Topolgical Charged Black Holes in Generalized Horava-Lifshitz Gravity

As a candidate of quantum gravity in ultrahigh energy, the $(3+1)$-dimensional Ho\v{r}ava-Lifshitz (HL) gravity with critical exponent $z\ne 1$, indicates anisotropy between time and space at short distance. In the paper, we investigate the most general $z=d$ Ho\v{r}ava-Lifshitz gravity in arbitrary spatial dimension $d$, with a generic dynamical Ricci flow parameter $\lambda$ and a detailed balance violation parameter $\epsilon$. In arbitrary dimensional generalized HL$_{d+1}$ gravity with $z\ge d$ at long distance, we study the topological neutral black hole solutions with general $\lambda$ in $z=d$ HL$_{d+1}$, as well as the topological charged black holes with $\lambda=1$ in $z=d$ HL$_{d+1}$. The HL gravity in the Lagrangian formulation is adopted, while in the Hamiltonian formulation, it reduces to Dirac$-$De Witt's canonical gravity with $\lambda=1$. In particular, the topological charged black holes in $z=5$ HL$_6$, $z=4$ HL$_5$, $z=3,4$ HL$_4$ and $z=2$ HL$_3$ with $\lambda=1$ are solved. Their asymptotical behaviors near the infinite boundary and near the horizon are explored respectively. We also study the behavior of the topological black holes in the $(d+1)$-dimensional HL gravity with $U(1)$ gauge field in the zero temperature limit and finite temperature limit, respectively. Thermodynamics of the topological charged black holes with $\lambda=1$, including temperature, entropy, heat capacity, and free energy are evaluated.Comment: 51 pages, published version. The theoretical framework of z=d HL gravity is set up, and higher curvature terms in spatial dimension become relevant at UV fixed point. Lovelock term, conformal term, new massive term, and Chern-Simons term with different critical exponent z are studie

Exponential Stability of the Inhomogeneous Navier-Stokes-Vlasov System in Vacuum

The main purpose of the present paper is to study the influence of the vacuum on the asymptotic behaviors of solutions to the inhomogeneous Navier-Stokes-Vlasov system in $\mathbb{R}^3\times\mathbb{R}^3$. To this end, we establish the uniform bound of the macroscopic density associated with the distribution function and prove the global existence and uniqueness of strong solutions to the Cauchy problem with vacuum for either small initial energy or large viscosity coefficient. The uniform boundedness and the presence of vacuum enable us to show that as the time evolves, the fluid velocity decays, while the distribution function concentrates towards a Dirac measure in velocity centred at $0$, with an exponential rate

Short hairpin RNA expression for enhancing the resistance of Bombyx mori (Bm) to nucleopolyhedrovirus in vitro and in vivo

A new paradigm of RNAi technology has been studied for enhancing the resistance to virus in plants and animals. Previous studies have shown that the Bombyx mori (Bm) U6 promoter based shRNA is an effective tool for inducing RNAi in Bombyx mori cell line. However, widespread knockdown and induction of phenotypes in Bm larvae have not been fully demonstrated. In this study, we examined Bm U6 promoter based shRNA expression for suppressing Bm nucleopolyhedrovirus (NPV) in the Bm cell line and silkworm larvae. We measured the relative expression level of replication genes of BmNPV in hemolymph of silkworm larvae and BmN cells transfected with recombinant targeting shRNA by quantitative real time polymerase chain reaction (PCR). These results indicated that the recombinant shRNA expression system was a useful tool for resistance to BmNPV in vivo and in vitro. The approach opens the door of RNAi technology as a wide range of strategies that offer a technically simpler, cheaper, and quicker gene-knockdown by recombinant shRNA for future genetics in silkworm Bm and other related species.Key words: RNA interference (RNAi), Silkworm Bombyx mori (Bm) cell line, short hairpin RNA (shRNA), Bm nucleopolyhedrovirus (BmNPV), quantitative real time polymerase chain reaction, Bm U6 promoter

Active Learning on a Programmable Photonic Quantum Processor

Training a quantum machine learning model generally requires a large labeled dataset, which incurs high labeling and computational costs. To reduce such costs, a selective training strategy, called active learning (AL), chooses only a subset of the original dataset to learn while maintaining the trained model's performance. Here, we design and implement two AL-enpowered variational quantum classifiers, to investigate the potential applications and effectiveness of AL in quantum machine learning. Firstly, we build a programmable free-space photonic quantum processor, which enables the programmed implementation of various hybrid quantum-classical computing algorithms. Then, we code the designed variational quantum classifier with AL into the quantum processor, and execute comparative tests for the classifiers with and without the AL strategy. The results validate the great advantage of AL in quantum machine learning, as it saves at most $85\%$ labeling efforts and $91.6\%$ percent computational efforts compared to the training without AL on a data classification task. Our results inspire AL's further applications in large-scale quantum machine learning to drastically reduce training data and speed up training, underpinning the exploration of practical quantum advantages in quantum physics or real-world applications

1-Benzyl-2,3-dihydro­quinolin-4(1H)-one

In the title compound, C16H15NO, the two aromatic rings are approximately perpendicular; the carbonyl group is twisted out of the adjacent benzene ring by 14.8 (2)°. In the heterocyclic ring, the C atom linked to the carbonyl group and the C atom linked to the N atom have opposite deviations of 0.467 (5) and 0.184 (4) Å, respectively, from the plane of the benzene ring. The N atom lies approximately in the plane of the phenyl ring. There are no conventional hydrogen bonds; the packing of mol­ecules in the crystal structure is stabilized by van der Waals forces