The arginine-phenylalanine-amide neuropeptide receptor family comprises a subclass within the G protein-coupled receptor superfamily with crucial roles in physiological regulation.These receptors recognize and bind ne...The arginine-phenylalanine-amide neuropeptide receptor family comprises a subclass within the G protein-coupled receptor superfamily with crucial roles in physiological regulation.These receptors recognize and bind neuropeptides with an arginine-phenylalanine-amide motif,thereby participating in a variety of biological processes such as energy metabolism,pain perception,and reproductive functions.In this review,we explore the physiological and pathological processes involving these receptors and delve into the structure-activity relationships of their ligand peptides,clarifying the key structural motifs within these neuropeptides that determine their biological activity,pharmacological potency,and receptor selectivity.Particular emphasis is placed on their roles in modulating nociception,regulating appetite,and maintaining reproductive health.Additionally,we discuss the therapeutic potential of structure-based drug design targeting these receptors based on existing cryo-electron microscopy structures.The available structural insights into ligand-binding pockets and G protein-receptor interaction interfaces provide a clear perspective and valuable complement to ligand optimization.展开更多
Reconfigurable Intelligent Surface(RIS)is envisioned as a promising technology to improve the system capacity of 6G network,by controlling the electromagnetic wave propagation.Most existing works use the Central Limit...Reconfigurable Intelligent Surface(RIS)is envisioned as a promising technology to improve the system capacity of 6G network,by controlling the electromagnetic wave propagation.Most existing works use the Central Limit Theorem(CLT)to analyze the performance of RIS-assisted systems for large number of reflective elements.However,the assumption of extremely large number of elements may not be practical in the actual situation.In addition,the CLT-based approximation yields an inaccurate scaling law of the outage probability when the transmit Signal-to-Noise Ratio(SNR)tends to infinity.Motivated by these limitations,in this paper,we investigate the performance of RIS-assisted cellular networks with multiple Device-to-Device(D2D)users under the general fading channels,i.e.,Nakagami-m fading channels.We propose a tractable solution to evaluate the outage probability and the ergodic achievable rate,which is accurate for any number of reflective elements,any network topology,as well as any SNR.In addition,the accurate approximations for the high SNR case and the large number of reflective elements case are further derived in simpler closed form.Numerical results verify the accuracy of our analytical results and analyze the performance between CLT and the proposed method.展开更多
Integration of natural gas and electricity transmission systems has strengthened interdependence between the two systems.Due to the close interconnection through coupling elements between the power system(PS)and natur...Integration of natural gas and electricity transmission systems has strengthened interdependence between the two systems.Due to the close interconnection through coupling elements between the power system(PS)and natural gas system(NGS)when a disturbance happens in one system,a series of complicated sequences of dependent events may follow in another system.Therefore,an integrated planning model jointing security-constrained considering cascading effects is proposed in this paper.Meanwhile,natural gas and electricity transmission systems considering stochastic failures and various operating characteristics of components can be viewed as a multistate systems.Moreover,power-to-gas(P2G),as a promising technology proposed to store surplus renewable energy,is considered in the integrated planning.First,multi-state models for different components are developed to describe realistic operating conditions in natural gas and electricity transmission systems.Furthermore,a mixed-integer linear programming(MILP)approach considers N-1 contingency and cascading effects between natural gas and the electrical power systems.Therefore,a security-constrained integrated planning model of natural gas and electricity transmission systems is represented.The proposed methods are validated using an integrated gas and power test system.展开更多
Background Ruminants and monogastric animals exhibit significant differences in gluconeogenic efficiency.In dairy cows,hepatic gluconeogenesis serves as the primary source of glucose.Metabolites modulate gluconeogenes...Background Ruminants and monogastric animals exhibit significant differences in gluconeogenic efficiency.In dairy cows,hepatic gluconeogenesis serves as the primary source of glucose.Metabolites modulate gluconeogenesis efficiency through allosteric regulation,redox state,and signal transduction pathways.However,the liver-enriched metabolites that regulate hepatic gluconeogenesis in dairy cows and their specific regulatory mechanisms remain incompletely characterized.Results Six Holstein dairy cows and six Duroc×(Landrace×Yorkshire)(DLY)crossbred pigs served as research subjects.Employing non-targeted and targeted metabolomics,we discovered that three bile acids—taurodeoxycholic acid(TDCA),taurocholic acid(TCA),and glycocholic acid(GCA)—were highly enriched in Holstein dairy cows'livers.In bovine hepatocytes,individual or combined stimulation of these bile acids significantly upregulated the expression of gluconeogenesis genes(FBP1,PCK1 and G6PC)and enhanced glucose production.In fasting mice with induced gluconeogenesis,TDCA,TCA,and GCA increased fasting blood glucose levels,and pyruvate tolerance tests further revealed their capacity to enhance hepatic gluconeogenesis,enabling more efficient glucose synthesis from pyruvate.Mechanistically,these bile acids activated Takeda G protein-coupled receptor 5(TGR5),elevated intracellular cAMP levels,and ultimately enhanced gluconeogenesis via the transcription factor cAMP-response element binding protein(CREB).Notably,a TGR5 inhibitor abrogated the stimulatory effects of TDCA,TCA,and GCA on hepatic gluconeogenesis in fasting mice.Conclusion TDCA,TCA,and GCA are key metabolites promoting hepatic gluconeogenesis in dairy cows,with TGR5 as the pivotal receptor and the cAMP/PKA/CREB pathway as the critical downstream mechanism.展开更多
