The thermoelectric properties of molybdenum monocarbide (MoC) monolayers, a new 2D material, are calculated from first-principles calculations using Boltzmann transport theory. The indirect bandgap of this monolayer semiconductor is 0.51 eV, and the calculated lattice thermal conductivity is 7.7 W/mK. The high Seebeck coefficient, indicating high thermoelectricity, is found in both p-type and n-type MoC monolayers. This coefficient increases with temperature. The electronic conductivity for the p-type is higher than for the n-type one because the valance band is much more delocalized than the conduction band around the Fermi level. However, the calculated electronic thermal conductivity is essentially independent of temperature. The thermoelectric figure of merit (ZT) value of the n-type doped 2D-MoC is smaller than that of the p-type; thus, the thermoelectric properties are dominated by the p-type.
The geometric phase in metasurfaces follows a symmetry restriction of chirality, which dictates that the phases of two orthogonal circularly polarized waves are identical but have opposite signs. In this study, we propose a general mechanism to disrupt this symmetric restriction on the chirality of orthogonal circular polarizations by introducing mirror-symmetry-breaking meta-atoms. This mechanism introduces a new degree of freedom in spin-decoupled phase modulation without necessitating the rotation of the meta-atom. To demonstrate the feasibility of this concept, we design what we believe is a novel meta-atom with a QR-code structure and successfully showcase circular-polarization multiplexing metasurface holography. Our investigation offers what we believe to be a novel understanding of the chirality in geometric phase within the realm of nanophotonics. Moreover, it paves the way for the development of what we believe will be novel design methodologies for electromagnetic structures, enabling applications in arbitrary wavefront engineering.
Projection twin support vector machine (PTSVM) is an effective tool for classification. However, it is sensitive to outliers or the noise due to the utilization of the squared L2-norm distance. To alleviate the sensitivity to outliers or the noise, we propose a capped L1-norm projection twin support vector machine (CPTSVM), where the L2-norm distance is replaced by the capped L1-norm to confer the robustness to classifiers. CPTSVM is formulated as a pair of non-convex and non-smooth SVM-type problems. To solve these difficult problems, we present an iterative algorithm for CPTSVM as well as its convergence properties. Numerical experiments on artificial and benchmark datasets demonstrate the robustness and feasibility of our proposed method.
Abstract Regarding to the actual situation of the new coronavirus disease 2019 epidemic, social factors should be taken into account and the increasing growth trend of confirmed populations needs to be explained. A proper model needs to be established, not only to simulate the epidemic, but also to evaluate the future epidemic situation and find a pilot indicator for the outbreak. The original susceptible-infectious-recover model is modified into the susceptible-infectious-quarantine-confirm-recover combined with social factors (SIDCRL) model, which combines the natural transmission with social factors such as external interventions and isolation. The numerical simulation method is used to imitate the change curve of the cumulative number of the confirmed cases and the number of cured patients. Furthermore, we investigate the relationship between the suspected close contacts (SCC) and the final outcome of the growth trend of confirmed cases with a simulation approach. This article selects four representative countries, that is, China, South Korea, Italy, and the United States, and gives separate numerical simulations. The simulation results of the model fit the actual situation of the epidemic development and reasonable predictions are made. In addition, it is analyzed that the increasing number of SCC contributes to the epidemic outbreak and the prediction of the United States based on the population of the SCC highlights the importance of external intervention and active prevention measures. The simulation of the model verifies its reliability and stresses that observable variable SCC can be taken as a pilot indicator of the coronavirus disease 2019 pandemic.
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