Learning programming and using programming languages are the essential aspects of computer science education.Students use programming languages to write their programs.These computer programs(students or practitioners...Learning programming and using programming languages are the essential aspects of computer science education.Students use programming languages to write their programs.These computer programs(students or practitioners written)make computers artificially intelligent and perform the tasks needed by the users.Without these programs,the computer may be visioned as a pointless machine.As the premise of writing programs is situated with specific programming languages,enormous efforts have been made to develop and create programming languages.However,each program-ming language is domain-specific and has its nuances,syntax and seman-tics,with specific pros and cons.These language-specific details,including syntax and semantics,are significant hurdles for novice programmers.Also,the instructors of introductory programming courses find these language specificities as the biggest hurdle in students learning,where more focus is on syntax than logic development and actual implementation of the program.Considering the conceptual difficulty of programming languages and novice students’struggles with the language syntax,this paper describes the design and development of a Context-Free Grammar(CFG)of a programming language for the novice,newcomers and students who do not have computer science as their major.Due to its syntax proximity to daily conversations,this paper hypothesizes that this language will be easy to use and understand by novice programmers.This paper systematically designed the language by identifying themes from various existing programming languages(e.g.,C,Python).Additionally,this paper surveyed computer science experts from industry and academia,where experts self-reported their satisfaction with the newly designed language.The results indicate that 93%of the experts reported satisfaction with the NewBee for novice,newcomer and non-Computer Sci-ence(CS)major students.展开更多
A common neural mechanism—the General Motor Programmer—is proposed by Keane (1999) to underlie both the perception of speech and the initiation of hand movement. A proposal to investigate the specific aspect of cogn...A common neural mechanism—the General Motor Programmer—is proposed by Keane (1999) to underlie both the perception of speech and the initiation of hand movement. A proposal to investigate the specific aspect of cognitive functioning this mechanism is specialized for, namely the timing or place of articulation, is outlined.展开更多
The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.H...The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.展开更多
Metamaterials programmed with target rate-dependent mechanical properties are efficient platforms for realizing advanced functionalities.Yet,the loading rate-dependent mechanical property programming has received limi...Metamaterials programmed with target rate-dependent mechanical properties are efficient platforms for realizing advanced functionalities.Yet,the loading rate-dependent mechanical property programming has received limited attention.Here,the“stair-building”strategy is employed in the rate domain by combining the bistability with viscoelasticity.An arbitrary target curve in the programmable space can be approximated by a“stair”built by two kinds of“bricks”.The“bricks”can be realized by a dual-bistable unit,constructed by two bistable structures in series.The dual-bistable unit can switch between two efficient stable phases without inducing changes in the global morphology.Such a unit exhibits N-shaped stress-strain curves at both efficient stable phases with different peak values,resulting in different heights of“bricks”.Moreover,the N-shaped curves have rate-dependent peak values,indicating that the heights of“bricks”change with loading rate.The“stair-building”strategy is realized by array-structured mechanical metamaterials based on dual-bistable units.Different stress-strain curves under various loading rates can be reprogrammed in the same piece of metamaterial by intentionally selecting the efficient stable phases of units.Besides,the rate effect of the metamaterial can also be tuned by reprogramming stress-strain curves under both low and high loading rates,respectively.This reprogrammable metamaterial is promising in smart vibration isolators and adaptive energy absorbers.展开更多
