Parallel finite volume simulation of the spherical shell dynamo with pseudo-vacuum magnetic boundary conditions

In this paper, we study the parallel simulation of the magnetohydrodynamic (MHD) dynamo in a rapidly rotating spherical shell with pseudo-vacuum magnetic boundary conditions. A second-order finite volume scheme based on a collocated quasi-uniform cubed-sphere grid is applied to the spatial discretization of the MHD dynamo equations. To ensure the solenoidal condition of the magnetic field, we adopt a widely-used approach whereby a pseudo-pressure is introduced into the induction equation. The temporal integration is split by a second-order approximate factorization approach, resulting in two linear algebraic systems both solved by a preconditioned Krylov subspace iterative method. A multi-level restricted additive Schwarz preconditioner based on domain decomposition and multigrid method is then designed to improve the efficiency and scalability. Accurate numerical solutions of two benchmark cases are obtained with our code, comparable to the existing local method results. Several large-scale tests performed on the Sunway TaihuLight supercomputer show good strong and weak scalabilities and a noticeable improvement from the multi-level preconditioner with up to 10368 processor cores

The Molecular Mechanisms of Trabecular Meshwork Damage in POAG and Treatment Advances

Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness affecting over 60 million people worldwide. Elevated intraocular pressure (IOP) due to dysfunction of trabecular meshwork (TM) is the most significant and the only known modifiable risk factor for POAG. Although, glaucomatous TM damage is known to be mainly responsible for IOP elevation, none of the current treatments target TM pathology. This is partly due to an incomplete understanding of the pathophysiological mechanisms of TM damage. In this review, we summarized pathological changes of TM damage in POAG and our current knowledge of the mechanisms of glaucomatous TM damage, particularly focusing on linking the genetic factors of POAG (e.g., mutations and variants in POAG risk genes, risk loci, dysregulation of gene expression) to molecular pathways of pathogenesis in TM. In terms of treatment, reduction of IOP is the mainstream strategy that can be achieved by medical, laser or surgical treatment. IOP lowering drugs, laser or surgery can lower IOP, but do not reverse or restore the oxidative stress or other TM damage in POAG. Additionally, antioxidants, ginkgo biloba extract and nutrients could be a promising treatment for POAG

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Paper architectures are 3D paper buildings created by folding and cutting. The creation process of paper architecture is often labor-intensive and highly skill-demanding, even with the aid of existing computer-aided design tools. We propose an automatic algorithm for generating paper architectures given a user-specified 3D model. The algorithm is grounded on geometric formulation of planar layout for paper architectures that can be popped-up in a rigid and stable manner, and sufficient conditions for a 3D surface to be popped-up from such a planar layout. Based on these conditions, our algorithm computes a class of paper architectures containing two sets of parallel patches that approximate the input geometry while guaranteed to be physically realizable. The method is demonstrated on a number of architectural examples, and physically engineered results are presented

T-cell infiltration in the central nervous system and their association with brain calcification in Slc20a2-deficient mice

Primary familial brain calcification (PFBC) is a rare neurodegenerative and neuropsychiatric disorder characterized by bilateral symmetric intracranial calcification along the microvessels or inside neuronal cells in the basal ganglia, thalamus, and cerebellum. Slc20a2 homozygous (HO) knockout mice are the most commonly used model to simulate the brain calcification phenotype observed in human patients. However, the cellular and molecular mechanisms related to brain calcification, particularly at the early stage much prior to the emergence of brain calcification, remain largely unknown. In this study, we quantified the central nervous system (CNS)-infiltrating T-cells of different age groups of Slc20a2-HO and matched wild type mice and found CD45+CD3+ T-cells to be significantly increased in the brain parenchyma, even in the pre-calcification stage of 1-month-old -HO mice. The accumulation of the CD3+ T-cells appeared to be associated with the severity of brain calcification. Further immunophenotyping revealed that the two main subtypes that had increased in the brain were CD3+ CD4− CD8– and CD3+ CD4+ T-cells. The expression of endothelial cell (EC) adhesion molecules increased, while that of tight and adherents junction proteins decreased, providing the molecular precondition for T-cell recruitment to ECs and paracellular migration into the brain. The fusion of lymphocytes and EC membranes and transcellular migration of CD3-related gold particles were captured, suggesting enhancement of transcytosis in the brain ECs. Exogenous fluorescent tracers and endogenous IgG and albumin leakage also revealed an impairment of transcellular pathway in the ECs. FTY720 significantly alleviated brain calcification, probably by reducing T-cell infiltration, modulating neuroinflammation and ossification process, and enhancing the autophagy and phagocytosis of CNS-resident immune cells. This study clearly demonstrated CNS-infiltrating T-cells to be associated with the progression of brain calcification. Impairment of blood–brain barrier (BBB) permeability, which was closely related to T-cell invasion into the CNS, could be explained by the BBB alterations of an increase in the paracellular and transcellular pathways of brain ECs. FTY720 was found to be a potential drug to protect patients from PFBC-related lesions in the future

Survival after alcohol septal ablation versus conservative therapy in obstructive hypertrophic cardiomyopathy

Background: The impact of alcohol septal ablation (ASA) on the survival of patients with drug-refractory obstructive hypertrophic cardiomyopathy (HCM) remains unresolved. The aim of this study was to compare survival after ASA vs. conservative therapy. Methods: We studied a consecutive cohort of 274 patients with severe drug-refractory obstructive HCM, 229 in ASA group and 45 in conservative group. The primary endpoint was a composite of all-cause mortality and aborted cardiac arrest. Results: With a median follow-up of 4.3 years, primary endpoint occurred in 13 (5.7%) patients in the ASA group, and 8 (17.8%) patients in the conservative group. The 5- and 10-year survival free from primary endpoint of the ASA group (94.5% and 93.0%, respectively) was significantly better than that of the conservative group (78.3% and 72.2%, respectively, log-rank p = 0.009). Independent determinants of primary endpoint were ASA therapy (hazard ratio [HR] 0.22; 95% confidence interval [CI] 0.08–0.60; p = 0.003) and maximal septal thickness (HR 1.14; 95% CI 1.03–1.27; p = 0.011). Conclusions: In patients with severe drug-refractory obstructive HCM, survival after ASA is favorable and better than that of conservative therapy. ASA seems to improve survival

Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models

Multimodal data, which can comprehensively perceive and recognize the physical world, has become an essential path towards general artificial intelligence. However, multimodal large models trained on public datasets often underperform in specific industrial domains. This paper proposes a multimodal federated learning framework that enables multiple enterprises to utilize private domain data to collaboratively train large models for vertical domains, achieving intelligent services across scenarios. The authors discuss in-depth the strategic transformation of federated learning in terms of intelligence foundation and objectives in the era of big model, as well as the new challenges faced in heterogeneous data, model aggregation, performance and cost trade-off, data privacy, and incentive mechanism. The paper elaborates a case study of leading enterprises contributing multimodal data and expert knowledge to city safety operation management , including distributed deployment and efficient coordination of the federated learning platform, technical innovations on data quality improvement based on large model capabilities and efficient joint fine-tuning approaches. Preliminary experiments show that enterprises can enhance and accumulate intelligent capabilities through multimodal model federated learning, thereby jointly creating an smart city model that provides high-quality intelligent services covering energy infrastructure safety, residential community security, and urban operation management. The established federated learning cooperation ecosystem is expected to further aggregate industry, academia, and research resources, realize large models in multiple vertical domains, and promote the large-scale industrial application of artificial intelligence and cutting-edge research on multimodal federated learning