0001). Logistic regression modeling revealed that the SRQ-IS-Aversive score had a stronger relationship, indicating a 12.6-times odds ratio for SUD (P = 0.0002). Finally, a risk score calculated from a linear combination of the logistic regression model parameters is presented based on the PSQ and SRQ. Conclusions This is the first study to explore sensory and aversive domains using experimental and self-reporting in situ, revealing pain perception alteration that co-occurs with high prevalence of SMD, specifically of the over-responsive type. Findings may be significant in clinical practice for treating pain, and for expanding therapeutic modalities as part of broader rehabilitation in TC and beyond, to better meet personalized therapy.

scholarly journals Modeling Dynamic Heterogeneity Using Gaussian Processes

2019 ◽  
Vol 57 (1) ◽  
pp. 55-77 ◽  
Author(s):  
Ryan Dew ◽  
Asim Ansari ◽  
Yang Li
Keyword(s):  
Gaussian Processes ◽  
Marketing Research ◽  
Population Level ◽  
Online Reviews ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Dynamic Heterogeneity ◽  
Cross Sectional ◽  
Individual Level ◽  
The Rich

Marketing research relies on individual-level estimates to understand the rich heterogeneity of consumers, firms, and products. While much of the literature focuses on capturing static cross-sectional heterogeneity, little research has been done on modeling dynamic heterogeneity, or the heterogeneous evolution of individual-level model parameters. In this work, the authors propose a novel framework for capturing the dynamics of heterogeneity, using individual-level, latent, Bayesian nonparametric Gaussian processes. Similar to standard heterogeneity specifications, this Gaussian process dynamic heterogeneity (GPDH) specification models individual-level parameters as flexible variations around population-level trends, allowing for sharing of statistical information both across individuals and within individuals over time. This hierarchical structure provides precise individual-level insights regarding parameter dynamics. The authors show that GPDH nests existing heterogeneity specifications and that not flexibly capturing individual-level dynamics may result in biased parameter estimates. Substantively, they apply GPDH to understand preference dynamics and to model the evolution of online reviews. Across both applications, they find robust evidence of dynamic heterogeneity and illustrate GPDH’s rich managerial insights, with implications for targeting, pricing, and market structure analysis.

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