In this article,we introduce a new theoretical approach to improve the accuracy of twodimensional(2D)atomic localization within a tripod-type,four-level atomic system by analyzing its transmission spectrum.In this met...In this article,we introduce a new theoretical approach to improve the accuracy of twodimensional(2D)atomic localization within a tripod-type,four-level atomic system by analyzing its transmission spectrum.In this method,the atom interacts with two orthogonal standing-wave fields and a weak probe field.By examining how the weak probe field passes through the system,we can determine the atom position.Our analysis reveals the presence of both double and sharply defined single localized peaks in the transmission spectrum,which correspond to specific positions of the atom.Importantly,we achieve ultra-high-resolution atomic localization with accuracy confined to a region smaller thanλ/32×λ/32.This level of precision is a significant improvement compared to earlier methods,which had lower localization accuracy.The increased precision is due to the complex interaction between the atom and the carefully controlled standing-wave and probe fields,which allows for precise control over the atom's position.The implications of this work are significant,especially for applications like nano-lithography,where precise atomic placement is essential,and for laser cooling technologies,where better atomic localization could lead to more effective cooling processes and improved manipulation of atomic states.展开更多
Unmanned aerial vehicle(UAV)-borne gamma-ray spectrum survey plays a crucial role in geological mapping,radioactive mineral exploration,and environmental monitoring.However,raw data are often compromised by flight and...Unmanned aerial vehicle(UAV)-borne gamma-ray spectrum survey plays a crucial role in geological mapping,radioactive mineral exploration,and environmental monitoring.However,raw data are often compromised by flight and instrument background noise,as well as detector resolution limitations,which affect the accuracy of geological interpretations.This study aims to explore the application of the Real-ESRGAN algorithm in the super-resolution reconstruction of UAV-borne gamma-ray spectrum images to enhance spatial resolution and the quality of geological feature visualization.We conducted super-resolution reconstruction experiments with 2×,4×and 6×magnification using the Real-ESRGAN algorithm,comparing the results with three other mainstream algorithms(SRCNN,SRGAN,FSRCNN)to verify the superiority in image quality.The experimental results indicate that Real-ESRGAN achieved a structural similarity index(SSIM)value of 0.950 at 2×magnification,significantly higher than the other algorithms,demonstrating its advantage in detail preservation.Furthermore,Real-ESRGAN effectively reduced ringing and overshoot artifacts,enhancing the clarity of geological structures and mineral deposit sites,thus providing high-quality visual information for geological exploration.展开更多
Autism spectrum disorder(AsD)is a highly heterogeneous neurodevelopmental disorder.Early diagnosis and intervention are crucial for improving outcomes.Traditional single-modality diagnostic methods are subjective,limi...Autism spectrum disorder(AsD)is a highly heterogeneous neurodevelopmental disorder.Early diagnosis and intervention are crucial for improving outcomes.Traditional single-modality diagnostic methods are subjective,limited,and struggle to reveal the underlying pathological mechanisms.In contrast,multimodal data analysis integrates behavioral,physiological,and neuroimaging information with advanced machine-learning and deeplearning algorithms to overcome these limitations.In this review,we surveyed the recent pediatric AsD literature,highlighting artificial intelligence-driven diagnostic techniques,multimodal data fusion strategies,and emerging trends in ASD assessment.We surveyed studies that integrated two or more modalities and summarized the fusion levels,learning paradigms,tasks,datasets,and metrics.Multimodal approaches outperform singlemodality baselines in classification,severity estimation,and subtyping by leveraging complementary information and reducing modality-specific biases.Multimodal approaches significantly enhance diagnostic accuracy and comprehensiveness,enabling early screening of AsD,symptom subtyping,severity assessment,and personalized interventions.Advances in multimodal fusion techniques have promoted progress in precision medicine for the treatment of ASD.展开更多