The intrinsic pressure framework,which treats self-propelling force as an external force,provides a convenient and consistent description of mechanical equilibrium in active matter.However,direct experimental evidence...The intrinsic pressure framework,which treats self-propelling force as an external force,provides a convenient and consistent description of mechanical equilibrium in active matter.However,direct experimental evidence is still lacking.To validate this framework,here we employ a programmable robotic platform,where a single light-controlled wheeled robot travels in an activity landscape.Our experiments quantitatively demonstrate that the intrinsic pressure difference across the activity interface is balanced by the emerged polarization force.This result unambiguously confirms the theoretical predictions,thus validating the intrinsic pressure framework and laying the experimental foundation for the intrinsic pressure-based mechanical description of dry active matter.展开更多
Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the loca...Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the locally calibrated Future Land Use Simulation(FLUS)model,which coupled system dynamics with cellular automata and integrated an artificial neural network algorithm and a roulette wheel selection mechanism.We projected future land use(2020–2100)dynamics of Lanzhou,a typical river valley city in Northwest China,under three different Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5).The simulation results were validated and subsequently reclassified using the International Geosphere Biosphere Programme(IGBP)system to produce a dataset suitable for driving climatic and environmental models.Under the SSP1-2.6 scenario,urban and built-up land expanded consistently,whereas irrigated cropland and pasture as well as grassland contracted continuously.Conversely,the SSP5-8.5 scenario was characterized by a contraction of urban and built-up land,and relative stability of irrigated cropland and pasture as well as grassland.The SSP2-4.5 scenario presented a more complex trade-off,where urban and built-up land and grassland increased first and then decreased,whereas irrigated cropland and pasture followed an opposite trajectory.A significant inverse relationship between urban and built-up land and irrigated cropland and pasture was observed under all scenarios,underscoring the fundamental spatial competition that prevailed in this land-constrained valley city.Furthermore,the negative correlation of grassland with urban and built-up land,coupled with the positive correlation of grassland with irrigated cropland and pasture under both the SSP1-2.6 and SSP5-8.5 scenarios,indicated an evolution from broad confrontation to intricate internal trade-offs within the urban–agricultural–ecological system.This study underscored the critical influence of regional topographic and hydrological constraints on land-use evolution in arid regions,providing guidance for water resource management and ecosystem protection in Lanzhou,with applications for sustainable land-use planning in other arid and semi-arid river valley cities.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
1|Introduction Metamaterials are artificially engineered systems in which the geometry and arrangement of designed unit cells give rise to effective properties that are not available in natural materials.Intelligent m...1|Introduction Metamaterials are artificially engineered systems in which the geometry and arrangement of designed unit cells give rise to effective properties that are not available in natural materials.Intelligent metamaterials extend this concept by integrating stimulus-responsive materials with programmable architectures,thereby creating functional matter that blurs the conventional boundary between materials and structures and enables dynamic,adaptive,and reconfigurable functionalities.These systems can respond to diverse stimuli such as thermal,electrical,optical,magnetic,and mechanical inputs,and convert them into tunable shape change,adaptive mechanical/optical responses,and other reconfigurable functionalities[1–5].Through this synergy,they acquire lifelike and emergent behaviors,making them attractive platforms for next-generation applications in soft robotics,bioengineering,information encryption,and mechanical computation.展开更多
Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security...Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.展开更多
This paper presents the development of a thermoplastic shape memory rubber that can be programmed at human body temperature for comfortable fitting applications.We hybridized commercially available thermoplastic rubbe...This paper presents the development of a thermoplastic shape memory rubber that can be programmed at human body temperature for comfortable fitting applications.We hybridized commercially available thermoplastic rubber(TPR)used in the footwear industry with un-crosslinked polycaprolactone(PCL)to create two samples,namely TP6040 and TP7030.The shape memory behavior,elasticity,and thermo-mechanical response of these rubbers were systematically investigated.The experimental results demonstrated outstanding shape memory performance,with both samples achieving shape fixity ratios(Rf)and shape recovery ratios(R_(r))exceeding 94%.TP6040 exhibited a fitting time of 80 s at body temperature(37℃),indicating a rapid response for shape fixing.The materials also showed good elasticity before and after programming,which is crucial for comfort fitting.These findings suggest that the developed shape memory thermoplastic rubber has potential applications in personalized comfort fitting products,offering advantages over traditional customization techniques in terms of efficiency and cost-effectiveness.展开更多
