Superior strength and high-temperature performance make γ-TiAl vital for lightweight aero-engines. However, its inherent brittleness poses machining problems. This study employed Elliptical Ultrasonic Vibration Milli...Superior strength and high-temperature performance make γ-TiAl vital for lightweight aero-engines. However, its inherent brittleness poses machining problems. This study employed Elliptical Ultrasonic Vibration Milling (EUVM) to address these problems. Considering the influence of machining parameters on vibration patterns of EUVM, a separation time model was established to analyze the vibration evolutionary process, thereby instructing the cutting mechanism. On this basis, deep discussions regarding chip formation, cutting force, edge breakage, and subsurface layer deformation were conducted for EUVM and Conventional Milling (CM). Chip morphology showed the chip formation was rooted in the periodic brittle fracture. Local dimples proved that the thermal effect of high-speed cutting improved the plasticity of γ-TiAl. EUVM achieved a maximum 18.17% reduction in cutting force compared with CM. The force variation mechanism differed with changes in the cutting speed or the vibration amplitude, and its correlation with thermal softening, strain hardening, and vibratory cutting effects was analyzed. EUVM attained desirable edge breakage by achieving smaller fracture lengths. The fracture mechanisms of different phases were distinct, causing a surge in edge fracture size of γ-TiAl under microstructural differences. In terms of subsurface deformation, EUVM also showed strengthening effects. Noteworthy, the lamellar deformation patterns under the cutting removal state differed from the quasi-static, which was categorized by the orientation angles. Additionally, the electron backscattering diffraction provided details of the influence of microstructural difference on the orientation and the deformation of grains in the subsurface layer. The results demonstrate that EUVM is a promising machining method for γ-TiAl and guide further research and development of EUVM γ-TiAl.展开更多
Quantum error-correcting codes are essential for fault-tolerant quantum computing,as they effectively detect and correct noise-induced errors by distributing information across multiple physical qubits.The subsystem s...Quantum error-correcting codes are essential for fault-tolerant quantum computing,as they effectively detect and correct noise-induced errors by distributing information across multiple physical qubits.The subsystem surface code with three-qubit check operators demonstrates significant application potential due to its simplified measurement operations and low logical error rates.However,the existing minimum-weight perfect matching(MWPM)algorithm exhibits high computational complexity and lacks flexibility in large-scale systems.Therefore,this paper proposes a decoder based on a graph attention network(GAT),representing error syndromes as undirected graphs with edge weights,and employing a multihead attention mechanism to efficiently aggregate node features and enable parallel computation.Compared to MWPM,the GAT decoder exhibits linear growth in computational complexity,adapts to different quantum code structures,and demonstrates stronger robustness under high physical error rates.The experimental results demonstrate that the proposed decoder achieves an overall accuracy of 89.95%under various small code lattice sizes(L=2,3,4,5),with the logical error rate threshold increasing to 0.0078,representing an improvement of approximately 13.04%compared to the MWPM decoder.This result significantly outperforms traditional methods,showcasing superior performance under small code lattice sizes and providing a more efficient decoding solution for large-scale quantum error correction.展开更多
In this paper,we study an Intelligent Reflecting Surface(IRS)assisted Mobile Edge Computing(MEC)system under eavesdropping threats,where the IRS is used to enhance the energy signal transmission and the offloading per...In this paper,we study an Intelligent Reflecting Surface(IRS)assisted Mobile Edge Computing(MEC)system under eavesdropping threats,where the IRS is used to enhance the energy signal transmission and the offloading performance between Wireless Devices(WDs)and the Access Point(AP).Specifically,in the proposed scheme,the AP first powers all WDs with the wireless power transfer through both direct and IRS-assisted links.Then,powered by the harvested energy,all WDs securely offload their computation tasks through the two links in the time division multiple access mode.To determine the local and offloading computational bits,we formulate an optimization problem to jointly design the IRS's phase shift and allocate the time slots constrained by the security and energy requirements.To cope with this non-convex optimization problem,we adopt semidefinite relaxations,singular value decomposition techniques,and Lagrange dual method.Moreover,we propose a dichotomy particle swarm algorithm based on the bisection method to process the overall optimization problem and improve the convergence speed.The numerical results illustrate that the proposed scheme can boost the performance of MEC and secure computation rates compared with other IRS-assisted MEC benchmark schemes.展开更多
The self-driven behavior of droplets on a functionalized surface,coupled with wetting gradient and wedge patterns,is systematically investigated using molecular dynamics(MD)simulations.The effects of key factors,inclu...The self-driven behavior of droplets on a functionalized surface,coupled with wetting gradient and wedge patterns,is systematically investigated using molecular dynamics(MD)simulations.The effects of key factors,including wedge angle,wettability,and wetting gradient,on the droplet self-driving effect is revealed from the nanoscale.Results indicate that the maximum velocity of droplets on hydrophobic wedge-shaped surfaces increases with the wedge angle,accompanied by a rapid attenuation of driving force;however,the average velocity decreases with the increased wedge angle.Conversely,droplet movement on hydrophilic wedge-shaped surfaces follows the opposite trend,particularly in terms of average velocity compared to the hydrophobic case.Both wedge-shaped and composite gradient wedge-shaped surfaces are found to induce droplet motion,with droplets exhibiting higher speeds and distances on hydrophobic surfaces compared to hydrophilic surfaces,regardless of surface type.Importantly,the inclusion of wettability gradients significantly influences droplet motion,with hydrophobic composite gradient wedge-shaped surfaces showing considerable improvements in droplet speed and distance compared to their hydrophilic counterparts.By combining suitable wettability gradients with wedge-shaped surfaces,the limitations inherent in the wettability gradient range and wedge-shaped configuration can be mitigated,thereby enhancing droplet speed and distance.The findings presented in this paper offer valuable insights for the design of advanced functional surfaces tailored for manipulating droplets in real-world applications.展开更多
Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in us...Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user experience.In this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their priority.Subsequently,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN framework.Next,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of sub-tasks.Simulation results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.展开更多
A surface edge element method is proposed and implemented in the study ofelectromagnetic scattering fields of general targets. The basis functions for surfaces of arbitraryshape are derived according to the geometrica...A surface edge element method is proposed and implemented in the study ofelectromagnetic scattering fields of general targets. The basis functions for surfaces of arbitraryshape are derived according to the geometrical properties of each triangular patch. The proposedbasis functions are 3-D linear functions and the tangential components of the vectors are continuousas the traditional edge element method. Combined field integral equations (CFIE) that include bothelectrical field and magnetic field integral equations are used to model the electromagneticscattering of general dielectric targets. Special treatment for singularity is presented to enhancethe quality of numerical solutions. The proposed method is used to compute the scattering fieldsfrom various targets. Numerical results obtained by the proposed method are validated by resultsfrom other numerical methods.展开更多
As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by...As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.展开更多
In this work,the influences of surface layer slurry at different temperatures(10℃,14℃,18℃,22℃)on wax patterns deformation,shrinkage,slurry coating characteristics,and the surface quality of the casting were invest...In this work,the influences of surface layer slurry at different temperatures(10℃,14℃,18℃,22℃)on wax patterns deformation,shrinkage,slurry coating characteristics,and the surface quality of the casting were investigated by using a single factor variable method.The surface morphologies of the shell molds produced by different temperatures of the surface(first)layer slurries were observed via electron microscopy.Furthermore,the microscopic composition of these shell molds was obtained by EDS,and the osmotic effect of the slurry on the wax patterns at different temperatures was also assessed by the PZ-200 Contact Angle detector.The forming reasons for the surface cracks and holes of thick and large ZTC4 titanium alloy by investment casting were analyzed.The experimental results show that the surface of the shell molds prepared by the surface layer slurry with a low temperature exhibits noticeable damage,which is mainly due to the poor coating performance and the serious expansion and contraction of wax pattern at low temperatures.The second layer shell material(SiO_(2),Al_(2)O_(3))immerses into the crack area of the surface layer,contacts and reacts with the molten titanium to form surface cracks and holes in the castings.With the increase of the temperature of surface layer slurry,the damage to the shell surface tends to weaken,and the composition of the shell molds'surface becomes more uniform with less impurities.The results show that the surface layer slurry at 22℃is evenly coated on the surface of the wax patterns with appropriate thickness,and there is no surface shell mold rupture caused by sliding slurry after sand leaching.The surface layer slurry temperature is consistent with the wax pattern temperature and the workshop temperature,so there is no damage of the surface layer shell caused by expansion and contraction.Therefore,the shell mold prepared by the surface layer slurry at this temperature has good integrity,isolating the contact between the low inert shell material and the titanium liquid effectively,and the ZTC4 titanium alloy cylinder casting prepared by this shell mold is smooth,without cracks and holes.展开更多
As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the...As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective optimization problem aimed at minimizing both delay and energy consumption. We model the task offloading strategy using a directed acyclic graph (DAG). Furthermore, we propose a distributed edge computing adaptive task offloading algorithm rooted in MRL. This algorithm integrates multiple Markov decision processes (MDP) with a sequence-to-sequence (seq2seq) network, enabling it to learn and adapt task offloading strategies responsively across diverse network environments. To achieve joint optimization of delay and energy consumption, we incorporate the non-dominated sorting genetic algorithm II (NSGA-II) into our framework. Simulation results demonstrate the superiority of our proposed solution, achieving a 21% reduction in time delay and a 19% decrease in energy consumption compared to alternative task offloading schemes. Moreover, our scheme exhibits remarkable adaptability, responding swiftly to changes in various network environments.展开更多
The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language proc...The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.展开更多