We achieved an ultra-flat broad spectrum output with a 20-dB bandwidth of 77.85 nm in a double-clad Yb-doped fiber laser.The intensity difference between the highest and lowest points of the spectrum indicates a flatn...We achieved an ultra-flat broad spectrum output with a 20-dB bandwidth of 77.85 nm in a double-clad Yb-doped fiber laser.The intensity difference between the highest and lowest points of the spectrum indicates a flatness better than4 dB.More notably,this ultra-flat broad spectrum maintains a stable single-pulse mode-locking state.With the increase of pump power,an ultra-wide spectrum with a 20-dB bandwidth approaching 100 nm was formed at a pump power of 2.25 W.Additionally,we obtained a 9-pulse mode-locked state at another PC station with the same pump,which is the highest number of stable mode-locked pulse bursts observed so far with a first-order Raman frequency shift.This fiber laser shows its benefits of ultra-flat broad spectrum,high stability,and ease of fabrication,which provides a new method of obtaining the broadband light source for multiple practical applications.展开更多
In fatigue damage tolerance verification tests of aircraft structures,the simulation and loading of flight-byflight spectra require considerable time and resources.To improve the efficiency of load spectrum design and...In fatigue damage tolerance verification tests of aircraft structures,the simulation and loading of flight-byflight spectra require considerable time and resources.To improve the efficiency of load spectrum design and testing,an equivalent constant-amplitude spectrum design method for flight-by-flight spectra is proposed based on the equivalence of crack growth behavior.By combining the Paris crack growth model with the Walker stress ratio correction,the equivalent stress amplitude is directly calculated using structural parameters and load spectrum characteristics,enabling a rapid transformation from variable-amplitude spectra to constant-amplitude spectra.The original spectrum is discretized based on the load-exceedance curve,and the equivalence relationship between multilevel block spectra and constant-amplitude spectra is established.Taking a typical lower wing skin structure of a transport aircraft as an example,two equivalent spectra are designed and validated through fatigue crack growth tests on 2024-T351 center-hole plate specimens.The experimental results show that the fatigue life deviation between the equivalent spectra and the original flight-by-flight spectrum is within 10%,demonstrating the effectiveness of the proposed method.Moreover,the equivalent spectrum constructed under the condition of invariant mean flight stress exhibits higher equivalence accuracy.The influence of spectral shape on the equivalent stress amplitude is further analyzed,revealing that the equivalent stress amplitude increases with the spectrum shape coefficient.The proposed method provides a useful reference for load spectrum design in aircraft structural damage tolerance verification tests.展开更多
As demand for land resources is rapidly growing nowadays,developing on slope lands has become a way to relieve pressure on flat lands.Although some studies use the concept of slope spectrum to explore the trend of lan...As demand for land resources is rapidly growing nowadays,developing on slope lands has become a way to relieve pressure on flat lands.Although some studies use the concept of slope spectrum to explore the trend of land use upslope,relying solely on the slope spectrum is too broad and prevents deeper research.Therefore,using China's land use and DEM data from 2000 to 2020,our study integrated the slope spectrum and the slope sensitivity coefficient(SSC)calculated by the land use transfer matrix as a new approach and method for understanding the underlying formations and impacts of upslope in farmland and construction land,supporting regional management strategies.The results show that:1)Farmlands were upslope in the South and developed horizontally in the North,and construction lands were upslope nationwide.2)Using the land use transfer matrix and SSC,we classified farmland upslope as passive and active patterns,and construction land upslope as saturation and avoidance patterns based on their land use transfer mechanisms in slope space.Provinces with passive and saturation patterns are mainly located near the east coast.3)Different patterns of upslope have distinct impacts on sustainable development.The passive pattern harms food security while the active pattern can relieve pressure on food security but increases ecological risks.Saturation pattern damages food security,ecological protection,and city livability,but avoidance pattern can promote food security and ecological protection.The findings will serve as an essential reference for developing land use strategies aimed at sustainable development.展开更多