Software-Defined Perimeter(SDP)provides a logical perimeter to restrict access to services.However,due to the security vulnerability of a single controller and the programmability lack of a gateway,existing SDP is fac...Software-Defined Perimeter(SDP)provides a logical perimeter to restrict access to services.However,due to the security vulnerability of a single controller and the programmability lack of a gateway,existing SDP is facing challenges.To solve the above problems,we propose a flexible and secure SDP mechanism named Mimic SDP(MSDP).MSDP consists of endogenous secure controllers and a dynamic gateway.The controllers avoid single point failure by heterogeneity and redundancy.And the dynamic gateway realizes flexible forwarding in programmable data plane by changing the processing of packet construction and deconstruction,thereby confusing the potential adversary.Besides,we propose a Markov model to evaluate the security of our SDP framework.We implement a prototype of MSDP and evaluate it in terms of functionality,performance,and scalability in different groups of systems and languages.Evaluation results demonstrate that MSDP can provide a secure connection of 93.38%with a cost of 6.34%under reasonable configuration.展开更多
Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structur...Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials.展开更多
Kirigami,through introducing cuts into a thin sheet,can greatly improve the stretchability of structures and also generate complex patterns,showing potentials in various applications.Interestingly,even with the same c...Kirigami,through introducing cuts into a thin sheet,can greatly improve the stretchability of structures and also generate complex patterns,showing potentials in various applications.Interestingly,even with the same cutting pattern,the mechanical response of kirigami metamaterials can exhibit significant differences depending on the cutting angles in respect to the loading direction.In this work,we investigate the structural deformation of kirigami metamaterials with square domains and varied cutting angles of 0°and 45°.We further introduce a second level of cutting on the basis of the first cutting pattern.By combining experiments and finite element simulations,it is found that,compared to the commonly used 0°cuts,the two-level kirigami metamaterials with 45°cuts exhibit a unique alternating arrangement phenomenon of expanded/unexpanded states in the loading process,which also results in distinct stress–strain response.Through tuning the cutting patterns of metamaterials with 45°cuts,precise control of the rotation of the kirigami unit is realized,leading to kirigami metamaterials with encryption properties.The current work demonstrates the programmability of structural deformation in hierarchical kirigami metamaterials through controlling the local cutting modes.展开更多
Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometric design instead of chemical composition.To make the mechanical deformation programmable,the non-...Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometric design instead of chemical composition.To make the mechanical deformation programmable,the non-uniform rational B-spline(NURBS)curves are taken to replace the traditional ligament boundaries of the chiral structure.The Neural networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency.For the problem of finding structure configuration with specified mechanical properties,such as Young’s modulus,Poisson’s ratio or deformation,an inverse design method using the Neural network-based proxy model is proposed to build the relationship between mechanical properties and geometric configuration.To satisfy some more complex deformation requirements,a non-homogeneous inverse design method is proposed and verified through simulation and experiments.Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the design of chiral metamaterials.展开更多
