Exosomes originating from neural stem cells undergoing necroptosis participate in cellular communication by inducing TSC2 upregulation of recipient cells following spinal cord injury

We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury.While exosomes are recognized as playing a pivotal role in neural stem cells exocrine function,their precise function in spinal cord injury remains unclear.To investigate the role of exosomes generated following neural stem cells necroptosis after spinal cord injury,we conducted singlecell RNA sequencing and validated that neural stem cells originate from ependymal cells and undergo necroptosis in response to spinal cord injury.Subsequently,we established an in vitro necroptosis model using neural stem cells isolated from embryonic mice aged 16-17 days and extracted exosomes.The results showed that necroptosis did not significantly impact the fundamental characteristics or number of exosomes.Transcriptome sequencing of exosomes in necroptosis group identified 108 differentially expressed messenger RNAs,104 long non-coding RNAs,720 circular RNAs,and 14 microRNAs compared with the control group.Construction of a competing endogenous RNA network identified the following hub genes:tuberous sclerosis 2(Tsc2),solute carrier family 16 member 3(Slc16a3),and forkhead box protein P1(Foxp1).Notably,a significant elevation in TSC2 expression was observed in spinal cord tissues following spinal cord injury.TSC2-positive cells were localized around SRY-box transcription factor 2-positive cells within the injury zone.Furthermore,in vitro analysis revealed increased TSC2 expression in exosomal receptor cells compared with other cells.Further assessment of cellular communication following spinal cord injury showed that Tsc2 was involved in ependymal cellular communication at 1 and 3 days post-injury through the epidermal growth factor and midkine signaling pathways.In addition,Slc16a3 participated in cellular communication in ependymal cells at 7 days post-injury via the vascular endothelial growth factor and macrophage migration inhibitory factor signaling pathways.Collectively,these findings confirm that exosomes derived from neural stem cells undergoing necroptosis play an important role in cellular communication after spinal cord injury and induce TSC2 upregulation in recipient cells.

Nonlocality Distillation and Trivial Communication Complexity for High-Dimensional Systems

A nonlocality distillation protocol for arbitrary high-dimensional systems is proposed. We study the nonlocality distillation in the 2-input d-output bi-partite case. Firstly, we give the one-parameter nonlocal boxes and their correlated distilling protocol. Then, we generalize the one-parameter nonlocality distillation protocol to the twoparameter case. Furthermore, we introduce a contracting protocol testifying that the 2-input d-output nonlocal boxes make communication complexity trivial.

Probabilistic remote preparation of a high-dimensional equatorial multiqubit with four-party and classical communication cost

This paper presents a protocol for probabilistic remote preparation of a high-dimensional equatorial multiqubit with four-party, consisting of a sender and three receivers. The quantum channel is composed of a partial entangled high-dimensional four-particle state. We calculate the successful total probability and the total classical communication cost required for this scheme. It is shown that both the entangled resources and classical communication cost are greatly reduced.

Quantum Secure Communication by Using GHZ State in High-Dimensional Hilbert Space

We propose a quantum superdense coding secure communication scheme by using GHZ state.This scheme combines the ideas of quantum superdense coding and sequence transmission.Its distinct advantage is high source capacity.In addition,in checking eavesdropping,we need not to destroy quantum entanglement.

Distributed Nash Equilibrium Seeking Strategies Under Quantized Communication

This paper is concerned with distributed Nash equi librium seeking strategies under quantized communication. In the proposed seeking strategy, a projection operator is synthesized with a gradient search method to achieve the optimization o players' objective functions while restricting their actions within required non-empty, convex and compact domains. In addition, a leader-following consensus protocol, in which quantized informa tion flows are utilized, is employed for information sharing among players. More specifically, logarithmic quantizers and uniform quantizers are investigated under both undirected and connected communication graphs and strongly connected digraphs, respec tively. Through Lyapunov stability analysis, it is shown that play ers' actions can be steered to a neighborhood of the Nash equilib rium with logarithmic and uniform quantizers, and the quanti fied convergence error depends on the parameter of the quan tizer for both undirected and directed cases. A numerical exam ple is given to verify the theoretical results.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

Cooperative UAV search strategy based on DMPC-AACO algorithm in restricted communication scenarios

Improvement of integrated battlefield situational awareness in complex environments involving dynamic factors such as restricted communications and electromagnetic interference(EMI)has become a contentious research problem.In certain mission environments,due to the impact of many interference sources on real-time communication or mission requirements such as the need to implement communication regulations,the mission stages are represented as a dynamic combination of several communication-available and communication-unavailable stages.Furthermore,the data interaction between unmanned aerial vehicles(UAVs)can only be performed in specific communication-available stages.Traditional cooperative search algorithms cannot handle such situations well.To solve this problem,this study constructed a distributed model predictive control(DMPC)architecture for a collaborative control of UAVs and used the Voronoi diagram generation method to re-plan the search areas of all UAVs in real time to avoid repetition of search areas and UAV collisions while improving the search efficiency and safety factor.An attention mechanism ant-colony optimization(AACO)algorithm is proposed for UAV search-control decision planning.The search strategy is adaptively updated by introducing an attention mechanism for regular instruction information,a priori information,and emergent information of the mission to satisfy different search expectations to the maximum extent.Simulation results show that the proposed algorithm achieves better search performance than traditional algorithms in restricted communication constraint scenarios.

