CFD simulation of flow through heart: a perspective review

This work addresses the problem of prescribing proper boundary conditions at the artificial boundaries that separate the vascular district from the remaining part of the circulatory system. A multiscale (MS) approach is used where the Navier–Stokes equations for the district of interest are coupled to a non-linear system of ordinary differential equations which describe the circulatory system. This technique is applied to three 3D models of a carotid bifurcation with increasing stenosis resembling three phases of a plaque growth. The results of the MS simulations are compared to those obtained by two stand-alone models. The MS shows a great flexibility in numerically predicting the haemodynamic changes due to the presence of a stenosis. Nonetheless, the results are not significantly different from a stand-alone approach where flows derived by the MS without stenosis are imposed. This is a consequence of the dominant role played by the outside districts with respect to the stenosis resistance.     

Multiscale simulations of protein folding: application to formation of secondary structures

A multiscale simulation method of protein folding is proposed, using atomic representation of protein and solvent, combing genetic algorithms to determine the key protein structures from a global view, with molecular dynamic simulations to reveal the local folding pathways, thus providing an integrated landscape of protein folding. The method is found to be superior to previously investigated global search algorithms or dynamic simulations alone. For secondary structure formation of a selected peptide, RN24, the structures and dynamics produced by this method agree well with corresponding experimental results. Three most populated conformations are observed, including hairpin, β-sheet and α-helix. The energetic barriers separating these three structures are comparable to the kinetic energy of the atoms of the peptide, implying that the transition between these states can be easily triggered by kinetic perturbations, mainly through electrostatic interactions between charged atoms. Transitions between α-helix and β-sheet should jump over at least two energy barriers and may stay in the energetic trap of hairpin. It is proposed that the structure of proteins should be jointly governed by thermodynamic and dynamic factors; free energy is not the exclusive dominant for stability of proteins.     

Effects of Dragonfly Wing Structure on the Dynamic Performances

The configurations of dragonfly wings, including the corrugations of the chordwise cross-section, the microstructure of the longitudinal veins and membrane, were comprehensively investigated using the Environmental Scanning Electron Microscopy (ESEM). Based on the experimental results reported previously, the multi-scale and multi-dimensional models with different structural features of dragonfly wing were created, and the biological dynamic behaviors of wing models were discussed through the Finite Element Method (FEM). The results demonstrate that the effects of different structural features on dynamic behaviors of dragonfly wing such as natural frequency/modal, bending/torsional deformation, reaction force/torque are very significant. The corrugations of dragonfly wing along the chordwise can observably improve the flapping frequency because of the greater structural stiffness of wings. In updated model, the novel sandwich microstructure of the longitudinal veins remarkably improves the torsional deformation of dragonfly wing while it has a little effect on the flapping frequency and bending deformation. These integrated structural features can adjust the deformation of wing oneself, therefore the flow field around the wings can be controlled adaptively. The fact is that the flights of dragonfly wing with sandwich microstructure of longitudinal veins are more efficient and intelligent.     

Lithium Doping to Enhance Thermoelectric Performance of MgAgSb with Weak Electron–Phonon Coupling

Despite the unfavorable band structure with twofold degeneracy at the valence band maximum, MgAgSb is still an excellent p‐type thermoelectric material for applications near room temperature. The intrinsically weak electron–phonon coupling, reflected by the low deformation potential E_def ≈ 6.3 eV, plays a crucial role in the relatively high power factor of MgAgSb. More importantly, Li is successfully doped into Mg site to tune the carrier concentration, leading to the resistivity reduction by a factor of 3 and a consequent increase in power factor by ≈30% at 300 K. Low lattice thermal conductivity can be simultaneously achieved by all‐scale hierarchical phonon scattering architecture including high density of dislocations and nanoscale stacking faults, nanoinclusions, and multiscale grain boundaries. Collectively, much higher average power factor ≈25 μW cm^?1 K^?2 with a high average ZT ≈ 1.1 from 300 to 548 K is achieved for 0.01 Li doping, which would result in a high output power density ≈1.56 W cm^?2 and leg efficiency ≈9.2% by calculations assuming cold‐side temperature T_c = 323 K, hot‐side temperature T_h = 548 K, and leg length = 2 mm.     