Vehicular Internet ofThings(V-IoT)networks need intelligent and adaptive spectrum access methods for ensuring ultra-reliable and low-latency communication(URLLC)in highly dynamic environments.Traditional reinforcement...Vehicular Internet ofThings(V-IoT)networks need intelligent and adaptive spectrum access methods for ensuring ultra-reliable and low-latency communication(URLLC)in highly dynamic environments.Traditional reinforcement learning(RL)-based algorithms,such as Q-Learning and Double Q-Learning,are often characterized by unstable convergence and inefficient exploration in the presence of stochastic vehicular traffic and interference.This paper proposes Adaptive Reinforcement Q-learning with Upper Confidence Bound(ARQ-UCB),a lightweight and reliability-aware RL framework,which explicitly reduces interruption and blocking probabilities while improving throughput and delay across diverse vehicular traffic conditions.This proposed ARQ-UCB algorithm extends the basic Q-updates with an exploration confidence term able to dynamically balance exploration and exploitation based on uncertainty estimates,hence allowing faster convergence in case of bursty vehicular traffic.A comprehensive simulation framework evaluates throughput,delay,fairness,energy efficiency,and computational complexity in several V-IoT scenarios.Obtained results indicate that ARQ–UCB attains substantial gains in terms of throughput,fairness,and blocking/delay probabilities while retaining sub-20μs decision latency and O(1)complexity per decision,thus validating real-time feasibility for reliable spectrum access in 5G and beyond V-IoT networks.展开更多
Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods...Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.展开更多
The octupole correlations of the K^(π)=5/2^(+)ground state and the rotational spectrum built on it in^(229)Th are studied using the microscopic relativistic density functional theory on a three-dimensional lattice sp...The octupole correlations of the K^(π)=5/2^(+)ground state and the rotational spectrum built on it in^(229)Th are studied using the microscopic relativistic density functional theory on a three-dimensional lattice space and the reflection-asymmetric triaxial particle rotor model.It is found that^(229)Th has a ground state with static axial octupole and quadrupole deformations.The occurrence of octupole correlations,driven by the octupole deformation,is analyzed through the evolution of single-particle levels around the Fermi surface.The experimental energy spectrum and the electromagnetic transition probabilities,including B(E2)and B(M1),are reasonably well reproduced.展开更多
Vehicular communication systems rely on secure vehicle-to-vehicle(V2V)communications for safety-critical information exchange.However,the presence of eavesdropping vehicles poses a significant challenge.This paper inv...Vehicular communication systems rely on secure vehicle-to-vehicle(V2V)communications for safety-critical information exchange.However,the presence of eavesdropping vehicles poses a significant challenge.This paper investigates the security of V2V communications in reconfigurable intelligent surface(RIS)-assisted vehicular communication systems with spectrum sharing.It proposes a three-stage alternating optimization(TSAO)algorithm to address the complex problem of multiple eavesdropped V2V links that reuse the spectrum already occupied by vehicle-toinfrastructure(V2I)links.To solve the mixed-integer and non-convex optimization problem due to coupled variables and complex constraints,the algorithm decomposes the original problem into three easily solvable sub-problems:RIS reflection coefficient optimization,vehicle transmission power optimization,and spectrum sharing optimization.First,the RIS reflection coefficients are optimized by using the penalty convex-concave procedure(CCP)method.Second,the optimal power points are determined in the power optimization sub-problem.Finally,the spectrum sharing optimization sub-problem is constructed as a weighted bipartite graph matching problem and solved by using the optimal matching algorithm.The TSAO algorithm not only maximizes the sum V2V secrecy rate but also ensures the quality-of-service(QoS)requirements of the V2I links.Simulation results validate the superiority of the proposed algorithm and highlight the improvement in the sum V2V secrecy rate achieved by utilizing RIS technology in vehicular communication systems with spectrum sharing.展开更多
Low-density non–local-thermodynamic-equilibrium plasmas in intense radiation fields occur widely in inertial confinement fusion and astrophysics. Understanding the X-ray spectrum and the atomic kinetics of such plasm...Low-density non–local-thermodynamic-equilibrium plasmas in intense radiation fields occur widely in inertial confinement fusion and astrophysics. Understanding the X-ray spectrum and the atomic kinetics of such plasmas is therefore of great importance. However, the creation of uniform-density nonequilibrium plasmas in intense radiation fields in the laboratory and the measurement of their spectra with high resolution are challenging tasks. Here, we present a new method to produce such a uniform aluminum plasma and explore photon-induced kinetics and relevant atomic physics by measuring its spectrum. It is observed that in the presence of an external radiation field, the satellites q, r and a–d of the He-α resonance line are greatly enhanced compared with the satellites j, k, l. Analysis of atomic kinetics reveals that this effect of intense radiation is due to competition between the photoexcitation and autoionization processes. With this effect taken into account,simulated spectra are able to reproduce the measured spectra quite well.展开更多
