The effect of the volume fraction of 3D-metal matrix composites(MMC)framework on the compressive properties of 3D interpenetrating hierarchical ZrO_(2)-toughened Al_(2)O_(3)particle(ZTAp)/40Cr steel composites was inv...The effect of the volume fraction of 3D-metal matrix composites(MMC)framework on the compressive properties of 3D interpenetrating hierarchical ZrO_(2)-toughened Al_(2)O_(3)particle(ZTAp)/40Cr steel composites was investigated.The results showed that the compressive properties of the material tended to decrease as the volume fraction of 3D-MMC framework increased.The composite with 35 vol.%3D-MMC had a yield strength of 1455.2 MPa and compressive strength of 1612.8 MPa,which occurred at a strain value of 5.6%.Compared to the homogeneously dispersed composite material,the composite with 35 vol.%3D-MMC had a 144.7%higher yield strength,which occurred at a 20%higher strain.An analysis of the cracks inside the material revealed that the crack was hindered and deflected by the matrix during propagation,which lengthened the crack propagation path and consumed more energy,thus leading to toughening.The results indicated that 3D interpenetrating hierarchical structure had a strengthening and toughening effect on ZTAp/40Cr composites.展开更多
Three-dimensional(3D)functional graphenebased architecture with superior electrical conductivity and good mechanical strength has promising applications in energy storage and electrics.Viscoelasticity-adjustable inks ...Three-dimensional(3D)functional graphenebased architecture with superior electrical conductivity and good mechanical strength has promising applications in energy storage and electrics.Viscoelasticity-adjustable inks make it possible to achieve desired 3D architectures with interconnected and continuous interior networks by microextrusion printing.In this work,ultra-low-concentration graphene oxide(GO)inks of~15 mg·ml-1 have been obtained and demonstrated in direct 3D printing with a facile cross-linking(direct ink writing).The rheological behavior of the GO strategy by cations,which is the lowest concentration to achieve direct ink writing inks,could be adjusted from 1×10^(4) to 1×10^(5) Pa·s^(-1) with different concentrations of cations due to strong cross-linking networks between GO sheets and cations.Meanwhile,the specific strength and electrical conductivity of 3D-printed graphene architecture are notably enhanced,reaching up to 51.7×10^(3) N·m·kg^(-1)and 119 S·m^(-1),which are superior to conventional graphene aerogels.Furthermore,3D printing graphene-based architecture assembled in micro-superc apacitor exhibits excellent electrochemical performance,which can be ascribed to the effective ion transportation through the interconnected networks.The strategy demonstrated is useful in the design of complex-shaped,graphene-based architectures for scalable manufacturing of practical energy storage applications.展开更多
Macro-architectured cellular （MAC） material is defined as a class of engineered materials having configurable cells of relatively large （i.e., visible） size that can be architecturally designed to achieve various ...Macro-architectured cellular （MAC） material is defined as a class of engineered materials having configurable cells of relatively large （i.e., visible） size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson＇s ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.展开更多
Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review s...Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.展开更多
Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive exa...Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.展开更多
Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instabili...Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.展开更多
Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence archite...Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence architectures in terms of latency,energy efficiency,and computational power.To achieve this vision,it is of vital importance to scale up the PNNs while simultaneously reducing the high demand on the dimensions required by them.The underlying cause of this strategy is the enormous gap between the scales of photonic and electronic integrated circuits.Here,we demonstrate monolithically integrated optical convolutional processors on thin film lithium niobate(TFLN)that harness inherent parallelism in photonics to enable large-scale programmable convolution kernels and,in turn,greatly reduce the dimensions required by subsequent fully connected layers.Experimental validation achieves high classification accuracies of 96%(86%)on the MNIST(Fashion-MNIST)dataset and 84.6%on the AG News dataset while dramatically reducing the required subsequent fully connected layer dimensions to 196×10(from 784×10)and 175×4(from 800×4),respectively.Furthermore,our devices can be driven by commercial field-programmable gate array systems;a unique advantage in addition to their scalable channel number and kernel size.Our architecture provides a solution to build practical machine learning photonic devices.展开更多
