Peer review has long served as a core mechanism for quality control and resource allocation in science. However, amid the rapid growth of research output, the traditional peer review system is increasingly strained in terms of efficiency, cost, and fairness, raising concerns about its institutional capacity. The rapid development of artificial intelligence (AI) has led to its gradual incorporation into academic review processes, where it is increasingly regarded as a potential institutional variable capable of reshaping conventional peer review. Building on a historical analysis of the evolution of peer review, this article examines the institutional legitimacy of AI's involvement in peer review and the practical drivers behind its adoption. While AI demonstrates potential advantages in accelerating review workflows, optimizing the allocation of review resources, and assisting in the correction of evaluation outcomes, its integration may also generate systemic risks, including the weakening of scholarly judgment, the amplification of algorithmic bias, the blurring of responsibility boundaries, and the encroachment of efficiency−oriented logic upon academic ethics. This article argues that the key to integrating AI into peer review lies in the careful delineation of its functional boundaries and governance frameworks. It further suggests that conceptualizing AI as a constrained auxiliary tool, and applying it cautiously within a human–machine collaborative model, may help enhance review efficiency and procedural fairness while mitigating the institutional risks associated with AI involvement in academic evaluation.

With the rapid advancement of sixth−generation (6G) mobile communications and the vision of the Internet of Everything, spectrum scarcity has become a critical bottleneck limiting further improvements in wireless system capacity. The efficiency of traditional time−frequency domain resource mining is gradually approaching the Shannon limit. Vortex wave technology, which exploits orbital angular momentum (OAM) as an independent physical degree of freedom, offers a promising solution by breaking the constraints of conventional planar−wave transmission and opening new possibilities for high−capacity wireless communications. This paper reviews the key technologies of vortex−wave−based communication, with particular emphasis on recent progress in beam generation and manipulation, full−space multiplexed transmission, physical−layer security, and intelligent signal processing. First, reconfigurable intelligent surfaces (RIS), owing to their flexible electromagnetic parameter control and ease of integration, are expected to play a pivotal role in multi−mode vortex beam shaping and dynamic reconfiguration. Second, the incorporation of deep learning algorithms enables high−accuracy mode recognition and wavefront correction at the receiver, significantly improving system robustness and environmental adaptability. Furthermore, the inherent mode orthogonality and phase singularity of vortex waves provide unique advantages for overcoming capacity limits, enhancing physical−layer security, and enabling high−dimensional quantum information processing. Finally, the difficulties and challenges still faced by vortex wave communication, including beam divergence, atmospheric turbulence phase distortion, and mode crosstalk, are discussed, and future trends are prospected.

Terahertz waves have shown significant application potential in sixth−generation mobile communications, biomedical imaging, and sensing, while metasurfaces provide a new approach for efficient terahertz−wave manipulation. This paper reviews recent progress in intelligent metasurface−based terahertz−wave control technologies. It systematically summarizes the major implementation routes, including mechanical reconfiguration, optoelectronic tuning, phase−change−material switching, integrated semiconductor devices, and programmable control. It also discusses recent advances in the use of artificial intelligence for inverse design, adaptive environmental interaction, multimodal sensing, and intelligent analysis of terahertz metasurfaces. Furthermore, representative applications in terahertz imaging, biomedical detection, 6G communications, defense and security, as well as system integration and prototype validation are reviewed. Existing studies indicate that intelligent terahertz metasurfaces are evolving from single−function devices toward system−level platforms integrating sensing, decision−making, and control. However, several key challenges remain, including sensitivity to device loss, insufficient front−end sensing hardware, complex array−level driving and packaging, stringent fabrication consistency requirements, and the lack of unified testing and evaluation methods. Future research should therefore focus on low−loss tunable materials, high−sensitivity sensing front ends, array−level collaborative integration, system prototype validation, and standardized evaluation methods, so as to promote the transition of intelligent terahertz metasurfaces from proof−of−concept demonstrations to stable engineering applications.

