Graphs with many independent vertex cuts

The cycles are the only $2$-connected graphs in which any two nonadjacent vertices form a vertex cut. We generalize this fact by proving that for every integer $k\ge 3$ there exists a unique graph $G$ satisfying the following conditions: (1) $G$ is $k$-connected; (2) the independence number of $G$ is greater than $k;$ (3) any independent set of cardinality $k$ is a vertex cut of $G.$ The edge version of this result does not hold. We also consider the problem when replacing independent sets by the periphery

Synchronization of reaction–diffusion Hopfield neural networks with s-delays through sliding mode control

Synchronization of reaction–diffusion Hopfield neural networks with s-delays via sliding mode control (SMC) is investigated in this paper. To begin with, the system is studied in an abstract Hilbert space C([–r; 0];U) rather than usual Euclid space Rn. Then we prove that the state vector of the drive system synchronizes to that of the response system on the switching surface, which relies on equivalent control. Furthermore, we prove that switching surface is the sliding mode area under SMC. Moreover, SMC controller can also force with any initial state to reach the switching surface within finite time, and the approximating time estimate is given explicitly. These criteria are easy to check and have less restrictions, so they can provide solid theoretical guidance for practical design in the future. Three different novel Lyapunov–Krasovskii functionals are used in corresponding proofs. Meanwhile, some inequalities such as Young inequality, Cauchy inequality, Poincaré inequality, Hanalay inequality are applied in these proofs. Finally, an example is given to illustrate the availability of our theoretical result, and the simulation is also carried out based on Runge–Kutta–Chebyshev method through Matlab

Effect of Electromagnetic Frequency on the Flow Behavior in Mold during Bloom Casting

Considering solidification, a large eddy simulation (LES) model of two-phase flow was established to simulate the thermal–magnetic flow coupled fields inside a jumbo bloom. The magnetic field was calculated based on Maxwell’s equations, constitutive equations, and Ohm’s law. An enthalpy–porosity technique was used to model the solidification of the steel. The movement of the free surface was described by the volume of fluid (VOF) approach. With the effect of electromagnetic stirring (MEMS), the vortices in the bloom tended to be strip-like; large vortices mostly appeared in the injection zone, while small ones were found near the surface of the bloom. It is newly found that even though the submerged entry nozzle (SEN) is asymmetrical about the bloom, a biased flow can also be found under the effect of MEMS. The reason for this phenomenon is because the magnetic force is asymmetrical and transient. A high frequency will reduce the period of biased flow; however, the frequency should not be too high because it could also intensify meniscus fluctuations and thus entrap slag droplets in the mold. The velocity near the solidification front can also be increased with a higher frequency

Effect of Electromagnetic Frequency on the Flow Behavior in Mold during Bloom Casting

Considering solidification, a large eddy simulation (LES) model of two-phase flow was established to simulate the thermal–magnetic flow coupled fields inside a jumbo bloom. The magnetic field was calculated based on Maxwell’s equations, constitutive equations, and Ohm’s law. An enthalpy–porosity technique was used to model the solidification of the steel. The movement of the free surface was described by the volume of fluid (VOF) approach. With the effect of electromagnetic stirring (MEMS), the vortices in the bloom tended to be strip-like; large vortices mostly appeared in the injection zone, while small ones were found near the surface of the bloom. It is newly found that even though the submerged entry nozzle (SEN) is asymmetrical about the bloom, a biased flow can also be found under the effect of MEMS. The reason for this phenomenon is because the magnetic force is asymmetrical and transient. A high frequency will reduce the period of biased flow; however, the frequency should not be too high because it could also intensify meniscus fluctuations and thus entrap slag droplets in the mold. The velocity near the solidification front can also be increased with a higher frequency

Spin-phonon coupling in two-dimensional magnetic materials

Recently, two-dimensional magnetic materials (2DMMs) have become a focused research direction in a broad range of two-dimensional materials, due to their underlying significance in fundamental research, as well as in technologically relevant applications for future spintronics, magnonics, quantum information and data storage. The rich toolbox of 2DMMs and their diverse tunability have enabled the unprecedented research concerning the two-dimensional magnetic order down to single atomic layer of materials, much beyond the classical thin film magnetism, showing an extremely promising avenue towards electronics, magneto-optics and photonics. Among various degrees of freedoms, the interaction between spin and phonon (i.e., quanta of lattice vibration), hence the so-called spin-phonon coupling, serves as an important tuning knob to explore the two-dimensional magnetism, creates new types of quasiparticles and controls the magnetic order. This review overviews the latest developments in spin-phonon coupling investigations in 2DMMs. Various techniques utilizing spin-phonon coupling to investigate two-dimensional magnetism are discussed. Recent progress in tuning two-dimensional magnetic order based on spin-phonon coupling is also summarized, with a focus to understand the new functionalities. Furthermore, device developments and concepts based on spin-phonon coupling are briefly discussed. This review will provide our perspectives on the existing challenges and future directions in spin-phonon coupling research in 2DMMs and their functional devices