With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has surged.In this work,a novel gradient-layered architecture was design based on single-pore hollow lignin...With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has surged.In this work,a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres(HLNPs)-intercalated two-dimensional transition metal carbide(Ti_(3)C_(2)T_(x) MXene)for fabricating highly stretchable and durable supercapacitors.By depositing and inserting HLNPs in the MXene layers with a bottom-up decreasing gradient,a multilayered porous MXene structure with smooth ion channels was constructed by reducing the overstacking of MXene lamella.Moreover,the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and MXene to improve ion and electron accessibility,thus better utilizing the pseudocapacitive property of lignin.All these strategies effectively enhanced the capacitive performance of the electrodes.In addition,HLNPs,which acted as a protective phase for MXene layer,enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the electrodes.Flexible electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600%uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm^(−2)(241 F g^(−1))and 514 mF cm^(−2)(95 F g^(−1)),respectively.Moreover,their capacitances were well preserved after 1000 times of 600%stretch-release cycling.This study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials.展开更多
In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high inves...In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment.This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent.The designed architecture scheme has been practically applied in the“Jiangxi emergency early warning information release system software platform(phase I)project”(hereinafter referred to as“provincial emergency”),which meets the needs of flexible deployment of multi-level applications across meteorological wide area network(WAN),business private network of other commissions,offices,and bureaus,government extranet,Internet and other complex networks,and fully verifies the scientificity and rationality of the scheme.It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment,greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters,provided a reliable guarantee for disaster prevention and reduction,and provided a reference for the construction of current and future early warning release system and capacity improvement project.展开更多
Branching is a critical aspect of plant architecture that significantly impacts the yield and adaptability of staple cereal crops like rice and wheat.Cereal crops develop tillers during the vegetative stage and panicl...Branching is a critical aspect of plant architecture that significantly impacts the yield and adaptability of staple cereal crops like rice and wheat.Cereal crops develop tillers during the vegetative stage and panicle or spike branches during the reproductive stage,respectively,both of which are significantly impacted by hormones and genetic factors.Tillering and panicle branching are closely interconnected and exhibit high environmental plasticity.Here,we summarize the recent progress in genetic,hormonal,and environmental factors regulation in the branching of rice and wheat.This review not only provides a comprehensive overview of the current knowledge on branching mechanisms in rice and wheat,but also explores the prospects for future research aimed at optimizing crop architecture for enhanced productivity.展开更多
The formation of root system architecture(RSA)plays a crucial role in plant growth.OsDRO1 is known to have a function in controlling RSA in rice,however,the role of potato StDRO2,a homolog of rice OsDRO1,in root growt...The formation of root system architecture(RSA)plays a crucial role in plant growth.OsDRO1 is known to have a function in controlling RSA in rice,however,the role of potato StDRO2,a homolog of rice OsDRO1,in root growth remains unclear.In this study,we obtained potato dro2 mutant lines by Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR-Associated 9(CRISPR/Cas9)-mediated genome editing system.The mutant lines were generated from a splicing defect of the StDRO2 intron 1,which causes a nonsense mutation in StDRO2.Furthermore,the secondary structure of StDRO2 mRNA analyzed with RNAfold Web Server was altered in the dro2 mutant.Mutation of StDRO2 conveys potato adaptation through changing the RSA via alteration of auxin transport under drought stress.The potato dro2 lines showed higher plant height,longer root length,smaller root growth angle and increased tuber weight than the wild-type.The alteration of RSA was associated with a disturbance of IAA distribution in the dro2 mutant,and the levels of StPIN7 and StPIN10 detected by using real-time PCR were up-regulated in the roots of potato dro2 lines grown under drought stress.Moreover,the microRNAs(miRNAs)PmiREN024536 and PmiREN024486 targeted the StDRO2 gene,and auxin positively and negatively regulated the expression of StDRO2 and the miRNAs PmiREN024536 and PmiREN024486,respectively,in the potato roots.Our data shows that a regulatory network involving auxin,StDRO2,PmiREN024536 and PmiREN024486 can control RSA to convey potato fitness under drought stress.展开更多
Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers ...Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.展开更多
To address the discrepancies between well and seismic data in stratigraphic correlation of the Triassic Yanchang Formation in the Ordos Basin,NW China,traditional stratigraphic classification schemes,the latest 3D sei...To address the discrepancies between well and seismic data in stratigraphic correlation of the Triassic Yanchang Formation in the Ordos Basin,NW China,traditional stratigraphic classification schemes,the latest 3D seismic and drilling data,and reservoir sections are thoroughly investigated.Guided by the theory of sequence stratigraphy,the progradational sequence stratigraphic framework of the Yanchang Formation is systematically constructed to elucidate new deposition mechanisms in the depressed lacustrine basin,and it has been successfully applied to the exploration and development practices in the Qingcheng Oilfield.Key findings are obtained in three aspects.First,the seismic progradational reflections,marker tuff beds,and condensed sections of flooding surfaces in the Yanchang Formation are consistent and isochronous.Using flooding surface markers as a reference,a progradational sequence stratigraphic architecture is reconstructed for the middle-upper part of Yanchang Formation,and divided into seven clinoform units(CF1-CF7).Second,progradation predominantly occurs in semi-deep to deep lake environments,with the depositional center not always coinciding with the thickest strata.The lacustrine basin underwent an evolution of“oscillatory regression-progradational infilling-multi-phase superimposition”.Third,the case study of Qingcheng Oilfield reveals that the major pay zones consist of“isochronous but heterochronous”gravity-flow sandstone complexes.Guided by the progradational sequence stratigraphic architecture,horizontal well oil-layer penetration rates remain above 82%.The progradational sequence stratigraphic architecture and associated geological insights are more consistent with the sedimentary infilling mechanisms of large-scale continental depressed lacustrine basins and actual drilling results.The research results provide crucial theoretical and technical support for subsequent refined exploration and development of the Yanchang Formation,and are expected to offer a reference for research and production practice in similar continental lacustrine basins.展开更多
This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA f...This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA framework integrates security by design principles, micro-segmentation, and Island Mode Operation (IMO) to enhance cyber resilience and ensure continuous, secure operations. The methodology deploys a Forward-Thinking Architecture Strategy (FTAS) algorithm, which utilises an industrial Intrusion Detection System (IDS) implemented with Python’s Network Intrusion Detection System (NIDS) library. The FTAS algorithm successfully identified and responded to cyber-attacks, ensuring minimal system disruption. ISERA has been validated through comprehensive testing scenarios simulating Denial of Service (DoS) attacks and malware intrusions, at both the IT and OT layers where it successfully mitigates the impact of malicious activity. Results demonstrate ISERA’s efficacy in real-time threat detection, containment, and incident response, thus ensuring the integrity and reliability of critical infrastructure systems. ISERA’s decentralised approach contributes to global net zero goals by optimising resource use and minimising environmental impact. By adopting a decentralised control architecture and leveraging virtualisation, ISERA significantly enhances the cyber resilience and sustainability of critical infrastructure systems. This approach not only strengthens defences against evolving cyber threats but also optimises resource allocation, reducing the system’s carbon footprint. As a result, ISERA ensures the uninterrupted operation of essential services while contributing to broader net zero goals.展开更多