Quality of Service(QoS)assurance in programmable IoT and 5G networks is increasingly threatened by cyberattacks such as Distributed Denial of Service(DDoS),spoofing,and botnet intrusions.This paper presents AutoSHARC,...Quality of Service(QoS)assurance in programmable IoT and 5G networks is increasingly threatened by cyberattacks such as Distributed Denial of Service(DDoS),spoofing,and botnet intrusions.This paper presents AutoSHARC,a feedback-driven,explainable intrusion detection framework that integrates Boruta and LightGBM–SHAP feature selection with a lightweight CNN–Attention–GRU classifier.AutoSHARC employs a two-stage feature selection pipeline to identify the most informative features from high-dimensional IoT traffic and reduces 46 features to 30 highly informative ones,followed by post-hoc SHAP-guided retraining to refine feature importance,forming a feedback loopwhere only the most impactful attributes are reused to retrain themodel.This iterative refinement reduces computational overhead,accelerates detection latency,and improves transparency.Evaluated on the CIC IoT 2023 dataset,AutoSHARC achieves 98.98%accuracy,98.9%F1-score,and strong robustness with a Matthews Correlation Coefficient of 0.98 and Cohen’s Kappa of 0.98.The final model contains only 531,272 trainable parameters with a compact 2 MB size,enabling real-time deployment on resource-constrained IoT nodes.By combining explainable AI with iterative feature refinement,AutoSHARC provides scalable and trustworthy intrusion detection while preserving key QoS indicators such as latency,throughput,and reliability.展开更多
The functionality of the biological brain is closely related to the dynamic behavior generated by synapses in its complex neural system.The self-connection synapse,as a critical form of feedback synapse in Hopfield ne...The functionality of the biological brain is closely related to the dynamic behavior generated by synapses in its complex neural system.The self-connection synapse,as a critical form of feedback synapse in Hopfield neurons,plays an essential role in understanding the dynamic behavior of the brain.Synaptic memristors can bring neural network models closer to the complexity of the brain's neural networks.Inspired by this,this study incorporates the nonlinear memory characteristics of synapses into the Hopfield neural network(HNN)by replacing a single self-synapse in a four-dimensional HNN model with a novel cosine memristor model,aiming to more realistically reproduce the dynamical behavior of biological neurons in artificial systems.By performing a dynamical analysis of the system using numerical methods,we find that the model exhibits infinitely many equilibrium points and can induce the formation of rare transient attractors,as well as an arbitrary number of multi-scroll attractors.Additionally,the model demonstrates complex coexisting attractor dynamics,including transient chaos,periodicity,decaying periodicity,and coexisting chaos.Furthermore,the feasibility of the proposed HNN model is verified using a field-programmable gate array(FPGA).Finally,an electronic codebook(ECB)–mode block cipher encryption algorithm is proposed for image encryption.The encryption performance is evaluated,with an information entropy value of 7.9993,demonstrating the excellent randomness of the system-generated numbers.展开更多
UNDP official discusses transforming Africa-China partnerships through innovation,trade,and green growth Representatives from numerous interna-tional organisations,including the United Nations Development Programme(UN...UNDP official discusses transforming Africa-China partnerships through innovation,trade,and green growth Representatives from numerous interna-tional organisations,including the United Nations Development Programme(UNDP),attended the fourth China-Africa Economic and Trade Expo(CAETE),held in June in Changsha,Hunan Province.Among them was Ahunna Eziakonwa,UN assistant secretary general and director of the UNDP Regional Bureau for Africa,who took part in several activities at the expo.Her mission focused on promoting sustainable development across Africa through trade,innovation,and responsible investment.展开更多
Smart elastomers have attracted great interest due to their excellent adaptability to changing environments and affinity to living organisms,characterized by their ability to undergo programmable deformations or prope...Smart elastomers have attracted great interest due to their excellent adaptability to changing environments and affinity to living organisms,characterized by their ability to undergo programmable deformations or property changes in response to external stimuli(e.g.,heat,light,pH,or electric/magnetic fields).They exhibit huge potential to drive the innovation of soft actuators,robotics,biomedical devices,and wearable electronics.This special issue of Chinese Journal of Polymer Science(CJPS)is dedicated to showcasing cutting-edge advancements in liquid crystal elastomers,hydrogels and the related soft actuators,with a focus on the design,synthesis,characterization,and application of stimuli-responsive soft elastomers and their integration into functional actuation systems.展开更多
基金supported by the startup fund provided to Dr.Saira Anwar by Texas A&M University,College Station,USA.Any opinions,findings,conclusion,or recommendations expressed in this material do not necessarily reflect those of Texas A&M University。