Securing restricted zones such as airports,research facilities,and military bases requires robust and reliable access control mechanisms to prevent unauthorized entry and safeguard critical assets.Face recognition has...Securing restricted zones such as airports,research facilities,and military bases requires robust and reliable access control mechanisms to prevent unauthorized entry and safeguard critical assets.Face recognition has emerged as a key biometric approach for this purpose;however,existing systems are often sensitive to variations in illumination,occlusion,and pose,which degrade their performance in real-world conditions.To address these challenges,this paper proposes a novel hybrid face recognition method that integrates complementary feature descriptors such as Fuzzy-Gabor 2D Fisher Linear Discriminant(FG-2DFLD),Generalized 2D Linear Discriminant Analysis(G2DLDA),andModular-Local Binary Patterns(Modular-LBP)with Dempster–Shafer(DS)evidence theory for decision fusion.The proposed framework extracts global,structural,and local texture features,models them using Gaussian distributions to estimate belief factors,and fuses these belief factors through DS theory to explicitly handle uncertainty and conflict among descriptors.Experimental validation was performed on two widely used benchmark datasets,ORL and Cropped Yale B,achieving recognition rates exceeding 98%,which outperform traditional methods as well as recent deep learning-based approaches.Furthermore,the method demonstrated strong robustness under noisy conditions,maintaining accuracies above 96%with salt-and-pepper and Gaussian noise.These results highlight the effectiveness of the proposed integration strategy in enhancing accuracy,reliability,and resilience compared to single-descriptor and conventional fusion methods.Given its high performance and efficiency,the proposed method shows strong potential for deployment in real-world restricted-zone applications such as smart parking systems,secure facility access,and other high-security domains.展开更多
The ultrasonic energy field(UEF)-induced grain refinement mechanisms in laser powder direct energy deposition-manufactured Ti5321G alloys were systematically investigated in this study.This study focused on the interp...The ultrasonic energy field(UEF)-induced grain refinement mechanisms in laser powder direct energy deposition-manufactured Ti5321G alloys were systematically investigated in this study.This study focused on the interplay between recrystallization in the high-temperature solid deposition layers and the ultrasonic cavitation-acoustic streaming effects during molten pool solidification.A novel experimental design was developed to decouple these mechanisms by creating four distinct UEF action zones(without UEF-N,withUEF-S,with UEF-L,and with UEF-S+L)within a single-pass multilayer sample.This approach enabled the dual effects of UEF(recrystallization in solidified layers and ultrasonic cavitation-acoustic streaming effects in liquid pools)to be directly compared.The UEF significantly refined the microstructures,reducing the average grain size by 64.2%(from(399.6±28.6)to(143.1±16.1)μm)in the with UEF-S+L zone,while promoting columnar-to-equiaxed transition,with the equiaxed grain probability increasing from 11.1%(without UEF) to 53.8%.The texture intensity was reduced by approximately 52.4%and the mechanical properties were enhanced,achieving a 6.2% increase in yield strength((702.0±10.6)MPa)and 31.7%improvement in elongation.Crucially,this study revealed the synergistic effect of the dual-action mechanisms of UEF,where recrystallization and cavitation-acoustic streaming collectively enabled non-linear grain refinement.This study provides a strategy for microstructural control in additive manufacturing,eliminating the need for complex post-processing and thereby advancing the industrial application of high-performance titanium components.展开更多
Background:Hepatocellular carcinoma(HCC)is an aggressive and lethal malignancy.Metabolic reprogramming dynamically remodels the tumor microenvironment(TME)and drives HCC progression.This study investigated the mechani...Background:Hepatocellular carcinoma(HCC)is an aggressive and lethal malignancy.Metabolic reprogramming dynamically remodels the tumor microenvironment(TME)and drives HCC progression.This study investigated the mechanism through which metabolic reprogramming remodels the TME in HCC.Methods:HCC patient transcriptome data were subjected to bioinformatics analysis to identify differentially expressed genes and immune infiltration status.Immunohistochemical analysis was performed to determine the correlation between succinate dehydrogenase complex subunit A(SDHA)expression and M2 macrophage infiltration.SDHA-knockdown or SDHA-overexpressing HCC cells were used for in vitro experiments,including co-culturing,flow cytometry,and enzyme-linked immunosorbent assay.Western blotting assay,functional assays,and subcutaneous tumor model mice were used to elucidate the molecular mechanisms underlying succinate-mediated HCC cell-macrophage interactions in the TME.Results:Higher infiltration of M2 macrophages correlated with worse prognosis in HCC patients.SDHA was downregulated in HCC tumor tissues and showed a negative correlation with M2 macrophage infiltration.SDHA knockdown promoted M2 macrophage polarization,whereas SDHA overexpression reversed this effect.Mechanistically,SDHA deficiency in HCC cells induced succinate accumulation,which promoted M2 macrophage polarization by activating the G protein-coupled receptor 91(GPR91)/signal transducer and activator of transcription 3(STAT3)pathway.Concurrently,succinate stimulation enhanced mitochondrial oxidative phosphorylation in M2 macrophages,thereby promoting HCC progression.Serum succinate levels were elevated in HCC patients.The receiver operating characteristic curve analysis indicated that serum succinate is a promising diagnostic marker for HCC(area under the curve=0.815).Conclusion:SDHA deficiency leads to succinate accumulation,which promotes M2 macrophage polarization through the GPR91/STAT3 pathway,thereby facilitating HCC progression.Based on these findings,serum succinate could be a promising diagnostic biomarker for HCC.展开更多
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
In this paper,we interpret the operator representation using g-frames as a generalization of U-cross Gram matrices.We establish the link between U-cross g-Gram matrices andg-Riesz bases,and obtain a characterization o...In this paper,we interpret the operator representation using g-frames as a generalization of U-cross Gram matrices.We establish the link between U-cross g-Gram matrices andg-Riesz bases,and obtain a characterization ofg-Riesz bases by U-cross g-Gram matrices.In particular,someexamples show that the invertibility of U-cross g-Gram matrix is not possible when the associated sequences are g-frames but not g-Riesz bases or at most one of them is a g-Riesz basis.Finally,we show that the invertibility of U-cross g-Gram matrices is preserved under small perturbations of the operators or the sequences.展开更多
