Quasi-topological Gravities on General Spherically Symmetric Metric

In this work we study a more restricted class of quasi-topological gravity theories where the higher curvature terms have no contribution to the equation of motion on general static spherically symmetric metric where $g_{tt} g_{rr} \ne \mathrm{constant}$. We construct such theories up to quintic order in Riemann tensor and observe an important property of these theories: the higher order term in the Lagrangian vanishes identically when evaluated on the most general non-stationary spherically symmetric metric ansatz. This not only signals the higher terms could only have non-trivial effects when considering perturbations, but also makes the theories quasi-topological on a much wider range of metrics. As an example of the holographic effects of such theories, we consider a general Einstein-scalar theory and calculate it's holographic shear viscosity.Comment: 10 + 11 pages and appendices, one supplementary Wolfram Language file; v2: Revised, accepted by JHE

What Chinese Medicine Can Do for Liver Cancer?

Liver cancer is an international problem, especially in Asian countries. It is because that most liver cancers are already late stage when they are diagnosed, and also most liver cancers have various previous chronic liver diseases induced by alcoholic, virus, and steatosis, etc. In recent years, laboratory and clinical studies focusing on liver cancer by Chinese medicine has been extensively studied. What Chinese medicine treatment formalities can be used in liver cancer? How Chinese medicine can be employed in treatment of liver cancer? What Chinese medicine can contribute to liver cancer? To answer these questions in this chapter, we will review and discuss treatment of liver cancer from Chinese medicine’s perspective with scientific evidences as following three parts: (1) Chinese medicine as the source of discovering new treatment for liver cancer, (2) Chinese medicine as a complementary treatment of liver cancer, and (3) to discuss future research and application of Chinese medicine in liver cancer treatment

Mathematical models and dynamic contact analysis of involute/noninvolute beveloid gears

This study investigates an approach for parametric modeling and dynamic contact analysis of involute/noninvolute beveloid gears. Firstly, the mathematical models of involute/noninvolute beveloid gear pairs are derived based on the theory of gearing and the generation mechanism. Then the parametric modeling programs of involute/noninvolute beveloid gears are developed to automatically generate exact model via a Matlab code. Subsequently, a numerical example of intersecting axes beveloid gears is presented to evaluate the dynamic stress distribution and dynamic transmission error. Finally, the dynamic contact characteristics of involute and noninvolute beveloid gears are calculated by three-dimensional dynamic contact finite element method, respectively. The results show that the noninvolute beveloid gear pairs can relieve the high dynamic stress and contact shock problem of intersecting axes beveloid gear pairs

Few-shot Image Classification based on Gradual Machine Learning

Few-shot image classification aims to accurately classify unlabeled images using only a few labeled samples. The state-of-the-art solutions are built by deep learning, which focuses on designing increasingly complex deep backbones. Unfortunately, the task remains very challenging due to the difficulty of transferring the knowledge learned in training classes to new ones. In this paper, we propose a novel approach based on the non-i.i.d paradigm of gradual machine learning (GML). It begins with only a few labeled observations, and then gradually labels target images in the increasing order of hardness by iterative factor inference in a factor graph. Specifically, our proposed solution extracts indicative feature representations by deep backbones, and then constructs both unary and binary factors based on the extracted features to facilitate gradual learning. The unary factors are constructed based on class center distance in an embedding space, while the binary factors are constructed based on k-nearest neighborhood. We have empirically validated the performance of the proposed approach on benchmark datasets by a comparative study. Our extensive experiments demonstrate that the proposed approach can improve the SOTA performance by 1-5% in terms of accuracy. More notably, it is more robust than the existing deep models in that its performance can consistently improve as the size of query set increases while the performance of deep models remains essentially flat or even becomes worse.Comment: 17 pages,6 figures,5 tables, 55 conference

Covid-19 Diagnosis Based on CT Images Through Deep Learning and Data Augmentation

Coronavirus disease 2019(Covid-19) has made people around the world suffer. And there are many researchers make efforts on deep learning methods based on CT imgaes, but the limitation of  this work is the lackage of the dataset, which is not easy to obtain. In this study, we try to use data augmentation to compensate this weakness. In the first part, we use traditional DenseNet-169, and the result shows that data augmentation can help improve the calculating speed and the accuracy. In the second part, we combine Self-trans and DenseNet-169, and the result shows that when doing data augmentation, many model performance metrics have been improved. In the third part, we use UNet++, which reaches accuracy of 0.8645. Apart from this, we think GAN and CNN may also make difference

The Underlying Mechanisms of Chinese Herbal Medicine-Induced Apoptotic Cell Death in Human Cancer

The high incidence of cancer is a global burden. Cancer cells acquire immortality, which results in loss of control in cell proliferation and population expansion. Cancer cells undergo a series of genomic instability, leading to mutated amplification or deletion of certain genes that strictly control the cell fate. Programmed cell death is a mechanism of cell fate control that is aberrantly regulated in cancer cells. Apoptosis is the major form of programmed cell death regulated by both intrinsic and extrinsic pathways. Discovering effective and specific alternative solutions that can reprogram apoptosis in cancer cells is always a challenge. Chinese herbal medicine has captured increasing attention from both researchers and manufacturers, as evidenced by observable curative effects from previous clinical experience. Hence, to clarify and reinforce the understanding of the effect of Chinese medicine on cancer, in this chapter, we will retrospectively review the latest 5 years of literature and summarize the mode of action of Chinese herbal medicine on apoptotic cell death in cancer. Both Chinese medicine-induced intrinsic and extrinsic mechanisms of apoptosis will be discussed, and common compounds from Chinese medicine with druggable potential as novel apoptosis-inducing agents will be highlighted

1−+1^{-+} Hybrid in J/ψJ/\psi Radiative Decays from Lattice QCD

We present the first theoretical prediction of the production rate of $1^{-+}$ light hybrid meson $\eta_1$ in $J/\psi$ radiative decays. In the $N_f=2$ lattice QCD formalism with the pion mass $m_\pi\approx 350$ MeV, the related electromagnetic multipole form factors are extracted from the three-point functions that involve necessarily quark annihilation diagrams, which are calculated through the distillation method. The partial width of $J/\psi\to \gamma \eta_1$ is determined to be $2.29(77)~\mathrm{eV}$ at the $\eta_1$ mass $m_{\eta_1}=2.23(4)$ GeV. If $\eta_1$ corresponds to the recently observed $\eta_1(1855)$ in the process $J/\psi\to \gamma\eta_1(1855)\to \gamma \eta\eta'$ by BESIII, then the branching fraction $\mathrm{Br}(J/\psi\to \gamma\eta_1(1855))$ is estimated to be $6.2(2.2)\times 10^{-5}$, which implies $\mathrm{Br}(\eta_1(1855)\to \eta\eta')\sim 4.3\%$