With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has surged.In this work,a novel gradient-layered architecture was design based on single-pore hollow lignin...With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has surged.In this work,a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres(HLNPs)-intercalated two-dimensional transition metal carbide(Ti_(3)C_(2)T_(x) MXene)for fabricating highly stretchable and durable supercapacitors.By depositing and inserting HLNPs in the MXene layers with a bottom-up decreasing gradient,a multilayered porous MXene structure with smooth ion channels was constructed by reducing the overstacking of MXene lamella.Moreover,the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and MXene to improve ion and electron accessibility,thus better utilizing the pseudocapacitive property of lignin.All these strategies effectively enhanced the capacitive performance of the electrodes.In addition,HLNPs,which acted as a protective phase for MXene layer,enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the electrodes.Flexible electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600%uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm^(−2)(241 F g^(−1))and 514 mF cm^(−2)(95 F g^(−1)),respectively.Moreover,their capacitances were well preserved after 1000 times of 600%stretch-release cycling.This study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials.展开更多
It’s possible for malicious operators to seize hold of electrical control systems, for instance, the engine control unit of driverless vehicles, from various vectors, e.g. autonomic control system, remote vehicle acc...It’s possible for malicious operators to seize hold of electrical control systems, for instance, the engine control unit of driverless vehicles, from various vectors, e.g. autonomic control system, remote vehicle access, or human drivers. To mitigate potential risks, this paper provides the inauguration study by proposing a theoretical framework in the physical, human and cyber triad. Its goal is to, at each time point, detect adversary control behaviors and protect control systems against malicious operations via integrating a variety of methods. This paper only proposes a theoretical framework which tries to indicate possible threats. With the support of the framework, the security system can lightly reduce the risk. The development and implementation of the system are out of scope.展开更多
This paper adopts the Global Workspace Theory as a neuro-scientifically plausible theory for developing conscious cognitive architecture.The Global Workspace Theory’s compatibility with the working mechanisms underne...This paper adopts the Global Workspace Theory as a neuro-scientifically plausible theory for developing conscious cognitive architecture.The Global Workspace Theory’s compatibility with the working mechanisms underneath human brains is enhanced by the implementation of different cognitive features based on this framework.Amongst the topics in the literature for intelligent systems,we start with attention,memory and learning mechanisms,and corresponding experiments are summarized here.We also discuss how other topics of cognitive robotics could be developed based on these three basic components,and their correlations.This provides a foundation for future long-term development of cognitive architectures of cognitive robots.The research in this paper follows the incremental research pathway for the architecture implementation,which is consistent with the Biologically Inspired Cognitive Architecture roadmap.展开更多
This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named C...This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named Clarion)has been justified by,and validated against,psychological data,findings,and theoretical constructs.One important theoretical background for it is the dual-process theories,which led to its overall two-level structuring in a hybrid neuro-symbolic way.Furthermore,given the recent advances in AI and computing technology,LLMs are being incorporated into the model to better capture human intuition and instinct(and implicit processes in general),in order to further enhance Clarion.Integrating Clarion and LLMs can also help to develop AI systems that are more capable,more reliable,and more human-like.Overall,the paper advocates a multidisciplinary approach towards developing better models for cognitive science and for AI.展开更多
The Multipurpose Enhanced Cognitive Architecture(MECA)is a cognitive framework designed to model complex,human-like processes across multiple domains.Originally focusing on implementing a Dual Process Theory approach ...The Multipurpose Enhanced Cognitive Architecture(MECA)is a cognitive framework designed to model complex,human-like processes across multiple domains.Originally focusing on implementing a Dual Process Theory approach and integrating a machine consciousness mechanism based on Global Workspace Theory,MECA has been updated to integrate a dual-layer subsumption mechanism,enabling both reactive and deliberative behaviors,dynamic goal setting and a visual-spatial memory subsystem,enhancing MECA’s capacity for real-world interaction and adaptive behavior.Also,with the introduction of the new computational ideas’knowledge representation scheme,MECA proposes to organize knowledge dynamically to handle context-sensitive reasoning and flexible categorization.MECA’s implementation relies on the Cognitive Systems Toolkit(CST),facilitating its integration with cutting-edge technologies.MECA and CST are being continuously developed and updated,aligned,and open to incorporate the latest AI artifacts and methodologies.This approach ensures the delivery of organized,monitorable,auditable,and controllable AI solutions,significantly reducing reliance on“black box”cognitive processes while enhancing transparency and accountability in AI-driven systems.These updates reinforce MECA’s potential as a robust architecture for developing autonomous,adaptable,and context-aware AI systems capable of real-world interaction and adaptive learning.展开更多
Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial...Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial for acquiring stable NiSe2-based materials for sodium-ion batteries(SIBs),Herein,a stress dissipation strategy driven by architecture engineering is proposed,which can achieve ultrafast and ultralong sodium storage properties.Different from the conventional sphere-like or rod-like architecture,the three-dimensional(3D)flower-like NiSe_(2)@C composite is delicately designed and assembled with onedimensional nanorods and carbon framework.More importantly,the fundamental mechanism of improved structure stability is unveiled by simulations and experimental results simultaneously.It demonstrates that this designed multidimensional flower-like architecture with dispersed nanorods can balance the structural mismatch,avoid concentrated local strain,and relax the internal stress,mainly induced by the unavoidable volume variation during the repeated conversion processes.Moreover,it can provide more Na^(+)-storage sites and multi-directional migration pathways,leading to a fast Na^(+)-migration channel with boosted reaction kinetic.As expected,it delivers superior rate performance(441 mA h g^(-1)at 5.0 A g^(-1))and long cycling stability(563 mA h g^(-1)at 1.0 A g^(-1)over 1000 cycles)for SIBs.This work provides useful insights for designing high-performance conversion-based anode materials for SIBs.展开更多
The flexible satellite batch production line is a complex discrete production system with multiple cross-disciplinary fields and mixed serial parallel tasks.As the source of the satellite batch production line process...The flexible satellite batch production line is a complex discrete production system with multiple cross-disciplinary fields and mixed serial parallel tasks.As the source of the satellite batch production line process,the warehousing system has urgent needs such as uncertain production scale and rapid iteration and optimization of business processes.Therefore,the requirements and architecture of complex discrete warehousing systems such as flexible satellite batch production lines are studied.The physical system of intelligent equipment is abstracted as a digital model to form the underlying module,and a digital fusion framework of“business domain+middleware platform+intelligent equipment information model”is constructed.The granularity of microservice splitting is calculated based on the dynamic correlation relationship between user access instances and database table structures.The general warehousing functions of the platform are divided to achieve module customization,addition,and configuration.An open discrete warehousing system based on microservices is designed.Software architecture and design develop complex discrete warehousing systems based on the SpringCloud framework.This architecture achieves the decoupling of business logic and physical hardware,enhances the maintainability and scalability of the system,and greatly improves the system’s adaptability to different complex discrete warehousing business scenarios.展开更多
The recent discovery of natural gas within the fifth member of the Xujiahe Formation(T_(3)x_(5))in the Dongfeng area within the Sichuan Basin highlights the significant exploration potential of this member.However,the...The recent discovery of natural gas within the fifth member of the Xujiahe Formation(T_(3)x_(5))in the Dongfeng area within the Sichuan Basin highlights the significant exploration potential of this member.However,the unconvincing previous understanding of the sedimentary microfacies,combined with a total lack of studies on the sand body architecture and reservoir distribution,hampers the further exploration of this member.Using core data,log curves,and seismic data,along with sedimentary microfacies analysis,this study investigated the interfaces between the sand bodies of various scales in the Dongfeng area.Furthermore,this study explored the morphological characteristics,types,and stacking patterns of these sand bodies and determined the distributions of sand bodies and reservoirs in the area.The results indicate that the first sand group of the T_(3)x_(5) member(T_(3)x^(1)_(5))exhibits delta-front deposits,including subaqueous distributary channels,sheet sands,and interdistributary bays.Seven levels of sand body interfaces are identified in the T_(3)x^(1)_(5) sand group.Among them,the interfaces of the first and second levels were identifed only in cores,those of the third and fourth levels were recog-nizable from cores combined with log curves,while those of the fifth,sixth,and seventh levels were distinguishable using seismic data.Three superimposed subaqueous distributary channel complexes are found in the Dongfeng area.Among them,complex 1 in the northwest exhibits the strongest water body energy,while complex 2 in the south displays the weakest.Complex 2 was formed earlier than com-plexes 1 and 3.Also,complex 1 is further subdivided into three vertically stacked subaqueous distrib-utary channels.The subdivision of sedimentary microfacies in the T_(3)x_(5) member reveals nine lithofacies types.Among them,stacked pancake-shaped,carbonaceous debris-bearing,massive,and cross-bedded medium-grained sandstones are considered favorable lithofacies.These four lithofacies types exhibit high porosity,as well as low natural gamma-ray(GR)values,low-to-medium deep investigate double lateral resistivity(RD),and high interval transit time(AC)on the log curves.Additionally,the reservoir distribution in the Dongfeng area was delineated based on the characterization of the favorable lith-ofacies.This study serves as a guide for future exploration and evaluation of the T_(3)x_(5) member in the Dongfeng area while also augmenting the methodologies for describing tight sandstone reservoirs.展开更多