Neuromyelitis optica spectrum disorder-related optic neuritis involves various cellular responses to inflammation and degeneration.In most patients,the primary mechanism underlying neuromyelitis optica spectrum disord...Neuromyelitis optica spectrum disorder-related optic neuritis involves various cellular responses to inflammation and degeneration.In most patients,the primary mechanism underlying neuromyelitis optica spectrum disorder-related optic neuritis is the interaction of aquaporin-4 antibodies with the aquaporin-4 protein present on astrocytes within posterior optic nerve.This binding subsequently initiates a cascade of events leading to secondary demyelination of the optic nerve,ultimately culminating in optic nerve degeneration.Earlier studies on this disorder primarily used systemic-induced animal models,which often require prior activation of a systemic immune response.This can result in primary demyelination of the optic nerve,complicating the interpretation of experimental results.Such methodologies hinder the ability to isolate immune responses triggered by specific antibodies.Additionally,the lack of a detailed profile of disease progression over time limits our capacity to identify potential intervention windows.Therefore,constructing a targeted optic neuritis animal model induced by specific antibodies and elucidate the disease progression arecrucial for exploring the mechanisms underlying neuromyelitis optica spectrum disorder-related optic neuritis.In this study,specific antibodies against aquaporin-4 were precisely injected into the retrobulbar optic nerve of mice to induce a targeted inflammatory response in the posterior optic nerve,resulting in a more representative mouse model of neuromyelitis optica spectrum disorder-related optic neuritis than current models.The progression of the disease was then dynamically observed from both histological and functional perspectives over the course of 1 month following the induction of inflammation.By the first week,astrocytes were damaged,as evidenced by the loss of aquaporin-4 and glial fibrillary acidic protein,the activation of microglia,and the upregulation of microglia-related cytokines,including tumor necrosis factor,interleukin-6,interleukin-1β,C-X-C motif ligand 10,and brain-derived neurotrophic factor.Starting from the second week,there were signs of optic nerve demyelination and significant damage to axonal fibers and retinal ganglion cell bodies.Visual-evoked potentials and dark adaptation threshold responses in electroretinogram both indicated dysfunction in the visual pathway and retina,while optical coherence tomography revealed thinning of the retinal nerve fiber layer in live mice.In summary,in this study we conducted a dynamic exploration of the occurrence and progression of neuromyelitis optica spectrum disorder-related optic neuritis triggered by specific antibodies.Our results show pathological changes at various stages and correlate histological and molecular alterations with in vivo structural and functional deterioration.The findings from this study lay an important foundation for further research on neuromyelitis optica spectrum disorder-related optic neuritis.展开更多
Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning sy...Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.展开更多
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R8)。
文摘In this article,we introduce a new theoretical approach to improve the accuracy of twodimensional(2D)atomic localization within a tripod-type,four-level atomic system by analyzing its transmission spectrum.In this method,the atom interacts with two orthogonal standing-wave fields and a weak probe field.By examining how the weak probe field passes through the system,we can determine the atom position.Our analysis reveals the presence of both double and sharply defined single localized peaks in the transmission spectrum,which correspond to specific positions of the atom.Importantly,we achieve ultra-high-resolution atomic localization with accuracy confined to a region smaller thanλ/32×λ/32.This level of precision is a significant improvement compared to earlier methods,which had lower localization accuracy.The increased precision is due to the complex interaction between the atom and the carefully controlled standing-wave and probe fields,which allows for precise control over the atom's position.The implications of this work are significant,especially for applications like nano-lithography,where precise atomic placement is essential,and for laser cooling technologies,where better atomic localization could lead to more effective cooling processes and improved manipulation of atomic states.