Traditional communication systems are unable to meet the urgent demand for transmission efficiency in intelligent communication scenarios. An overview of semantic communication is presented as a new communication paradigm, which can understand and transmit the essence of information in intelligent communication scenarios. The development prospects of semantic communication in future wireless communication technologies are also discussed. Firstly, based on the type of data, semantic communication is classified into three categories: single−modal semantic communication, cross−modal semantic communication, and multi−modal semantic communication. The current research status under each mode is combed. Furthermore, an in−depth analysis is conducted on performance evaluation metrics, transceiver system design, and resource management strategies within semantic communication networks. Related studies from recent years are analyzed with a focus on three enabling technologies and the challenges faced by various technologies and the key issues to be solved in future development have been proposed. Finally, the deep integration of semantic communication with future communication networks is explored and summarized. In the future, semantic communication urgently needs to establish a unified semantic performance evaluation system. Further research is required on cross−modal semantic fusion and semantic communication resource management strategies, and efforts should be made to continuously integrate semantic communication with the existing network architecture, in order to achieve the future communication vision of "semantic empowerment and intelligent interconnection".

Weak magnetic field detection plays a crucial role in biomedicine, resource exploration and national defense, industrial inspection, and frontier scientific research, and is one of the key technologies for acquiring magnetic signals with high sensitivity and high resolution. By enhancing the local magnetic flux density and optimizing the efficiency of magnetic signal coupling, flux concentrators can significantly improve the sensitivity and signal−to−noise ratio of sensors, and thus have become core components in high−precision weak magnetic field detection systems. This paper reviews recent advances in flux concentration technology, with an emphasis on the development of magnetic circuit theory, design strategies for magnetic materials with high permeability and low coercivity, and optimization methods for flux concentrator structures with low eddy−current loss. In addition, the current status and future trends of weak magnetic field sensor technologies based on flux concentration effects are analyzed, providing references and directions for improving the sensitivity and magnetic field resolution in weak magnetic signal detection.

With the rapid development of metasurfaces for precise electromagnetic wave manipulation, the efficient and automated design of complex functional devices has become a critical research challenge. This paper proposes a multi−model collaborative framework for metasurface inverse design driven by visual images, aiming to automatically generate electromagnetic metasurface array structures directly from visual image inputs. The method employs a synergistic multi−model strategy to establish an end−to−end mapping from image semantic features to physical metasurface structural parameters. Specifically, a conditional generative adversarial network (Pix2Pix) is first employed to transform visual images into target holographic textures, followed by a U−shaped convolutional neural network (U−Net) for high−fidelity phase distribution prediction. Subsequently, a variational autoencoder (VAE) is introduced to map the desired phase profiles to manufacturable unit−cell geometries, effectively bridging the long−standing gap between phase synthesis and structural modeling in conventional design workflows. Numerical simulations demonstrate that the designed holographic metasurfaces can accurately reconstruct target holographic patterns at designated operating frequencies, achieving significantly improved reconstruction fidelity and design stability compared with traditional single−network approaches. This work provides an efficient and automated new paradigm for image−driven intelligent metasurface design and offers a promising solution for the rapid development of complex electromagnetic functional devices.

In next−generation electronic information systems, ambient wireless energy harvesting (WEH) has emerged as a prominent research frontier. This work first presents a dual−band metasurface−based energy harvester leveraging an open split−ring resonator (SRR) architecture, achieving absorption efficiencies exceeding 90% at both 2.45 and 5.80GHz. Second, we propose a dual−band rectification system tailored for low−power−density environments, implemented via a single−stage voltage−doubler topology that jointly optimizes harmonic suppression and impedance matching. Under a load resistance of 800 Ω and an input power of 0 dBm, the RF−DC conversion efficiency reaches 53.5% at 2.45 GHz and 38.2% at 5.8 GHz. Third, a dual−band energy combining network is introduced to integrate the harvester and rectifier into a rectifying metasurface. Experimental validation confirms overall conversion efficiencies of 48.2% at 2.45 GHz and 37.7% at 5.8 GHz. Notably, the proposed rectifying metasurface maintains robust rectification performance over incident angles of ±40° at 2.45 GHz and ±30° at 5.8 GHz. Collectively, this design simultaneously addresses three critical challenges—low incident power sensitivity, dual−band operation, and wide−angle incident—demonstrating strong integration capability.