End-to-end object detection Transformer(DETR)successfully established the paradigm of the Transformer architecture in the field of object detection.Its end-to-end detection process and the idea of set prediction have ...End-to-end object detection Transformer(DETR)successfully established the paradigm of the Transformer architecture in the field of object detection.Its end-to-end detection process and the idea of set prediction have become one of the hottest network architectures in recent years.There has been an abundance of work improving upon DETR.However,DETR and its variants require a substantial amount of memory resources and computational costs,and the vast number of parameters in these networks is unfavorable for model deployment.To address this issue,a greedy pruning(GP)algorithm is proposed,applied to a variant denoising-DETR(DN-DETR),which can eliminate redundant parameters in the Transformer architecture of DN-DETR.Considering the different roles of the multi-head attention(MHA)module and the feed-forward network(FFN)module in the Transformer architecture,a modular greedy pruning(MGP)algorithm is proposed.This algorithm separates the two modules and applies their respective optimal strategies and parameters.The effectiveness of the proposed algorithm is validated on the COCO 2017 dataset.The model obtained through the MGP algorithm reduces the parameters by 49%and the number of floating point operations(FLOPs)by 44%compared to the Transformer architecture of DN-DETR.At the same time,the mean average precision(mAP)of the model increases from 44.1%to 45.3%.展开更多
The size of the Audio and Video(AV)content of the 8K program is four times larger than that of 4K content,providing viewers with a more ideal audiovisual experience while placing higher demands on the capability and e...The size of the Audio and Video(AV)content of the 8K program is four times larger than that of 4K content,providing viewers with a more ideal audiovisual experience while placing higher demands on the capability and efficiency of document preparation and processing,signal transmission,and scheduling.However,it is difficult to meet the high robustness requirements of 8K broadcast services because the existing broadcast system architecture is limited by efficiency,cost,and other factors.In this study,an 8K Ultra-High-Definition(UHD)TV program broadcast scheme was designed.The verification results show that the scheme is high quality,highly efficient,and robust.In particular,in the research,the file format normalizing module was first placed in the broadcast area instead of the file preparation area,and the low-compression transmission scheme of the all-IP signal JPEG XS was designed in the signal transmission area for improving the efficiency of the scheme.Next,to reduce the impact on the robustness of broadcast services,the broadcast control logic of the broadcast core components is optimized.Finally,a series of 8K TV program broadcasting systems have been implemented and their performance has been verified.The results show that the system meets the efficiency and robustness requirements of a high-quality 8K AV broadcast system,and thus has a high degree of practicability.展开更多
Root system architecture has often been overlooked in plant research despite its critical role in plant adaptation to environmental conditions.This study focused on the root system architecture of the desert shrub Rea...Root system architecture has often been overlooked in plant research despite its critical role in plant adaptation to environmental conditions.This study focused on the root system architecture of the desert shrub Reaumuria soongorica in the Alxa steppe desert,Northwest China.Plant samples were collected during May-September 2019.Using excavation methods,in situ measurements,and root scanning techniques,we analyzed the root distribution,topology,and branching patterns of R.soongorica across an age sequence of 7-51 a.Additionally,we investigated the allometric relationships of root collar diameter with total coarse root length,biomass,and topological parameters.The results showed that the roots of R.soongorica were predominantly concentrated in shallow soil layers(10-50 cm),with lateral root branching and biomass allocation increasing with shrub age.The root topology exhibited a herringbone-like structure,with average topological and modified topological indices of 0.89 and 0.96,respectively,both of which adjusted with shrub age.The root system displayed a self-similar branching pattern,maintaining a constant cross-sectional area ratio of 1.13 before and after branching,deviating from the area-preserving rule.These adaptive traits allow R.soongorica to efficiently expand its nutrient acquisition zone,minimize internal competition,and optimize resource uptake from the upper soil layers.Furthermore,significant linear relationships were observed between log10-transformed root collar diameter and log10-transformed total coarse root length,biomass,and topological parameters.These findings advance non-destructive approaches for studying root characteristics and contribute to the development of root-related models.Besides,this study provides new insights into the adaptive strategies of R.soongorica under extreme drought conditions,offering valuable guidance for species selection and cultivation in desert restoration efforts.展开更多