基金supported by the National Natural Science Foundation of China(Nos.12205044 and 12265003)2024 Jiangxi Province Civil-Military Integration Research Institute‘BeiDou+’Project Subtopic(No.2024JXRH0Y06).
文摘Unmanned aerial vehicle(UAV)-borne gamma-ray spectrum survey plays a crucial role in geological mapping,radioactive mineral exploration,and environmental monitoring.However,raw data are often compromised by flight and instrument background noise,as well as detector resolution limitations,which affect the accuracy of geological interpretations.This study aims to explore the application of the Real-ESRGAN algorithm in the super-resolution reconstruction of UAV-borne gamma-ray spectrum images to enhance spatial resolution and the quality of geological feature visualization.We conducted super-resolution reconstruction experiments with 2×,4×and 6×magnification using the Real-ESRGAN algorithm,comparing the results with three other mainstream algorithms(SRCNN,SRGAN,FSRCNN)to verify the superiority in image quality.The experimental results indicate that Real-ESRGAN achieved a structural similarity index(SSIM)value of 0.950 at 2×magnification,significantly higher than the other algorithms,demonstrating its advantage in detail preservation.Furthermore,Real-ESRGAN effectively reduced ringing and overshoot artifacts,enhancing the clarity of geological structures and mineral deposit sites,thus providing high-quality visual information for geological exploration.
基金supported by the National Key Research and Development Program of China(Research Grant Number:2023YFC3603600).
文摘Autism spectrum disorder(AsD)is a highly heterogeneous neurodevelopmental disorder.Early diagnosis and intervention are crucial for improving outcomes.Traditional single-modality diagnostic methods are subjective,limited,and struggle to reveal the underlying pathological mechanisms.In contrast,multimodal data analysis integrates behavioral,physiological,and neuroimaging information with advanced machine-learning and deeplearning algorithms to overcome these limitations.In this review,we surveyed the recent pediatric AsD literature,highlighting artificial intelligence-driven diagnostic techniques,multimodal data fusion strategies,and emerging trends in ASD assessment.We surveyed studies that integrated two or more modalities and summarized the fusion levels,learning paradigms,tasks,datasets,and metrics.Multimodal approaches outperform singlemodality baselines in classification,severity estimation,and subtyping by leveraging complementary information and reducing modality-specific biases.Multimodal approaches significantly enhance diagnostic accuracy and comprehensiveness,enabling early screening of AsD,symptom subtyping,severity assessment,and personalized interventions.Advances in multimodal fusion techniques have promoted progress in precision medicine for the treatment of ASD.
基金Project supported by the National Natural Science Foundation of China(Grant No.12204132)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2021MF122)+1 种基金Shandong Province TechnologyBased SME Innovation Enhancement Project(Grant No.2024TSGC0715)the Postgraduate Education Reform Project of Shandong Province,China(Grant No.SDYJSJGC2024107)。
文摘We achieved an ultra-flat broad spectrum output with a 20-dB bandwidth of 77.85 nm in a double-clad Yb-doped fiber laser.The intensity difference between the highest and lowest points of the spectrum indicates a flatness better than4 dB.More notably,this ultra-flat broad spectrum maintains a stable single-pulse mode-locking state.With the increase of pump power,an ultra-wide spectrum with a 20-dB bandwidth approaching 100 nm was formed at a pump power of 2.25 W.Additionally,we obtained a 9-pulse mode-locked state at another PC station with the same pump,which is the highest number of stable mode-locked pulse bursts observed so far with a first-order Raman frequency shift.This fiber laser shows its benefits of ultra-flat broad spectrum,high stability,and ease of fabrication,which provides a new method of obtaining the broadband light source for multiple practical applications.