The growing developments in 5G and 6G wireless communications have revolutionized communications technologies,providing faster speeds with reduced latency and improved connectivity to users.However,it raises significa...The growing developments in 5G and 6G wireless communications have revolutionized communications technologies,providing faster speeds with reduced latency and improved connectivity to users.However,it raises significant security challenges,including impersonation threats,data manipulation,distributed denial of service(DDoS)attacks,and privacy breaches.Traditional security measures are inadequate due to the decentralized and dynamic nature of next-generation networks.This survey provides a comprehensive review of how Federated Learning(FL),Blockchain,and Digital Twin(DT)technologies can collectively enhance the security of 5G and 6G systems.Blockchain offers decentralized,immutable,and transparent mechanisms for securing network transactions,while FL enables privacy-preserving collaborative learning without sharing raw data.Digital Twins create virtual replicas of network components,enabling real-time monitoring,anomaly detection,and predictive threat analysis.The survey examines major security issues in emerging wireless architectures and analyzes recent advancements that integrate FL,Blockchain,and DT to mitigate these threats.Additionally,it presents practical use cases,synthesizes key lessons learned,and identifies ongoing research challenges.Finally,the survey outlines future research directions to support the development of scalable,intelligent,and robust security frameworks for next-generation wireless networks.展开更多
The expansion of 5G-enabled Internet of Things(IoT)networks,while enabling transformative applications,significantly increases the attack surface and necessitates security solutions that extend beyond traditional intr...The expansion of 5G-enabled Internet of Things(IoT)networks,while enabling transformative applications,significantly increases the attack surface and necessitates security solutions that extend beyond traditional intrusion detection.Existing intrusion detection systems(IDSs)mainly operate in an open-loop manner,excelling at classification but lacking the ability for autonomous,safety-aware remediation.This gap is particularly critical in 5G environments,where manual intervention is too slow and naive automation can lead to severe service disruptions.To address this issue,we propose a novel Self-Healing Intrusion Detection System(SH-IDS)framework that develops a closed-loop cyber defense mechanism.The main technical contribution is the integration of a deep neural networkbased threat detector,which offers uncertainty-quantified predictions,with a safety-aware reinforcement learning(RL)engine formulated as a Constrained Markov Decision Process(CMDP).The CMDP explicitly models operational safety as cost constraints,and a new runtime safety shield actively adjusts any unsafe action proposed by the RL agent to the nearest safe alternative,ensuring operational integrity.Additionally,we introduce a composite utility function for the comprehensive evaluation of the system.Empirical analysis on the 5G-NIDD dataset demonstrates the superior performance of our framework:the detector achieves 98.26%accuracy,while the safe RL agent learns effective mitigation policies.Importantly,the safety shield blocked up to 70 unsafe actions under strict constraints,and analysis of the learned Q-tables confirms that the agent internalizes safety,avoiding overly disruptive actions,such as isolating nodes for minor threats.The system also maintains high efficiency with a compact model size of 121.7 KB and sub-millisecond latency,confirming its practical deployability for real-time 5G-IoT security.展开更多
The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G en...The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.展开更多
The rapid growth of mobile and Internet of Things(IoT)applications in dense urban environments places stringent demands on future Beyond 5G(B5G)or Beyond 6G(B6G)networks,which must ensure high Quality of Service(QoS)w...The rapid growth of mobile and Internet of Things(IoT)applications in dense urban environments places stringent demands on future Beyond 5G(B5G)or Beyond 6G(B6G)networks,which must ensure high Quality of Service(QoS)while maintaining cost-efficiency and sustainable deployment.Traditional strategies struggle with complex 3D propagation,building penetration loss,and the balance between coverage and infrastructure cost.To address this challenge,this study presents the first application of a Global-best Guided Quantum-inspired Tabu Search with Quantum-Not Gate(GQTS-QNG)framework for 3D base-station deployment optimization.The problem is formulated as a multi-objective model that simultaneously maximizes coverage and minimizes deployment cost.A binary-to-decimal encodingmechanism is designed to represent discrete placement coordinates and base station types,leveraging a quantum-inspired method to efficiently search and refine solutions within challenging combinatorial environments.Global-best guidance and tabu memory are integrated to strengthen convergence stability and avoid revisiting previously explored solutions.Simulation results across user densities ranging from 1000 to 10,000 show that GQTS-QNG consistently finds deployment configurations achieving full coverage while reducing deployment cost compared with the state-of-the-art algorithms under equal iteration times.Additionally,our method generates welldistributed and structured Pareto fronts,offering diverse planning options that allow operators to flexibly balance cost and performance requirements.These findings demonstrate that GQTS-QNG is a scalable and efficient algorithm for sustainable 3D cellular network deployment in B5G/6G urban scenarios.展开更多