With the continuous advancement of wireless mobile communication technologies, user demand for high−quality communication services is growing significantly. As distance increases, the signal weakens at the cell edge, and the issue of insufficient base station coverage in these areas becomes a key factor constraining communication quality. Consequently, enhancing the performance of cell−edge users has become a major research focus in the field of wireless communications. Addressing this challenge, this study proposes utilizing reconfigurable intelligent surface (RIS) technology to achieve near−field focusing in the 3.5 GHz band to enhance cell−edge coverage. The near−field focusing effect of the electromagnetic superstructure was verified through both theoretical calculation and full−wave electromagnetic simulation. The analysis results indicated that RIS can achieve near−field focusing of electromagnetic waves by precisely controlling the phase of the electromagnetic waves. Field trial measurement in outdoor environments using a constructed RIS proof−of−concept prototype measured signal strength at various positions within the near−field region, validating the RIS's near−field focusing capability. System performance tests were conducted to evaluate the signal enhancement based on RIS near−field focusing, combined with a commercial base station antenna. Experimental results demonstrate that the intelligent metasurface exhibits excellent coverage enhancement effects in near−field focusing and can improve communication quality in the edge regions of base stations.

Conventional biological detection methods typically suffer from drawbacks such as long detection duration, low detection efficiency, and insufficient sensitivity. Terahertz (THz) metasurface sensors exhibit promising application potential in the field of biosensing owing to their merits of label−free detection, non−invasiveness, and high sensitivity. Aiming at the issues of single resonant mode and unsatisfactory performance of existing THz metasurface biosensors, a multi−resonant THz metasurface biosensor is proposed in this work. The device generates three narrowband high−absorption resonant peaks at 2.933, 3.412, and 3.637 THz, respectively. Within the refractive index range of 1~1.40, the resonant frequencies display a red−shift with the increase in refractive index. The maximum refractive index sensitivities of the resonant peaks at 2.933 and 3.412 THz are 541 and 981 GHz/RIU, with ultra−high quality factors of 320 and 82, respectively. The THz metasurface structure designed in this study holds broad application prospects for the highly sensitive biomedical detection of cancer cells and their related biomarkers.

This paper systematically analyzes the global development trend of low−cost and efficient space access capabilities and their profound impacts on the aerospace industry landscape, space security, and the future space economy, with a focus on the cost revolution driven by reusable launch vehicle technologies. By evaluating the technical paths, economic efficiency, and strategic deployment of leading international companies such as SpaceX, it identifies that the United States has established a generational advantage in this field, forming a virtuous cycle of "order−of−magnitude reduction in launch cost—enhanced market dominance—industrial chain restructuring." In contrast, China faces significant challenges in talent, technological reserves, and commercialization pathways, particularly in the areas of heavy−lift rockets and reusable technologies. The paper further assesses the current development status of China's commercial launch vehicles and concludes that although small− and medium−sized rockets are developing rapidly, they have yet to achieve breakthroughs in cost structure and technological models, making it difficult to support the high−frequency launch demands of satellite constellations and future space industries. Based on these findings, the paper proposes four policy recommendations: leveraging China’s unique national system, promoting coordinated innovation between state−owned and private enterprises, planning ahead for next−generation space transportation systems, and expanding international space information service exports. These aim to build a globally competitive space access capability framework.

Academician Wang Xiaomo, a recipient of the National Highest Science and Technology Award and the honorary title of "People's Scientist," is recognized as the pioneer and founder of China's airborne early warning and control (AEW&C) program. This paper systematically reviews his scientific journey from independently developing three−coordinate radar to leading the establishment of a domestically produced AEW&C aircraft system, and elucidates the core of his scientific spirit. Wang Xiaomo's life epitomizes "laying the electromagnetic foundation and guarding the skies". He not only forged a "national strategic asset" for the country, but also embodied the spiritual traits of patriotism, strategic foresight, engineering practice, continuous learning, and collaborative mentorship. These traits provide essential intellectual resources for sci−tech self−reliance and self−strengthening at higher levels and cultivating top−tier innovative talents in the new era.