Herein,the surface of Moso bamboo was hydrophobically modified by combining O_(2)/N_(2)plasma treatments with polydimethylsiloxane(PDMS)solution treatment as the hydrophobic solution.The effects of plasma treatment pr...Herein,the surface of Moso bamboo was hydrophobically modified by combining O_(2)/N_(2)plasma treatments with polydimethylsiloxane(PDMS)solution treatment as the hydrophobic solution.The effects of plasma treatment process(power and time),PDMS solution concentration,and maceration time on the hydrophobic performance of bamboo specimens were studied,and the optimal treatment conditions for improving the hydrophobicity were determined.Scanning electron microscopy(SEM),fourier transform infrared(FTIR),X-ray diffraction(XRD),and X-ray photoelectron spectroscopy(XPS)were used to analyze the surface morphology,chemical structure,and functional groups in the specimens before and after the plasma and PDMS solution treatments under optimal conditions.Response surface analysis was also performed to determine the optimal treatment conditions.Results show that the hydrophobic performance of the Moso bamboo surface is effectively improved and the surface energy is reduced after the coordinated treatment.The optimal conditions for improving the hydrophobic performance of Moso bamboo surface are a treatment power of 800 W,treatment time of 15 s,O_(2)flow rate of 1.5 L/min,PDMS solution concentration of 5%,and maceration time of 60 min for O_(2)plasma treatment and a treatment power of 1000 W,treatment time of 15 s,N_(2)flow rate of 1.5 L/min,PDMS solution concentration of 5%,and maceration time of 60 min for N_(2)plasma treatment.After treatment,silicone oil particles and plasma etching traces are observed on the bamboo surface.Moreover,Si-O bonds in the PDMS solution are grafted to the bamboo surface via covalent bonds,thereby increasing the contact angle and decreasing the surface energy to achieve the hydrophobic effect.展开更多
Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power sta...Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power stations).To solve the problem,we propose an energy harvesting based task scheduling and resource management framework to provide robust and low-cost edge computing services for smart grid.First,we formulate an energy consumption minimization problem with regard to task offloading,time switching,and resource allocation for mobile devices,which can be decoupled and transformed into a typical knapsack problem.Then,solutions are derived by two different algorithms.Furthermore,we deploy renewable energy and energy storage units at edge servers to tackle intermittency and instability problems.Finally,we design an energy management algorithm based on sampling average approximation for edge computing servers to derive the optimal charging/discharging strategies,number of energy storage units,and renewable energy utilization.The simulation results show the efficiency and superiority of our proposed framework.展开更多
As one of the lightest engineering materials,magnesium(Mg)alloy possesses excellent mechanical performance,meeting the needs of versatile engineering fields and holding the potential to address cutting-edge issues in ...As one of the lightest engineering materials,magnesium(Mg)alloy possesses excellent mechanical performance,meeting the needs of versatile engineering fields and holding the potential to address cutting-edge issues in aerospace,electronics,biomedicine.The design of superhydrophobic(SHB)surfaces with micro and nanostructures can endow Mg alloys with multiple functionalities,such as self-cleaning,self-healing,antibacterial,and corrosion resistance.Over the past decade,researchers have drawn inspiration from nature to implement biomimetic design principles,resulting in the rapid development of micro/nanostructured SHB surfaces on Mg alloys,which hold great promise for biomedical applications.This review comprehensively introduces the biomimetic design principles of micro/nanostructured SHB surfaces on Mg alloys,discusses the challenges along with advantages and disadvantages of current preparation methods,and explores the future perspectives for preparing these SHB surfaces,providing strategies to enhance their performance in biomedical applications.展开更多
In recent decades,capacitive pressure sensors(CPSs)with high sensitivity have demonstrated significant potential in applications such as medical monitoring,artificial intelligence,and soft robotics.Efforts to enhance ...In recent decades,capacitive pressure sensors(CPSs)with high sensitivity have demonstrated significant potential in applications such as medical monitoring,artificial intelligence,and soft robotics.Efforts to enhance this sensitivity have predominantly focused on material design and structural optimization,with surface microstructures such as wrinkles,pyramids,and micro-pillars proving effective.Although finite element modeling(FEM)has guided enhancements in CPS sensitivity across various surface designs,a theoretical understanding of sensitivity improvements remains underexplored.This paper employs sinusoidal wavy surfaces as a representative model to analytically elucidate the underlying mechanisms of sensitivity enhancement through contact mechanics.These theoretical insights are corroborated by FEM and experimental validations.Our findings underscore that optimizing material properties,such as Young’s modulus and relative permittivity,alongside adjustments in surface roughness and substrate thickness,can significantly elevate the sensitivity.The optimal performance is achieved when the amplitude-to-wavelength ratio(H/)is about 0.2.These results offer critical insights for designing ultrasensitive CPS devices,paving the way for advancements in sensor technology.展开更多
Magnesium(Mg)-based bioresorbable stents represent a potentially groundbreaking advancement in cardiovascular therapy;offering tem-porary vessel support and complete biodegradability—addressing limitations of traditi...Magnesium(Mg)-based bioresorbable stents represent a potentially groundbreaking advancement in cardiovascular therapy;offering tem-porary vessel support and complete biodegradability—addressing limitations of traditional stents like in-stent restenosis and long-term com-plications.However,challenges such as rapid corrosion and suboptimal endothelialisation have hindered their clinical adoption.This review highlights the latest breakthroughs in surface modification,alloying,and coating strategies to enhance the mechanical integrity,corrosion resistance,and biocompatibility of Mg-based stents.Key surface engineering techniques,including polymer and bioactive coatings,are ex-amined for their role in promoting endothelial healing and minimising inflammatory responses.Future directions are proposed,focusing on personalised stent designs to optimize efficacy and long-term outcomes,positioning Mg-based stents as a transformative solution in interventional cardiology.展开更多
