A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.     

Temperature-controlled power modulation compensates for heterogeneous nanoparticle distributions: a computational optimization analysis for magnetic hyperthermia

Purpose: To study, with computational models, the utility of power modulation to reduce tissue temperature heterogeneity for variable nanoparticle distributions in magnetic nanoparticle hyperthermia.

Methods: Tumour and surrounding tissue were modeled by elliptical two- and three-dimensional computational phantoms having six different nanoparticle distributions. Nanoparticles were modeled as point heat sources having amplitude-dependent loss power. The total number of nanoparticles was fixed, and their spatial distribution and heat output were varied. Heat transfer was computed by solving the Pennes’ bioheat equation using finite element methods (FEM) with temperature-dependent blood perfusion. Local temperature was regulated using a proportional-integral-derivative (PID) controller. Tissue temperature, thermal dose and tissue damage were calculated. The required minimum thermal dose delivered to the tumor was kept constant, and heating power was adjusted for comparison of both the heating methods.

Results: Modulated power heating produced lower and more homogeneous temperature distributions than did constant power heating for all studied nanoparticle distributions. For a concentrated nanoparticle distribution, located off-center within the tumor, the maximum temperatures inside the tumor were 16% lower for modulated power heating when compared to constant power heating. This resulted in less damage to surrounding normal tissue. Modulated power heating reached target thermal doses up to nine-fold more rapidly when compared to constant power heating.

Conclusions: Controlling the temperature at the tumor-healthy tissue boundary by modulating the heating power of magnetic nanoparticles demonstrably compensates for a variable nanoparticle distribution to deliver effective treatment.     

A Multi-Scale DNN Algorithm for Nonlinear Elliptic Equations with Multiple Scales

Algorithms based on deep neural networks (DNNs) have attracted increasing attention from the scientific computing community. DNN based algorithms are easy to implement, natural for nonlinear problems, and have shown great potential to overcome the curse of dimensionality. In this work, we utilize the multi-scale DNN-based algorithm (MscaleDNN) proposed by Liu, Cai and Xu (2020) to solve multi-scale elliptic problems with possible nonlinearity, for example, the p-Laplacian problem. We improve the MscaleDNN algorithm by a smooth and localized activation function. Several numerical examples of multi-scale elliptic problems with separable or non-separable scales in low-dimensional and high-dimensional Euclidean spaces are used to demonstrate the effectiveness and accuracy of the MscaleDNN numerical scheme.     

Long-term health and socioeconomic outcome of obstructive sleep apnea in children and adolescents

BackgroundThere is limited information about the long-term outcome of obstructive sleep apnea (OSA) diagnosed in children and adolescents for educational and social factors. Here, we estimate the long-term socioeconomic outcome and health care costs of OSA.MethodsThe historical case-control cohort study included Danish individuals with OSA diagnosed in childhood or adolescence between 1994 and 2015. Health care costs and socioeconomic data were obtained from nationwide administrative and health registers. A total of 5419 were diagnosed during this period; of these we traced 1004 patients who we compared with 4085 controls (mean index age, 10.2 years; Standard Deviation (SD), 5.6 years) until the age of 20 years. Controls were matched for age, gender, and residency.ResultsComparing the OSA patient and control groups at age 20 years we found: 1) lower parental educational level; 2) significantly lower educational level also after adjustment for parental educational level; 3) lower school grade-point averages; 4) lower employment rate and lower income, which was not fully compensated when transfer payments were considered; and 5) patients' initial health care costs were higher due to higher morbidity. Patients showed higher mortality rates than controls (Hazard Ratio (HR) = 7.63, 95% CI = 4.87–11.95, P < 0.001).ConclusionsOSA in children and adolescent is associated with a significant influence on morbidity, mortality, educational level, grading, social outcome, and welfare consequences.     

Pathways in the association between sugar sweetened beverages and child asthma traits in the 2nd year of life: Findings from the BRISA cohort

Studies on the exposure of children to sugar-sweetened beverages (SSBs) at an early age may contribute to better understand the common causes and the temporal order of the relationships between obesity and asthma in early childhood. The objective of this study was to estimate the association between SSB and child asthma traits in the 2nd year of life, modeling direct and indirect pathways mediated by the highest BMI-z of the child and allergic inflammation. Data from the BRISA cohort, São Luís-MA, Brazil (n = 1140), were obtained from the baseline and from the follow-up performed at the 2nd year of life. The main explanatory variable was the calories from added sugars in SSBs as a percentage of the total daily energy intake. The outcome child asthma traits was a latent variable deduced from four indicators: medical diagnosis of asthma, wheezing, emergency visit due to intense wheezing, and medical diagnosis of rhinitis. A high percentage of daily calories from sugars added to SSBs was directly associated with higher values of child asthma traits (standardized coefficient (SC = 0.073; P = .030)). High levels of eosinophils were also directly associated with child asthma traits (SC = 0.118; P = .049). No mediation pathways were observed via greater BMI-z or eosinophil counts. Therefore, early exposure of children to SSB may contribute to increased risk of childhood asthma, preceding the link between sugar consumption and overweight/obesity, not yet evident in children in the first 2 years of life.     

Estimating Potency for the E max-Model Without Attaining Maximal Effects

The most widely applied model relating drug concentrations to effects is the E_max model. In practice, concentration–effect relationships often deviate from a simple linear relationship but without reaching a clear maximum because a further increase in concentration might be associated with unacceptable or distorting side effects. The parameters for the E_max model can only be estimated with reasonable precision if the curve shows sign of reaching a maximum, otherwise both EC₅₀ and E_max estimates may be extremely imprecise. This paper provides a solution by introducing a new parameter (S₀ ) equal to E_max/EC₅₀ that can be used to characterize potency adequately even if there are no signs of a clear maximum. Simulations are presented to investigate the nature of the new parameter and published examples are used as illustration.     

Which constructs can predict emotional exhaustion in a working population? A study into its determinants

The main objective of this study was to examine the psychosocial stress model developed by Taylor and Aspinwall with emotional exhaustion as the outcome variable. Respondents, 409 men and 346 women, who had a paid job for at least 20 hours per week, completed questionnaires concerning demographic variables, personality, temperament, work pressure, workload, perceived social support, appraisal, coping, and emotional exhaustion. Structural equation analyses provided only partial support for the validity of the model. First, on theoretical and statistical grounds, one more path linking external resources to social support was added. Second, contrary to expectations, coping styles did not predict emotional exhaustion. To conclude, when coping is measured retrospectively, it does not add to our understanding of emotional exhaustion. It is suggested that future studies should be longitudinal and include objective measures of stressors and psychosocial health outcomes in addition to self‐reports. Copyright © 2007 John Wiley & Sons, Ltd.     

Is the political system really related to health?

We analyze whether the political system and its stability are related to cross-country differences in health. We apply factor analysis on various national health indicators for a large sample of countries over the period 2000–2005 and use the outcomes of the factor analysis to construct two new health measures, i.e., the health of individuals and the quality of the health care sector. Using a cross-country structural equation model with various economic and demographic control variables, we examine the relationship between the type of regime and political stability on the one hand and health on the other. The political variables and the control variables are measured as averages over the period 1980–1999. Our results suggest that democracy has a positive relationship with the health of individuals, while regime instability has a negative relationship with the health of individuals. Government instability is negatively related to individual health via its link with the quality of the health care sector, while democracy is positively related with individual health through its link with income. Our main findings are confirmed by the results of a panel model and various sensitivity tests.