Double-Active-IRS Aided Wireless Communication: Deployment Optimization and Capacity Scaling

In this letter, we consider a double-active-intelligent reflecting surface (IRS) aided wireless communication system, where two active IRSs are properly deployed to assist the communication from a base station (BS) to multiple users located in a given zone via the double-reflection links. Under the assumption of fixed per-element amplification power for each active-IRS element, we formulate a rate maximization problem subject to practical constraints on the reflection design, elements allocation, and placement of active IRSs. To solve this non-convex problem, we first obtain the optimal active-IRS reflections and BS beamforming, based on which we then jointly optimize the active-IRS elements allocation and placement by using the alternating optimization (AO) method. Moreover, we show that given the fixed per-element amplification power, the received signal-to-noise ratio (SNR) at the user increases asymptotically with the square of the number of reflecting elements; while given the fixed number of reflecting elements, the SNR does not increase with the per-element amplification power when it is asymptotically large. Last, numerical results are presented to validate the effectiveness of the proposed AO-based algorithm and compare the rate performance of the considered double-active-IRS aided wireless system with various benchmark systems

Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler

Digital twin, which enables emulation, evaluation, and optimization of physical entities through synchronized digital replicas, has gained increasingly attention as a promising technology for intricate wireless networks. For 6G, numerous innovative wireless technologies and network architectures have posed new challenges in establishing wireless network digital twins. To tackle these challenges, artificial intelligence (AI), particularly the flourishing generative AI, emerges as a potential solution. In this article, we discuss emerging prerequisites for wireless network digital twins considering the complicated network architecture, tremendous network scale, extensive coverage, and diversified application scenarios in the 6G era. We further explore the applications of generative AI, such as transformer and diffusion model, to empower the 6G digital twin from multiple perspectives including implementation, physical-digital synchronization, and slicing capability. Subsequently, we propose a hierarchical generative AI-enabled wireless network digital twin at both the message-level and policy-level, and provide a typical use case with numerical results to validate the effectiveness and efficiency. Finally, open research issues for wireless network digital twins in the 6G era are discussed

Deep Learning-Based Modeling of 5G Core Control Plane for 5G Network Digital Twin

Digital twin is a key enabler to facilitate the development and implementation of new technologies in 5G and beyond networks. However, the complex structure and diverse functions of the current 5G core network, especially the control plane, lead to difficulties in building the core network of the digital twin. In this paper, we propose two novel data-driven architectures for modeling the 5G control plane and implement corresponding deep learning models, namely 5GC-Seq2Seq and 5GC-former, based on the Vanilla Seq2Seq model and Transformer decoder respectively. To train and test models, we also present a solution that allows the signaling messages to be interconverted with vectors, which can be utilized in dataset construction. The experiments are based on 5G core network signaling data collected by the Spirent C50 network tester, including various procedures related to registration, handover, PDU sessions, etc. Our results show that 5GC-Seq2Seq achieves over 99.98% F1-score (A metric to measure the accuracy of positive samples) with a relatively simple structure, while 5GC-former attains higher than 99.998% F1-score by establishing a more complex and highly parallel model, indicating that the method proposed in this paper reproduces the major functions of the core network control plane in 5G digital twin with high accuracy

EGFR inhibitor C225 increases the radiosensitivity of human lung squamous cancer cells

Background: The purpose of the present study is to investigate the direct biological effects of the epidermal growth factor receptor (EGFR) inhibitor C225 on the radiosensitivity of human lung squamous cancer cell-H520. H520 cells were treated with different dosage of (60)Co gamma ray irradiation (1.953 Gy/min) in the presence or absence of C225. The cellular proliferation, colony forming capacity, apoptosis, the cell cycle distribution as well as caspase-3 were analyzed in vitro. Results: We found that C225 treatment significantly increased radiosensitivity of H-520 cells to irradiation, and led to cell cycle arrest in G(1) phase, whereas (60)Co gamma ray irradiation mainly caused G(2) phase arrest. H-520 cells thus displayed both the G(1) and G(2) phase arrest upon treatment with C225 in combination with (60)Co gamma ray irradiation. Moreover, C225 treatment significantly increased the apoptosis percentage of H-520 cells (13.91% +/- 1.88%) compared with the control group (5.75% +/- 0.64%, P < 0.05). Conclusion: In this regard, C225 treatment may make H-520 cells more sensitive to irradiation through the enhancement of caspase-3 mediated tumor cell apoptosis and cell cycle arrest.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000284001800001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701OncologySCI(E)PubMed2ARTICLE391

Absence of dystrophin in mice reduces NO-dependent vascular function and vascular density: total recovery after a treatment with the aminoglycoside gentamicin.

International audienceOBJECTIVE: Mutations in the dystrophin gene causing Duchenne's muscular dystrophy (DMD) lead to premature stop codons. In mice lacking dystrophin (mdx mice), a model for DMD, these mutations can be suppressed by aminoglycosides such as gentamicin. Dystrophin plays a role in flow (shear stress)-mediated endothelium-dependent dilation (FMD) in arteries. We investigated the effect of gentamicin on vascular contractile and dilatory functions, vascular structure, and density in mdx mice. METHODS AND RESULTS: Isolated mice carotid and mesenteric resistance arteries were mounted in arteriographs allowing continuous diameter measurements. Mdx mice showed lower nitric oxide (NO)-dependent FMD and endothelial NO synthase (eNOS) expression as well as decreased vascular density in gracilis and cardiac muscles compared with control mice. Treatment with gentamycin restored these parameters. In contrast, smooth muscle-dependent contractions as well as endothelium-dependent or -independent dilation were not affected by dystrophin deficiency or by gentamicin treatment. CONCLUSIONS: Dystrophin deficiency induces a selective defect in flow-dependent mechanotransduction, thus attenuating FMD and eNOS expression, and may contribute to low arteriolar density. These findings open important perspectives regarding the mechanism involved in the pathophysiology of genetic diseases related to premature stop codons such as DMD

A Truncation Method Based on Hermite Expansion for Unknown Source in Space Fractional Diffusion Equation

In this paper we consider the problem for identifying an unknown steady source in a space fractional diffusion equation. A truncation method based on a Hermite function expansion is proposed, and the regularization parameter is chosen by a discrepancy principle. An error estimate between the exact solution and its approximation is given. A numerical implementation is discussed and corresponding results are presented to verify the effectiveness of the method