Non-Hermitian topological whispering gallery

In 1878, Lord Rayleigh observed the highly celebrated phenomenon of sound waves that creep around the curved gallery of St Paul's Cathedral in London1,2. These whispering-gallery waves scatter efficiently with little diffraction around an enclosure and have since found applications in ultrasonic fatigue and crack testing, and in the optical sensing of nanoparticles or molecules using silica microscale toroids. Recently, intense research efforts have focused on exploring non-Hermitian systems with cleverly matched gain and loss, facilitating unidirectional invisibility and exotic characteristics of exceptional points3,4. Likewise, the surge in physics using topological insulators comprising non-trivial symmetry-protected phases has laid the groundwork in reshaping highly unconventional avenues for robust and reflection-free guiding and steering of both sound and light5,6. Here we construct a topological gallery insulator using sonic crystals made of thermoplastic rods that are decorated with carbon nanotube films, which act as a sonic gain medium by virtue of electro-thermoacoustic coupling. By engineering specific non-Hermiticity textures to the activated rods, we are able to break the chiral symmetry of the whispering-gallery modes, which enables the out-coupling of topological "audio lasing" modes with the desired handedness. We foresee that these findings will stimulate progress in non-destructive testing and acoustic sensing.This work was supported by the National Basic Research Program of China (2017YFA0303702), NSFC (12074183, 11922407, 11904035, 11834008, 11874215 and 12104226) and the Fundamental Research Funds for the Central Universities (020414380181). Z.Z. acknowledges the support from the China National Postdoctoral Program for Innovative Talents (BX20200165) and the China Postdoctoral Science Foundation (2020M681541). L.Z. acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement 801538. J.C. acknowledges support from the European Research Council (ERC) through the Starting Grant 714577 PHONOMETA and from the MINECO through a Ramón y Cajal grant (grant number RYC-2015-17156)

Adiponectin Protects against Glutamate-Induced Excitotoxicity via Activating SIRT1-Dependent PGC-1 α

Glutamate- (Glu-) induced excitotoxicity plays a critical role in stroke. This study aimed to investigate the effects of APN on Glu-induced injury in HT22 neurons. HT22 neurons were treated with Glu in the absence or the presence of an APN peptide. Cell viability was assessed using the MTT assay, while cell apoptosis was evaluated using TUNEL staining. Levels of LDH, MDA, SOD, and GSH-Px were detected using the respective kits, and ROS levels were detected using dichlorofluorescein diacetate. Western blot was used to detect the expression levels of silent information regulator 1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), cleaved caspase-3, Bax, and Bcl-2. In addition to the western blot, immunofluorescence was used to investigate the expression levels of SIRT1 and PGC-1α. Our results suggest that APN peptide increased cell viability, SOD, and GSH-Px levels and decreased LDH release, ROS and MDA levels, and cell apoptosis. APN peptide upregulated the expression of SIRT1, PGC-1α, and Bcl-2 and downregulated the expression of cleaved caspase-3 and Bax. Furthermore, the protective effects of the APN peptide were abolished by SIRT1 siRNA. Our findings suggest that APN peptide protects HT22 neurons against Glu-induced injury by inhibiting neuronal apoptosis and activating SIRT1-dependent PGC-1α signaling

Disastrous Mechanism of Water Discharge in Abandoned Gob above the Stope in Mining Extra-Thick Coal Seam

The Datong mining area is a typical double system coal seam mining area in China, where the Jurassic and Carboniferous coal seams are mined simultaneously. The upper Jurassic coal seam has been largely mined, leaving a large amount of gob area. Besides, a large amount of harmful water is accumulated. With the exploitation of the 3-5# extra-thick coal seam in the Carboniferous system, the scope of overburden damage is greatly increasing, and the mining fracture field is further developed. Once the mining-induced fractures connect with the overlying gob, it is easy to induce the water discharge disaster. With the mining geological conditions of the 8202 working face in the Tongxin coal mine as references, the disastrous mechanism of water discharge in the abandoned gob above the stope in the mining extra-thick coal seam is researched by numerical simulation with the UDEC numerical software, and the research results are obtained. The water in the overlying gob percolates through the mining-induced fractures in the higher key layer forming a “shower” seepage pattern. The water in the above gob converges in the key fracture channel, flowing into the working face. The seepage in the fractures in the high key stratum experiences the process of increase, decrease, and stabilization, related with the stretching and extrusion deformation between the high key stratum blocks. Compared with other fractures, the flow rates in the No.2 and No.4 fractures in the far field key lay are larger, because the fractures are in the tension state, forming the “saddle-shaped” flow pattern. The influencing distance of mining-induced seepage is about 80 m in front of the working face. The research results provide a guided reference for the prediction and prevention of water discharge disaster in an abandoned gob above the stope in a mining extra-thick coal seam

Cyclically Disentangled Feature Translation for Face Anti-spoofing

Current domain adaptation methods for face anti-spoofing leverage labeled source domain data and unlabeled target domain data to obtain a promising generalizable decision boundary. However, it is usually difficult for these methods to achieve a perfect domain-invariant liveness feature disentanglement, which may degrade the final classification performance by domain differences in illumination, face category, spoof type, etc. In this work, we tackle cross-scenario face anti-spoofing by proposing a novel domain adaptation method called cyclically disentangled feature translation network (CDFTN). Specifically, CDFTN generates pseudo-labeled samples that possess: 1) source domain-invariant liveness features and 2) target domain-specific content features, which are disentangled through domain adversarial training. A robust classifier is trained based on the synthetic pseudo-labeled images under the supervision of source domain labels. We further extend CDFTN for multi-target domain adaptation by leveraging data from more unlabeled target domains. Extensive experiments on several public datasets demonstrate that our proposed approach significantly outperforms the state of the art. Code and models are available at https://github.com/vis-face/CDFTN