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 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
Ceramic 4D printing,which integrates dynamic deformation with additive manufacturing,demonstrates significant potential in intelligent manufacturing,on-demand shaping of complex structures,and multifunctional device d...Ceramic 4D printing,which integrates dynamic deformation with additive manufacturing,demonstrates significant potential in intelligent manufacturing,on-demand shaping of complex structures,and multifunctional device development.Its core advantage lies in endowing materials with environmentally responsive dynamic deformation capabilities.However,current technologies still face limitations in responsiveness,reversibility,and mechanical performance.To address these challenges,this study proposes a programmable ceramic precursor system based on synergistic reinforcement of phase-separating hydrogels and shape memory polymers,combined with a nano-ceramic particle enhancement strategy.Using stereolithography 3D printing,high-precision fabrication of complex structures was achieved.By adjusting precursor composition,programming time,and structural thickness,the phase-separation kinetics-driven delayed recovery mechanism was elucidated,enabling precise control over recovery onset time.Furthermore,the thermal response mechanism of the precursor materials is explored,along with their potential for multi-shape transformation in biomedical applications,which is further extended to shape memory polymer systems.By employing a layered printing strategy,the autonomous reversible deformation of ceramic precursors is realized,providing new possibilities for specific applications.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
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
Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to ...Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to the inability to effectively capture global information from images,CNNs can easily lead to loss of contours and textures in segmentation results.Notice that the transformer model can effectively capture the properties of long-range dependencies in the image,and furthermore,combining the CNN and the transformer can effectively extract local details and global contextual features of the image.Motivated by this,we propose a multi-branch and multi-scale attention network(M2ANet)for medical image segmentation,whose architecture consists of three components.Specifically,in the first component,we construct an adaptive multi-branch patch module for parallel extraction of image features to reduce information loss caused by downsampling.In the second component,we apply residual block to the well-known convolutional block attention module to enhance the network’s ability to recognize important features of images and alleviate the phenomenon of gradient vanishing.In the third component,we design a multi-scale feature fusion module,in which we adopt adaptive average pooling and position encoding to enhance contextual features,and then multi-head attention is introduced to further enrich feature representation.Finally,we validate the effectiveness and feasibility of the proposed M2ANet method through comparative experiments on four benchmark medical image segmentation datasets,particularly in the context of preserving contours and textures.展开更多
Automatic pancreas segmentation plays a pivotal role in assisting physicians with diagnosing pancreatic diseases,facilitating treatment evaluations,and designing surgical plans.Due to the pancreas’s tiny size,signifi...Automatic pancreas segmentation plays a pivotal role in assisting physicians with diagnosing pancreatic diseases,facilitating treatment evaluations,and designing surgical plans.Due to the pancreas’s tiny size,significant variability in shape and location,and low contrast with surrounding tissues,achieving high segmentation accuracy remains challenging.To improve segmentation precision,we propose a novel network utilizing EfficientNetV2 and multi-branch structures for automatically segmenting the pancreas fromCT images.Firstly,an EfficientNetV2 encoder is employed to extract complex and multi-level features,enhancing the model’s ability to capture the pancreas’s intricate morphology.Then,a residual multi-branch dilated attention(RMDA)module is designed to suppress irrelevant background noise and highlight useful pancreatic features.And re-parameterization Visual Geometry Group(RepVGG)blocks with amulti-branch structure are introduced in the decoder to effectively integrate deep features and low-level details,improving segmentation accuracy.Furthermore,we apply re-parameterization to the model,reducing computations and parameters while accelerating inference and reducing memory usage.Our approach achieves average dice similarity coefficient(DSC)of 85.59%,intersection over union(IoU)of 75.03%,precision of 85.09%,and recall of 86.57%on the NIH pancreas dataset.Compared with other methods,our model has fewer parameters and faster inference speed,demonstrating its enormous potential in practical applications of pancreatic segmentation.展开更多
