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.     

Difference in Survival in Early Kidney after Liver Transplantation Compared with Simultaneous Liver-Kidney Transplantation: Evaluating the Potential of the “Safety Net”

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马来酸罗格列酮胃漂浮型缓释片的研究

目的：根据流体动力学平衡控释原理（HBS）研制了马来酸罗列酮胃漂浮型缓释片。方法；以体外释放度和漂浮情况为筛选指标，采用单因素考察和正交试验设计相结合， 对胃漂浮缓释片的处方、制备工艺及体外释放条件进行优化筛选；采用γ闪烁照相技术对优化处方的内漂浮情况进行胃内动态观察。结果：马来酸罗格列酮胃漂浮缓释片在释放介质中迅速起漂，持漂时间超过12h,12h达最大累积释放；初步确定在胃内滞留时间达3h以上。结论：优化处方的释放过程符合Higuchi方程，释放机制为异常扩散；胃漂浮片在胃滞时间明显长于普通片。     

Multiple spike-train analysis using mutual interval matrix

The principal-component approach is applied to the analysis of sequences of neuronal action potentials (spike trains). Multiple spike trains are represented as a sequence of vectors of mutual interspike intervals and are considered to be part of the trajectory of a dynamic system. The trajectory matrix is decomposed into a number of ‘basic spike patterns’ and their relative magnitudes by singular-value decomposition. The representation provides a convenient framework for analysis of dynamic relations and cooperation between neurons in an observed network. Examples of applications to simulated and cerebellar data are presented.