Spin-phonon coupling in two-dimensional magnetic materials

Recently, two-dimensional magnetic materials (2DMMs) have become a focused research direction in a broad range of two-dimensional materials, due to their underlying significance in fundamental research, as well as in technologically relevant applications for future spintronics, magnonics, quantum information and data storage. The rich toolbox of 2DMMs and their diverse tunability have enabled the unprecedented research concerning the two-dimensional magnetic order down to single atomic layer of materials, much beyond the classical thin film magnetism, showing an extremely promising avenue towards electronics, magneto-optics and photonics. Among various degrees of freedoms, the interaction between spin and phonon (i.e., quanta of lattice vibration), hence the so-called spin-phonon coupling, serves as an important tuning knob to explore the two-dimensional magnetism, creates new types of quasiparticles and controls the magnetic order. This review overviews the latest developments in spin-phonon coupling investigations in 2DMMs. Various techniques utilizing spin-phonon coupling to investigate two-dimensional magnetism are discussed. Recent progress in tuning two-dimensional magnetic order based on spin-phonon coupling is also summarized, with a focus to understand the new functionalities. Furthermore, device developments and concepts based on spin-phonon coupling are briefly discussed. This review will provide our perspectives on the existing challenges and future directions in spin-phonon coupling research in 2DMMs and their functional devices.</p

Review of the Research Progress in Combat Simulation Software

To address the new functional requirements brought by the introduction of new weapons and new combat modes, a comprehensive survey of the research progress in the area of combat simulation software is performed from the perspective of software engineering. First, the top-level specification, simulation engine, and simulation framework of combat simulation software are reviewed. Then, several typical combat simulation software systems are demonstrated, and the relevant software frameworks are analyzed. Finally, combining the application prospect of artificial intelligence, metaverse, and other new technologies in combat simulation, the development trends of combat simulation software are presented, namely intellectualization, adaptation to an LVC (live, virtual, and constructive) system, and a more game-based experience. Based on a comprehensive comparison between the mentioned simulation frameworks, we believe that the AFSIM (Advanced framework for simulation, integration, and modeling) and the E-CARGO (Environments—classes, agents, roles, groups, and objects) are appropriate candidates for developing distributed combat simulation software

Perspectives on the Training of Chinese Primary Health Care Physicians to Reduce Chronic Illnesses and Their Burden

This paper is a commentary on the training of Chinese Primary Health Care Doctors to reduce chronic illness and its burden. First, we will consider the policy position of the Chinese government concerning the development of a competent and enlarged primary physician workforce to deliver the proposed primary health care system reforms. We then turn to a review of the drivers of the high burden of chronic illnesses especially in older people in China. We argue that the curriculum for the training of primary health care medical practitioners should match the demonstrated high prevalence chronic illnesses and their risk factors and that there needs to specific competencies in prevention and mitigation of the diseases and their risk factors.This research was funded by The Sanming Project of Medicine in Shenzhen Sanming Project team code: SZSM201511046 and the Australian Research Council Discovery Grant - Aging in China and Australia: Promoting health, productivity and well-being Grant number DP160103023

Mapping the Invasive Species <i>Stellera chamaejasme</i> in Alpine Grasslands Using Ecological Clustering, Spectral Separability and Image Classification

Stellera chamaejasme (Thymelaeaceae) is amongst the worst invasive species of the alpine grasslands on the Qinghai–Tibet Plateau; timely and effective monitoring is critical for its prevention and control. In this study, by using high spatial resolution Planet imagery, an optimal approach was explored to improve the discrimination of S. chamaejasme from surrounding communities, integrated with TWINSAPN technique, Transformed divergence and image classification algorithms. Results demonstrated that there were obvious spectral conflicts observed among the TWINSPAN ecological communities, owing to the inconsistency of S. chamaejasme coverage within the communities. By determining the threshold of spectral separability, the adjustment of ecological classification produced spectrally separated S. chamaejasme communities and native species communities. The sensitive index characterizing the spectra of S. chamaejasme contributes to its discrimination; moderate or good classification accuracy was obtained by using four machine learning algorithms, of which Random Forest achieved the highest accuracy of S. chamaejasme classification. Our study suggests the distinct phenological feature of S. chamaejasme provides a basis for the detection of the toxic weed, and the establishment of communities using the rule of spectral similarity can assist the accurate discrimination of invasive species