文摘Learning programming and using programming languages are the essential aspects of computer science education.Students use programming languages to write their programs.These computer programs(students or practitioners written)make computers artificially intelligent and perform the tasks needed by the users.Without these programs,the computer may be visioned as a pointless machine.As the premise of writing programs is situated with specific programming languages,enormous efforts have been made to develop and create programming languages.However,each program-ming language is domain-specific and has its nuances,syntax and seman-tics,with specific pros and cons.These language-specific details,including syntax and semantics,are significant hurdles for novice programmers.Also,the instructors of introductory programming courses find these language specificities as the biggest hurdle in students learning,where more focus is on syntax than logic development and actual implementation of the program.Considering the conceptual difficulty of programming languages and novice students’struggles with the language syntax,this paper describes the design and development of a Context-Free Grammar(CFG)of a programming language for the novice,newcomers and students who do not have computer science as their major.Due to its syntax proximity to daily conversations,this paper hypothesizes that this language will be easy to use and understand by novice programmers.This paper systematically designed the language by identifying themes from various existing programming languages(e.g.,C,Python).Additionally,this paper surveyed computer science experts from industry and academia,where experts self-reported their satisfaction with the newly designed language.The results indicate that 93%of the experts reported satisfaction with the NewBee for novice,newcomer and non-Computer Sci-ence(CS)major students.
文摘A common neural mechanism—the General Motor Programmer—is proposed by Keane (1999) to underlie both the perception of speech and the initiation of hand movement. A proposal to investigate the specific aspect of cognitive functioning this mechanism is specialized for, namely the timing or place of articulation, is outlined.
基金supported by the National Key Research and Development Program of China under Grant 2022YFB2901501in part by the Science and Technology Innovation leading Talents Subsidy Project of Central Plains under Grant 244200510038.
文摘The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.
基金supported by the National Natural Science Foundation of China(Grant Nos.12225201,12372126,12002016,and 12172026)the National Key Research and Development Program of China(Grant No.2020YFB1313003)the Fundamental Research Funds for the Central Universities are gratefully acknowledged.
文摘Metamaterials programmed with target rate-dependent mechanical properties are efficient platforms for realizing advanced functionalities.Yet,the loading rate-dependent mechanical property programming has received limited attention.Here,the“stair-building”strategy is employed in the rate domain by combining the bistability with viscoelasticity.An arbitrary target curve in the programmable space can be approximated by a“stair”built by two kinds of“bricks”.The“bricks”can be realized by a dual-bistable unit,constructed by two bistable structures in series.The dual-bistable unit can switch between two efficient stable phases without inducing changes in the global morphology.Such a unit exhibits N-shaped stress-strain curves at both efficient stable phases with different peak values,resulting in different heights of“bricks”.Moreover,the N-shaped curves have rate-dependent peak values,indicating that the heights of“bricks”change with loading rate.The“stair-building”strategy is realized by array-structured mechanical metamaterials based on dual-bistable units.Different stress-strain curves under various loading rates can be reprogrammed in the same piece of metamaterial by intentionally selecting the efficient stable phases of units.Besides,the rate effect of the metamaterial can also be tuned by reprogramming stress-strain curves under both low and high loading rates,respectively.This reprogrammable metamaterial is promising in smart vibration isolators and adaptive energy absorbers.
基金supported by the National Natural Science Foundation of China (Grant Nos.T2325027,12274448,T2350007,12404239,12174041,12325405,12090054,and T2221001)the National Key R&D Program of China (Grant No.2022YFF0503504)。
文摘The intrinsic pressure framework,which treats self-propelling force as an external force,provides a convenient and consistent description of mechanical equilibrium in active matter.However,direct experimental evidence is still lacking.To validate this framework,here we employ a programmable robotic platform,where a single light-controlled wheeled robot travels in an activity landscape.Our experiments quantitatively demonstrate that the intrinsic pressure difference across the activity interface is balanced by the emerged polarization force.This result unambiguously confirms the theoretical predictions,thus validating the intrinsic pressure framework and laying the experimental foundation for the intrinsic pressure-based mechanical description of dry active matter.