A multi‐resolution model to capture both global fluctuations of an enzyme and molecular recognition in the ligand‐binding site

In multi‐resolution simulations, different system components are simultaneously modeled at different levels of resolution, these being smoothly coupled together. In the case of enzyme systems, computationally expensive atomistic detail is needed in the active site to capture the chemistry of ligand binding. Global properties of the rest of the protein also play an essential role, determining the structure and fluctuations of the binding site; however, these can be modeled on a coarser level. Similarly, in the most computationally efficient scheme only the solvent hydrating the active site requires atomistic detail. We present a methodology to couple atomistic and coarse‐grained protein models, while solvating the atomistic part of the protein in atomistic water. This allows a free choice of which protein and solvent degrees of freedom to include atomistically. This multi‐resolution methodology can successfully model stable ligand binding, and we further confirm its validity by exploring the reproduction of system properties relevant to enzymatic function. In addition to a computational speedup, such an approach can allow the identification of the essential degrees of freedom playing a role in a given process, potentially yielding new insights into biomolecular function. Proteins 2016; 84:1902–1913. © 2016 Wiley Periodicals, Inc.     

Multiscale modeling of cellular actin filaments: from atomistic molecular to coarse-grained dynamics

In this article, we present a computational multiscale model for the characterization of subcellular proteins. The model is encoded inside a simulation tool that builds coarse-grained (CG) force fields from atomistic simulations. Equilibrium molecular dynamics simulations on an all-atom model of the actin filament are performed. Then, using the statistical distribution of the distances between pairs of selected groups of atoms at the output of the MD simulations, the force field is parameterized using the Boltzmann inversion approach. This CG force field is further used to characterize the dynamics of the protein via Brownian dynamics simulations. This combination of methods into a single computational tool flow enables the simulation of actin filaments with length up to 400 nm, extending the time and length scales compared to state-of-the-art approaches. Moreover, the proposed multiscale modeling approach allows to investigate the relationship between atomistic structure and changes on the overall dynamics and mechanics of the filament and can be easily (i) extended to the characterization of other subcellular structures and (ii) used to investigate the cellular effects of molecular alterations due to pathological conditions.     

Spatial Controls of Pre–Euro-American Wind and Fire Disturbance in Northern Wisconsin (USA) Forest Landscapes

We elucidate spatial controls of wind and fire disturbance across northern Wisconsin (USA), where climatic and topographic gradients are not strong, using data from the original US Public Land Survey (PLS) notes. These records contain information on the location and extent of heavy windthrows and stand-replacing fires prior to Euro-American settlement. The spatial patterns of windthrow and fire were spatially clustered at all scales in this historical environment, with stronger associations at local than regional scales. Logistic regression shows environmental variables to have a strong influence on this pattern. In the case of heavy windthrow, environmental drivers of disturbance pattern are fairly consistent across the region. The effects of climate and vegetation are predominant at all scales, but effects are often indirect, with strong interactions between them. Interactions between these two drivers and soil characteristics are also sometimes present. In contrast, models of stand-replacing fire show simple and direct control within and across fire-prone landscapes of historical northern Wisconsin, with climate and physiography as the main factors explaining the distribution of fire disturbance. This simple and direct control is lost at the regional scale, where climate, physiographic, soil, and vegetation variables, along with interactions between them, are significant factors. Contrary to other regions, the topographic effects are generally not important in predicting either wind or fire disturbance. Our work suggests that, in landscapes that lack strong environmental patterning, climate maintains its role as a primary driver of these natural disturbances, but topography is replaced by interactions and feedbacks with other forms of environmental heterogeneity.     

Scaling Theory: Application to Marine Ornithology

The problem of scale has three components: (a) direct measurement is usually confined to small areas and brief periods, (b) the most pressing issues occur at the scale of ecosystems and decades, but (c) direct scale-up fails when pattern and process at small scales differ from those at larger scales. Recognition of this dilemma has grown exponentially since around 1980. The problem of scale is particularly acute for seabirds, which inhabit one of the most extensive habitats on the planet—the surface of the ocean. The application of power laws is a promising solution to the problem. Power laws have a long empirical tradition, are readily estimated from data, and now have a theoretical basis. Power law behavior (with nonintegral exponents) appears in systems with episodically warring exponential rates. In marine ornithology, examples of areas where power laws can be applied include patchy spatial distributions, the association of predator with prey, the scaling of food intake to body size, and fractal habitat structure. Scaling theory and power laws are applicable to a wide variety of ecosystem phenomena and dynamics, including fluxes of material and energy. Received 7 May 2001; accepted 12 April 2002.