基金supported by the National Natural Science Foundation of China(No.52075244).
文摘In fatigue damage tolerance verification tests of aircraft structures,the simulation and loading of flight-byflight spectra require considerable time and resources.To improve the efficiency of load spectrum design and testing,an equivalent constant-amplitude spectrum design method for flight-by-flight spectra is proposed based on the equivalence of crack growth behavior.By combining the Paris crack growth model with the Walker stress ratio correction,the equivalent stress amplitude is directly calculated using structural parameters and load spectrum characteristics,enabling a rapid transformation from variable-amplitude spectra to constant-amplitude spectra.The original spectrum is discretized based on the load-exceedance curve,and the equivalence relationship between multilevel block spectra and constant-amplitude spectra is established.Taking a typical lower wing skin structure of a transport aircraft as an example,two equivalent spectra are designed and validated through fatigue crack growth tests on 2024-T351 center-hole plate specimens.The experimental results show that the fatigue life deviation between the equivalent spectra and the original flight-by-flight spectrum is within 10%,demonstrating the effectiveness of the proposed method.Moreover,the equivalent spectrum constructed under the condition of invariant mean flight stress exhibits higher equivalence accuracy.The influence of spectral shape on the equivalent stress amplitude is further analyzed,revealing that the equivalent stress amplitude increases with the spectrum shape coefficient.The proposed method provides a useful reference for load spectrum design in aircraft structural damage tolerance verification tests.
基金funded by the National Natural Science Foundation of China(Grant No.72504262)Natural Science Foundation of Hubei Province of China(Grant No.2024AFB102)。
文摘As demand for land resources is rapidly growing nowadays,developing on slope lands has become a way to relieve pressure on flat lands.Although some studies use the concept of slope spectrum to explore the trend of land use upslope,relying solely on the slope spectrum is too broad and prevents deeper research.Therefore,using China's land use and DEM data from 2000 to 2020,our study integrated the slope spectrum and the slope sensitivity coefficient(SSC)calculated by the land use transfer matrix as a new approach and method for understanding the underlying formations and impacts of upslope in farmland and construction land,supporting regional management strategies.The results show that:1)Farmlands were upslope in the South and developed horizontally in the North,and construction lands were upslope nationwide.2)Using the land use transfer matrix and SSC,we classified farmland upslope as passive and active patterns,and construction land upslope as saturation and avoidance patterns based on their land use transfer mechanisms in slope space.Provinces with passive and saturation patterns are mainly located near the east coast.3)Different patterns of upslope have distinct impacts on sustainable development.The passive pattern harms food security while the active pattern can relieve pressure on food security but increases ecological risks.Saturation pattern damages food security,ecological protection,and city livability,but avoidance pattern can promote food security and ecological protection.The findings will serve as an essential reference for developing land use strategies aimed at sustainable development.
基金support the findings of this study are available from the corresponding authors upon reasonable request.