A clean environment with low carbon emissions is the goal of research on the development of green and sustainable buildings that use bio-sourced materials in conjunction with solar energy to create more sustainable ci...A clean environment with low carbon emissions is the goal of research on the development of green and sustainable buildings that use bio-sourced materials in conjunction with solar energy to create more sustainable cities.This is particularly true in Africa,where there aren’t many studies on the topic.The current study suggests a 90 m^(2) model of a sustainable building in a dry climate that is movable to address the issue of housing in remote areas,ensures comfort in harsh weather conditions,uses solar renewable resources—which are plentiful in Africa—uses biosourced materials,and examines how these materials relate to temperature and humidity control while emitting minimal carbon emissions.In order to solve the topic under consideration,the work is split into two sections:numerical and experimental approaches.Using TRNSYS and Revit,the suggested prototype building is examined numerically to examine the impact of orientation,envelope composition made of bio-sourced materials,and carbon emissions.Through a hygrothermal investigation,experiments are conducted to evaluate this prototype’s effectiveness.Furthermore,an examination of the photovoltaic system’s production,consumption,and several scenarios used tomaximize battery life is included in the paper.Because the biosourcedmaterial achieves a thermal transmittance of 0.15(W.m^(-2).K^(-1)),the results demonstrate an intriguing finding in terms of comfort.This value satisfies the requirements of passive building,energy autonomy of the dwelling,and injection in-network with an annual value of 15,757 kWh.Additionally,compared to the literature,the heating needs ratio is 6.38(kWh/m^(2).an)and the cooling needs ratio is 49(kWh/m^(2).an),both of which are good values.According to international norms,the inside temperature doesn’t go above 26℃,and the humidity level is within a comfortable range.展开更多
Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a vi...Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.展开更多
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual...Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.展开更多
基金supported by the National Natural Science Foundation of China(No.51461025).
文摘The effect of the volume fraction of 3D-metal matrix composites(MMC)framework on the compressive properties of 3D interpenetrating hierarchical ZrO_(2)-toughened Al_(2)O_(3)particle(ZTAp)/40Cr steel composites was investigated.The results showed that the compressive properties of the material tended to decrease as the volume fraction of 3D-MMC framework increased.The composite with 35 vol.%3D-MMC had a yield strength of 1455.2 MPa and compressive strength of 1612.8 MPa,which occurred at a strain value of 5.6%.Compared to the homogeneously dispersed composite material,the composite with 35 vol.%3D-MMC had a 144.7%higher yield strength,which occurred at a 20%higher strain.An analysis of the cracks inside the material revealed that the crack was hindered and deflected by the matrix during propagation,which lengthened the crack propagation path and consumed more energy,thus leading to toughening.The results indicated that 3D interpenetrating hierarchical structure had a strengthening and toughening effect on ZTAp/40Cr composites.
基金financially supported by the National Natural Science Foundation of China(No.51802195)Chen Guang Scholar Project of Shanghai Education Commission(No.19CG53)。
文摘Three-dimensional(3D)functional graphenebased architecture with superior electrical conductivity and good mechanical strength has promising applications in energy storage and electrics.Viscoelasticity-adjustable inks make it possible to achieve desired 3D architectures with interconnected and continuous interior networks by microextrusion printing.In this work,ultra-low-concentration graphene oxide(GO)inks of~15 mg·ml-1 have been obtained and demonstrated in direct 3D printing with a facile cross-linking(direct ink writing).The rheological behavior of the GO strategy by cations,which is the lowest concentration to achieve direct ink writing inks,could be adjusted from 1×10^(4) to 1×10^(5) Pa·s^(-1) with different concentrations of cations due to strong cross-linking networks between GO sheets and cations.Meanwhile,the specific strength and electrical conductivity of 3D-printed graphene architecture are notably enhanced,reaching up to 51.7×10^(3) N·m·kg^(-1)and 119 S·m^(-1),which are superior to conventional graphene aerogels.Furthermore,3D printing graphene-based architecture assembled in micro-superc apacitor exhibits excellent electrochemical performance,which can be ascribed to the effective ion transportation through the interconnected networks.The strategy demonstrated is useful in the design of complex-shaped,graphene-based architectures for scalable manufacturing of practical energy storage applications.