The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to case...The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.展开更多
By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-grow...By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.展开更多
Rice(Oryza sativa)plant architecture and grain shape,which determine grain quality and yield,are modulatedby auxin and brassinosteroid via regulation of cell elongation and proliferation.We review the signaltransducti...Rice(Oryza sativa)plant architecture and grain shape,which determine grain quality and yield,are modulatedby auxin and brassinosteroid via regulation of cell elongation and proliferation.We review the signaltransduction of these hormones and the crosstalk between their signals on the regulation of rice plantarchitecture and grain shape.展开更多
Plant height,spike,leaf,stem and grain morphologies are key components of plant architecture and related to wheat yield.A wheat(Triticum aestivum L.)mutant,wpa1,displaying temperaturedependent pleiotropic developmenta...Plant height,spike,leaf,stem and grain morphologies are key components of plant architecture and related to wheat yield.A wheat(Triticum aestivum L.)mutant,wpa1,displaying temperaturedependent pleiotropic developmental anomalies,was isolated.The WPA1 gene,encoding a von Willebrand factor type A(vWA)domain protein,was located on chromosome arm 7DS and isolated by map-based cloning.The functionality of WPA1 was validated by multiple independent EMS-induced mutants and gene editing.Phylogenetic analysis revealed that WPA1 is monocotyledon-specific in higher plants.The identification of WPA1 provides opportunity to study the temperature regulated wheat development and grain yield.展开更多
Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and p...Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and poor fast‐charging capability limiting its commercial applications.Here,we propose a multilevel carbon architecture with vertical graphene sheets(VGSs)grown on surfaces of subnanoscopically and homogeneously dispersed Si–C composite nanospheres,which are subsequently embedded into a carbon matrix(C/VGSs@Si–C).Subnanoscopic C in the Si–C nanospheres,VGSs,and carbon matrix form a three‐dimensional conductive and robust network,which significantly improves the conductivity and suppresses the volume expansion of Si,thereby boosting charge transport and improving electrode stability.The VGSs with vast exposed edges considerably increase the contact area with the carbon matrix and supply directional transport channels through the entire material,which boosts charge transport.The carbon matrix encapsulates VGSs@Si–C to decrease the specific surface area and increase tap density,thus yielding high first Coulombic efficiency and electrode compaction density.Consequently,C/VGSs@Si–C delivers excellent Li‐ion storage performances under industrial electrode conditions.In particular,the full cells show high energy densities of 603.5 Wh kg^(−1)and 1685.5 Wh L^(−1)at 0.1 C and maintain 80.7%of the energy density at 3 C.展开更多
Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human ...Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.展开更多
With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 pre...With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 presents a new business model of“Internet of everything,intelligent leading,data driving,shared services,cross-border integration,and universal innovation”.The network boundaries are becoming increasingly blurred,NCMS is facing security risks such as equipment unauthorized use,account theft,static and extensive access control policies,unauthorized access,supply chain attacks,sensitive data leaks,and industrial control vulnerability attacks.Traditional security architectures mainly use information security technology,which cannot meet the active security protection requirements of NCMS.In order to solve the above problems,this paper proposes an integrated cloud-edge-terminal security system architecture of NCMS.It adopts the zero trust concept and effectively integrates multiple security capabilities such as network,equipment,cloud computing environment,application,identity,and data.It adopts a new access control mode of“continuous verification+dynamic authorization”,classified access control mechanisms such as attribute-based access control,rolebased access control,policy-based access control,and a new data security protection system based on blockchain,achieving“trustworthy subject identity,controllable access behavior,and effective protection of subject and object resources”.This architecture provides an active security protection method for NCMS in the digital transformation of large enterprises,and can effectively enhance network security protection capabilities and cope with increasingly severe network security situations.展开更多
To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new lig...To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.展开更多
Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper anal...Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics.展开更多
基金supported by Natural Science and Engineering Research Council of Canada(RGPIN-2017-06737)Canada Research Chairs program,the National Key Research and Development Program of China(2017YFD0601005,2022YFD0904201)+1 种基金the National Natural Science Foundation of China(51203075)the China Scholarship Council(Grant No.CSC202208320361).
