A full divergence-free of high order virtual finite element method to approximation of stationary inductionless magnetohydrodynamic equations on polygonal meshes

In this present paper we consider a full divergence-free of high order virtual finite element algorithm to approximate the stationary inductionless magnetohydrodynamic model on polygonal meshes. More precisely, we choice appropriate virtual spaces and necessary degrees of freedom for velocity and current density to guarantee that their final discrete formats are both pointwise divergence-free. Moreover, we hope to achieve higher approximation accuracy at higher "polynomial" orders k_{1} \geq 2, k_{2} \geq 1, while the full divergence-free property has always been satisfied. And then we processed rigorous error analysis to show that the proposed method is stable and convergent. Several numerical tests are presented, confirming the theoretical predictions

Independent markers of nonalcoholic fatty liver disease in a gentrifying population‐based Chinese cohort

BackgroundPrevalence of nonalcoholic fatty liver disease (NAFLD) is increasing in developing countries, but its causes are not known. We aimed to ascertain the prevalence and determinants of NAFLD in a new largely unmedicated population‐based cohort from the rapidly gentrifying region of Pinggu, China.MethodsWe randomized cluster sampled 4002 Pinggu residents aged 26 to 76 years. Data from 1238 men and 1928 women without significant alcohol drinking or hepatitis virus B or C infection were analysed. NAFLD was defined using a liver‐spleen ratio (L/S ratio) ≤1.1 on unenhanced abdominal computed tomography (CT) scanning.ResultsOf men and women, 26.5% and 20.1%, respectively, had NAFLD. NAFLD prevalence was highest in younger men and older women. In multivariate logistic regression models, higher body mass index, waist circumference, serum triglyceride, alanine transaminase, and haemoglobin A1c independently increased the odds of NAFLD in both men and women separately. Higher annual household income and systolic blood pressure for men and higher serum uric acid and red meat intake and lower physical activity levels for women also independently associated with higher odds of NAFLD. Individuals with L/S ratio ≤1.1 had linearly increasing rates of obesity, diabetes, and metabolic syndrome that paralleled fatty liver increase.ConclusionsNAFLD is common in a gentrifying Chinese population particularly in younger men of high socioeconomic status and older women with sedentary behaviour who eat red meat. Demographic factors add independent risk of NAFLD above traditional metabolic risk factors. A CT L/S ratio of ≤1.1 identifies individuals at high risk of metabolic disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149708/1/dmrr3156_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149708/2/dmrr3156.pd

Diabetes and obesity are the main metabolic drivers of peripheral neuropathy

ObjectiveTo determine the associations between individual metabolic syndrome (MetS) components and peripheral neuropathy in a large populationâ based cohort from Pinggu, China.MethodsA crossâ sectional, randomly selected, populationâ based survey of participants from Pinggu, China was performed. Metabolic phenotyping and neuropathy outcomes were performed by trained personnel. Glycemic status was defined according to the American Diabetes Association criteria, and the MetS using modified consensus criteria (body mass index instead of waist circumference). The primary peripheral neuropathy outcome was the Michigan Neuropathy Screening Instrument (MNSI) examination. Secondary outcomes were the MNSI questionnaire and monofilament testing. Multivariable models were used to assess for associations between individual MetS components and peripheral neuropathy. Treeâ based methods were used to construct a classifier for peripheral neuropathy using demographics and MetS components.ResultsThe mean (SD) age of the 4002 participants was 51.6 (11.8) and 51.0% were male; 37.2% of the population had normoglycemia, 44.0% prediabetes, and 18.9% diabetes. The prevalence of peripheral neuropathy increased with worsening glycemic status (3.25% in normoglycemia, 6.29% in prediabetes, and 15.12% in diabetes, P < 0.0001). Diabetes (odds ratio [OR] 2.60, 95% CI 1.77â 3.80) and weight (OR 1.09, 95% CI 1.02â 1.18) were significantly associated with peripheral neuropathy. Age, diabetes, and weight were the primary splitters in the classification tree for peripheral neuropathy.InterpretationSimilar to previous studies, diabetes and obesity are the main metabolic drivers of peripheral neuropathy. The consistency of these results reinforces the urgent need for effective interventions that target these metabolic factors to prevent and/or treat peripheral neuropathy.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143679/1/acn3531_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143679/2/acn3531.pd