文摘Macro-architectured cellular （MAC） material is defined as a class of engineered materials having configurable cells of relatively large （i.e., visible） size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson＇s ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.
基金supported by the Ministry of Education and Science of the Republic of North Macedonia through the project“Utilizing AI and National Large Language Models to Advance Macedonian Language Capabilties”。
文摘Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.
文摘Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.
基金Supported by the National Defense Basic Scientific Research Program of China.
文摘Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.
基金supported by the National Natural Science Foundation of China (Grant Nos.12192251,12334014,62335019,12134001,1230441812474378)+1 种基金the Quantum Science and Technology National Science and Technology Major Project(Grant No.2021ZD0301403)the Shanghai Municipal Science and Technology Major Project (Grant No.2019SHZDZX01)。
文摘Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence architectures in terms of latency,energy efficiency,and computational power.To achieve this vision,it is of vital importance to scale up the PNNs while simultaneously reducing the high demand on the dimensions required by them.The underlying cause of this strategy is the enormous gap between the scales of photonic and electronic integrated circuits.Here,we demonstrate monolithically integrated optical convolutional processors on thin film lithium niobate(TFLN)that harness inherent parallelism in photonics to enable large-scale programmable convolution kernels and,in turn,greatly reduce the dimensions required by subsequent fully connected layers.Experimental validation achieves high classification accuracies of 96%(86%)on the MNIST(Fashion-MNIST)dataset and 84.6%on the AG News dataset while dramatically reducing the required subsequent fully connected layer dimensions to 196×10(from 784×10)and 175×4(from 800×4),respectively.Furthermore,our devices can be driven by commercial field-programmable gate array systems;a unique advantage in addition to their scalable channel number and kernel size.Our architecture provides a solution to build practical machine learning photonic devices.
基金supported by Natural Science and Engineering Research Council of Canada(RGPIN-2017-06737)Canada Research Chairs program,the National Key Research and Development Program of China(2017YFD0601005,2022YFD0904201)+1 种基金the National Natural Science Foundation of China(51203075)the China Scholarship Council(Grant No.CSC202208320361).
文摘With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has surged.In this work,a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres(HLNPs)-intercalated two-dimensional transition metal carbide(Ti_(3)C_(2)T_(x) MXene)for fabricating highly stretchable and durable supercapacitors.By depositing and inserting HLNPs in the MXene layers with a bottom-up decreasing gradient,a multilayered porous MXene structure with smooth ion channels was constructed by reducing the overstacking of MXene lamella.Moreover,the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and MXene to improve ion and electron accessibility,thus better utilizing the pseudocapacitive property of lignin.All these strategies effectively enhanced the capacitive performance of the electrodes.In addition,HLNPs,which acted as a protective phase for MXene layer,enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the electrodes.Flexible electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600%uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm^(−2)(241 F g^(−1))and 514 mF cm^(−2)(95 F g^(−1)),respectively.Moreover,their capacitances were well preserved after 1000 times of 600%stretch-release cycling.This study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials.
文摘In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment.This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent.The designed architecture scheme has been practically applied in the“Jiangxi emergency early warning information release system software platform(phase I)project”(hereinafter referred to as“provincial emergency”),which meets the needs of flexible deployment of multi-level applications across meteorological wide area network(WAN),business private network of other commissions,offices,and bureaus,government extranet,Internet and other complex networks,and fully verifies the scientificity and rationality of the scheme.It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment,greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters,provided a reliable guarantee for disaster prevention and reduction,and provided a reference for the construction of current and future early warning release system and capacity improvement project.
基金funded by grants from the National Natural Science Foundation of China (31930006 to Y.W.)the National Key Research and Development Program of China (2022YFF1002903 to Y.W.)+1 种基金the Top Talents Program “One Case One Discussion”(Yishiyiyi to Y.W.)from Shandong provinceShandong Agricultural University Talent Introduction Start-up Fund (to N.Z.)