The rapid growth in available network bandwidth has directly contributed to an exponential increase in mobile data traffic,creating significant challenges for network energy consumption.Also,with the extraordinary gro...The rapid growth in available network bandwidth has directly contributed to an exponential increase in mobile data traffic,creating significant challenges for network energy consumption.Also,with the extraordinary growth of mobile communications,the data traffic has dramatically expanded,which has led to massive grid power consumption and incurred high operating expenditure(OPEX).However,the majority of current network designs struggle to efficientlymanage a massive amount of data using little power,which degrades energy efficiency performance.Thereby,it is necessary to have an efficient mechanism to reduce power consumption when processing large amounts of data in network data centers.Utilizing renewable energy sources to power the Cloud Radio Access Network(C-RAN)greatly reduces the need to purchase energy from the utility grid.In this paper,we propose a bandwidth-aware hybrid energypowered C-RAN that focuses on throughput and energy efficiency(EE)by lowering grid usage,aiming to enhance the EE.This paper examines the energy efficiency,spectral efficiency(SE),and average on-grid energy consumption,dealing with the major challenges of the temporal and spatial nature of traffic and renewable energy generation across various network setups.To assess the effectiveness of the suggested network by changing the transmission bandwidth,a comprehensive simulation has been conducted.The numerical findings support the efficacy of the suggested approach.展开更多
Altermagnets,a class of unconventional antiferromagnets with non-relativistic spin-splitting,offer promising potential for antiferromagnetic spintronic devices.While many altermagnets are limited by either low magneti...Altermagnets,a class of unconventional antiferromagnets with non-relativistic spin-splitting,offer promising potential for antiferromagnetic spintronic devices.While many altermagnets are limited by either low magnetic transition temperatures or weak spin splitting,the recently discovered metal CrSb,with high N′eel temperature(T_(N)=710 K)and significant spin-splitting due to its unique spin space group,provides a robust platform for remarkable tunneling magnetoresistance(TMR)in collinear all-antiferromagnetic tunnel junctions(AATJs).This study systematically investigates the spin-polarized Fermi surface of CrSb and spin-dependent electron transport in CrSb-based AATJs.The CrSb/β-InSe/CrSb junction with a three-monolayer InSe barrier exhibits a TMR ratio of approximately 290%,with energy-dependent analysis revealing TMR ratios that may exceed 850%when considering the shift of the Fermi energy.We also demonstrate the angle-dependent TMR of CrSb-based AATJs by adjusting N′eel vector orientations.Our findings might provide strong theoretical support for CrSb as a versatile building block for all-antiferromagnetic memory devices.展开更多
To overcome the limitations of traditional photocatalysts,such as inefficient separation of charge carriers and poor visible-light absorption,S-scheme g-C_(3)N_(4)/TiO_(2) heterojunction photocatalysts were synthesize...To overcome the limitations of traditional photocatalysts,such as inefficient separation of charge carriers and poor visible-light absorption,S-scheme g-C_(3)N_(4)/TiO_(2) heterojunction photocatalysts were synthesized via a combined method of thermal polymerization,hydrothermal synthesis,and calcination.The crystal structures,morphological features,and optical properties of the composites were systematically characterized,and their photocatalytic performance was evaluated through tetracycline(TC)degradation and hydrogen evolution experiments.Trapping experiments and electron paramagnetic resonance(EPR)measurements were conducted to elucidate the reaction mechanisms.The results demonstrate that the S-scheme heterojunction effectively extends the visible-light absorption range and facilitates the efficient separation of photogenerated electron-hole pairs.Under optimal conditions,the composite achieved a TC degradation rate of 94.5%and a hydrogen evolution rate of 329.1μmol·h^(-1)·g^(-1) after 8 h of irradiation,both values being significantly higher than those of pristine g-C_(3)N_(4) or TiO_(2).Moreover,the S-scheme g-C_(3)N_(4)/TiO_(2) heterojunction retained high photocatalytic activity over five consecutive cycles,confirming its excellent stability.Mechanistic investigations revealed that the S-scheme heterojunction maintained strong redox capacities,with superoxide radicals(·O_(2)^(-)),hydroxyl radicals(·OH),electrons(e-),and holes(h+)serving as the primary active species responsible for TC degradation and H2 production.展开更多
Osteosarcoma(OS)is the most frequent primary bone sarcomas with high recurrence and poor prognosis.Emerging evidence indicates that membraneless organelles stress granules(SGs),whose assemblies are driven by scaffold ...Osteosarcoma(OS)is the most frequent primary bone sarcomas with high recurrence and poor prognosis.Emerging evidence indicates that membraneless organelles stress granules(SGs),whose assemblies are driven by scaffold protein G3BP1,are extensively involved in tumor,especially in OS.However,how SGs behave and communicate with organelles,particularly nucleoli and mitochondria,during drug challenges remain unknown.This study revealed that chemotherapeutic drugs activated the cysteine protease asparagine endopeptidase(AEP)to specifically cleave the SG core protein G3BP1 at N258/N309 in OS and malignant glioma.tG3BP1-Ns modulated SG dynamics by competitively binding to full-length G3BP1.Strikingly,tG3BP1-Cs,containing a conserved RNA recognition motif CCUBSCUS,sequestered mRNAs of ribosomal proteins and oxidative phosphorylation genes in the nucleoli and mitochondria to repress translation and oxidative stress.Moreover,the inhibition of AEP promoted the tumor-suppressing effect of chemotherapeutic drugs,whereas AEP-cleaved G3BP1 rescue reversed the effect in both OS and glioma models.Cancerous tissues exhibited high levels of AEP and G3BP1 truncations,which were strongly associated with poor prognosis.展开更多
At this historic juncture of deepening technological revolution and industrial transformation,China's communication sector stands on the eve of another great leap forward.Reflecting on the development of communica...At this historic juncture of deepening technological revolution and industrial transformation,China's communication sector stands on the eve of another great leap forward.Reflecting on the development of communications over the past two decades,China has forged an innovative path from catching up to keeping pace and then to leading the way.Today,at the new starting point of 6G development and facing the paradigm shift brought about by“AI+communications,”China's scientific research community,with the courage to venture into uncharted territory,is advancing original theories such as the new communication paradigm based on a unified theoretical framework of information theory to the global forefront.展开更多
Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—esp...Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.展开更多
基金supported by the Shenzhen Science and Technology Innovation Commission,No.JCYJ20220818103009018(to YD).
