Neural Machine Translation with Dynamic Graph Convolutional Decoder

Existing wisdom demonstrates the significance of syntactic knowledge for the improvement of neural machine translation models. However, most previous works merely focus on leveraging the source syntax in the well-known encoder-decoder framework. In sharp contrast, this paper proposes an end-to-end translation architecture from the (graph \& sequence) structural inputs to the (graph \& sequence) outputs, where the target translation and its corresponding syntactic graph are jointly modeled and generated. We propose a customized Dynamic Spatial-Temporal Graph Convolutional Decoder (Dyn-STGCD), which is designed for consuming source feature representations and their syntactic graph, and auto-regressively generating the target syntactic graph and tokens simultaneously. We conduct extensive experiments on five widely acknowledged translation benchmarks, verifying that our proposal achieves consistent improvements over baselines and other syntax-aware variants

Federated Deep Reinforcement Learning for THz-Beam Search with Limited CSI

Terahertz (THz) communication with ultra-wide available spectrum is a promising technique that can achieve the stringent requirement of high data rate in the next-generation wireless networks, yet its severe propagation attenuation significantly hinders its implementation in practice. Finding beam directions for a large-scale antenna array to effectively overcome severe propagation attenuation of THz signals is a pressing need. This paper proposes a novel approach of federated deep reinforcement learning (FDRL) to swiftly perform THz-beam search for multiple base stations (BSs) coordinated by an edge server in a cellular network. All the BSs conduct deep deterministic policy gradient (DDPG)-based DRL to obtain THz beamforming policy with limited channel state information (CSI). They update their DDPG models with hidden information in order to mitigate inter-cell interference. We demonstrate that the cell network can achieve higher throughput as more THz CSI and hidden neurons of DDPG are adopted. We also show that FDRL with partial model update is able to nearly achieve the same performance of FDRL with full model update, which indicates an effective means to reduce communication load between the edge server and the BSs by partial model uploading. Moreover, the proposed FDRL outperforms conventional non-learning-based and existing non-FDRL benchmark optimization methods

Effect of C-type natriuretic peptide and amiodarone in Chinese patients with arrhythmia

Purpose: To compare the effect of C-type natriuretic peptide and amiodarone in Chinese patients with arrhythmia. Method: Chinese men and women aged 18 to 65 years with premature ventricular complexes (PVCs), were administered C-type natriuretic peptide (CNP) - test group or amiodarone (study group) in ratio of 1:1 for 96 h. Patients in CNP group received infusion of synthetic human CNP (10 pmol/kg/min) for an initial 2 h, and then for 30 min every day until discharge. Patients in amiodarone group received initial dose of 1000 mg over the first 24 h. Change in PVCs from baseline was the primary efficacy endpoint. Secondary efficacy endpoint includes: change in PVCs-related symptom scores from baseline, change in ejection fraction of left ventricle (LV), end‑diastolic diameter of LV, and cardiac events as composite outcome (CCE). The effect of both treatments on hemodynamic and electrocardiography parameters, and safety were evaluated. Data from 200 patients were analyzed. Results: The CNP showed significantly greater decrease in the number of PVCs when compared to amiodarone (p < 0.005). Moreover, CNP was superior in alleviating PVCs- related symptoms when compared to amiodarone (p < 0.005). A similar trend of favorable effect of CNP was observed for other endpoints. Conclusion: The C-type natriuretic peptide offers significantly greater benefits of suppressing PVCs and related symptoms, and demonstrates significantly greater improvement of cardiac function and clinical outcome. Thus, CNP can be considered for further investigation as a suitable alternative in the management of ventricular arrhythmia with PVC among Chinese patients

Two Opposite Sides Synchronous Tracking X-ray Based Robotic Welding Inspection System

For inspecting welding seams of large-scale equipment such as storage tanks and spherical tanks, it usually cost much manpower and material, while automated testing robot can achieve fast and accurate detection. Because X-ray Flat Panel Detector is dependent on specialized automated equipment, it can greatly enhance X-ray inspection technology in large storage tanks that applying the Mecanum Omnidirectional Mobile Robot into automated weld detection. In this paper, an X-ray Flat Panel Detector based wall-climbing robotic system is developed for intelligent detecting of welding seams. The robot system consists of two Mecanum vehicles equipped with either a Flat Panel Detector or an X-ray generator and climbing on both side of the tank wall. Inspection robot can carry detector stably with reliable suction force and adapt to different surfaces. To let the X-ray Flat Panel Detector work properly, dual cameras positioning system is used to ensure synchronous operation of the two robots. Some experiment was conducted and reported

Observation of Majorana fermions with spin selective Andreev reflection in the vortex of topological superconductor

Majorana fermion (MF) whose antiparticle is itself has been predicted in condensed matter systems. Signatures of the MFs have been reported as zero energy modes in various systems. More definitive evidences are highly desired to verify the existence of the MF. Very recently, theory has predicted MFs to induce spin selective Andreev reflection (SSAR), a novel magnetic property which can be used to detect the MFs. Here we report the first observation of the SSAR from MFs inside vortices in Bi2Te3/NbSe2 hetero-structure, in which topological superconductivity was previously established. By using spin-polarized scanning tunneling microscopy/spectroscopy (STM/STS), we show that the zero-bias peak of the tunneling differential conductance at the vortex center is substantially higher when the tip polarization and the external magnetic field are parallel than anti-parallel to each other. Such strong spin dependence of the tunneling is absent away from the vortex center, or in a conventional superconductor. The observed spin dependent tunneling effect is a direct evidence for the SSAR from MFs, fully consistent with theoretical analyses. Our work provides definitive evidences of MFs and will stimulate the MFs research on their novel physical properties, hence a step towards their statistics and application in quantum computing.Comment: 4 figures 15 page