Emerging contaminants(ECs)have raised global concern due to their adverse effect on ecosystems and human health.However,the occurrence and transport of ECs in stormwater remain unclear.The impact of ECs from stormwate...Emerging contaminants(ECs)have raised global concern due to their adverse effect on ecosystems and human health.However,the occurrence and transport of ECs in stormwater remain unclear.The impact of ECs from stormwater on surface water quality and ecosystem health is also poorly documented.In this review,we examined the variations in EC concentrations in surface water resulting from stormwater.During the wet weather,the concentrations of most investigated ECs,e.g.,microplastics,per-and polyfluoroalkyl substances,and vehicle-related compounds,significantly increase in surface water,indicating that stormwater may be a critical source of these contaminants.Furthermore,the potential pathways of ECs from stormwater enter surface water are outlined.Studies demonstrate that surface runoff and combined sewer overflows are important pathways for ECs,with discharges comparable to or exceeding those from wastewater treatment plants.Illicit connection also plays an important part in elevated EC concentrations in surface water.Overall,our findings underscore the importance of stormwater as a source for ECs in surface waters,and urge for increased emphasis on,and reinforcement of,stormwater monitoring and control measures to minimize the transport of ECs into receiving water bodies.展开更多
The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle o...The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle on the fracture surface roughness plays an important role in estimating the damage degree and stability of deep rock mass.In this paper,the variations of fracture surface roughness of granite after different heating and thermal cycles were investigated using the joint roughness coefficient method(JRC),three-dimensional(3D)roughness parameters,and fractal dimension(D),and the mechanism of damage and deterioration of granite were revealed.The experimental results show an increase in the roughness of the granite fracture surface as temperature and cycle number were incremented.The variations of JRC,height parameter,inclination parameter and area parameter with the temperature conformed to the Boltzmann's functional distribution,while the D decreased linearly as the temperature increased.Besides,the anisotropy index(Ip)of the granite fracture surface increased as the temperature increased,and the larger parameter values of roughness characterization at different temperatures were attained mainly in directions of 20°–40°,60°–100°and 140°–160°.The fracture aperture of granite after fracture followed the Gauss distribution and the average aperture increased with increasing temperature,which increased from 0.665 mm at 25℃to 1.058 mm at 800℃.High temperature caused an uneven thermal expansion,water evaporation,and oxidation of minerals within the granite,which promoted the growth and expansion of microfractures,and reduced interparticle bonding strength.In particular,the damage was exacerbated by the expansion and cracking of the quartz phase transition after T>500℃.Thermal cycles contributed to the accumulation of this damage and further weakened the interparticle bonding forces,resulting in a significant increase in the roughness,anisotropy,and aperture of the fracture surface after five cycles.展开更多
Rod-airfoil interaction noise becomes a major issue in some aeronautical applications.The design of four wavy leading edges(WLEs)with varying wavelengths,bioinspired by the tubercles on humpback whales’flippers,aims ...Rod-airfoil interaction noise becomes a major issue in some aeronautical applications.The design of four wavy leading edges(WLEs)with varying wavelengths,bioinspired by the tubercles on humpback whales’flippers,aims to mitigate far-field noise.Among these cases,a reduction in the wavelength is found to be advantageous for noise suppression,with the smallest wavelength case achieving a maximum noise reduction of 1.9 dB.Furthermore,the noise radiation induced by WLEs is suppressed mainly at medium frequencies.The theory of multiprocess aeroacoustics is applied to reveal their underlying mechanisms.The dominant factor is the source cutoff effect,which significantly decreases the source strength on hills.Additionally,spanwise decoherence with phase interference serves as another crucial mechanism,particularly for reducing mid-frequency noise.展开更多
基金co-supported by the Science Center for Gas Turbine Project, China(No. P2022-AB-IV-001-002)the National Natural Science Foundation of China (No. 91960203)+1 种基金the Fundamental Research Funds for the Central Universities (No. D5000230048)the Innovation Capability Support Program of Shaanxi (No. 2022TD-60)
文摘Superior strength and high-temperature performance make γ-TiAl vital for lightweight aero-engines. However, its inherent brittleness poses machining problems. This study employed Elliptical Ultrasonic Vibration Milling (EUVM) to address these problems. Considering the influence of machining parameters on vibration patterns of EUVM, a separation time model was established to analyze the vibration evolutionary process, thereby instructing the cutting mechanism. On this basis, deep discussions regarding chip formation, cutting force, edge breakage, and subsurface layer deformation were conducted for EUVM and Conventional Milling (CM). Chip morphology showed the chip formation was rooted in the periodic brittle fracture. Local dimples proved that the thermal effect of high-speed cutting improved the plasticity of γ-TiAl. EUVM achieved a maximum 18.17% reduction in cutting force compared with CM. The force variation mechanism differed with changes in the cutting speed or the vibration amplitude, and its correlation with thermal softening, strain hardening, and vibratory cutting effects was analyzed. EUVM attained desirable edge breakage by achieving smaller fracture lengths. The fracture mechanisms of different phases were distinct, causing a surge in edge fracture size of γ-TiAl under microstructural differences. In terms of subsurface deformation, EUVM also showed strengthening effects. Noteworthy, the lamellar deformation patterns under the cutting removal state differed from the quasi-static, which was categorized by the orientation angles. Additionally, the electron backscattering diffraction provided details of the influence of microstructural difference on the orientation and the deformation of grains in the subsurface layer. The results demonstrate that EUVM is a promising machining method for γ-TiAl and guide further research and development of EUVM γ-TiAl.