文摘With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has surged.In this work,a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres(HLNPs)-intercalated two-dimensional transition metal carbide(Ti_(3)C_(2)T_(x) MXene)for fabricating highly stretchable and durable supercapacitors.By depositing and inserting HLNPs in the MXene layers with a bottom-up decreasing gradient,a multilayered porous MXene structure with smooth ion channels was constructed by reducing the overstacking of MXene lamella.Moreover,the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and MXene to improve ion and electron accessibility,thus better utilizing the pseudocapacitive property of lignin.All these strategies effectively enhanced the capacitive performance of the electrodes.In addition,HLNPs,which acted as a protective phase for MXene layer,enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the electrodes.Flexible electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600%uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm^(−2)(241 F g^(−1))and 514 mF cm^(−2)(95 F g^(−1)),respectively.Moreover,their capacitances were well preserved after 1000 times of 600%stretch-release cycling.This study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials.
文摘It’s possible for malicious operators to seize hold of electrical control systems, for instance, the engine control unit of driverless vehicles, from various vectors, e.g. autonomic control system, remote vehicle access, or human drivers. To mitigate potential risks, this paper provides the inauguration study by proposing a theoretical framework in the physical, human and cyber triad. Its goal is to, at each time point, detect adversary control behaviors and protect control systems against malicious operations via integrating a variety of methods. This paper only proposes a theoretical framework which tries to indicate possible threats. With the support of the framework, the security system can lightly reduce the risk. The development and implementation of the system are out of scope.
基金Supported by the European Union’s Horizon Europe research and innovation program(101120727-PRIMI).
文摘This paper adopts the Global Workspace Theory as a neuro-scientifically plausible theory for developing conscious cognitive architecture.The Global Workspace Theory’s compatibility with the working mechanisms underneath human brains is enhanced by the implementation of different cognitive features based on this framework.Amongst the topics in the literature for intelligent systems,we start with attention,memory and learning mechanisms,and corresponding experiments are summarized here.We also discuss how other topics of cognitive robotics could be developed based on these three basic components,and their correlations.This provides a foundation for future long-term development of cognitive architectures of cognitive robots.The research in this paper follows the incremental research pathway for the architecture implementation,which is consistent with the Biologically Inspired Cognitive Architecture roadmap.
文摘This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named Clarion)has been justified by,and validated against,psychological data,findings,and theoretical constructs.One important theoretical background for it is the dual-process theories,which led to its overall two-level structuring in a hybrid neuro-symbolic way.Furthermore,given the recent advances in AI and computing technology,LLMs are being incorporated into the model to better capture human intuition and instinct(and implicit processes in general),in order to further enhance Clarion.Integrating Clarion and LLMs can also help to develop AI systems that are more capable,more reliable,and more human-like.Overall,the paper advocates a multidisciplinary approach towards developing better models for cognitive science and for AI.
基金Supported by the Sao Paulo Research Foundation(FAPESP),CPE SMARTNESS(2021/00199-8)and CEPID/BRAINN(2013/07559-3).
文摘The Multipurpose Enhanced Cognitive Architecture(MECA)is a cognitive framework designed to model complex,human-like processes across multiple domains.Originally focusing on implementing a Dual Process Theory approach and integrating a machine consciousness mechanism based on Global Workspace Theory,MECA has been updated to integrate a dual-layer subsumption mechanism,enabling both reactive and deliberative behaviors,dynamic goal setting and a visual-spatial memory subsystem,enhancing MECA’s capacity for real-world interaction and adaptive behavior.Also,with the introduction of the new computational ideas’knowledge representation scheme,MECA proposes to organize knowledge dynamically to handle context-sensitive reasoning and flexible categorization.MECA’s implementation relies on the Cognitive Systems Toolkit(CST),facilitating its integration with cutting-edge technologies.MECA and CST are being continuously developed and updated,aligned,and open to incorporate the latest AI artifacts and methodologies.This approach ensures the delivery of organized,monitorable,auditable,and controllable AI solutions,significantly reducing reliance on“black box”cognitive processes while enhancing transparency and accountability in AI-driven systems.These updates reinforce MECA’s potential as a robust architecture for developing autonomous,adaptable,and context-aware AI systems capable of real-world interaction and adaptive learning.
基金the financial support from the Guangxi Natural Science Foundation(grant no.2021GXNSFDA075012,2023GXNSFGA026002)National Natural Science Foundation of China(52104298,22075073,52362027,52462029)Fundamental Research Funds for the Central Universities(531107051077).