基金supported by the Soft Science Special Project of Gansu Basic Research Plan(25JRZA206)the Longyuan Youth Talent Project of Gansu Province(ZHU Rong)+1 种基金the Innovation Development Special Project of China Meteorological Administration(CXFZ2025J036)the Program of the State Key Laboratory of Cryospheric Science and Frozen Soil Engineering,Chinese Academy of Sciences(CSFSE-KF-2402).
文摘Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the locally calibrated Future Land Use Simulation(FLUS)model,which coupled system dynamics with cellular automata and integrated an artificial neural network algorithm and a roulette wheel selection mechanism.We projected future land use(2020–2100)dynamics of Lanzhou,a typical river valley city in Northwest China,under three different Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5).The simulation results were validated and subsequently reclassified using the International Geosphere Biosphere Programme(IGBP)system to produce a dataset suitable for driving climatic and environmental models.Under the SSP1-2.6 scenario,urban and built-up land expanded consistently,whereas irrigated cropland and pasture as well as grassland contracted continuously.Conversely,the SSP5-8.5 scenario was characterized by a contraction of urban and built-up land,and relative stability of irrigated cropland and pasture as well as grassland.The SSP2-4.5 scenario presented a more complex trade-off,where urban and built-up land and grassland increased first and then decreased,whereas irrigated cropland and pasture followed an opposite trajectory.A significant inverse relationship between urban and built-up land and irrigated cropland and pasture was observed under all scenarios,underscoring the fundamental spatial competition that prevailed in this land-constrained valley city.Furthermore,the negative correlation of grassland with urban and built-up land,coupled with the positive correlation of grassland with irrigated cropland and pasture under both the SSP1-2.6 and SSP5-8.5 scenarios,indicated an evolution from broad confrontation to intricate internal trade-offs within the urban–agricultural–ecological system.This study underscored the critical influence of regional topographic and hydrological constraints on land-use evolution in arid regions,providing guidance for water resource management and ecosystem protection in Lanzhou,with applications for sustainable land-use planning in other arid and semi-arid river valley cities.
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.
基金supported by the National University of Singapore Presidential Young Professorship Start-Up Grant.
文摘1|Introduction Metamaterials are artificially engineered systems in which the geometry and arrangement of designed unit cells give rise to effective properties that are not available in natural materials.Intelligent metamaterials extend this concept by integrating stimulus-responsive materials with programmable architectures,thereby creating functional matter that blurs the conventional boundary between materials and structures and enables dynamic,adaptive,and reconfigurable functionalities.These systems can respond to diverse stimuli such as thermal,electrical,optical,magnetic,and mechanical inputs,and convert them into tunable shape change,adaptive mechanical/optical responses,and other reconfigurable functionalities[1–5].Through this synergy,they acquire lifelike and emergent behaviors,making them attractive platforms for next-generation applications in soft robotics,bioengineering,information encryption,and mechanical computation.
基金supported by the National Undergraduate Innovation and Entrepreneurship Training Program of China(Project No.202510559076)at Jinan University,a nationwide initiative administered by the Ministry of Educationthe National Natural Science Foundation of China(NSFC)under Grant No.62172189.
文摘Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.
基金supported by the Aeronautical Science Foundation of China(Grant Nos.2024Z009052003,20230038052001 and 20230015052002)the Third Batch of Science and Technology Plan Projects in Changzhou City in 2023(Applied Basic Research,Grant No.CJ20230080).
