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
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
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
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
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
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
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
Inspired by the way sea turtles rely on the Earth’s magnetic field for navigation and locomotion,a novel magnetic soft robotic turtle with programmable magnetization has been developed and investigated to achieve bio...Inspired by the way sea turtles rely on the Earth’s magnetic field for navigation and locomotion,a novel magnetic soft robotic turtle with programmable magnetization has been developed and investigated to achieve biomimetic locomotion patterns such as straight-line swimming and turning swimming.The soft robotic turtle(12.50 mm in length and 0.24 g in weight)is integrated with an Ecoflex-based torso and four magnetically programmed acrylic elastomer VHB-based limbs containing samarium-iron–nitrogen particles,and was able to carry a load more than twice its own weight.Similar to the limb locomotion characteristics of sea turtles,the magnetic torque causes the four limbs to mimic sinusoidal bending deformation under the influence of an external magnetic field,so that the turtle swims continuously forward.Significantly,when the bending deformation magnitudes of its left and right limbs differ,the soft robotic turtle switches from straight-line to turning swimming at 6.334 rad/s.Furthermore,the tracking swimming activities of the soft robotic turtle along specific planned paths,such as square-shaped,S-shaped,and double U-shaped maze,is anticipated to be utilized for special detection and targeted drug delivery,among other applications owing to its superior remote directional control ability.展开更多
Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum information.In this ...Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum information.In this paper,we propose pixelated programmable Si_(3)N_(4)PICs with record-high 20-level intermediate states at 785 nm wavelength.Such flexibility in phase or amplitude modulation is achieved by a programmable Sb_(2)S_(3)matrix,the footprint of whose elements can be as small as 1.2μm,limited only by the optical diffraction limit of anin-house developed pulsed laser writing system.We believe our work lays the foundation for laser-writing ultra-high-level(20 levels and even more)programmable photonic systems and metasurfaces based on phase change materials,which could catalyze diverse applications such as programmable neuromorphic photonics,biosensing,optical computing,photonic quantum computing,and reconfigurable metasurfaces.展开更多
The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-bran...The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.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
Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges i...Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.展开更多
Essential amino acids(EAAs)deprivation is a potential antitumor approach because EAAs are critical for tumor growth.To efficiently inhibit tumor growth,continuous deprivation of EAAs is required,how-ever,continuous de...Essential amino acids(EAAs)deprivation is a potential antitumor approach because EAAs are critical for tumor growth.To efficiently inhibit tumor growth,continuous deprivation of EAAs is required,how-ever,continuous deprivation without precise control will introduce toxicity to normal cells.Herein,a programmable double-unlock nanocomplex(ROCK)was prepared,which could self-supply phenylalanine ammonia-lyase(PAL)to tumor cells for phenylalanine(Phe)deprivation.ROCK was double-locked in physiological conditions when administered systemically.While ROCK actively targeted to tumor cells by integrinαvβ3/5 and CD44,ROCK was firstly unlocked by cleavage of protease on tumor cell membrane,exposing CendR and R8 to enhance endocytosis.Then,hyaluronic acid was digested by hyaluronidase overexpressed in endo/lysosome of tumor cells,in which ROCK was secondly unlocked,resulting in pro-moting endo/lysosome escape and PAL plasmid(pPAL)release.Released pPAL could sustainably express PAL in host tumor cells until the self-supplied PAL precisely and successfully deprived Phe,thereby block-ing the protein synthesis and killing tumor cells specifically.Overall,our precise Phe deprivation strategy effectively inhibited tumor growth with no observable toxicity to normal cells,providing new insights to efficiently remove intratumoral nutrition for cancer therapy.展开更多
