Construction of Diffeomorphisms with Prescribed Jacobian Determinant and Curl: - that forms a new definition of Averaging Diffeomorphisms.

The Variational Principle (VP) is designed to generate non-folding grids (diffeomorphisms) with prescribed Jacobian determinant (JD) and curl. The solution pool of the original VP is based on an additive formulation and, consequently, is not invariant in the diffeomorphic Lie algebra. The original VP works well when the prescribed pair of JD and curl is calculated from a diffeomorphism, but not necessarily when the prescribed JD and curl are unknown to come from a diffeomorphism. In spite of that, the original VP works effectively in 2D grid generations. To resolve this issue, in this paper, we describe a new version of VP (revised VP), which is based on the composition of transformations and, therefore, is invariant in the Lie algebra. The revised VP seems to have overcome the inaccuracy of the original VP in 3D grid generations. In the following sections, the mathematical derivations are presented. It is shown that the revised VP can calculate the inverse transformation of a known diffeomorphism. Its inverse consistency and transitivity of transformations are also demonstrated numerically. Finally, a new definition of averaging diffeomorphisms based on the revised VP is proposed.

Effect of Tool Coatings on Machining Properties of Compacted Graphite Iron.

Compacted graphite iron (CGI) has become the most ideal material for automotive engine manufacturing owing to its excellent mechanical properties. However, tools are severely worn during processing, considerably shortening their lifespan. In this study, we prepared a series of cemented carbide-coated tools and evaluated their coating properties in cutting tests. Among all tested coatings, PVD coating made of AlCrN (AC) presented with the best surface integrity and mechanical properties, achieving the best comprehensive performance in the coating test. The AC-coated tool also exhibited the best cutting performance at a low speed of 120 m/min, corresponding to a 60% longer cutting life and the lowest workpiece surface roughness relative to other coated tools. In the cutting test at a high speed of 350 m/min, the CVD double-layer coated tool (MT) with a TiCN inner layer of and an Al2O3 outer layer had a 70% longer cutting life and the lowest workpiece surface roughness relative to other coated tools.

Impact of dipole-dipole interactions on motility-induced phase separation.

We present a hydrodynamic theory for systems of dipolar active Brownian particles which, in the regime of weak dipolar coupling, predicts the onset of motility-induced phase separation (MIPS), consistent with Brownian dynamics (BD) simulations. The hydrodynamic equations are derived by explicitly coarse-graining the microscopic Langevin dynamics, thus allowing for a mapping of the coarse-grained model and particle-resolved simulations. Performing BD simulations at fixed density, we find that dipolar interactions tend to hinder MIPS, as first reported in [Liao et al., Soft Matter, 2020, 16, 2208]. Here we demonstrate that the theoretical approach indeed captures the suppression of MIPS. Moreover, the analysis of the numerically obtained, angle-dependent correlation functions sheds light into the underlying microscopic mechanisms leading to the destabilization of the homogeneous phase.

A novel approach to form Normal Distribution of Medical Image Segmentation based on multiple doctors' annotations.

Medical image segmentation annotated by experts provides the labeled data sets for many scientific researches. However, due to the unevenly experienced backgrounds of the experts and limited numbers of patients with certain diseases or illnesses, not only do such labeled data sets have smaller samples but their quality and normality also can range in wide variabilities and be ambiguous. In practice, these segmentations are usually assigned to be the ground truths for the scientific studies, so it may undermine the trustworthiness of the resulting findings. Therefore, it is meaningful to consider how to give a more unified opinion of the annotations among different experts. In this paper, a novel approach to form normal distributions of segmentation is proposed based on multiple doctors' annotations for the same patient. The proposed approach is developed through the following steps: (1) utilize a framework7 of averaging images to construct an averaged annotation based on different given annotations; (2) determine the image registration deformations from the averaged annotation to the given annotations; (3) build a joint multivariate Gaussian distribution over the logorithm of Jacobian determinants and curls of the registration deformations; lastly, (4) simulate a normal distribution of segmentation by the joint Gaussian distribution of registration deformation. This work translates the problem of forming a normal distribution of the image segmentation into a problem of forming joint Gaussian distribution of image registration deformations, which the latter can be reasoned by Jacobian determinant (models local size of pixel cells) and curl (models local rotation of pixel cells) information. In the following sections, a detailed walk-through of the proposed approach is provided along with its analytical mathematics and numerical examples for its effectiveness. A synthetic example of 3 manually defined label image is made to show how to construct a mean label image, and an example of a real cancer image annotated by 3 doctors demonstrates the formation of the normal distribution and the effectiveness of the propose method.