基金Project supported by the Natural Science Foundation of Shandong Province,China(Grant No.ZR2021MF049)the Joint Fund of the Natural Science Foundation of Shandong Province,China(Grant Nos.ZR2022LLZ012 and ZR2021LLZ001)the Key Research and Development Program of Shandong Province,China(Grant No.2023CXGC010901)。
文摘Quantum error-correcting codes are essential for fault-tolerant quantum computing,as they effectively detect and correct noise-induced errors by distributing information across multiple physical qubits.The subsystem surface code with three-qubit check operators demonstrates significant application potential due to its simplified measurement operations and low logical error rates.However,the existing minimum-weight perfect matching(MWPM)algorithm exhibits high computational complexity and lacks flexibility in large-scale systems.Therefore,this paper proposes a decoder based on a graph attention network(GAT),representing error syndromes as undirected graphs with edge weights,and employing a multihead attention mechanism to efficiently aggregate node features and enable parallel computation.Compared to MWPM,the GAT decoder exhibits linear growth in computational complexity,adapts to different quantum code structures,and demonstrates stronger robustness under high physical error rates.The experimental results demonstrate that the proposed decoder achieves an overall accuracy of 89.95%under various small code lattice sizes(L=2,3,4,5),with the logical error rate threshold increasing to 0.0078,representing an improvement of approximately 13.04%compared to the MWPM decoder.This result significantly outperforms traditional methods,showcasing superior performance under small code lattice sizes and providing a more efficient decoding solution for large-scale quantum error correction.
基金supported in part by the National Natural Science Foundation of China under Grant 62271399 and 62206221in part by the Key Research and Development Program of Shaanxi Province under Grant 2022KW-07+1 种基金in part by National Key Research and Development Program of China under Grant 2020YFB1807003in part by the Shanghai Sailing Program under Grant 20YF1416700。
文摘In this paper,we study an Intelligent Reflecting Surface(IRS)assisted Mobile Edge Computing(MEC)system under eavesdropping threats,where the IRS is used to enhance the energy signal transmission and the offloading performance between Wireless Devices(WDs)and the Access Point(AP).Specifically,in the proposed scheme,the AP first powers all WDs with the wireless power transfer through both direct and IRS-assisted links.Then,powered by the harvested energy,all WDs securely offload their computation tasks through the two links in the time division multiple access mode.To determine the local and offloading computational bits,we formulate an optimization problem to jointly design the IRS's phase shift and allocate the time slots constrained by the security and energy requirements.To cope with this non-convex optimization problem,we adopt semidefinite relaxations,singular value decomposition techniques,and Lagrange dual method.Moreover,we propose a dichotomy particle swarm algorithm based on the bisection method to process the overall optimization problem and improve the convergence speed.The numerical results illustrate that the proposed scheme can boost the performance of MEC and secure computation rates compared with other IRS-assisted MEC benchmark schemes.
基金supported by the National Natural Science Foundation of China(No.52206073)the University Outstanding Youth Fund Project of Anhui Province(Nos.2022AH020028 and 2022AH030037)+2 种基金the Natural Science Foundation of Anhui Province(Nos.1908085QF292 and 2308085ME173)Anhui Province Outstanding Young Talents Support Program(No.gxyqZD2022058)Guangdong Basic and Applied Basic Research Foundation(Nos.2024A1515011379 and 2023A1515110613).