Based on the finite element-discrete element numerical method,a numerical model of fracture propagation in deflagration fracturing was established by considering the impact of stress wave,quasi-static pressure of expl...Based on the finite element-discrete element numerical method,a numerical model of fracture propagation in deflagration fracturing was established by considering the impact of stress wave,quasi-static pressure of explosive gas,and reflection of stress wave.The model was validated against the results of physical experiments.Taking the shale reservoirs of Silurian Longmaxi Formation in Luzhou area of the Sichuan Basin as an example,the effects of in-situ stress difference,natural fracture parameters,branch wellbore spacing,delay detonation time,and angle between branch wellbore and main wellbore on fracture propagation were identified.The results show that the fracture propagation morphology in deflagration fracturing is less affected by the in-situ stress difference when it is 5-15 MPa,and the tendency of fracture intersection between branch wellbores is significantly weakened when the in-situ stress difference reaches 20 MPa.The increase of natural fracture length promotes the fracture propagation along the natural fracture direction,while the increase of volumetric natural fracture density and angle limits the fracture propagation area and reduces the probability of fracture intersection between branch wells.The larger the branch wellbore spacing,the less probability of the fracture intersection between branch wells,allowing for the fracture propagation in multiple directions.Increasing the delay detonation time decreases the fracture spacing between branch wellbores.When the angle between the branch wellbore and the main wellbore is 45°and 90°,there is a tendency of fracture intersection between branch wellbores.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
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
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
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
A programmable low-profile array antenna based on nematic liquid crystals(NLCs)is proposed.Each antenna unit comprises a square patch radiating structure and a tunable NLC-based phase shifter capable of achieving a ph...A programmable low-profile array antenna based on nematic liquid crystals(NLCs)is proposed.Each antenna unit comprises a square patch radiating structure and a tunable NLC-based phase shifter capable of achieving a phase shift exceeding 360°with high linearity.First,the above 64 antenna units are periodically arranged into an 8×8 NLC-based antenna array,and the bias voltage of the NLC-based phase shifter loaded on the antenna unit is adjusted through the control of the field-programmable gate array(FPGA)programming sequences.This configuration enables precise phase changes for all 64 channels.Numerical simulation,sample processing,and experimental measurements of the antenna array are conducted to validate the performance of the antenna.The numerical and experimental results demonstrate that the proposed antenna performs well within the frequency range of 19.5-20.5 GHz,with a 3 dB relative bandwidth of 10%and a maximum main lobe gain of 14.1 dBi.A maximum scanning angle of±34°is achieved through the adjustment of the FPGA programming sequence.This NLC-based programmable array antenna shows promising potential for applications in satellite communication.展开更多
To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location(FL)research of distribution networks with complex topologies,this paper proposes an FL method of Multi-B...To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location(FL)research of distribution networks with complex topologies,this paper proposes an FL method of Multi-Branch distribution line based on Maximal Overlap Discrete Wavelet Transform(MODWT)combined with the improved Teager Energy Operator(TEO).Firstly,the current and voltage Traveling Wave(TW)signals at the head of each line are extracted,and the fault-induced components are obtained to determine the fault line by analyzing the polarity of the mutation amount of fault voltage and current TWs.Subsequently,the fault discrimination mark is calculated based on the fault-induced line-mode current and the zero-mode voltage,with the fault type determined by comparing each mark’s value against the fault discrimination table,transforming the FL problem in complex topology into a single-line FL problem.Finally,the fault voltage TW is extracted fromthe fault line,and the wave head detection method based on MODWT combined with improved TEO is used to precisely identify the arrival instants of both the first TW wave head and its first reflection at each line terminal,and then the FL result is calculated by applying the double-ended TW ranging formula that removes the influence of wave velocity.Simulation results demonstrate that the proposed method accurately identifies the fault line and types of faults occurring and maintains the ranging accuracy within 0.5%under various fault scenarios.展开更多
On April 19th,"the Youth Table Tennis Programme—Photo Exhibition of Zhou Enlai and the Bandung Conference&China-ASEAN(Indonesia)Youth Table Tennis Training Camp"opened in Jakarta,Indonesia.The event was...On April 19th,"the Youth Table Tennis Programme—Photo Exhibition of Zhou Enlai and the Bandung Conference&China-ASEAN(Indonesia)Youth Table Tennis Training Camp"opened in Jakarta,Indonesia.The event was guided by the Chinese Embassy in Indonesia and co-organised by the ASEAN-China Centre(ACC),the Memorial to Zhou Enlai and Deng Yingchao,the China Friendship Foundation for Peace and Development,the Beijing One Heart Sphere Charity Foundation,and the Enlai Foundation.展开更多
On January 15,2025,the China Road and Bridge Corporation(CRBC)Kenya Office and Africa Star Railway Operation Company Limited(Afristar),in collaboration with the Dream Building Service Association(DBSA),held the launch...On January 15,2025,the China Road and Bridge Corporation(CRBC)Kenya Office and Africa Star Railway Operation Company Limited(Afristar),in collaboration with the Dream Building Service Association(DBSA),held the launching ceremony for the International Free Lunch Programme at a school in the Mathare slum community of Nairobi.展开更多
On February 6,2025,Branko Balon,President of the Croatia-China Friendship Association for Cultural,Scientific and Economic Cooperation and Professor at the VSITE College of Information Technology in Zagreb.