Stacking Order Driven Optical Properties and Carrier Dynamics in ReS2

Two distinct stacking orders in ReS2 are identified without ambiguity and their influence on vibrational, optical properties and carrier dynamics are investigated. With atomic resolution scanning transmission electron microscopy (STEM), two stacking orders are determined as AA stacking with negligible displacement across layers, and AB stacking with about a one-unit cell displacement along the a axis. First-principle calculations confirm that these two stacking orders correspond to two local energy minima. Raman spectra inform a consistent difference of modes I & III, about 13 cm-1 for AA stacking, and 20 cm-1 for AB stacking, making a simple tool for determining the stacking orders in ReS2. Polarized photoluminescence (PL) reveals that AB stacking possesses blue-shifted PL peak positions, and broader peak widths, compared with AA stacking, indicating stronger interlayer interaction. Transient transmission measured with femtosecond pump probe spectroscopy suggests exciton dynamics being more anisotropic in AB stacking, where excited state absorption related to Exc. III mode disappears when probe polarization aligns perpendicular to b axis. Our findings underscore the stacking-order driven optical properties and carrier dynamics of ReS2, mediate many seemingly contradictory results in literature, and open up an opportunity to engineer electronic devices with new functionalities by manipulating the stacking order

Defect-modulated thermal transport behavior of BAs under high pressure

Boron arsenide (BAs) is a covalent semiconductor with a theoretical intrinsic thermal conductivity approaching 1300 W/m K. The existence of defects not only limits the thermal conductivity of BAs significantly but also changes its pressure-dependent thermal transport behavior. Using both picosecond transient thermoreflectance and femtosecond time-domain thermoreflectance techniques, we observed a non-monotonic dependence of thermal conductivity on pressure. This trend is not caused by the pressure-modulated phonon–phonon scattering, which was predicted to only change the thermal conductivity by 10%–20%, but a result of several competing effects, including defect–phonon scattering and modification of structural defects under high pressure. Our findings reveal the complexity of the defect-modulated thermal behavior under pressure.The authors are grateful for the support from the National Science Foundation (NASCENT, Grant No. EEC-1160494; Center for Dynamics and Control of Materials DMR-1720595; CBET- 2211660); F.T., Z.R., and L.S. were supported by the Office of Naval Research under Multidisciplinary University Research Initiative (Grant No. N00014-16-1-2436).Center for Dynamics and Control of Material

A genome-wide association study identifies GRK5 and RASGRP1 as type 2 diabetes loci in Chinese Hans.

Substantial progress has been made in identification of type 2 diabetes (T2D) risk loci in the past few years, but our understanding of the genetic basis of T2D in ethnically diverse populations remains limited. We performed a genome-wide association study and a replication study in Chinese Hans comprising 8,569 T2D case subjects and 8,923 control subjects in total, from which 10 single nucleotide polymorphisms were selected for further follow-up in a de novo replication sample of 3,410 T2D case and 3,412 control subjects and an in silico replication sample of 6,952 T2D case and 11,865 control subjects. Besides confirming seven established T2D loci (CDKAL1, CDKN2A/B, KCNQ1, CDC123, GLIS3, HNF1B, and DUSP9) at genome-wide significance, we identified two novel T2D loci, including G-protein-coupled receptor kinase 5 (GRK5) (rs10886471: P = 7.1 × 10(-9)) and RASGRP1 (rs7403531: P = 3.9 × 10(-9)), of which the association signal at GRK5 seems to be specific to East Asians. In nondiabetic individuals, the T2D risk-increasing allele of RASGRP1-rs7403531 was also associated with higher HbA(1c) and lower homeostasis model assessment of β-cell function (P = 0.03 and 0.0209, respectively), whereas the T2D risk-increasing allele of GRK5-rs10886471 was also associated with higher fasting insulin (P = 0.0169) but not with fasting glucose. Our findings not only provide new insights into the pathophysiology of T2D, but may also shed light on the ethnic differences in T2D susceptibility

RSIMS: Large-Scale Heterogeneous Remote Sensing Images Management System

With the remarkable development and progress of earth-observation techniques, remote sensing data keep growing rapidly and their volume has reached exabyte scale. However, it’s still a big challenge to manage and process such huge amounts of remote sensing data with complex and diverse structures. This paper designs and realizes a distributed storage system for large-scale remote sensing data storage, access, and retrieval, called RSIMS (remote sensing images management system), which is composed of three sub-modules: RSIAPI, RSIMeta, RSIData. Structured text metadata of different remote sensing images are all stored in RSIMeta based on a set of uniform models, and then indexed by the distributed multi-level Hilbert grids for high spatiotemporal retrieval performance. Unstructured binary image files are stored in RSIData, which provides large scalable storage capacity and efficient GDAL (Geospatial Data Abstraction Library) compatible I/O interfaces. Popular GIS software and tools (e.g., QGIS, ArcGIS, rasterio) can access data stored in RSIData directly. RSIAPI provides users a set of uniform interfaces for data access and retrieval, hiding the complex inner structures of RSIMS. The test results show that RSIMS can store and manage large amounts of remote sensing images from various sources with high and stable performance, and is easy to deploy and use