文摘The self-driven behavior of droplets on a functionalized surface,coupled with wetting gradient and wedge patterns,is systematically investigated using molecular dynamics(MD)simulations.The effects of key factors,including wedge angle,wettability,and wetting gradient,on the droplet self-driving effect is revealed from the nanoscale.Results indicate that the maximum velocity of droplets on hydrophobic wedge-shaped surfaces increases with the wedge angle,accompanied by a rapid attenuation of driving force;however,the average velocity decreases with the increased wedge angle.Conversely,droplet movement on hydrophilic wedge-shaped surfaces follows the opposite trend,particularly in terms of average velocity compared to the hydrophobic case.Both wedge-shaped and composite gradient wedge-shaped surfaces are found to induce droplet motion,with droplets exhibiting higher speeds and distances on hydrophobic surfaces compared to hydrophilic surfaces,regardless of surface type.Importantly,the inclusion of wettability gradients significantly influences droplet motion,with hydrophobic composite gradient wedge-shaped surfaces showing considerable improvements in droplet speed and distance compared to their hydrophilic counterparts.By combining suitable wettability gradients with wedge-shaped surfaces,the limitations inherent in the wettability gradient range and wedge-shaped configuration can be mitigated,thereby enhancing droplet speed and distance.The findings presented in this paper offer valuable insights for the design of advanced functional surfaces tailored for manipulating droplets in real-world applications.
文摘Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user experience.In this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their priority.Subsequently,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN framework.Next,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of sub-tasks.Simulation results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.
文摘A surface edge element method is proposed and implemented in the study ofelectromagnetic scattering fields of general targets. The basis functions for surfaces of arbitraryshape are derived according to the geometrical properties of each triangular patch. The proposedbasis functions are 3-D linear functions and the tangential components of the vectors are continuousas the traditional edge element method. Combined field integral equations (CFIE) that include bothelectrical field and magnetic field integral equations are used to model the electromagneticscattering of general dielectric targets. Special treatment for singularity is presented to enhancethe quality of numerical solutions. The proposed method is used to compute the scattering fieldsfrom various targets. Numerical results obtained by the proposed method are validated by resultsfrom other numerical methods.
文摘As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.
文摘In this work,the influences of surface layer slurry at different temperatures(10℃,14℃,18℃,22℃)on wax patterns deformation,shrinkage,slurry coating characteristics,and the surface quality of the casting were investigated by using a single factor variable method.The surface morphologies of the shell molds produced by different temperatures of the surface(first)layer slurries were observed via electron microscopy.Furthermore,the microscopic composition of these shell molds was obtained by EDS,and the osmotic effect of the slurry on the wax patterns at different temperatures was also assessed by the PZ-200 Contact Angle detector.The forming reasons for the surface cracks and holes of thick and large ZTC4 titanium alloy by investment casting were analyzed.The experimental results show that the surface of the shell molds prepared by the surface layer slurry with a low temperature exhibits noticeable damage,which is mainly due to the poor coating performance and the serious expansion and contraction of wax pattern at low temperatures.The second layer shell material(SiO_(2),Al_(2)O_(3))immerses into the crack area of the surface layer,contacts and reacts with the molten titanium to form surface cracks and holes in the castings.With the increase of the temperature of surface layer slurry,the damage to the shell surface tends to weaken,and the composition of the shell molds'surface becomes more uniform with less impurities.The results show that the surface layer slurry at 22℃is evenly coated on the surface of the wax patterns with appropriate thickness,and there is no surface shell mold rupture caused by sliding slurry after sand leaching.The surface layer slurry temperature is consistent with the wax pattern temperature and the workshop temperature,so there is no damage of the surface layer shell caused by expansion and contraction.Therefore,the shell mold prepared by the surface layer slurry at this temperature has good integrity,isolating the contact between the low inert shell material and the titanium liquid effectively,and the ZTC4 titanium alloy cylinder casting prepared by this shell mold is smooth,without cracks and holes.
基金funded by the Fundamental Research Funds for the Central Universities(J2023-024,J2023-027).
文摘As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective optimization problem aimed at minimizing both delay and energy consumption. We model the task offloading strategy using a directed acyclic graph (DAG). Furthermore, we propose a distributed edge computing adaptive task offloading algorithm rooted in MRL. This algorithm integrates multiple Markov decision processes (MDP) with a sequence-to-sequence (seq2seq) network, enabling it to learn and adapt task offloading strategies responsively across diverse network environments. To achieve joint optimization of delay and energy consumption, we incorporate the non-dominated sorting genetic algorithm II (NSGA-II) into our framework. Simulation results demonstrate the superiority of our proposed solution, achieving a 21% reduction in time delay and a 19% decrease in energy consumption compared to alternative task offloading schemes. Moreover, our scheme exhibits remarkable adaptability, responding swiftly to changes in various network environments.
基金the National Research Foundation(NRF)Singapore mid-sized center grant(NRF-MSG-2023-0002)FrontierCRP grant(NRF-F-CRP-2024-0006)+2 种基金A*STAR Singapore MTC RIE2025 project(M24W1NS005)IAF-PP project(M23M5a0069)Ministry of Education(MOE)Singapore Tier 2 project(MOE-T2EP50220-0014).
文摘The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.
基金Zhejiang Provincial Cooperative Forestry Science and Technology Project(No.2023SY05)Zhejiang Provincial Science and Technology Project(No.2024F1065-2).