基于IPv6的段路由(segment routing over IPv6,SRv6)作为下一代网络架构的关键使能技术,通过引入灵活的段路由转发平面,为提升网络智能化水平、拓展业务服务能力带来革新机遇.旨在全面梳理近年来SRv6的演进趋势和研究现状.首先,系统总结...基于IPv6的段路由(segment routing over IPv6,SRv6)作为下一代网络架构的关键使能技术,通过引入灵活的段路由转发平面,为提升网络智能化水平、拓展业务服务能力带来革新机遇.旨在全面梳理近年来SRv6的演进趋势和研究现状.首先,系统总结SRv6在网络架构与性能、网络管理与运维以及新兴业务支撑等方面的应用,凸显了SRv6精细调度、灵活编程、服务融合等独特优势.与此同时,深入剖析SRv6在性能与效率、可靠性与安全性、部署与演进策略这3个方面所面临的关键挑战,并重点讨论当前主流的解决思路和发展趋势.最后,立足产业生态构建、人工智能引入、行业融合创新等视角,对SRv6未来的发展方向和挑战进行前瞻性思考和展望.研究成果将为运营商构建开放、智能、安全的新一代网络提供理论参考和实践指导.展开更多
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 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.52025053 and 52235006)the Jilin Provincial Scientific and Technological Development Program(20220204119YY)the Natural Science Foundation of Shandong Province(ZR2023ME154)。
文摘Ceramic 4D printing,which integrates dynamic deformation with additive manufacturing,demonstrates significant potential in intelligent manufacturing,on-demand shaping of complex structures,and multifunctional device development.Its core advantage lies in endowing materials with environmentally responsive dynamic deformation capabilities.However,current technologies still face limitations in responsiveness,reversibility,and mechanical performance.To address these challenges,this study proposes a programmable ceramic precursor system based on synergistic reinforcement of phase-separating hydrogels and shape memory polymers,combined with a nano-ceramic particle enhancement strategy.Using stereolithography 3D printing,high-precision fabrication of complex structures was achieved.By adjusting precursor composition,programming time,and structural thickness,the phase-separation kinetics-driven delayed recovery mechanism was elucidated,enabling precise control over recovery onset time.Furthermore,the thermal response mechanism of the precursor materials is explored,along with their potential for multi-shape transformation in biomedical applications,which is further extended to shape memory polymer systems.By employing a layered printing strategy,the autonomous reversible deformation of ceramic precursors is realized,providing new possibilities for specific applications.
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 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.
基金supported by the Natural Science Foundation of the Anhui Higher Education Institutions of China(Grant Nos.2023AH040149 and 2024AH051915)the Anhui Provincial Natural Science Foundation(Grant No.2208085MF168)+1 种基金the Science and Technology Innovation Tackle Plan Project of Maanshan(Grant No.2024RGZN001)the Scientific Research Fund Project of Anhui Medical University(Grant No.2023xkj122).