文摘Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial for acquiring stable NiSe2-based materials for sodium-ion batteries(SIBs),Herein,a stress dissipation strategy driven by architecture engineering is proposed,which can achieve ultrafast and ultralong sodium storage properties.Different from the conventional sphere-like or rod-like architecture,the three-dimensional(3D)flower-like NiSe_(2)@C composite is delicately designed and assembled with onedimensional nanorods and carbon framework.More importantly,the fundamental mechanism of improved structure stability is unveiled by simulations and experimental results simultaneously.It demonstrates that this designed multidimensional flower-like architecture with dispersed nanorods can balance the structural mismatch,avoid concentrated local strain,and relax the internal stress,mainly induced by the unavoidable volume variation during the repeated conversion processes.Moreover,it can provide more Na^(+)-storage sites and multi-directional migration pathways,leading to a fast Na^(+)-migration channel with boosted reaction kinetic.As expected,it delivers superior rate performance(441 mA h g^(-1)at 5.0 A g^(-1))and long cycling stability(563 mA h g^(-1)at 1.0 A g^(-1)over 1000 cycles)for SIBs.This work provides useful insights for designing high-performance conversion-based anode materials for SIBs.
文摘The flexible satellite batch production line is a complex discrete production system with multiple cross-disciplinary fields and mixed serial parallel tasks.As the source of the satellite batch production line process,the warehousing system has urgent needs such as uncertain production scale and rapid iteration and optimization of business processes.Therefore,the requirements and architecture of complex discrete warehousing systems such as flexible satellite batch production lines are studied.The physical system of intelligent equipment is abstracted as a digital model to form the underlying module,and a digital fusion framework of“business domain+middleware platform+intelligent equipment information model”is constructed.The granularity of microservice splitting is calculated based on the dynamic correlation relationship between user access instances and database table structures.The general warehousing functions of the platform are divided to achieve module customization,addition,and configuration.An open discrete warehousing system based on microservices is designed.Software architecture and design develop complex discrete warehousing systems based on the SpringCloud framework.This architecture achieves the decoupling of business logic and physical hardware,enhances the maintainability and scalability of the system,and greatly improves the system’s adaptability to different complex discrete warehousing business scenarios.
基金funded by a SINOPEC project entitled Exploration Potential and Target Evaluation of Xujiahe Formation in the Northeastern Sichuan Basin(No.P23130).
文摘The recent discovery of natural gas within the fifth member of the Xujiahe Formation(T_(3)x_(5))in the Dongfeng area within the Sichuan Basin highlights the significant exploration potential of this member.However,the unconvincing previous understanding of the sedimentary microfacies,combined with a total lack of studies on the sand body architecture and reservoir distribution,hampers the further exploration of this member.Using core data,log curves,and seismic data,along with sedimentary microfacies analysis,this study investigated the interfaces between the sand bodies of various scales in the Dongfeng area.Furthermore,this study explored the morphological characteristics,types,and stacking patterns of these sand bodies and determined the distributions of sand bodies and reservoirs in the area.The results indicate that the first sand group of the T_(3)x_(5) member(T_(3)x^(1)_(5))exhibits delta-front deposits,including subaqueous distributary channels,sheet sands,and interdistributary bays.Seven levels of sand body interfaces are identified in the T_(3)x^(1)_(5) sand group.Among them,the interfaces of the first and second levels were identifed only in cores,those of the third and fourth levels were recog-nizable from cores combined with log curves,while those of the fifth,sixth,and seventh levels were distinguishable using seismic data.Three superimposed subaqueous distributary channel complexes are found in the Dongfeng area.Among them,complex 1 in the northwest exhibits the strongest water body energy,while complex 2 in the south displays the weakest.Complex 2 was formed earlier than com-plexes 1 and 3.Also,complex 1 is further subdivided into three vertically stacked subaqueous distrib-utary channels.The subdivision of sedimentary microfacies in the T_(3)x_(5) member reveals nine lithofacies types.Among them,stacked pancake-shaped,carbonaceous debris-bearing,massive,and cross-bedded medium-grained sandstones are considered favorable lithofacies.These four lithofacies types exhibit high porosity,as well as low natural gamma-ray(GR)values,low-to-medium deep investigate double lateral resistivity(RD),and high interval transit time(AC)on the log curves.Additionally,the reservoir distribution in the Dongfeng area was delineated based on the characterization of the favorable lith-ofacies.This study serves as a guide for future exploration and evaluation of the T_(3)x_(5) member in the Dongfeng area while also augmenting the methodologies for describing tight sandstone reservoirs.
