Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-li...Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.展开更多
The performance of a material is directly affected by its microstructural development during the solidification phase. Discrete cellular automaton (CA) models are widelyused in materials science to simulate and predic...The performance of a material is directly affected by its microstructural development during the solidification phase. Discrete cellular automaton (CA) models are widelyused in materials science to simulate and predict microstructural growth. This review comprehensively explains the developments and applications of CA in solidification structure simulation, including the theoretical underpinnings, computational procedures, software development, and recent advances. Summarizes the potential and limitations of cellular automata in understanding microstructure evolution during solidification, explores the evolution of microstructures during solidification, and adds to our existing knowledge of cellular automaton theory. Finally, the research trend in simulating the evolution of the solidification microstructure using cellular automaton theory is explored.展开更多
Accurate wind speed measurements on maritime vessels are crucial for weather forecasting,sea state prediction,and safe navigation.However,vessel motion and challenging environmental conditions often affect measurement...Accurate wind speed measurements on maritime vessels are crucial for weather forecasting,sea state prediction,and safe navigation.However,vessel motion and challenging environmental conditions often affect measurement precision.To address this issue,this study proposes an innovative framework for correcting and predicting shipborne wind speed.By integrating a main network with a momentum updating network,the proposed framework effectively extracts features from the time and frequency domains,thereby allowing for precise adjustments and predictions of shipborne wind speed data.Validation using real sensor data collected at the Qingdao Oceanographic Institute demonstrates that the proposed method outperforms existing approaches in single-and multi-step predictions compared to existing methods,achieving higher accuracy in wind speed forecasting.The proposed innovative approach offers a promising direction for future validation in more realistic maritime onboard scenarios.展开更多
The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous flui...The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous fluid density distributions over time.It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems.The Sunway Bluelight II supercomputer,as a new generation of China’s developed supercomputer,possesses powerful computational capabilities.Porting and optimizing industrial software on this platform holds significant importance.For the optimization of the DDFT algorithm,based on the Sunway Bluelight II supercomputer and the unique hardware architecture of the SW39000 processor,this work proposes three acceleration strategies to enhance computational efficiency and performance,including direct parallel optimization,local-memory constrained optimization for CPEs,and multi-core groups collaboration and communication optimization.This method combines the characteristics of the program’s algorithm with the unique hardware architecture of the Sunway Bluelight II supercomputer,optimizing the storage and transmission structures to achieve a closer integration of software and hardware.For the first time,this paper presents Sunway-Dynamical Density Functional Theory(SW-DDFT).Experimental results show that SW-DDFT achieves a speedup of 6.67 times within a single-core group compared to the original DDFT implementation,with six core groups(a total of 384 CPEs),the maximum speedup can reach 28.64 times,and parallel efficiency can reach 71%,demonstrating excellent acceleration performance.展开更多
1.Data security in smart manufacturing The global manufacturing sector is undergoing a digital transformation as traditional systems-reliant on physical assets such as raw materials and labor-struggle to meet demands ...1.Data security in smart manufacturing The global manufacturing sector is undergoing a digital transformation as traditional systems-reliant on physical assets such as raw materials and labor-struggle to meet demands for greater flexibility and efficiency.The integration of advanced information technology facilitates smart manufacturing(SM),which optimizes production,management,and supply chains[1].展开更多
The integrated waveguide polarizer is essential for photonic integrated circuits,and various designs of waveguide polarizers have been developed.As the demand for dense photonic integration increases rapidly,new strat...The integrated waveguide polarizer is essential for photonic integrated circuits,and various designs of waveguide polarizers have been developed.As the demand for dense photonic integration increases rapidly,new strategies to minimize the device size are needed.In this paper,we have inversely designed an integrated transverse electric pass(TE-pass)polarizer with a footprint of 2.88μm×2.88μm,which is the smallest footprint ever achieved.A direct binary search algorithm is used to inversely design the device for maximizing the transverse electric(TE)transmission while minimizing transverse magnetic(TM)transmission.Finally,the inverse-designed device provides an average insertion loss of 0.99 dB and an average extinction ratio of 33 dB over a wavelength range of 100 nm.展开更多
Imprinted genes play a key role in regulating mammalian placental and embryonic development.Here,we generated glutaminyl-peptide cyclotransferase-knockout(Qpct^(-/-))mice utilizing the clustered regularly interspaced ...Imprinted genes play a key role in regulating mammalian placental and embryonic development.Here,we generated glutaminyl-peptide cyclotransferase-knockout(Qpct^(-/-))mice utilizing the clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein 9(Cas9)platform and identified Qpct as a novel anti-angiogenic factor in regulating mouse placentation.Compared with Qpct^(+/+)mice,placentae and embryos(Qpct^(-/+)and Qpct^(-/-))showed significant overgrowth at embryonic Day 12.5(E12.5),E15.5,and E18.5.Using single-cell transcriptome analysis of 32309 cells from Qpct^(+/+)and Qpct^(-/-)mouse placentae,we identified 13 cell clusters via single-nucleus RNA sequencing(snRNA-seq)(8880 Qpct^(+/+)and 13577 Qpct^(-/-)cells)and 20 cell clusters via single-cell RNA sequencing(scRNA-seq)(6567 Qpct^(+/+)and 3285 Qpct^(-/-)cells).Furthermore,we observed a global up-regulation of pro-angiogenic genes in the Qpct^(-/-)background.Immunohistochemistry assays revealed a notable increase in the number of blood vessels in the decidual and labyrinthine layers of E15.5 Qpct^(-/+)and Qpct^(-/-)mice.Moreover,the elevation of multiple pairs of ligand-receptor interactions was observed in decidual cells,endothelial cells,and macrophages,promoting angiogenesis and inflammatory response.Our findings indicate that loss of maternal Qpct leads to altered phenotypic characteristics of placentae and embryos and promotes angiogenesis in murine placentae.展开更多