文摘Herein,the surface of Moso bamboo was hydrophobically modified by combining O_(2)/N_(2)plasma treatments with polydimethylsiloxane(PDMS)solution treatment as the hydrophobic solution.The effects of plasma treatment process(power and time),PDMS solution concentration,and maceration time on the hydrophobic performance of bamboo specimens were studied,and the optimal treatment conditions for improving the hydrophobicity were determined.Scanning electron microscopy(SEM),fourier transform infrared(FTIR),X-ray diffraction(XRD),and X-ray photoelectron spectroscopy(XPS)were used to analyze the surface morphology,chemical structure,and functional groups in the specimens before and after the plasma and PDMS solution treatments under optimal conditions.Response surface analysis was also performed to determine the optimal treatment conditions.Results show that the hydrophobic performance of the Moso bamboo surface is effectively improved and the surface energy is reduced after the coordinated treatment.The optimal conditions for improving the hydrophobic performance of Moso bamboo surface are a treatment power of 800 W,treatment time of 15 s,O_(2)flow rate of 1.5 L/min,PDMS solution concentration of 5%,and maceration time of 60 min for O_(2)plasma treatment and a treatment power of 1000 W,treatment time of 15 s,N_(2)flow rate of 1.5 L/min,PDMS solution concentration of 5%,and maceration time of 60 min for N_(2)plasma treatment.After treatment,silicone oil particles and plasma etching traces are observed on the bamboo surface.Moreover,Si-O bonds in the PDMS solution are grafted to the bamboo surface via covalent bonds,thereby increasing the contact angle and decreasing the surface energy to achieve the hydrophobic effect.
基金supported in part by the National Natural Science Foundation of China under Grant No.61473066in part by the Natural Science Foundation of Hebei Province under Grant No.F2021501020+2 种基金in part by the S&T Program of Qinhuangdao under Grant No.202401A195in part by the Science Research Project of Hebei Education Department under Grant No.QN2025008in part by the Innovation Capability Improvement Plan Project of Hebei Province under Grant No.22567637H
文摘Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power stations).To solve the problem,we propose an energy harvesting based task scheduling and resource management framework to provide robust and low-cost edge computing services for smart grid.First,we formulate an energy consumption minimization problem with regard to task offloading,time switching,and resource allocation for mobile devices,which can be decoupled and transformed into a typical knapsack problem.Then,solutions are derived by two different algorithms.Furthermore,we deploy renewable energy and energy storage units at edge servers to tackle intermittency and instability problems.Finally,we design an energy management algorithm based on sampling average approximation for edge computing servers to derive the optimal charging/discharging strategies,number of energy storage units,and renewable energy utilization.The simulation results show the efficiency and superiority of our proposed framework.
基金supported by the National Natural Science Found for Distinguished Young Scholars(52225101)the Fundamental Research Funds for the Central Universities(WUT:104972024RSCbs0018 and 2023CDJYXTD-002)+1 种基金the Natural Science Foundation of Chongqing(CSTB2023NSCQ-MSX0527)the Chongqing Academician Special Fund(2022YSZXJCX0014CSTB).
文摘As one of the lightest engineering materials,magnesium(Mg)alloy possesses excellent mechanical performance,meeting the needs of versatile engineering fields and holding the potential to address cutting-edge issues in aerospace,electronics,biomedicine.The design of superhydrophobic(SHB)surfaces with micro and nanostructures can endow Mg alloys with multiple functionalities,such as self-cleaning,self-healing,antibacterial,and corrosion resistance.Over the past decade,researchers have drawn inspiration from nature to implement biomimetic design principles,resulting in the rapid development of micro/nanostructured SHB surfaces on Mg alloys,which hold great promise for biomedical applications.This review comprehensively introduces the biomimetic design principles of micro/nanostructured SHB surfaces on Mg alloys,discusses the challenges along with advantages and disadvantages of current preparation methods,and explores the future perspectives for preparing these SHB surfaces,providing strategies to enhance their performance in biomedical applications.
基金supported by the National Natural Science Foundation of China(Grant No.12272369)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0620101).
文摘In recent decades,capacitive pressure sensors(CPSs)with high sensitivity have demonstrated significant potential in applications such as medical monitoring,artificial intelligence,and soft robotics.Efforts to enhance this sensitivity have predominantly focused on material design and structural optimization,with surface microstructures such as wrinkles,pyramids,and micro-pillars proving effective.Although finite element modeling(FEM)has guided enhancements in CPS sensitivity across various surface designs,a theoretical understanding of sensitivity improvements remains underexplored.This paper employs sinusoidal wavy surfaces as a representative model to analytically elucidate the underlying mechanisms of sensitivity enhancement through contact mechanics.These theoretical insights are corroborated by FEM and experimental validations.Our findings underscore that optimizing material properties,such as Young’s modulus and relative permittivity,alongside adjustments in surface roughness and substrate thickness,can significantly elevate the sensitivity.The optimal performance is achieved when the amplitude-to-wavelength ratio(H/)is about 0.2.These results offer critical insights for designing ultrasensitive CPS devices,paving the way for advancements in sensor technology.