文摘Branching is a critical aspect of plant architecture that significantly impacts the yield and adaptability of staple cereal crops like rice and wheat.Cereal crops develop tillers during the vegetative stage and panicle or spike branches during the reproductive stage,respectively,both of which are significantly impacted by hormones and genetic factors.Tillering and panicle branching are closely interconnected and exhibit high environmental plasticity.Here,we summarize the recent progress in genetic,hormonal,and environmental factors regulation in the branching of rice and wheat.This review not only provides a comprehensive overview of the current knowledge on branching mechanisms in rice and wheat,but also explores the prospects for future research aimed at optimizing crop architecture for enhanced productivity.
基金supported by grants from the National Natural Science Foundation of China(Grant Nos.32260085,31860064,31660501,31970609,32260718 and 31901870)the Key Projects of the Applied Basic Research Plan of Yunnan Province(Grant No.202301AS070082)+3 种基金the Start-up fund from Xishuangbanna Tropical Botanical Garden,the‘Top Talents Program in Science and Technology’from Yunnan Province,the Major Science and Technology Project in Yunnan Province(Grant Nos.202102AE090042 and 202202AE090036)the Young and Middle-Aged Academic and Technical Leaders Reserve Talent Program in Yunnan Province(Grant No.202205AC160076)China Postdoctoral Science Foundation(Grant No.2019M653849XB)the High-level Talents Introduction Plan of Yunnan Province-Young Talents Special Project。
文摘The formation of root system architecture(RSA)plays a crucial role in plant growth.OsDRO1 is known to have a function in controlling RSA in rice,however,the role of potato StDRO2,a homolog of rice OsDRO1,in root growth remains unclear.In this study,we obtained potato dro2 mutant lines by Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR-Associated 9(CRISPR/Cas9)-mediated genome editing system.The mutant lines were generated from a splicing defect of the StDRO2 intron 1,which causes a nonsense mutation in StDRO2.Furthermore,the secondary structure of StDRO2 mRNA analyzed with RNAfold Web Server was altered in the dro2 mutant.Mutation of StDRO2 conveys potato adaptation through changing the RSA via alteration of auxin transport under drought stress.The potato dro2 lines showed higher plant height,longer root length,smaller root growth angle and increased tuber weight than the wild-type.The alteration of RSA was associated with a disturbance of IAA distribution in the dro2 mutant,and the levels of StPIN7 and StPIN10 detected by using real-time PCR were up-regulated in the roots of potato dro2 lines grown under drought stress.Moreover,the microRNAs(miRNAs)PmiREN024536 and PmiREN024486 targeted the StDRO2 gene,and auxin positively and negatively regulated the expression of StDRO2 and the miRNAs PmiREN024536 and PmiREN024486,respectively,in the potato roots.Our data shows that a regulatory network involving auxin,StDRO2,PmiREN024536 and PmiREN024486 can control RSA to convey potato fitness under drought stress.
文摘Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.
基金Supported by the National Science and Technology Major Project(2017ZX05001)CNPC Technology Project(2023YQX20111).
文摘To address the discrepancies between well and seismic data in stratigraphic correlation of the Triassic Yanchang Formation in the Ordos Basin,NW China,traditional stratigraphic classification schemes,the latest 3D seismic and drilling data,and reservoir sections are thoroughly investigated.Guided by the theory of sequence stratigraphy,the progradational sequence stratigraphic framework of the Yanchang Formation is systematically constructed to elucidate new deposition mechanisms in the depressed lacustrine basin,and it has been successfully applied to the exploration and development practices in the Qingcheng Oilfield.Key findings are obtained in three aspects.First,the seismic progradational reflections,marker tuff beds,and condensed sections of flooding surfaces in the Yanchang Formation are consistent and isochronous.Using flooding surface markers as a reference,a progradational sequence stratigraphic architecture is reconstructed for the middle-upper part of Yanchang Formation,and divided into seven clinoform units(CF1-CF7).Second,progradation predominantly occurs in semi-deep to deep lake environments,with the depositional center not always coinciding with the thickest strata.The lacustrine basin underwent an evolution of“oscillatory regression-progradational infilling-multi-phase superimposition”.Third,the case study of Qingcheng Oilfield reveals that the major pay zones consist of“isochronous but heterochronous”gravity-flow sandstone complexes.Guided by the progradational sequence stratigraphic architecture,horizontal well oil-layer penetration rates remain above 82%.The progradational sequence stratigraphic architecture and associated geological insights are more consistent with the sedimentary infilling mechanisms of large-scale continental depressed lacustrine basins and actual drilling results.The research results provide crucial theoretical and technical support for subsequent refined exploration and development of the Yanchang Formation,and are expected to offer a reference for research and production practice in similar continental lacustrine basins.
