Concurrent coupling of atomistic simulation and mesoscopic hydrodynamics for flows over soft multi-functional surfaces

We develop an efficient parallel multiscale method that bridges the atomistic and mesoscale regimes, from nanometer to micron and beyond, via concurrent coupling of atomistic simulation and mesoscopic dynamics. In particular, we combine an all-atom molecular dynamics (MD) description for specific atomistic details in the vicinity of the functional surface, with a dissipative particle dynamics (DPD) approach that captures mesoscopic hydrodynamics in the domain away from the functional surface. In order to achieve a seamless transition in dynamic properties we endow the MD simulation with a DPD thermostat, which is validated against experimental results by modeling water at different temperatures. We then validate the MD-DPD coupling method for transient Couette and Poiseuille flows, demonstrating that the concurrent MD-DPD coupling can resolve accurately the continuum-based analytical solutions. Subsequently, we simulate shear flows over polydimethylsiloxane (PDMS)-grafted surfaces (polymer brushes) for various grafting densities, and investigate the slip flow as a function of the shear stress. We verify that a "universal" power law exists for the sliplength, in agreement with published results. Having validated the MD-DPD coupling method, we simulate time-dependent flows past an endothelial glycocalyx layer (EGL) in a microchannel. Coupled simulation results elucidate the dynamics of EGL changing from an equilibrium state to a compressed state under shear by aligning the molecular structures along the shear direction. MD-DPD simulation results agree well with results of a single MD simulation, but with the former more than two orders of magnitude faster than the latter for system sizes above one micron.Comment: 11 pages, 12 figure

Uncertainty shocks of Trump election in an interval model of stock market

This paper proposes a new class of nonlinear interval models for interval-valued time series. By matching the interval model with interval observations, we develop a nonlinear minimum-distance estimation method for the proposed models, and establish the asymptotic theory for the proposed estimators. Superior to traditional point-based methods, the proposed interval modelling approach can assess the change in both the trend and volatility simultaneously. Within the proposed interval framework, this paper examines the impact of the 2016 US presidential election (henceforth Trump election) on the US stock market as a case study. Considering the validity of daily high-low range as a proxy of market efficiency, we employ an interval-valued return to jointly measure the fundamental value movement and market efficiency simultaneously. Empirical results suggest a strong evidence that the Trump election has increased the level/trend and lowered the volatility of the S&P 500 index in both ex ante and ex post analysis. Furthermore, a longer half-life period for the impact on fundamental value (62.4 days) than high-low range (15.9 days) has shown that the impact of Trump's victory on fundamental value is more persistent than its impact on market efficiency

A Study of (

We deal with topics regarding (λ,μ)-fuzzy subgroups, mainly (λ,μ)-fuzzy cosets and (λ,μ)-fuzzy normal subgroups. We give basic properties of (λ,μ)-fuzzy subgroups and present some results related to (λ,μ)-fuzzy cosets and (λ,μ)-fuzzy normal subgroups

Long-Term Effects of Tillage and Residue Management on the Soil Microbial Community Structure in the Loess Plateau

The severe soil erosion present in the Loess Plateau of western China has resulted from a combination of highly erodible soil, variable rainfall and intensive cultivation (Shi and Shao 2000). Conservation agriculture practices, including no till, crop residue retention and crop rotation, have been found to increase crop yield, improve water use efficiency, reduce energy inputs and improve soil fertility (Bukert et al. 2000; Rahman et al. 2008). The soil microbial community function and structure play key roles in the decomposition of organic matter, nutrient cycling and altering the availability of nutrients to plants, which has been shown to change under conservation agriculture (González-Chávez et al. 2010). The aims of our research are to quantify impacts of tillage and crop residue management on soil microbial community structural diversity on the Loess Plateau by PLFA techniques

Temporal Variations in the Carbon and Nitrogen Ecological Stoichiometry of Lucerne

Ecological stoichiometry has been of great help in research investigating the coupling between plant and environment (Sterner and Elser 2002). It provides some synchronized evidence to explain the response and adaptability of plants to the environment. Carbon and nitrogen ecological stoichiometry (C/N) also embraces the use efficiency of nitrogen in plants. Previous research has focused on the spatial responses of plant C/N to different environmental factors (Yang and Wang 2011). However, there is still insufficient attention on the temporal variation in C/N, in the hope that such effort will help elucidate the mechanisms underlying plant growth/regrowth. Lucerne (Medicago sativa L) has long been globally utilised. It can be cut 3-4 times annually and lasts for many years. The regrowth process in lucerne is of fundamental importance for the continuous utilisation of the forage and the sustainability of lucerne production. In this study, temporal variations in carbon and nitrogen content and C/N were studied in lucerne leaf, stem and root, as part of an effort to clarify the lucerne growth/regrowth mechanisms from the viewpoint of ecological stoichiometry