Elastic metamaterials with unusual elastic properties offer unprecedented ways to modulate the polarization and propagation of elastic waves.However,most of them rely on the resonant structural components,and thus are...Elastic metamaterials with unusual elastic properties offer unprecedented ways to modulate the polarization and propagation of elastic waves.However,most of them rely on the resonant structural components,and thus are frequency-dependent and unchangeable.Here,we present a reconfigurable 2D mechanism-based metamaterial which possesses transformable and frequency-independent elastic properties.Based on the proposed mechanism-based metamaterial,interesting functionalities,such as ternarycoded elastic wave polarizer and programmable refraction,are demonstrated.Particularly,unique ternary-coded polarizers,with 1-trit polarization filtering and 2-trit polarization separating of longitudinal and transverse waves,are first achieved.Then,the strong anisotropy of the proposed metamaterial is harnessed to realize positive-negative bi-refraction,only-positive refraction,and only-negative refraction.Finally,the wave functions with detailed microstructures are numerically verified.展开更多
In this work,a novel one-time-programmable memory unit based on a Schottky-type p-GaN diode is proposed.During the programming process,the junction switches from a high-resistance state to a low-resistance state throu...In this work,a novel one-time-programmable memory unit based on a Schottky-type p-GaN diode is proposed.During the programming process,the junction switches from a high-resistance state to a low-resistance state through Schottky junction breakdown,and the state is permanently preserved.The memory unit features a current ratio of more than 10^(3),a read voltage window of 6 V,a programming time of less than 10^(−4)s,a stability of more than 108 read cycles,and a lifetime of far more than 10 years.Besides,the fabrication of the device is fully compatible with commercial Si-based GaN process platforms,which is of great significance for the realization of low-cost read-only memory in all-GaN integration.展开更多
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 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 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 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 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 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 National Natural Science Foundation of China(Grant nos.52275290,51905222)Natural Science Foundation of Jiangsu Province(Grant no.BK20211068)+2 种基金Research Project of State Key Laboratory of Mechanical System and Vibration(Grant no.MSV202419)Major Program of National Natural Science Foundation of China(NSFC)for Basic Theory and Key Technology of Tri-Co Robots(Grant no.92248301)Opening project of the Key Laboratory of Bionic Engineering(Ministry of Education),Jilin University(Grant no.KF2023006).
文摘Inspired by the way sea turtles rely on the Earth’s magnetic field for navigation and locomotion,a novel magnetic soft robotic turtle with programmable magnetization has been developed and investigated to achieve biomimetic locomotion patterns such as straight-line swimming and turning swimming.The soft robotic turtle(12.50 mm in length and 0.24 g in weight)is integrated with an Ecoflex-based torso and four magnetically programmed acrylic elastomer VHB-based limbs containing samarium-iron–nitrogen particles,and was able to carry a load more than twice its own weight.Similar to the limb locomotion characteristics of sea turtles,the magnetic torque causes the four limbs to mimic sinusoidal bending deformation under the influence of an external magnetic field,so that the turtle swims continuously forward.Significantly,when the bending deformation magnitudes of its left and right limbs differ,the soft robotic turtle switches from straight-line to turning swimming at 6.334 rad/s.Furthermore,the tracking swimming activities of the soft robotic turtle along specific planned paths,such as square-shaped,S-shaped,and double U-shaped maze,is anticipated to be utilized for special detection and targeted drug delivery,among other applications owing to its superior remote directional control ability.
基金funded by the National Nature Science Foundation of China(Grant Nos.52175509 and 52130504)National Key Research and Development Program of China(2017YFF0204705)2021 Postdoctoral Innovation Research Plan of Hubei Province(0106100226)。
文摘Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum information.In this paper,we propose pixelated programmable Si_(3)N_(4)PICs with record-high 20-level intermediate states at 785 nm wavelength.Such flexibility in phase or amplitude modulation is achieved by a programmable Sb_(2)S_(3)matrix,the footprint of whose elements can be as small as 1.2μm,limited only by the optical diffraction limit of anin-house developed pulsed laser writing system.We believe our work lays the foundation for laser-writing ultra-high-level(20 levels and even more)programmable photonic systems and metasurfaces based on phase change materials,which could catalyze diverse applications such as programmable neuromorphic photonics,biosensing,optical computing,photonic quantum computing,and reconfigurable metasurfaces.