基金funded by the Office of Gas and Electricity Markets(Ofgem)and supported by De Montfort University(DMU)and Nottingham Trent University(NTU),UK.
文摘This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA framework integrates security by design principles, micro-segmentation, and Island Mode Operation (IMO) to enhance cyber resilience and ensure continuous, secure operations. The methodology deploys a Forward-Thinking Architecture Strategy (FTAS) algorithm, which utilises an industrial Intrusion Detection System (IDS) implemented with Python’s Network Intrusion Detection System (NIDS) library. The FTAS algorithm successfully identified and responded to cyber-attacks, ensuring minimal system disruption. ISERA has been validated through comprehensive testing scenarios simulating Denial of Service (DoS) attacks and malware intrusions, at both the IT and OT layers where it successfully mitigates the impact of malicious activity. Results demonstrate ISERA’s efficacy in real-time threat detection, containment, and incident response, thus ensuring the integrity and reliability of critical infrastructure systems. ISERA’s decentralised approach contributes to global net zero goals by optimising resource use and minimising environmental impact. By adopting a decentralised control architecture and leveraging virtualisation, ISERA significantly enhances the cyber resilience and sustainability of critical infrastructure systems. This approach not only strengthens defences against evolving cyber threats but also optimises resource allocation, reducing the system’s carbon footprint. As a result, ISERA ensures the uninterrupted operation of essential services while contributing to broader net zero goals.
文摘A clean environment with low carbon emissions is the goal of research on the development of green and sustainable buildings that use bio-sourced materials in conjunction with solar energy to create more sustainable cities.This is particularly true in Africa,where there aren’t many studies on the topic.The current study suggests a 90 m^(2) model of a sustainable building in a dry climate that is movable to address the issue of housing in remote areas,ensures comfort in harsh weather conditions,uses solar renewable resources—which are plentiful in Africa—uses biosourced materials,and examines how these materials relate to temperature and humidity control while emitting minimal carbon emissions.In order to solve the topic under consideration,the work is split into two sections:numerical and experimental approaches.Using TRNSYS and Revit,the suggested prototype building is examined numerically to examine the impact of orientation,envelope composition made of bio-sourced materials,and carbon emissions.Through a hygrothermal investigation,experiments are conducted to evaluate this prototype’s effectiveness.Furthermore,an examination of the photovoltaic system’s production,consumption,and several scenarios used tomaximize battery life is included in the paper.Because the biosourcedmaterial achieves a thermal transmittance of 0.15(W.m^(-2).K^(-1)),the results demonstrate an intriguing finding in terms of comfort.This value satisfies the requirements of passive building,energy autonomy of the dwelling,and injection in-network with an annual value of 15,757 kWh.Additionally,compared to the literature,the heating needs ratio is 6.38(kWh/m^(2).an)and the cooling needs ratio is 49(kWh/m^(2).an),both of which are good values.According to international norms,the inside temperature doesn’t go above 26℃,and the humidity level is within a comfortable range.
基金National Natural Science Foundation of China(71690233,71971213,71901214)。
文摘Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
文摘Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.