文摘The arginine-phenylalanine-amide neuropeptide receptor family comprises a subclass within the G protein-coupled receptor superfamily with crucial roles in physiological regulation.These receptors recognize and bind neuropeptides with an arginine-phenylalanine-amide motif,thereby participating in a variety of biological processes such as energy metabolism,pain perception,and reproductive functions.In this review,we explore the physiological and pathological processes involving these receptors and delve into the structure-activity relationships of their ligand peptides,clarifying the key structural motifs within these neuropeptides that determine their biological activity,pharmacological potency,and receptor selectivity.Particular emphasis is placed on their roles in modulating nociception,regulating appetite,and maintaining reproductive health.Additionally,we discuss the therapeutic potential of structure-based drug design targeting these receptors based on existing cryo-electron microscopy structures.The available structural insights into ligand-binding pockets and G protein-receptor interaction interfaces provide a clear perspective and valuable complement to ligand optimization.
基金supported in part by Jiangsu Provincial Key Research and Development Program(No.BE2023022-2)in part by National Natural Science Foundation of China(No.62471204,92367302)in part by Major Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(No.24KJA510003)。
文摘Reconfigurable Intelligent Surface(RIS)is envisioned as a promising technology to improve the system capacity of 6G network,by controlling the electromagnetic wave propagation.Most existing works use the Central Limit Theorem(CLT)to analyze the performance of RIS-assisted systems for large number of reflective elements.However,the assumption of extremely large number of elements may not be practical in the actual situation.In addition,the CLT-based approximation yields an inaccurate scaling law of the outage probability when the transmit Signal-to-Noise Ratio(SNR)tends to infinity.Motivated by these limitations,in this paper,we investigate the performance of RIS-assisted cellular networks with multiple Device-to-Device(D2D)users under the general fading channels,i.e.,Nakagami-m fading channels.We propose a tractable solution to evaluate the outage probability and the ergodic achievable rate,which is accurate for any number of reflective elements,any network topology,as well as any SNR.In addition,the accurate approximations for the high SNR case and the large number of reflective elements case are further derived in simpler closed form.Numerical results verify the accuracy of our analytical results and analyze the performance between CLT and the proposed method.
基金supported in part by the Key Projects of National Natural Science Foundation of China under Grant 51936003.
文摘Integration of natural gas and electricity transmission systems has strengthened interdependence between the two systems.Due to the close interconnection through coupling elements between the power system(PS)and natural gas system(NGS)when a disturbance happens in one system,a series of complicated sequences of dependent events may follow in another system.Therefore,an integrated planning model jointing security-constrained considering cascading effects is proposed in this paper.Meanwhile,natural gas and electricity transmission systems considering stochastic failures and various operating characteristics of components can be viewed as a multistate systems.Moreover,power-to-gas(P2G),as a promising technology proposed to store surplus renewable energy,is considered in the integrated planning.First,multi-state models for different components are developed to describe realistic operating conditions in natural gas and electricity transmission systems.Furthermore,a mixed-integer linear programming(MILP)approach considers N-1 contingency and cascading effects between natural gas and the electrical power systems.Therefore,a security-constrained integrated planning model of natural gas and electricity transmission systems is represented.The proposed methods are validated using an integrated gas and power test system.
基金supported by the National Science Fund for Excellent Young Scholars(grant number 32422082)the Natural Science Basic Research Plan in Shaanxi Province(grant number 2025JC-QYXQ-009)。
文摘Background Ruminants and monogastric animals exhibit significant differences in gluconeogenic efficiency.In dairy cows,hepatic gluconeogenesis serves as the primary source of glucose.Metabolites modulate gluconeogenesis efficiency through allosteric regulation,redox state,and signal transduction pathways.However,the liver-enriched metabolites that regulate hepatic gluconeogenesis in dairy cows and their specific regulatory mechanisms remain incompletely characterized.Results Six Holstein dairy cows and six Duroc×(Landrace×Yorkshire)(DLY)crossbred pigs served as research subjects.Employing non-targeted and targeted metabolomics,we discovered that three bile acids—taurodeoxycholic acid(TDCA),taurocholic acid(TCA),and glycocholic acid(GCA)—were highly enriched in Holstein dairy cows'livers.In bovine hepatocytes,individual or combined stimulation of these bile acids significantly upregulated the expression of gluconeogenesis genes(FBP1,PCK1 and G6PC)and enhanced glucose production.In fasting mice with induced gluconeogenesis,TDCA,TCA,and GCA increased fasting blood glucose levels,and pyruvate tolerance tests further revealed their capacity to enhance hepatic gluconeogenesis,enabling more efficient glucose synthesis from pyruvate.Mechanistically,these bile acids activated Takeda G protein-coupled receptor 5(TGR5),elevated intracellular cAMP levels,and ultimately enhanced gluconeogenesis via the transcription factor cAMP-response element binding protein(CREB).Notably,a TGR5 inhibitor abrogated the stimulatory effects of TDCA,TCA,and GCA on hepatic gluconeogenesis in fasting mice.Conclusion TDCA,TCA,and GCA are key metabolites promoting hepatic gluconeogenesis in dairy cows,with TGR5 as the pivotal receptor and the cAMP/PKA/CREB pathway as the critical downstream mechanism.