文摘Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to the inability to effectively capture global information from images,CNNs can easily lead to loss of contours and textures in segmentation results.Notice that the transformer model can effectively capture the properties of long-range dependencies in the image,and furthermore,combining the CNN and the transformer can effectively extract local details and global contextual features of the image.Motivated by this,we propose a multi-branch and multi-scale attention network(M2ANet)for medical image segmentation,whose architecture consists of three components.Specifically,in the first component,we construct an adaptive multi-branch patch module for parallel extraction of image features to reduce information loss caused by downsampling.In the second component,we apply residual block to the well-known convolutional block attention module to enhance the network’s ability to recognize important features of images and alleviate the phenomenon of gradient vanishing.In the third component,we design a multi-scale feature fusion module,in which we adopt adaptive average pooling and position encoding to enhance contextual features,and then multi-head attention is introduced to further enrich feature representation.Finally,we validate the effectiveness and feasibility of the proposed M2ANet method through comparative experiments on four benchmark medical image segmentation datasets,particularly in the context of preserving contours and textures.
基金supported by the Science and Technology Innovation Programof Hunan Province(Grant No.2022RC1021)the Hunan Provincial Natural Science Foundation Project(Grant No.2023JJ60124)+1 种基金the Changsha Natural Science Foundation Project(Grant No.kq2202265)the key project of the Hunan Provincial of Education(Grant No.22A0255).
文摘Automatic pancreas segmentation plays a pivotal role in assisting physicians with diagnosing pancreatic diseases,facilitating treatment evaluations,and designing surgical plans.Due to the pancreas’s tiny size,significant variability in shape and location,and low contrast with surrounding tissues,achieving high segmentation accuracy remains challenging.To improve segmentation precision,we propose a novel network utilizing EfficientNetV2 and multi-branch structures for automatically segmenting the pancreas fromCT images.Firstly,an EfficientNetV2 encoder is employed to extract complex and multi-level features,enhancing the model’s ability to capture the pancreas’s intricate morphology.Then,a residual multi-branch dilated attention(RMDA)module is designed to suppress irrelevant background noise and highlight useful pancreatic features.And re-parameterization Visual Geometry Group(RepVGG)blocks with amulti-branch structure are introduced in the decoder to effectively integrate deep features and low-level details,improving segmentation accuracy.Furthermore,we apply re-parameterization to the model,reducing computations and parameters while accelerating inference and reducing memory usage.Our approach achieves average dice similarity coefficient(DSC)of 85.59%,intersection over union(IoU)of 75.03%,precision of 85.09%,and recall of 86.57%on the NIH pancreas dataset.Compared with other methods,our model has fewer parameters and faster inference speed,demonstrating its enormous potential in practical applications of pancreatic segmentation.
基金Supported by the National Natural Science Foundation of China(52374004)National Key R&D Program of China(2023YFF0614102,2023YFE0110900).
文摘Based on the finite element-discrete element numerical method,a numerical model of fracture propagation in deflagration fracturing was established by considering the impact of stress wave,quasi-static pressure of explosive gas,and reflection of stress wave.The model was validated against the results of physical experiments.Taking the shale reservoirs of Silurian Longmaxi Formation in Luzhou area of the Sichuan Basin as an example,the effects of in-situ stress difference,natural fracture parameters,branch wellbore spacing,delay detonation time,and angle between branch wellbore and main wellbore on fracture propagation were identified.The results show that the fracture propagation morphology in deflagration fracturing is less affected by the in-situ stress difference when it is 5-15 MPa,and the tendency of fracture intersection between branch wellbores is significantly weakened when the in-situ stress difference reaches 20 MPa.The increase of natural fracture length promotes the fracture propagation along the natural fracture direction,while the increase of volumetric natural fracture density and angle limits the fracture propagation area and reduces the probability of fracture intersection between branch wells.The larger the branch wellbore spacing,the less probability of the fracture intersection between branch wells,allowing for the fracture propagation in multiple directions.Increasing the delay detonation time decreases the fracture spacing between branch wellbores.When the angle between the branch wellbore and the main wellbore is 45°and 90°,there is a tendency of fracture intersection between branch wellbores.
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 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.