Effect of sequential nursing care combined with communication intervention on visual recovery and pain after cataract ultrasound emulsification

BACKGROUND Cataracts are a common ophthalmic disease and postoperative vision recovery is crucial to patient quality of life.Rational and efficient care models play an impor-tant role in promoting vision recovery.AIM To evaluate the clinical effectiveness of procedural nursing care combined with communication intervention in vision recovery after cataract ultrasound emulsi-fication.METHODS A randomized controlled study was conducted on 100 patients with cataracts who underwent ultrasound emulsification surgery.They were randomly assigned to an experimental group or a control group.The experimental group received procedural nursing combined with Connect,Introduce,Communicate,Ask,Respond,Exit(CICARE)communication intervention,whereas the control group received conventional nursing.The effectiveness of the nursing model was assessed by comparing differences in vision recovery,pain scores,and mental health status between the two groups.RESULTS It was found that over time the visual acuity of patients in both groups gradually recovered and patients in the experimental group had lower pain scores and superior mental health status than the control group(P<0.05).CONCLUSION Procedural nursing combined with CICARE communication intervention has positive effects on vision recovery in patients after cataract ultrasound emulsification.

A survey on semantic communications:Technologies,solutions,applications and challenges

Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity limit.Despite the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for SC.In this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are summarized.Next,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are summarized.Applications of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are summarized.Finally,some challenges and future research directions are presented to provide guidance for further research of SC.

Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

Building Semantic Communication System via Molecules:An End-to-End Training Approach

The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources.In this paper,we propose an end-to-end(E2E)semantic molecular communication system,aiming to enhance the efficiency of molecular communication systems by reducing the transmitted information.Specifically,following the joint source channel coding paradigm,the network is designed to encode the task-relevant information into the concentration of the information molecules,which is robust to the degradation of the molecular communication channel.Furthermore,we propose a channel network to enable the E2E learning over the non-differentiable molecular channel.Experimental results demonstrate the superior performance of the semantic molecular communication system over the conventional methods in classification tasks.

Multi-Objective Equilibrium Optimizer for Feature Selection in High-Dimensional English Speech Emotion Recognition

Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions.The number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition system.The proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum accuracy.First,we use the information gain and Fisher Score to sort the features extracted from signals.Then,we employ a multi-objective ranking method to evaluate these features and assign different importance to them.Features with high rankings have a large probability of being selected.Finally,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local traps.Using random forest and K-nearest neighbor classifiers,four English speech emotion datasets are employed to test the proposed algorithm(MBEO)as well as other multi-objective emotion identification techniques.The results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBEO is appropriate for high-dimensional English SER.

Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

Single Photon Detection Technology in Underwater Wireless Optical Communication:Modulation Modes and Error Correction Coding Analysis

This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.

Satellite Communications with 5G, B5G, and 6G: Challenges and Prospects

Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.

Call for Papers--Feature Topic Vol. 22, No. 3, 2025 Special Issue of China Communications: Convergence of 6G empowered Edge Intelligence and Generative AI: Theories, Algorithms, and Applications

Generative artificial intelligence(AI), as an emerging paradigm in content generation, has demonstrated its great potentials in creating high-fidelity data including images, texts, and videos. Nowadays wireless networks and applications have been rapidly evolving from achieving “connected things” to embracing “connected intelligence”.

INTELLIGENT COVERT COMMUNICATION

As increasing amounts of private and confidential information are transmitted over wireless networks,their openness and broadcast pose significant security risks.In high-security scenarios like healthcare and financial activities,initial exposure of transmitted information can lead to serious threats.Covert communication,or low probability of detection(LPD)communication,has gained attention for its ability to hide transmission behaviors.

Multi-wavelength nanowire micro-LEDs for future high speed optical communication

The future of optoelectronics is directed towards small-area light sources,foremost being microLEDs.However,their use has been inhibited so far primarily due to fabrication and integration challenges,which impair efficiency and yield.Recently,bottom-up nanostructures grown using selective area epitaxy have garnered attention as a solution to the aforementioned issues.Prof.Lan Fu et.al.have used this technique to demonstrate uniform p-i-n core-shell InGaAs/InP nanowire array light emitting diodes.The devices are capable of voltage and geometry-controlled multi-wavelength and high-speed operations.Their publication accentuates the wide capabilities of bottom-up nanostructures to resolve the difficulties of nanoscale optoelectronics.