文摘Securing restricted zones such as airports,research facilities,and military bases requires robust and reliable access control mechanisms to prevent unauthorized entry and safeguard critical assets.Face recognition has emerged as a key biometric approach for this purpose;however,existing systems are often sensitive to variations in illumination,occlusion,and pose,which degrade their performance in real-world conditions.To address these challenges,this paper proposes a novel hybrid face recognition method that integrates complementary feature descriptors such as Fuzzy-Gabor 2D Fisher Linear Discriminant(FG-2DFLD),Generalized 2D Linear Discriminant Analysis(G2DLDA),andModular-Local Binary Patterns(Modular-LBP)with Dempster–Shafer(DS)evidence theory for decision fusion.The proposed framework extracts global,structural,and local texture features,models them using Gaussian distributions to estimate belief factors,and fuses these belief factors through DS theory to explicitly handle uncertainty and conflict among descriptors.Experimental validation was performed on two widely used benchmark datasets,ORL and Cropped Yale B,achieving recognition rates exceeding 98%,which outperform traditional methods as well as recent deep learning-based approaches.Furthermore,the method demonstrated strong robustness under noisy conditions,maintaining accuracies above 96%with salt-and-pepper and Gaussian noise.These results highlight the effectiveness of the proposed integration strategy in enhancing accuracy,reliability,and resilience compared to single-descriptor and conventional fusion methods.Given its high performance and efficiency,the proposed method shows strong potential for deployment in real-world restricted-zone applications such as smart parking systems,secure facility access,and other high-security domains.
基金supported by the National Key Researchand Development Program of China(No.2021YFC2801904)the Science Fund of Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai,China(No.AMGM2024F11).
文摘The ultrasonic energy field(UEF)-induced grain refinement mechanisms in laser powder direct energy deposition-manufactured Ti5321G alloys were systematically investigated in this study.This study focused on the interplay between recrystallization in the high-temperature solid deposition layers and the ultrasonic cavitation-acoustic streaming effects during molten pool solidification.A novel experimental design was developed to decouple these mechanisms by creating four distinct UEF action zones(without UEF-N,withUEF-S,with UEF-L,and with UEF-S+L)within a single-pass multilayer sample.This approach enabled the dual effects of UEF(recrystallization in solidified layers and ultrasonic cavitation-acoustic streaming effects in liquid pools)to be directly compared.The UEF significantly refined the microstructures,reducing the average grain size by 64.2%(from(399.6±28.6)to(143.1±16.1)μm)in the with UEF-S+L zone,while promoting columnar-to-equiaxed transition,with the equiaxed grain probability increasing from 11.1%(without UEF) to 53.8%.The texture intensity was reduced by approximately 52.4%and the mechanical properties were enhanced,achieving a 6.2% increase in yield strength((702.0±10.6)MPa)and 31.7%improvement in elongation.Crucially,this study revealed the synergistic effect of the dual-action mechanisms of UEF,where recrystallization and cavitation-acoustic streaming collectively enabled non-linear grain refinement.This study provides a strategy for microstructural control in additive manufacturing,eliminating the need for complex post-processing and thereby advancing the industrial application of high-performance titanium components.
基金supported by the Central Government-Guided Local Science and Technology Development Fund Project(Science and Technology Innovation Base Project)(Grant No.236Z7749G)Hebei Provincial Precision Medicine Innovation and Development Joint Fund Incubation Project(Grant No.H2025206547)Hebei Provincial Basic Research Special Youth Science Fund Project(Grant No.H2025206274).
文摘Background:Hepatocellular carcinoma(HCC)is an aggressive and lethal malignancy.Metabolic reprogramming dynamically remodels the tumor microenvironment(TME)and drives HCC progression.This study investigated the mechanism through which metabolic reprogramming remodels the TME in HCC.Methods:HCC patient transcriptome data were subjected to bioinformatics analysis to identify differentially expressed genes and immune infiltration status.Immunohistochemical analysis was performed to determine the correlation between succinate dehydrogenase complex subunit A(SDHA)expression and M2 macrophage infiltration.SDHA-knockdown or SDHA-overexpressing HCC cells were used for in vitro experiments,including co-culturing,flow cytometry,and enzyme-linked immunosorbent assay.Western blotting assay,functional assays,and subcutaneous tumor model mice were used to elucidate the molecular mechanisms underlying succinate-mediated HCC cell-macrophage interactions in the TME.Results:Higher infiltration of M2 macrophages correlated with worse prognosis in HCC patients.SDHA was downregulated in HCC tumor tissues and showed a negative correlation with M2 macrophage infiltration.SDHA knockdown promoted M2 macrophage polarization,whereas SDHA overexpression reversed this effect.Mechanistically,SDHA deficiency in HCC cells induced succinate accumulation,which promoted M2 macrophage polarization by activating the G protein-coupled receptor 91(GPR91)/signal transducer and activator of transcription 3(STAT3)pathway.Concurrently,succinate stimulation enhanced mitochondrial oxidative phosphorylation in M2 macrophages,thereby promoting HCC progression.Serum succinate levels were elevated in HCC patients.The receiver operating characteristic curve analysis indicated that serum succinate is a promising diagnostic marker for HCC(area under the curve=0.815).Conclusion:SDHA deficiency leads to succinate accumulation,which promotes M2 macrophage polarization through the GPR91/STAT3 pathway,thereby facilitating HCC progression.Based on these findings,serum succinate could be a promising diagnostic biomarker for HCC.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
基金Supported by NSF of Henan Province (Nos.252300420353,252300421973)Key Scientific and Technological Project of Henan Province (No.242102210049)。
文摘In this paper,we interpret the operator representation using g-frames as a generalization of U-cross Gram matrices.We establish the link between U-cross g-Gram matrices andg-Riesz bases,and obtain a characterization ofg-Riesz bases by U-cross g-Gram matrices.In particular,someexamples show that the invertibility of U-cross g-Gram matrix is not possible when the associated sequences are g-frames but not g-Riesz bases or at most one of them is a g-Riesz basis.Finally,we show that the invertibility of U-cross g-Gram matrices is preserved under small perturbations of the operators or the sequences.