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 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The National Natural Science Foundation of China(No.62401168,62401139,62401170)China Postdoctoral Science Foundation(No.2023MD744197)+2 种基金Postdoctoral Fellowship Program of CPSF(No.GZC20230631)Project for Enhancing Young and Middle-aged Teacher’s Research Basis Ability in Colleges of Guangxi(No.2023KY0218)Guangxi Key Laboratory Foundation of Optoelectronic Information Processing(No.GD23102)。
文摘A programmable low-profile array antenna based on nematic liquid crystals(NLCs)is proposed.Each antenna unit comprises a square patch radiating structure and a tunable NLC-based phase shifter capable of achieving a phase shift exceeding 360°with high linearity.First,the above 64 antenna units are periodically arranged into an 8×8 NLC-based antenna array,and the bias voltage of the NLC-based phase shifter loaded on the antenna unit is adjusted through the control of the field-programmable gate array(FPGA)programming sequences.This configuration enables precise phase changes for all 64 channels.Numerical simulation,sample processing,and experimental measurements of the antenna array are conducted to validate the performance of the antenna.The numerical and experimental results demonstrate that the proposed antenna performs well within the frequency range of 19.5-20.5 GHz,with a 3 dB relative bandwidth of 10%and a maximum main lobe gain of 14.1 dBi.A maximum scanning angle of±34°is achieved through the adjustment of the FPGA programming sequence.This NLC-based programmable array antenna shows promising potential for applications in satellite communication.
基金funded by the project of Guizhou Power Grid Co.,Ltd.Guiyang Power Supply Bureau(No.GZKJXM20232317).
文摘To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location(FL)research of distribution networks with complex topologies,this paper proposes an FL method of Multi-Branch distribution line based on Maximal Overlap Discrete Wavelet Transform(MODWT)combined with the improved Teager Energy Operator(TEO).Firstly,the current and voltage Traveling Wave(TW)signals at the head of each line are extracted,and the fault-induced components are obtained to determine the fault line by analyzing the polarity of the mutation amount of fault voltage and current TWs.Subsequently,the fault discrimination mark is calculated based on the fault-induced line-mode current and the zero-mode voltage,with the fault type determined by comparing each mark’s value against the fault discrimination table,transforming the FL problem in complex topology into a single-line FL problem.Finally,the fault voltage TW is extracted fromthe fault line,and the wave head detection method based on MODWT combined with improved TEO is used to precisely identify the arrival instants of both the first TW wave head and its first reflection at each line terminal,and then the FL result is calculated by applying the double-ended TW ranging formula that removes the influence of wave velocity.Simulation results demonstrate that the proposed method accurately identifies the fault line and types of faults occurring and maintains the ranging accuracy within 0.5%under various fault scenarios.
文摘On April 19th,"the Youth Table Tennis Programme—Photo Exhibition of Zhou Enlai and the Bandung Conference&China-ASEAN(Indonesia)Youth Table Tennis Training Camp"opened in Jakarta,Indonesia.The event was guided by the Chinese Embassy in Indonesia and co-organised by the ASEAN-China Centre(ACC),the Memorial to Zhou Enlai and Deng Yingchao,the China Friendship Foundation for Peace and Development,the Beijing One Heart Sphere Charity Foundation,and the Enlai Foundation.
文摘On January 15,2025,the China Road and Bridge Corporation(CRBC)Kenya Office and Africa Star Railway Operation Company Limited(Afristar),in collaboration with the Dream Building Service Association(DBSA),held the launching ceremony for the International Free Lunch Programme at a school in the Mathare slum community of Nairobi.
文摘On February 6,2025,Branko Balon,President of the Croatia-China Friendship Association for Cultural,Scientific and Economic Cooperation and Professor at the VSITE College of Information Technology in Zagreb.
文摘基于IPv6的段路由(segment routing over IPv6,SRv6)作为下一代网络架构的关键使能技术,通过引入灵活的段路由转发平面,为提升网络智能化水平、拓展业务服务能力带来革新机遇.旨在全面梳理近年来SRv6的演进趋势和研究现状.首先,系统总结SRv6在网络架构与性能、网络管理与运维以及新兴业务支撑等方面的应用,凸显了SRv6精细调度、灵活编程、服务融合等独特优势.与此同时,深入剖析SRv6在性能与效率、可靠性与安全性、部署与演进策略这3个方面所面临的关键挑战,并重点讨论当前主流的解决思路和发展趋势.最后,立足产业生态构建、人工智能引入、行业融合创新等视角,对SRv6未来的发展方向和挑战进行前瞻性思考和展望.研究成果将为运营商构建开放、智能、安全的新一代网络提供理论参考和实践指导.