文摘Vehicular Internet ofThings(V-IoT)networks need intelligent and adaptive spectrum access methods for ensuring ultra-reliable and low-latency communication(URLLC)in highly dynamic environments.Traditional reinforcement learning(RL)-based algorithms,such as Q-Learning and Double Q-Learning,are often characterized by unstable convergence and inefficient exploration in the presence of stochastic vehicular traffic and interference.This paper proposes Adaptive Reinforcement Q-learning with Upper Confidence Bound(ARQ-UCB),a lightweight and reliability-aware RL framework,which explicitly reduces interruption and blocking probabilities while improving throughput and delay across diverse vehicular traffic conditions.This proposed ARQ-UCB algorithm extends the basic Q-updates with an exploration confidence term able to dynamically balance exploration and exploitation based on uncertainty estimates,hence allowing faster convergence in case of bursty vehicular traffic.A comprehensive simulation framework evaluates throughput,delay,fairness,energy efficiency,and computational complexity in several V-IoT scenarios.Obtained results indicate that ARQ–UCB attains substantial gains in terms of throughput,fairness,and blocking/delay probabilities while retaining sub-20μs decision latency and O(1)complexity per decision,thus validating real-time feasibility for reliable spectrum access in 5G and beyond V-IoT networks.
基金National Key Scientific Instrument and Equipment Development Project under Grant No.61827801the open research fund of State Key Laboratory of Integrated Services Networks,No.ISN22-11+1 种基金Natural Science Foundation of Jiangsu Province,No.BK20211182open research fund of National Mobile Communications Research Laboratory,Southeast University,No.2022D04。
文摘Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.
基金supported by the National Natural Science Foundation of China(Grant Nos.12205097,12141501,12475117,and 12435006)the National Key Laboratory of Neutron Science and Technology(Grant No.NST202401016)+1 种基金the National Key R&D Program of China(Grant Nos.2024YFA1612600 and 2024YFE0109803)the High-performance Computing Platform of Peking University。
文摘The octupole correlations of the K^(π)=5/2^(+)ground state and the rotational spectrum built on it in^(229)Th are studied using the microscopic relativistic density functional theory on a three-dimensional lattice space and the reflection-asymmetric triaxial particle rotor model.It is found that^(229)Th has a ground state with static axial octupole and quadrupole deformations.The occurrence of octupole correlations,driven by the octupole deformation,is analyzed through the evolution of single-particle levels around the Fermi surface.The experimental energy spectrum and the electromagnetic transition probabilities,including B(E2)and B(M1),are reasonably well reproduced.
基金National Natural Science Foundation of China(Nos.61772130,71171045 and 61901104)Innovation Program of Shanghai Municipal Education Commission,China(No.14YZ130)。
文摘Vehicular communication systems rely on secure vehicle-to-vehicle(V2V)communications for safety-critical information exchange.However,the presence of eavesdropping vehicles poses a significant challenge.This paper investigates the security of V2V communications in reconfigurable intelligent surface(RIS)-assisted vehicular communication systems with spectrum sharing.It proposes a three-stage alternating optimization(TSAO)algorithm to address the complex problem of multiple eavesdropped V2V links that reuse the spectrum already occupied by vehicle-toinfrastructure(V2I)links.To solve the mixed-integer and non-convex optimization problem due to coupled variables and complex constraints,the algorithm decomposes the original problem into three easily solvable sub-problems:RIS reflection coefficient optimization,vehicle transmission power optimization,and spectrum sharing optimization.First,the RIS reflection coefficients are optimized by using the penalty convex-concave procedure(CCP)method.Second,the optimal power points are determined in the power optimization sub-problem.Finally,the spectrum sharing optimization sub-problem is constructed as a weighted bipartite graph matching problem and solved by using the optimal matching algorithm.The TSAO algorithm not only maximizes the sum V2V secrecy rate but also ensures the quality-of-service(QoS)requirements of the V2I links.Simulation results validate the superiority of the proposed algorithm and highlight the improvement in the sum V2V secrecy rate achieved by utilizing RIS technology in vehicular communication systems with spectrum sharing.
基金supported by Science Challenge Project Nos.TZ2025013,TZ2018005,and TZ2018001the National Nature Science Foundation(NSFC)of China under Grant Nos.12335015,12375238,and 12374261National Safety Academic Fund(NSAF)Grant No.U2430206.