文摘Magnesium(Mg)-based bioresorbable stents represent a potentially groundbreaking advancement in cardiovascular therapy;offering tem-porary vessel support and complete biodegradability—addressing limitations of traditional stents like in-stent restenosis and long-term com-plications.However,challenges such as rapid corrosion and suboptimal endothelialisation have hindered their clinical adoption.This review highlights the latest breakthroughs in surface modification,alloying,and coating strategies to enhance the mechanical integrity,corrosion resistance,and biocompatibility of Mg-based stents.Key surface engineering techniques,including polymer and bioactive coatings,are ex-amined for their role in promoting endothelial healing and minimising inflammatory responses.Future directions are proposed,focusing on personalised stent designs to optimize efficacy and long-term outcomes,positioning Mg-based stents as a transformative solution in interventional cardiology.
基金supported by the National Natural Science Foundation of China(Nos.52325001 and 52170009)the National Key Research and Development Program of China(No.2021YFC3200700)the Programof Shanghai Academic Research Leader,China(No.21XD1424000).
文摘Emerging contaminants(ECs)have raised global concern due to their adverse effect on ecosystems and human health.However,the occurrence and transport of ECs in stormwater remain unclear.The impact of ECs from stormwater on surface water quality and ecosystem health is also poorly documented.In this review,we examined the variations in EC concentrations in surface water resulting from stormwater.During the wet weather,the concentrations of most investigated ECs,e.g.,microplastics,per-and polyfluoroalkyl substances,and vehicle-related compounds,significantly increase in surface water,indicating that stormwater may be a critical source of these contaminants.Furthermore,the potential pathways of ECs from stormwater enter surface water are outlined.Studies demonstrate that surface runoff and combined sewer overflows are important pathways for ECs,with discharges comparable to or exceeding those from wastewater treatment plants.Illicit connection also plays an important part in elevated EC concentrations in surface water.Overall,our findings underscore the importance of stormwater as a source for ECs in surface waters,and urge for increased emphasis on,and reinforcement of,stormwater monitoring and control measures to minimize the transport of ECs into receiving water bodies.
基金funding support from the National Natural Science Foundation of China(Grant No.52274082)the Program of Qingjiang Excellent Young Talents,Jiangxi University of Science and Technology(Grant No.JXUSTQJBJ2020003)the Innovation Fund Designated for Graduate Students of Jiangxi Province(Grant No.YC2023-B215).
文摘The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle on the fracture surface roughness plays an important role in estimating the damage degree and stability of deep rock mass.In this paper,the variations of fracture surface roughness of granite after different heating and thermal cycles were investigated using the joint roughness coefficient method(JRC),three-dimensional(3D)roughness parameters,and fractal dimension(D),and the mechanism of damage and deterioration of granite were revealed.The experimental results show an increase in the roughness of the granite fracture surface as temperature and cycle number were incremented.The variations of JRC,height parameter,inclination parameter and area parameter with the temperature conformed to the Boltzmann's functional distribution,while the D decreased linearly as the temperature increased.Besides,the anisotropy index(Ip)of the granite fracture surface increased as the temperature increased,and the larger parameter values of roughness characterization at different temperatures were attained mainly in directions of 20°–40°,60°–100°and 140°–160°.The fracture aperture of granite after fracture followed the Gauss distribution and the average aperture increased with increasing temperature,which increased from 0.665 mm at 25℃to 1.058 mm at 800℃.High temperature caused an uneven thermal expansion,water evaporation,and oxidation of minerals within the granite,which promoted the growth and expansion of microfractures,and reduced interparticle bonding strength.In particular,the damage was exacerbated by the expansion and cracking of the quartz phase transition after T>500℃.Thermal cycles contributed to the accumulation of this damage and further weakened the interparticle bonding forces,resulting in a significant increase in the roughness,anisotropy,and aperture of the fracture surface after five cycles.
基金supported by the National Natural Science Foundation of China(12322210,12172351,92252202,and 12388101)the Fundamental Research Funds for the Central Universities.
文摘Rod-airfoil interaction noise becomes a major issue in some aeronautical applications.The design of four wavy leading edges(WLEs)with varying wavelengths,bioinspired by the tubercles on humpback whales’flippers,aims to mitigate far-field noise.Among these cases,a reduction in the wavelength is found to be advantageous for noise suppression,with the smallest wavelength case achieving a maximum noise reduction of 1.9 dB.Furthermore,the noise radiation induced by WLEs is suppressed mainly at medium frequencies.The theory of multiprocess aeroacoustics is applied to reveal their underlying mechanisms.The dominant factor is the source cutoff effect,which significantly decreases the source strength on hills.Additionally,spanwise decoherence with phase interference serves as another crucial mechanism,particularly for reducing mid-frequency noise.