基金derived from a research grant“Cybersecurity Research and Innovation Pioneers Grants Initiative”funded by The National Program for RDI in Cybersecurity(National Cybersecurity Authority)-Kingdom of Saudi Arabia-with grant number(CRPG-25-3168)supported by EIAS Data Science and Blockchain Lab,CCIS,Prince Sultan University.
文摘The growing developments in 5G and 6G wireless communications have revolutionized communications technologies,providing faster speeds with reduced latency and improved connectivity to users.However,it raises significant security challenges,including impersonation threats,data manipulation,distributed denial of service(DDoS)attacks,and privacy breaches.Traditional security measures are inadequate due to the decentralized and dynamic nature of next-generation networks.This survey provides a comprehensive review of how Federated Learning(FL),Blockchain,and Digital Twin(DT)technologies can collectively enhance the security of 5G and 6G systems.Blockchain offers decentralized,immutable,and transparent mechanisms for securing network transactions,while FL enables privacy-preserving collaborative learning without sharing raw data.Digital Twins create virtual replicas of network components,enabling real-time monitoring,anomaly detection,and predictive threat analysis.The survey examines major security issues in emerging wireless architectures and analyzes recent advancements that integrate FL,Blockchain,and DT to mitigate these threats.Additionally,it presents practical use cases,synthesizes key lessons learned,and identifies ongoing research challenges.Finally,the survey outlines future research directions to support the development of scalable,intelligent,and robust security frameworks for next-generation wireless networks.
基金appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Group Project under grant number(RGP2/245/46)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R333)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The expansion of 5G-enabled Internet of Things(IoT)networks,while enabling transformative applications,significantly increases the attack surface and necessitates security solutions that extend beyond traditional intrusion detection.Existing intrusion detection systems(IDSs)mainly operate in an open-loop manner,excelling at classification but lacking the ability for autonomous,safety-aware remediation.This gap is particularly critical in 5G environments,where manual intervention is too slow and naive automation can lead to severe service disruptions.To address this issue,we propose a novel Self-Healing Intrusion Detection System(SH-IDS)framework that develops a closed-loop cyber defense mechanism.The main technical contribution is the integration of a deep neural networkbased threat detector,which offers uncertainty-quantified predictions,with a safety-aware reinforcement learning(RL)engine formulated as a Constrained Markov Decision Process(CMDP).The CMDP explicitly models operational safety as cost constraints,and a new runtime safety shield actively adjusts any unsafe action proposed by the RL agent to the nearest safe alternative,ensuring operational integrity.Additionally,we introduce a composite utility function for the comprehensive evaluation of the system.Empirical analysis on the 5G-NIDD dataset demonstrates the superior performance of our framework:the detector achieves 98.26%accuracy,while the safe RL agent learns effective mitigation policies.Importantly,the safety shield blocked up to 70 unsafe actions under strict constraints,and analysis of the learned Q-tables confirms that the agent internalizes safety,avoiding overly disruptive actions,such as isolating nodes for minor threats.The system also maintains high efficiency with a compact model size of 121.7 KB and sub-millisecond latency,confirming its practical deployability for real-time 5G-IoT security.
文摘The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.
基金supported by the National Science and Technology Council,Taiwan,under Grants 113-2221-E-260-014-MY2 and 114-2119-M-033-001.
文摘The rapid growth of mobile and Internet of Things(IoT)applications in dense urban environments places stringent demands on future Beyond 5G(B5G)or Beyond 6G(B6G)networks,which must ensure high Quality of Service(QoS)while maintaining cost-efficiency and sustainable deployment.Traditional strategies struggle with complex 3D propagation,building penetration loss,and the balance between coverage and infrastructure cost.To address this challenge,this study presents the first application of a Global-best Guided Quantum-inspired Tabu Search with Quantum-Not Gate(GQTS-QNG)framework for 3D base-station deployment optimization.The problem is formulated as a multi-objective model that simultaneously maximizes coverage and minimizes deployment cost.A binary-to-decimal encodingmechanism is designed to represent discrete placement coordinates and base station types,leveraging a quantum-inspired method to efficiently search and refine solutions within challenging combinatorial environments.Global-best guidance and tabu memory are integrated to strengthen convergence stability and avoid revisiting previously explored solutions.Simulation results across user densities ranging from 1000 to 10,000 show that GQTS-QNG consistently finds deployment configurations achieving full coverage while reducing deployment cost compared with the state-of-the-art algorithms under equal iteration times.Additionally,our method generates welldistributed and structured Pareto fronts,offering diverse planning options that allow operators to flexibly balance cost and performance requirements.These findings demonstrate that GQTS-QNG is a scalable and efficient algorithm for sustainable 3D cellular network deployment in B5G/6G urban scenarios.
文摘The rapid growth in available network bandwidth has directly contributed to an exponential increase in mobile data traffic,creating significant challenges for network energy consumption.Also,with the extraordinary growth of mobile communications,the data traffic has dramatically expanded,which has led to massive grid power consumption and incurred high operating expenditure(OPEX).However,the majority of current network designs struggle to efficientlymanage a massive amount of data using little power,which degrades energy efficiency performance.Thereby,it is necessary to have an efficient mechanism to reduce power consumption when processing large amounts of data in network data centers.Utilizing renewable energy sources to power the Cloud Radio Access Network(C-RAN)greatly reduces the need to purchase energy from the utility grid.In this paper,we propose a bandwidth-aware hybrid energypowered C-RAN that focuses on throughput and energy efficiency(EE)by lowering grid usage,aiming to enhance the EE.This paper examines the energy efficiency,spectral efficiency(SE),and average on-grid energy consumption,dealing with the major challenges of the temporal and spatial nature of traffic and renewable energy generation across various network setups.To assess the effectiveness of the suggested network by changing the transmission bandwidth,a comprehensive simulation has been conducted.The numerical findings support the efficacy of the suggested approach.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2394475,T2394470,T2394471,and 12174129)the China Postdoctoral Science Foundation(Grant No.2023M741269).