Emergent vortices and phase separation in systems of chiral active particles with dipolar interactions.

Using Brownian dynamics (BD) simulations we investigate the self-organization of a monolayer of chiral active particles with dipolar interactions. Each particle is driven by both, translational and rotational self-propulsion, and carries a permanent point dipole moment at its center. The direction of the translational propulsion for each particle is chosen to be parallel to its dipole moment. Simulations are performed at high dipolar coupling strength and a density below that related to motility-induced phase separation in simple active Brownian particles. Despite this restriction, we observe a wealth of phenomena including formation of two types of vortices, phase separation, and flocking transitions. To understand the appearance and disappearance of vortices in the many-particle system, we further investigate the dynamics of simple ring structures under the impact of self-propulsion.

Correction: Dynamical self-assembly of dipolar active Brownian particles in two dimensions.

Correction for 'Dynamical self-assembly of dipolar active Brownian particles in two dimensions' by Guo-Jun Liao et al., Soft Matter, 2020, 16, 2208-2223, DOI: .

Clustering and phase separation in mixtures of dipolar and active particles.

The self-assembly of colloidal particles in dynamic environments has become an important field of study because of potential applications in fabricating out-of-equilibrium materials. We investigate the phase behavior of mixtures of passive dipolar colloids and active soft spheres using Brownian dynamics simulations in two dimensions. The phase behaviors exhibited include dipolar percolated network, dipolar string-fluid, isotropic fluid, and a phase-separated state. We find that the clustering of dipolar colloids is enhanced in the presence of slow-moving active particles compared to the clustering of dipolar particles mixed with passive particles. When the active particle motility is high, the chains of dipolar particles are either broken into short chains or pushed into dense clusters. Motility-induced phase separation into dense and dilute phases is also present. The area fraction of particles in the dilute phase increases as the fraction of active particles in the system decreases, while the area fraction of particles in the dense phase remains constant. Our findings are relevant to the development of reconfigurable self-assembled materials.

Dynamical self-assembly of dipolar active Brownian particles in two dimensions.

Based on Brownian Dynamics (BD) simulations, we study the dynamical self-assembly of active Brownian particles with dipole-dipole interactions, stemming from a permanent point dipole at the particle center. The propulsion direction of each particle is chosen to be parallel to its dipole moment. We explore a wide range of motilities and dipolar coupling strengths and characterize the corresponding behavior based on several order parameters. At low densities and low motilities, the most important structural phenomenon is the aggregation of the dipolar particles into chains. Upon increasing the particle motility, these chain-like structures break, and the system transforms into a weakly correlated isotropic fluid. At high densities, we observe that the motility-induced phase separation is strongly suppressed by the dipolar coupling. Once the dipolar coupling dominates the thermal energy, the phase separation disappears, and the system rather displays a flocking state, where particles form giant clusters and move collective along one direction. We provide arguments for the emergence of the flocking behavior, which is absent in the passive dipolar system.

Clustering and phase separation of circle swimmers dispersed in a monolayer.

We perform Brownian dynamics simulations in two dimensions to study the collective behavior of circle swimmers, which are driven by both, an (effective) translational and rotational self-propulsion, and interact via steric repulsion. We find that active rotation generally opposes motility-induced clustering and phase separation, as demonstrated by a narrowing of the coexistence region upon increase of the propulsion angular velocity. Moreover, although the particles are intrinsically assigned to rotate counterclockwise, a novel state of clockwise vortices emerges at an optimal value of the effective propulsion torque. We propose a simple gear-like model to capture the underlying mechanism of the clockwise vortices.

Entropic attraction: Polymer compaction and expansion induced by nano-particles in confinement.

We investigated nanoparticle (NP)-induced coil-to-globule transition of a semi-flexible polymer in a confined suspension of ideal NP using Langevin dynamics. DNA molecules are often found to be highly compact, bound with oppositely charged proteins in a crowded environment within cells and viruses. Recent studies found that high concentration of electrostatically neutral NP also condenses DNA due to entropically induced depletion attraction between DNA segments. Langevin dynamics simulations with a semi-flexible chain under strong confinement were performed to investigate the competition between NP-induced monomer-monomer and monomer-wall attraction under different confinement heights and NP volume fractions. We found that whether NP induce polymer segments to adsorb to the walls and swell or to attract one another and compact strongly depends on the relative strength of the monomer-wall and the NP-wall interactions.