文摘This paper presents the development of a thermoplastic shape memory rubber that can be programmed at human body temperature for comfortable fitting applications.We hybridized commercially available thermoplastic rubber(TPR)used in the footwear industry with un-crosslinked polycaprolactone(PCL)to create two samples,namely TP6040 and TP7030.The shape memory behavior,elasticity,and thermo-mechanical response of these rubbers were systematically investigated.The experimental results demonstrated outstanding shape memory performance,with both samples achieving shape fixity ratios(Rf)and shape recovery ratios(R_(r))exceeding 94%.TP6040 exhibited a fitting time of 80 s at body temperature(37℃),indicating a rapid response for shape fixing.The materials also showed good elasticity before and after programming,which is crucial for comfort fitting.These findings suggest that the developed shape memory thermoplastic rubber has potential applications in personalized comfort fitting products,offering advantages over traditional customization techniques in terms of efficiency and cost-effectiveness.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFB2901304)。
文摘Software-Defined Perimeter(SDP)provides a logical perimeter to restrict access to services.However,due to the security vulnerability of a single controller and the programmability lack of a gateway,existing SDP is facing challenges.To solve the above problems,we propose a flexible and secure SDP mechanism named Mimic SDP(MSDP).MSDP consists of endogenous secure controllers and a dynamic gateway.The controllers avoid single point failure by heterogeneity and redundancy.And the dynamic gateway realizes flexible forwarding in programmable data plane by changing the processing of packet construction and deconstruction,thereby confusing the potential adversary.Besides,we propose a Markov model to evaluate the security of our SDP framework.We implement a prototype of MSDP and evaluate it in terms of functionality,performance,and scalability in different groups of systems and languages.Evaluation results demonstrate that MSDP can provide a secure connection of 93.38%with a cost of 6.34%under reasonable configuration.
基金supported by the National Natural Science Foundation of China (Grant Nos.12102021,12372105,12172026,and 12225201)the Fundamental Research Funds for the Central Universities and the Academic Excellence Foundation of BUAA for PhD Students.
文摘Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials.
基金supported by the National Natural Science Foundation of China(Grant Nos.12102392 and 12272341)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LQ21A020008).
文摘Kirigami,through introducing cuts into a thin sheet,can greatly improve the stretchability of structures and also generate complex patterns,showing potentials in various applications.Interestingly,even with the same cutting pattern,the mechanical response of kirigami metamaterials can exhibit significant differences depending on the cutting angles in respect to the loading direction.In this work,we investigate the structural deformation of kirigami metamaterials with square domains and varied cutting angles of 0°and 45°.We further introduce a second level of cutting on the basis of the first cutting pattern.By combining experiments and finite element simulations,it is found that,compared to the commonly used 0°cuts,the two-level kirigami metamaterials with 45°cuts exhibit a unique alternating arrangement phenomenon of expanded/unexpanded states in the loading process,which also results in distinct stress–strain response.Through tuning the cutting patterns of metamaterials with 45°cuts,precise control of the rotation of the kirigami unit is realized,leading to kirigami metamaterials with encryption properties.The current work demonstrates the programmability of structural deformation in hierarchical kirigami metamaterials through controlling the local cutting modes.
基金supported by the National Natural Science Foundation of China(grant numbers 11972287 and 12072266)the State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ23106)+1 种基金the National Key Laboratory of Aircraft Configuration Design(No.2023-JCJQ-LB-070)the Fundamental Research Funds for the Central Universities.
文摘Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometric design instead of chemical composition.To make the mechanical deformation programmable,the non-uniform rational B-spline(NURBS)curves are taken to replace the traditional ligament boundaries of the chiral structure.The Neural networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency.For the problem of finding structure configuration with specified mechanical properties,such as Young’s modulus,Poisson’s ratio or deformation,an inverse design method using the Neural network-based proxy model is proposed to build the relationship between mechanical properties and geometric configuration.To satisfy some more complex deformation requirements,a non-homogeneous inverse design method is proposed and verified through simulation and experiments.Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the design of chiral metamaterials.