文摘Low-density non–local-thermodynamic-equilibrium plasmas in intense radiation fields occur widely in inertial confinement fusion and astrophysics. Understanding the X-ray spectrum and the atomic kinetics of such plasmas is therefore of great importance. However, the creation of uniform-density nonequilibrium plasmas in intense radiation fields in the laboratory and the measurement of their spectra with high resolution are challenging tasks. Here, we present a new method to produce such a uniform aluminum plasma and explore photon-induced kinetics and relevant atomic physics by measuring its spectrum. It is observed that in the presence of an external radiation field, the satellites q, r and a–d of the He-α resonance line are greatly enhanced compared with the satellites j, k, l. Analysis of atomic kinetics reveals that this effect of intense radiation is due to competition between the photoexcitation and autoionization processes. With this effect taken into account,simulated spectra are able to reproduce the measured spectra quite well.
基金The study was partially supported by the General Research Fund(GRF)from the Research Grants Council(RGC)of the Hong Kong Special Administrative Region,China,No.15103522(to ST)the Internal Research Grant from the Hong Kong Polytechnic University 2021-23,No.P0035512(to ST)and P0035375(to HHLC)+1 种基金the Innovation and Technology Commission of the Hong Kong Special Administrative Region(ITC InnoHK CEVR Project)The Hong Kong Polytechnics University Research Center for Sharp Vision,No.P0039595.
文摘Neuromyelitis optica spectrum disorder-related optic neuritis involves various cellular responses to inflammation and degeneration.In most patients,the primary mechanism underlying neuromyelitis optica spectrum disorder-related optic neuritis is the interaction of aquaporin-4 antibodies with the aquaporin-4 protein present on astrocytes within posterior optic nerve.This binding subsequently initiates a cascade of events leading to secondary demyelination of the optic nerve,ultimately culminating in optic nerve degeneration.Earlier studies on this disorder primarily used systemic-induced animal models,which often require prior activation of a systemic immune response.This can result in primary demyelination of the optic nerve,complicating the interpretation of experimental results.Such methodologies hinder the ability to isolate immune responses triggered by specific antibodies.Additionally,the lack of a detailed profile of disease progression over time limits our capacity to identify potential intervention windows.Therefore,constructing a targeted optic neuritis animal model induced by specific antibodies and elucidate the disease progression arecrucial for exploring the mechanisms underlying neuromyelitis optica spectrum disorder-related optic neuritis.In this study,specific antibodies against aquaporin-4 were precisely injected into the retrobulbar optic nerve of mice to induce a targeted inflammatory response in the posterior optic nerve,resulting in a more representative mouse model of neuromyelitis optica spectrum disorder-related optic neuritis than current models.The progression of the disease was then dynamically observed from both histological and functional perspectives over the course of 1 month following the induction of inflammation.By the first week,astrocytes were damaged,as evidenced by the loss of aquaporin-4 and glial fibrillary acidic protein,the activation of microglia,and the upregulation of microglia-related cytokines,including tumor necrosis factor,interleukin-6,interleukin-1β,C-X-C motif ligand 10,and brain-derived neurotrophic factor.Starting from the second week,there were signs of optic nerve demyelination and significant damage to axonal fibers and retinal ganglion cell bodies.Visual-evoked potentials and dark adaptation threshold responses in electroretinogram both indicated dysfunction in the visual pathway and retina,while optical coherence tomography revealed thinning of the retinal nerve fiber layer in live mice.In summary,in this study we conducted a dynamic exploration of the occurrence and progression of neuromyelitis optica spectrum disorder-related optic neuritis triggered by specific antibodies.Our results show pathological changes at various stages and correlate histological and molecular alterations with in vivo structural and functional deterioration.The findings from this study lay an important foundation for further research on neuromyelitis optica spectrum disorder-related optic neuritis.
基金the King Salman center for Disability Research for funding this work through Research Group No.KSRG-2024-050.
文摘Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.