基金Shanghai Municipal Commission of Economy and Information Technology,China(No.202301054)。
文摘End-to-end object detection Transformer(DETR)successfully established the paradigm of the Transformer architecture in the field of object detection.Its end-to-end detection process and the idea of set prediction have become one of the hottest network architectures in recent years.There has been an abundance of work improving upon DETR.However,DETR and its variants require a substantial amount of memory resources and computational costs,and the vast number of parameters in these networks is unfavorable for model deployment.To address this issue,a greedy pruning(GP)algorithm is proposed,applied to a variant denoising-DETR(DN-DETR),which can eliminate redundant parameters in the Transformer architecture of DN-DETR.Considering the different roles of the multi-head attention(MHA)module and the feed-forward network(FFN)module in the Transformer architecture,a modular greedy pruning(MGP)algorithm is proposed.This algorithm separates the two modules and applies their respective optimal strategies and parameters.The effectiveness of the proposed algorithm is validated on the COCO 2017 dataset.The model obtained through the MGP algorithm reduces the parameters by 49%and the number of floating point operations(FLOPs)by 44%compared to the Transformer architecture of DN-DETR.At the same time,the mean average precision(mAP)of the model increases from 44.1%to 45.3%.
文摘The size of the Audio and Video(AV)content of the 8K program is four times larger than that of 4K content,providing viewers with a more ideal audiovisual experience while placing higher demands on the capability and efficiency of document preparation and processing,signal transmission,and scheduling.However,it is difficult to meet the high robustness requirements of 8K broadcast services because the existing broadcast system architecture is limited by efficiency,cost,and other factors.In this study,an 8K Ultra-High-Definition(UHD)TV program broadcast scheme was designed.The verification results show that the scheme is high quality,highly efficient,and robust.In particular,in the research,the file format normalizing module was first placed in the broadcast area instead of the file preparation area,and the low-compression transmission scheme of the all-IP signal JPEG XS was designed in the signal transmission area for improving the efficiency of the scheme.Next,to reduce the impact on the robustness of broadcast services,the broadcast control logic of the broadcast core components is optimized.Finally,a series of 8K TV program broadcasting systems have been implemented and their performance has been verified.The results show that the system meets the efficiency and robustness requirements of a high-quality 8K AV broadcast system,and thus has a high degree of practicability.
基金funded by the Guangxi Science and Technology Plan Project(Guike AD22080050)the Basic Research Ability Improvement Project of Young and Middle-aged Teachers of Universities in Guangxi(2022KY0386)+1 种基金the Opening Foundation of Key Laboratory of Environment Change and Resources Use in Beibu Gulf,Ministry of Education,Nanning Normal University(NNNU-KLOP-K2202)the National Natural Science Foundation of China(42471055).
文摘Root system architecture has often been overlooked in plant research despite its critical role in plant adaptation to environmental conditions.This study focused on the root system architecture of the desert shrub Reaumuria soongorica in the Alxa steppe desert,Northwest China.Plant samples were collected during May-September 2019.Using excavation methods,in situ measurements,and root scanning techniques,we analyzed the root distribution,topology,and branching patterns of R.soongorica across an age sequence of 7-51 a.Additionally,we investigated the allometric relationships of root collar diameter with total coarse root length,biomass,and topological parameters.The results showed that the roots of R.soongorica were predominantly concentrated in shallow soil layers(10-50 cm),with lateral root branching and biomass allocation increasing with shrub age.The root topology exhibited a herringbone-like structure,with average topological and modified topological indices of 0.89 and 0.96,respectively,both of which adjusted with shrub age.The root system displayed a self-similar branching pattern,maintaining a constant cross-sectional area ratio of 1.13 before and after branching,deviating from the area-preserving rule.These adaptive traits allow R.soongorica to efficiently expand its nutrient acquisition zone,minimize internal competition,and optimize resource uptake from the upper soil layers.Furthermore,significant linear relationships were observed between log10-transformed root collar diameter and log10-transformed total coarse root length,biomass,and topological parameters.These findings advance non-destructive approaches for studying root characteristics and contribute to the development of root-related models.Besides,this study provides new insights into the adaptive strategies of R.soongorica under extreme drought conditions,offering valuable guidance for species selection and cultivation in desert restoration efforts.
基金supported by the National Natural Science Foundation of China(No.12305344)the 2023 Anhui university research project of China(No.2023AH052179).
文摘The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.
基金supported in part by the National Natural Science Foundation of China under Grant 62171465,62072303,62272223,U22A2031。
文摘By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.
基金the National Natural Science Foundation of China(32370248)the Jiangsu Seed Industry Revitalization Project(JBGS[2021]001)a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Rice(Oryza sativa)plant architecture and grain shape,which determine grain quality and yield,are modulatedby auxin and brassinosteroid via regulation of cell elongation and proliferation.We review the signaltransduction of these hormones and the crosstalk between their signals on the regulation of rice plantarchitecture and grain shape.
