Decay Constants of Pseudoscalar DD-mesons in Lattice QCD with Domain-Wall Fermion

We present the first study of the masses and decay constants of the pseudoscalar $D$ mesons in two flavors lattice QCD with domain-wall fermion. The gauge ensembles are generated on the $24^3 \times 48$ lattice with the extent $N_s = 16$ in the fifth dimension, and the plaquette gauge action at $\beta = 6.10$, for three sea-quark masses with corresponding pion masses in the range $260-475$ MeV. We compute the point-to-point quark propagators, and measure the time-correlation functions of the pseudoscalar and vector mesons. The inverse lattice spacing is determined by the Wilson flow, while the strange and the charm quark masses by the masses of the vector mesons $\phi(1020)$ and $J/\psi(3097)$ respectively. Using heavy meson chiral perturbation theory (HMChPT) to extrapolate to the physical pion mass, we obtain $f_D = 202.3(2.2)(2.6)$ MeV and $f_{D_s} = 258.7(1.1)(2.9)$ MeV.Comment: 15 pages, 3 figures. v2: the statistics of ensemble (A) with m_sea = 0.005 has been increased, more details on the systematic error, to appear in Phys. Lett.

GAN Ensemble for Anomaly Detection

When formulated as an unsupervised learning problem, anomaly detection often requires a model to learn the distribution of normal data. Previous works apply Generative Adversarial Networks (GANs) to anomaly detection tasks and show good performances from these models. Motivated by the observation that GAN ensembles often outperform single GANs in generation tasks, we propose to construct GAN ensembles for anomaly detection. In the proposed method, a group of generators and a group of discriminators are trained together, so every generator gets feedback from multiple discriminators, and vice versa. Compared to a single GAN, a GAN ensemble can better model the distribution of normal data and thus better detect anomalies. Our theoretical analysis of GANs and GAN ensembles explains the role of a GAN discriminator in anomaly detection. In the empirical study, we evaluate ensembles constructed from four types of base models, and the results show that these ensembles clearly outperform single models in a series of tasks of anomaly detection.Comment: 8 pages, 6 figures. To appear in Proceedings 35th AAAI Conference on Artificial Intelligence (AAAI 21

Changes In The Bargaining Power Of Chinese Migrant Workers And The Factors Enhancing Laborers Power

The shortage of migrant workers phenomenon is not only a reflection of the changing concept of occupation for Chinese migrant workers, but it also increases job opportunities for such workers. Migrant workers fight for higher wages through strikes and collective negotiations. These changes reflect the enhancement of the bargaining power of Chinese migrant workers.This paper explores the factors that enhance Chinese migrant workers bargaining power, uses a fuzzy comprehensive evaluation based on the analytic hierarchy process to assess the effect of various factors, and analyzes the positive and negative effects of enhancing the bargaining power. Finally, this paper predicts changes in the bargaining power of Chinese migrant workers and provides corresponding recommendations to protect their advantages

Improvement on thermal performance of a disk-shaped miniature heat pipe with nanofluid

The present study aims to investigate the effect of suspended nanoparticles in base fluids, namely nanofluids, on the thermal resistance of a disk-shaped miniature heat pipe [DMHP]. In this study, two types of nanoparticles, gold and carbon, in aqueous solution are used respectively. An experimental system was set up to measure the thermal resistance of the DMHP with both nanofluids and deionized [DI] water as the working medium. The measured results show that the thermal resistance of DMHP varies with the charge volume and the type of working medium. At the same charge volume, a significant reduction in thermal resistance of DMHP can be found if nanofluid is used instead of DI water