Statistics of grain microstructure evolution under anisotropic grain boundary energies and mobilities using threshold-dynamics

This paper investigates the statistical behavior of two-dimensional grain microstructures during grain growth under anisotropic grain boundary characters. We employ the threshold-dynamics method, which allows for unparalleled computational speed, to simulate the full-field curvature motion of grain boundaries in a large polycrystal ensemble. Two sets of numerical experiments are performed to explore the effect of grain boundary anisotropy on the evolution of microstructure features. In the first experiment, we focus on abnormal grain growth and find that grain boundary anisotropy introduces a statistical preference for certain grain orientations. This leads to changes in the overall grain size distribution from the isotropic case. In the second experiment, we examine the texture development and growth of twin grain boundaries at different initial microstructures. We find that both phenomena are more pronounced when the initial microstructure has a dominant fraction of high-angle grain boundaries. Our results suggest effective grain boundary engineering strategies for improving material properties.Comment: 25pages, Figure

Segment-Based Wall Treatment Model for Heat Transfer Rate in Smoothed Particle Hydrodynamics

In this study, a smoothed particle hydrodynamics (SPH) model that applies a segment-based boundary treatment is used to simulate natural convection. In a natural convection simulated using an SPH model, the wall boundary treatment is a major issue because accurate heat transfer from boundaries should be calculated. The boundary particle method, which models the boundary by placing multiple layers of particles on and behind the wall boundary, is the most widely used boundary treatment method. Although this method can impose accurate boundary conditions, boundary modeling for complex shapes is challenging and requires excessive computational costs depending on the boundary shape. In this study, we utilize a segment-based boundary treatment method to model the wall boundary and apply this method to the energy conservation equation for the wall heat transfer model. The proposed method solves the problems arising from the use of boundary particles and simultaneously provides accurate heat transfer calculation results for the wall. In various numerical examples, the proposed method is verified through a comparison with available experimental results, SPH results using the boundary particle method, and finite volume method (FVM) results

Fast Marching based Rendezvous Path Planning for a Team of Heterogeneous Vehicle

A formulation is developed for deterministically calculating the optimized paths for a multi-agent system consisting of heterogeneous vehicles. The essence of this formulation is the calculation of the shortest time for each agent to reach every grid point from its known initial position. Such arrival time map can be readily assessed using the Fast Marching Method (FMM), a computational algorithm originally designed for solving boundary value problems of the Eikonal equation. Leveraging the FMM method, we demonstrate that the minimal time rendezvous point and paths for all member vehicles can be uniquely determined with minimal computational concerns. To showcase the potential of our method, we use an example of a virtual rendezvous scenario that entails the coordination of a ship, an underwater vehicle, an aerial vehicle, and a ground vehicle to converge at the optimal location within the Tampa Bay area in minimal time. It illustrates the value of the developed framework in efficiently constructing continuous path planning, while accommodating different operational constraints of heterogeneous member vehicles

miR-27a and miR-27b regulate autophagic clearance of damaged mitochondria by targeting PTEN-induced putative kinase 1 (PINK1)

Computational prediction of miRNA candidates for human PINK1. a Computation prediction of miRNAs expressed in human midbrain with putative binding sites in the 3′UTR of human PINK1 mRNA. We first searched miRNAs that have putative binding sites in the 3′UTR of human PINK1 mRNA by utilizing several miRNA-target prediction algorithms, such as miRanda [67], miRWalk [68], RNAhybrid [37], and Targetscan [69]. Among 49 miRNAs commonly predicted by different algorithms, 7 miRNAs were known to be expressed in human midbrain [34]. miR-27a/b are predicted to have 2 putative binding sites in the 3′UTR of human PINK1 mRNA, while all other miRNAs are predicted to have 1 putative binding site. b Computational binding prediction of miR-27a/b and their binding sites in the 3′UTR of human PINK1 mRNA. The binding free energies were determined by the RNAhybrid algorithm. (PDF 68 kb

Imiquimod enhances excitability of dorsal root ganglion neurons by inhibiting background (K2P) and voltage-gated (Kv1.1 and Kv1.2) potassium channels

<p>Abstract</p> <p>Background</p> <p>Imiquimod (IQ) is known as an agonist of Toll-like receptor 7 (TLR7) and is widely used to treat various infectious skin diseases. However, it causes severe itching sensation as its side effect. The precise mechanism of how IQ causes itching sensation is unknown. A recent report suggested a molecular target of IQ as TLR7 expressed in dorsal root ganglion (DRG) neurons. However, we recently proposed a TLR7-independent mechanism, in which the activation of TLR7 is not required for the action of IQ in DRG neurons. To resolve this controversy regarding the involvement of TLR7 and to address the exact molecular identity of itching sensation by IQ, we investigated the possible molecular target of IQ in DRG neurons.</p> <p>Findings</p> <p>When IQ was applied to DRG neurons, we observed an increase in action potential (AP) duration and membrane resistance both in wild type and TLR7-deficient mice. Based on these results, we tested whether the treatment of IQ has an effect on the activity of K⁺channels, K_v1.1 and K_v1.2 (voltage-gated K⁺channels) and TREK1 and TRAAK (K_2Pchannels). IQ effectively reduced the currents mediated by both K⁺channels in a dose-dependent manner, acting as an antagonist at TREK1 and TRAAK and as a partial antagonist at K_v1.1 and K_v1.2.</p> <p>Conclusions</p> <p>Our results demonstrate that IQ blocks the voltage-gated K⁺channels to increase AP duration and K_2Pchannels to increase membrane resistance, which are critical for the membrane excitability of DRG neurons. Therefore, we propose that IQ enhances the excitability of DRG neurons by blocking multiple potassium channels and causing pruritus.</p