基金supported by the Key Research and Development Program of Zhejiang(2024SSYS0099)the National Key Research and Development Program of China(2022YFD1200203)Key Research and Development Program of Hebei province(22326305D).
文摘Plant height,spike,leaf,stem and grain morphologies are key components of plant architecture and related to wheat yield.A wheat(Triticum aestivum L.)mutant,wpa1,displaying temperaturedependent pleiotropic developmental anomalies,was isolated.The WPA1 gene,encoding a von Willebrand factor type A(vWA)domain protein,was located on chromosome arm 7DS and isolated by map-based cloning.The functionality of WPA1 was validated by multiple independent EMS-induced mutants and gene editing.Phylogenetic analysis revealed that WPA1 is monocotyledon-specific in higher plants.The identification of WPA1 provides opportunity to study the temperature regulated wheat development and grain yield.
基金Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2020A1515110762Research Grants Council of the Hong Kong Special Administrative Region,China,Grant/Award Number:R6005‐20Shenzhen Key Laboratory of Advanced Energy Storage,Grant/Award Number:ZDSYS20220401141000001。
文摘Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and poor fast‐charging capability limiting its commercial applications.Here,we propose a multilevel carbon architecture with vertical graphene sheets(VGSs)grown on surfaces of subnanoscopically and homogeneously dispersed Si–C composite nanospheres,which are subsequently embedded into a carbon matrix(C/VGSs@Si–C).Subnanoscopic C in the Si–C nanospheres,VGSs,and carbon matrix form a three‐dimensional conductive and robust network,which significantly improves the conductivity and suppresses the volume expansion of Si,thereby boosting charge transport and improving electrode stability.The VGSs with vast exposed edges considerably increase the contact area with the carbon matrix and supply directional transport channels through the entire material,which boosts charge transport.The carbon matrix encapsulates VGSs@Si–C to decrease the specific surface area and increase tap density,thus yielding high first Coulombic efficiency and electrode compaction density.Consequently,C/VGSs@Si–C delivers excellent Li‐ion storage performances under industrial electrode conditions.In particular,the full cells show high energy densities of 603.5 Wh kg^(−1)and 1685.5 Wh L^(−1)at 0.1 C and maintain 80.7%of the energy density at 3 C.
基金supported in part by the National Natural Science Foundation of China (NSFC) under Grant No.61976242in part by the Natural Science Fund of Hebei Province for Distinguished Young Scholars under Grant No.F2021202010+2 种基金in part by the Fundamental Scientific Research Funds for Interdisciplinary Team of Hebei University of Technology under Grant No.JBKYTD2002funded by Science and Technology Project of Hebei Education Department under Grant No.JZX2023007supported by 2022 Interdisciplinary Postgraduate Training Program of Hebei University of Technology under Grant No.HEBUT-YXKJC-2022122.
文摘Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.
文摘With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 presents a new business model of“Internet of everything,intelligent leading,data driving,shared services,cross-border integration,and universal innovation”.The network boundaries are becoming increasingly blurred,NCMS is facing security risks such as equipment unauthorized use,account theft,static and extensive access control policies,unauthorized access,supply chain attacks,sensitive data leaks,and industrial control vulnerability attacks.Traditional security architectures mainly use information security technology,which cannot meet the active security protection requirements of NCMS.In order to solve the above problems,this paper proposes an integrated cloud-edge-terminal security system architecture of NCMS.It adopts the zero trust concept and effectively integrates multiple security capabilities such as network,equipment,cloud computing environment,application,identity,and data.It adopts a new access control mode of“continuous verification+dynamic authorization”,classified access control mechanisms such as attribute-based access control,rolebased access control,policy-based access control,and a new data security protection system based on blockchain,achieving“trustworthy subject identity,controllable access behavior,and effective protection of subject and object resources”.This architecture provides an active security protection method for NCMS in the digital transformation of large enterprises,and can effectively enhance network security protection capabilities and cope with increasingly severe network security situations.
基金support provided by the National Natural Science Foundation of China(22122802,22278044,and 21878028)the Chongqing Science Fund for Distinguished Young Scholars(CSTB2022NSCQ-JQX0021)the Fundamental Research Funds for the Central Universities(2022CDJXY-003).
文摘To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.
基金University-level Graduate Education Reform Project of Yangtze University(YJY202329).
文摘Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics.