文摘Altermagnets,a class of unconventional antiferromagnets with non-relativistic spin-splitting,offer promising potential for antiferromagnetic spintronic devices.While many altermagnets are limited by either low magnetic transition temperatures or weak spin splitting,the recently discovered metal CrSb,with high N′eel temperature(T_(N)=710 K)and significant spin-splitting due to its unique spin space group,provides a robust platform for remarkable tunneling magnetoresistance(TMR)in collinear all-antiferromagnetic tunnel junctions(AATJs).This study systematically investigates the spin-polarized Fermi surface of CrSb and spin-dependent electron transport in CrSb-based AATJs.The CrSb/β-InSe/CrSb junction with a three-monolayer InSe barrier exhibits a TMR ratio of approximately 290%,with energy-dependent analysis revealing TMR ratios that may exceed 850%when considering the shift of the Fermi energy.We also demonstrate the angle-dependent TMR of CrSb-based AATJs by adjusting N′eel vector orientations.Our findings might provide strong theoretical support for CrSb as a versatile building block for all-antiferromagnetic memory devices.
文摘To overcome the limitations of traditional photocatalysts,such as inefficient separation of charge carriers and poor visible-light absorption,S-scheme g-C_(3)N_(4)/TiO_(2) heterojunction photocatalysts were synthesized via a combined method of thermal polymerization,hydrothermal synthesis,and calcination.The crystal structures,morphological features,and optical properties of the composites were systematically characterized,and their photocatalytic performance was evaluated through tetracycline(TC)degradation and hydrogen evolution experiments.Trapping experiments and electron paramagnetic resonance(EPR)measurements were conducted to elucidate the reaction mechanisms.The results demonstrate that the S-scheme heterojunction effectively extends the visible-light absorption range and facilitates the efficient separation of photogenerated electron-hole pairs.Under optimal conditions,the composite achieved a TC degradation rate of 94.5%and a hydrogen evolution rate of 329.1μmol·h^(-1)·g^(-1) after 8 h of irradiation,both values being significantly higher than those of pristine g-C_(3)N_(4) or TiO_(2).Moreover,the S-scheme g-C_(3)N_(4)/TiO_(2) heterojunction retained high photocatalytic activity over five consecutive cycles,confirming its excellent stability.Mechanistic investigations revealed that the S-scheme heterojunction maintained strong redox capacities,with superoxide radicals(·O_(2)^(-)),hydroxyl radicals(·OH),electrons(e-),and holes(h+)serving as the primary active species responsible for TC degradation and H2 production.
基金supported by the National Key R&D Program of China(grant number 2023ZD0502206,2024YFB3213200,Topic No.2024YFB3213204)National Natural Science Foundation of China(nos.82273278,82373514,82373202,82272728,82002630,81772654)+5 种基金the National Key Research and Development Program of China(grant number 2022YFC2404602)Shanghai Hospital Development Center Foundation(grant number SHDC12023108)Scientific and Technological Innovation Action Plan of Shanghai Science and Technology Committee(grant number 22Y31900103)Beijing Science and Technology Innovation Medical Development Foundation(grant number KC2021-JX-0170-9)the Shanghai Association for Science and Technology(nos.201409003000,201409002400,20YF1426200)Shanghai Science and Technology Innovation Action Plan(grant number 23Y41900100).
文摘Osteosarcoma(OS)is the most frequent primary bone sarcomas with high recurrence and poor prognosis.Emerging evidence indicates that membraneless organelles stress granules(SGs),whose assemblies are driven by scaffold protein G3BP1,are extensively involved in tumor,especially in OS.However,how SGs behave and communicate with organelles,particularly nucleoli and mitochondria,during drug challenges remain unknown.This study revealed that chemotherapeutic drugs activated the cysteine protease asparagine endopeptidase(AEP)to specifically cleave the SG core protein G3BP1 at N258/N309 in OS and malignant glioma.tG3BP1-Ns modulated SG dynamics by competitively binding to full-length G3BP1.Strikingly,tG3BP1-Cs,containing a conserved RNA recognition motif CCUBSCUS,sequestered mRNAs of ribosomal proteins and oxidative phosphorylation genes in the nucleoli and mitochondria to repress translation and oxidative stress.Moreover,the inhibition of AEP promoted the tumor-suppressing effect of chemotherapeutic drugs,whereas AEP-cleaved G3BP1 rescue reversed the effect in both OS and glioma models.Cancerous tissues exhibited high levels of AEP and G3BP1 truncations,which were strongly associated with poor prognosis.
文摘At this historic juncture of deepening technological revolution and industrial transformation,China's communication sector stands on the eve of another great leap forward.Reflecting on the development of communications over the past two decades,China has forged an innovative path from catching up to keeping pace and then to leading the way.Today,at the new starting point of 6G development and facing the paradigm shift brought about by“AI+communications,”China's scientific research community,with the courage to venture into uncharted territory,is advancing original theories such as the new communication paradigm based on a unified theoretical framework of information theory to the global forefront.
基金funded by the National Natural Science Foundation of China(NSFC)under Grant Number 72071209.
文摘Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.