基金This work was funded by the project of State Grid Hunan Electric Power Research Institute(No.SGHNDK00PWJS2210033).
文摘The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.
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Double First-Class Innovation Research Project for People’s Public Security University of China(2023SYL08).
文摘Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.
基金supported by funds of Sichuan Province for Distinguished Young Scholar(No.2021JDJQ0037)the National Natural Science Foundation of China(No.82172094).
文摘Essential amino acids(EAAs)deprivation is a potential antitumor approach because EAAs are critical for tumor growth.To efficiently inhibit tumor growth,continuous deprivation of EAAs is required,how-ever,continuous deprivation without precise control will introduce toxicity to normal cells.Herein,a programmable double-unlock nanocomplex(ROCK)was prepared,which could self-supply phenylalanine ammonia-lyase(PAL)to tumor cells for phenylalanine(Phe)deprivation.ROCK was double-locked in physiological conditions when administered systemically.While ROCK actively targeted to tumor cells by integrinαvβ3/5 and CD44,ROCK was firstly unlocked by cleavage of protease on tumor cell membrane,exposing CendR and R8 to enhance endocytosis.Then,hyaluronic acid was digested by hyaluronidase overexpressed in endo/lysosome of tumor cells,in which ROCK was secondly unlocked,resulting in pro-moting endo/lysosome escape and PAL plasmid(pPAL)release.Released pPAL could sustainably express PAL in host tumor cells until the self-supplied PAL precisely and successfully deprived Phe,thereby block-ing the protein synthesis and killing tumor cells specifically.Overall,our precise Phe deprivation strategy effectively inhibited tumor growth with no observable toxicity to normal cells,providing new insights to efficiently remove intratumoral nutrition for cancer therapy.
基金supported by the National Key R&D Program of China(No.2021YFE0110900)the National Natural Science Foundation of China(Nos.U22B2078 and 11991033)。
文摘Elastic metamaterials with unusual elastic properties offer unprecedented ways to modulate the polarization and propagation of elastic waves.However,most of them rely on the resonant structural components,and thus are frequency-dependent and unchangeable.Here,we present a reconfigurable 2D mechanism-based metamaterial which possesses transformable and frequency-independent elastic properties.Based on the proposed mechanism-based metamaterial,interesting functionalities,such as ternarycoded elastic wave polarizer and programmable refraction,are demonstrated.Particularly,unique ternary-coded polarizers,with 1-trit polarization filtering and 2-trit polarization separating of longitudinal and transverse waves,are first achieved.Then,the strong anisotropy of the proposed metamaterial is harnessed to realize positive-negative bi-refraction,only-positive refraction,and only-negative refraction.Finally,the wave functions with detailed microstructures are numerically verified.
基金supported in part by the National Key Research and Development Program of China under Grant 2022YFB3604400in part by the Youth Innovation Promotion Association of Chinese Academy Sciences (CAS)+4 种基金in part by the CAS-Croucher Funding Scheme under Grant CAS22801in part by National Natural Science Foundation of China under Grant 62334012, Grant 62074161, Grant 62004213, Grant U20A20208, and Grant 62304252in part by the Beijing Municipal Science and Technology Commission project under Grant Z201100008420009 and Grant Z211100007921018in part by the University of CASin part by the IMECAS-HKUST-Joint Laboratory of Microelectronics
文摘In this work,a novel one-time-programmable memory unit based on a Schottky-type p-GaN diode is proposed.During the programming process,the junction switches from a high-resistance state to a low-resistance state through Schottky junction breakdown,and the state is permanently preserved.The memory unit features a current ratio of more than 10^(3),a read voltage window of 6 V,a programming time of less than 10^(−4)s,a stability of more than 108 read cycles,and a lifetime of far more than 10 years.Besides,the fabrication of the device is fully compatible with commercial Si-based GaN process platforms,which is of great significance for the realization of low-cost read-only memory in all-GaN integration.
