A 1+5-dimensional gravitational-wave solution: curvature singularity and spacetime singularity

We solve a $1+5$-dimensional cylindrical gravitational-wave solution of the Einstein equation, in which there are two curvature singularities. Then we show that one of the curvature singularities can be removed by an extension of the spacetime. The result exemplifies that the curvature singularity is not always a spacetime singularity; in other words, the curvature singularity cannot serve as a criterion for spacetime singularities

Scalar scattering in Schwarzschild spacetime: Integral equation method

An integral equation method for scalar scattering in Schwarzschild spacetime is constructed. The zeroth-order and first-order scattering phase shift is obtained

Why the entropy of spacetime is independent of species of particles -- the species problem

The Hawking radiation emits all species of particles, but the Bekenstein-Hawking entropy is independent of the number of the species of particles. This is the so-called species problem --- a puzzling problem for a long time. In this paper, we suggest a solution to this problem. A result of the scheme is that the black hole atmosphere has a mass equaling 3/8 mass of a classical Schwarzschild black hole, which agrees with 't Hooft's brick wall model

Synthesis and Characterization of Bowl-Like Single-Crystalline BaTiO3 Nanoparticles

Novel bowl-like single-crystalline BaTiO(3) nanoparticles were synthesized by a simple hydrothermal method using Ba(OH)(2)·8H(2)O and TiO(2) as precursors. The as-prepared products were characterized by XRD, Raman spectroscopy, SEM and TEM. The results show that the bowl-like BaTiO(3) nanoparticles are single-crystalline and have a size about 100–200 nm in diameter. Local piezoresponse force measurements indicate that the BaTiO(3) nanoparticles have switchable polarization at room temperature. The local effective piezoelectric coefficient [Image: see text] is approximately 28 pm/V

The Highest Melting Point Material: Searched by Bayesian Global Optimization with Deep Potential Molecular Dynamics

The interest in refractory materials is increasing rapidly in recent decades due to the development of hypersonic vehicles. However, which substance has the highest melting point keeps a secret, since precise measurements in extreme condition are overwhelmingly difficult. In the present work, an accurate deep potential model of Hf-Ta-C-N system was firstly trained, and then applied to search for the highest melting point material by using molecular dynamics simulation and Bayesian global optimization. The predicted melting points agree well with experiments, and confirm that the carbon site vacancy can enhance melting points of rock-salt structure carbides. Solid solution with N is verified as another new and more effective melting point enhancing approach for HfC, while the conventional routing of solid solution with Ta (e.g. HfTa4C5) is not suggested to result in a maximum melting point. The highest melting point (~ 4236 K) is achieved with composition of HfC0.638N0.271, which is ~ 80 K higher than the highest value in Hf-C binary system. The dominating mechanism of N addition is believed to be the instable C-N and N-N bonds in liquid phase, which reduces the liquid phase entropy and renders the liquid phase less stable. The improved melting point and fewer gas generation during oxidation by addition of N provides new routing to modify the thermal protection materials for hypersonic vehicles

Domain Adaptive Faster R-CNN for Object Detection in the Wild

Object detection typically assumes that training and test data are drawn from an identical distribution, which, however, does not always hold in practice. Such a distribution mismatch will lead to a significant performance drop. In this work, we aim to improve the cross-domain robustness of object detection. We tackle the domain shift on two levels: 1) the image-level shift, such as image style, illumination, etc, and 2) the instance-level shift, such as object appearance, size, etc. We build our approach based on the recent state-of-the-art Faster R-CNN model, and design two domain adaptation components, on image level and instance level, to reduce the domain discrepancy. The two domain adaptation components are based on H-divergence theory, and are implemented by learning a domain classifier in adversarial training manner. The domain classifiers on different levels are further reinforced with a consistency regularization to learn a domain-invariant region proposal network (RPN) in the Faster R-CNN model. We evaluate our newly proposed approach using multiple datasets including Cityscapes, KITTI, SIM10K, etc. The results demonstrate the effectiveness of our proposed approach for robust object detection in various domain shift scenarios.Comment: Accepted to CVPR 201

Genome-wide search for the genes accountable for the induced resistance to HIV-1 infection in activated CD4+ T cells: apparent transcriptional signatures, co-expression networks and possible cellular processes

BACKGROUND: Upon co-stimulation with CD3/CD28 antibodies, activated CD4 + T cells were found to lose their susceptibility to HIV-1 infection, exhibiting an induced resistant phenotype. This rather unexpected phenomenon has been repeatedly confirmed but the underlying cell and molecular mechanisms are still unknown. METHODS: We first replicated the reported system using the specified Dynal beads with PHA/IL-2-stimulated and un-stimulated cells as controls. Genome-wide expression and analysis were then performed by using Agilent whole genome microarrays and established bioinformatics tools. RESULTS: We showed that following CD3/CD28 co-stimulation, a homogeneous population emerged with uniform expression of activation markers CD25 and CD69 as well as a memory marker CD45RO at high levels. These cells differentially expressed 7,824 genes when compared with the controls on microarrays. Series-Cluster analysis identified 6 distinct expression profiles containing 1,345 genes as the representative signatures in the permissive and resistant cells. Of them, 245 (101 potentially permissive and 144 potentially resistant) were significant in gene ontology categories related to immune response, cell adhesion and metabolism. Co-expression networks analysis identified 137 “key regulatory” genes (84 potentially permissive and 53 potentially resistant), holding hub positions in the gene interactions. By mapping these genes on KEGG pathways, the predominance of actin cytoskeleton functions, proteasomes, and cell cycle arrest in induced resistance emerged. We also revealed an entire set of previously unreported novel genes for further mining and functional validation. CONCLUSIONS: This initial microarray study will stimulate renewed interest in exploring this system and open new avenues for research into HIV-1 susceptibility and its reversal in target cells, serving as a foundation for the development of novel therapeutic and clinical treatments