Symbol-Level Precoding for Integrated Sensing and Communications: A Faster-Than-Nyquist Approach

In this paper, we propose a novel symbol-level precoding (SLP) method for a multi-user multi-input multi-output (MU-MIMO) downlink Integrated Sensing and Communications (ISAC) system based on faster-than-Nyquist (FTN) signaling. Our method minimizes the minimum mean squared error (MMSE) for target parameter estimation while guaranteeing per-user quality-of-service by exploiting constructive interference (CI) techniques. We tackle the non-convex problem using an efficient successive convex approximation (SCA) method. Numerical results demonstrate that our FTN-ISAC-SLP design significantly outperforms conventional benchmarks in both communication and sensing performance

Defining the minimal components of the influenza A virus replication machinery via an in vitro reconstitution system

During influenza A virus infection, the viral RNA polymerase transcribes the viral negative-sense segmented RNA genome and replicates it in a two-step process via complementary RNA within viral ribonucleoprotein (vRNP) complexes. While numerous viral and host factors involved in vRNP functions have been identified, dissecting the roles of individual factors remains challenging due to the complex cellular environment in which vRNP activity has been studied. To overcome this challenge, we reconstituted viral transcription and a full cycle of replication in a test tube using vRNPs isolated from virions and recombinant factors essential for these processes. This novel system uncovers the minimal components required for influenza virus replication and also reveals new roles of regulatory factors in viral replication. Moreover, it sheds light on the molecular interplay underlying the temporal regulation of viral transcription and replication. Our highly robust in vitro system enables systematic functional analysis of factors modulating influenza virus vRNP activity and paves the way for imaging key steps of viral transcription and replication

Anomaly Detection and Prediction Based on Holt-Winters Method

Outliers, detection and prediction of abnormal periods, and prediction of trends in a given time base on existing data are the first problems to be solved in intelligent operation and maintenance. This paper took KPI performance index of 58 cells covered by 5 base stations from August 28 to September 25, 2021 as research data, chose 3 indexes (average number of users, PDCP traffic and average activation number), established a set of outlier prediction system based on Holt-Winters method

Neural Network-PSO-based Velocity Control Algorithm for Landing UAVs on a Boat

Precise landing of Unmanned Aerial Vehicles (UAVs) onto moving platforms like Autonomous Surface Vehicles (ASVs) is both important and challenging, especially in GPS-denied environments, for collaborative navigation of heterogeneous vehicles. UAVs need to land within a confined space onboard ASV to get energy replenishment, while ASV is subject to translational and rotational disturbances due to wind and water flow. Current solutions either rely on high-level waypoint navigation, which struggles to robustly land on varied-speed targets, or necessitate laborious manual tuning of controller parameters, and expensive sensors for target localization. Therefore, we propose an adaptive velocity control algorithm that leverages Particle Swarm Optimization (PSO) and Neural Network (NN) to optimize PID parameters across varying flight altitudes and distinct speeds of a moving boat. The cost function of PSO includes the status change rates of UAV and proximity to the target. The NN further interpolates the PSO-founded PID parameters. The proposed method implemented on a water strider hexacopter design, not only ensures accuracy but also increases robustness. Moreover, this NN-PSO can be readily adapted to suit various mission requirements. Its ability to achieve precise landings extends its applicability to scenarios, including but not limited to rescue missions, package deliveries, and workspace inspections