文摘Quality of Service(QoS)assurance in programmable IoT and 5G networks is increasingly threatened by cyberattacks such as Distributed Denial of Service(DDoS),spoofing,and botnet intrusions.This paper presents AutoSHARC,a feedback-driven,explainable intrusion detection framework that integrates Boruta and LightGBM–SHAP feature selection with a lightweight CNN–Attention–GRU classifier.AutoSHARC employs a two-stage feature selection pipeline to identify the most informative features from high-dimensional IoT traffic and reduces 46 features to 30 highly informative ones,followed by post-hoc SHAP-guided retraining to refine feature importance,forming a feedback loopwhere only the most impactful attributes are reused to retrain themodel.This iterative refinement reduces computational overhead,accelerates detection latency,and improves transparency.Evaluated on the CIC IoT 2023 dataset,AutoSHARC achieves 98.98%accuracy,98.9%F1-score,and strong robustness with a Matthews Correlation Coefficient of 0.98 and Cohen’s Kappa of 0.98.The final model contains only 531,272 trainable parameters with a compact 2 MB size,enabling real-time deployment on resource-constrained IoT nodes.By combining explainable AI with iterative feature refinement,AutoSHARC provides scalable and trustworthy intrusion detection while preserving key QoS indicators such as latency,throughput,and reliability.
基金supported by the Guiding Science and Technology Plan Project of Changsha City under Grant kzd2501129by the Natural Science Foundation of Hunan Province(Grant No.2025JJ50368)+1 种基金the Scientific Research Fund of Hunan Provincial Education Department(Grant No.24A0248)the National Natural Science Foundation of China(Grant No.62273141)。
文摘The functionality of the biological brain is closely related to the dynamic behavior generated by synapses in its complex neural system.The self-connection synapse,as a critical form of feedback synapse in Hopfield neurons,plays an essential role in understanding the dynamic behavior of the brain.Synaptic memristors can bring neural network models closer to the complexity of the brain's neural networks.Inspired by this,this study incorporates the nonlinear memory characteristics of synapses into the Hopfield neural network(HNN)by replacing a single self-synapse in a four-dimensional HNN model with a novel cosine memristor model,aiming to more realistically reproduce the dynamical behavior of biological neurons in artificial systems.By performing a dynamical analysis of the system using numerical methods,we find that the model exhibits infinitely many equilibrium points and can induce the formation of rare transient attractors,as well as an arbitrary number of multi-scroll attractors.Additionally,the model demonstrates complex coexisting attractor dynamics,including transient chaos,periodicity,decaying periodicity,and coexisting chaos.Furthermore,the feasibility of the proposed HNN model is verified using a field-programmable gate array(FPGA).Finally,an electronic codebook(ECB)–mode block cipher encryption algorithm is proposed for image encryption.The encryption performance is evaluated,with an information entropy value of 7.9993,demonstrating the excellent randomness of the system-generated numbers.
文摘UNDP official discusses transforming Africa-China partnerships through innovation,trade,and green growth Representatives from numerous interna-tional organisations,including the United Nations Development Programme(UNDP),attended the fourth China-Africa Economic and Trade Expo(CAETE),held in June in Changsha,Hunan Province.Among them was Ahunna Eziakonwa,UN assistant secretary general and director of the UNDP Regional Bureau for Africa,who took part in several activities at the expo.Her mission focused on promoting sustainable development across Africa through trade,innovation,and responsible investment.
文摘Smart elastomers have attracted great interest due to their excellent adaptability to changing environments and affinity to living organisms,characterized by their ability to undergo programmable deformations or property changes in response to external stimuli(e.g.,heat,light,pH,or electric/magnetic fields).They exhibit huge potential to drive the innovation of soft actuators,robotics,biomedical devices,and wearable electronics.This special issue of Chinese Journal of Polymer Science(CJPS)is dedicated to showcasing cutting-edge advancements in liquid crystal elastomers,hydrogels and the related soft actuators,with a focus on the design,synthesis,characterization,and application of stimuli-responsive soft elastomers and their integration into functional actuation systems.