To address the challenge of missing modal information in entity alignment and to mitigate information loss or bias arising frommodal heterogeneity during fusion,while also capturing shared information acrossmodalities...To address the challenge of missing modal information in entity alignment and to mitigate information loss or bias arising frommodal heterogeneity during fusion,while also capturing shared information acrossmodalities,this paper proposes a Multi-modal Pre-synergistic Entity Alignmentmodel based on Cross-modalMutual Information Strategy Optimization(MPSEA).The model first employs independent encoders to process multi-modal features,including text,images,and numerical values.Next,a multi-modal pre-synergistic fusion mechanism integrates graph structural and visual modal features into the textual modality as preparatory information.This pre-fusion strategy enables unified perception of heterogeneous modalities at the model’s initial stage,reducing discrepancies during the fusion process.Finally,using cross-modal deep perception reinforcement learning,the model achieves adaptive multilevel feature fusion between modalities,supporting learningmore effective alignment strategies.Extensive experiments on multiple public datasets show that the MPSEA method achieves gains of up to 7% in Hits@1 and 8.2% in MRR on the FBDB15K dataset,and up to 9.1% in Hits@1 and 7.7% in MRR on the FBYG15K dataset,compared to existing state-of-the-art methods.These results confirm the effectiveness of the proposed model.展开更多
As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitati...As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.展开更多
Frequent typhoons can significantly change the temperature,nutrient availability,and phytoplankton biomass in marginal seas.The oceanic response to typhoons is usually influenced by the features of the typhoon,among w...Frequent typhoons can significantly change the temperature,nutrient availability,and phytoplankton biomass in marginal seas.The oceanic response to typhoons is usually influenced by the features of the typhoon,among which the translational speed is critically important.By using a high resolution coupled physical-biological model,we investigated the response of the Yellow and East China seas(YECS)to two typhoons at different translational speeds,Muifa in August 2011 and Bolaven in August 2012.The model well reproduced the spatial and temporal variations of temperature,chlorophyll-a concentration over the YECS.Results show that typhoons with slower translational speeds uplift more deep water,leading to a more significant oceanic response.Divergence and convergence caused nutrient fluxes in opposite directions in the surface and bottom layers.Moreover,the nutrient flux in the bottom layer was greater than that in the surface layer.These phenomena are closely related to the spatial distribution of nutrients.Further studies show that the degree of ocean response to typhoons is highly correlated with the initial conditions of physical and biological elements of the upper ocean before the typhoon,as well as with ocean structure.Pretyphoon initial conditions of oceanic physical and ecological elements,mixed layer depth,and potential energy anomalies can all alter the degree of typhoon-induced oceanic response.This study emphasizes the important roles of the translational speed of typhoons and the initial oceanic conditions in the oceanic response to typhoons.展开更多
Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,tra...Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain.Due to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many scenarios.To improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling technology.Nevertheless,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected aim.This paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction distribution.Bymitigating crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the blockchain.Therefore,the scheme can achieve a high-frequency transaction as well as a better blockchain scalability.Experiments results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.展开更多
Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)protocol.More specifically,to reduce the communicat...Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)protocol.More specifically,to reduce the communication burden,a TOD protocol with novel update rules on protocol weights is designed for scheduling measurement outputs.In addition,unknown nonlinear functions vulnerable to DoS attacks are considered due to the openness and vulnerability of the network.展开更多
Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary mea...Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression assessment.Non-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively utilized.Specialized physicians usually require extensive training and experience to capture changes in these features.Advancements in deep learning technology have provided technical support for capturing non-biological markers.Several researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression screening.This article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.展开更多
The parabrachial nucleus(PBN)integrates interoceptive and exteroceptive information to control various behavioral and physiological processes including breathing,emotion,and sleep/wake regulation through the neural ci...The parabrachial nucleus(PBN)integrates interoceptive and exteroceptive information to control various behavioral and physiological processes including breathing,emotion,and sleep/wake regulation through the neural circuits that connect to the forebrain and the brainstem.However,the precise identity and function of distinct PBN subpopulations are still largely unknown.Here,we leveraged molecular characterization,retrograde tracing,optogenetics,chemogenetics,and electrocortical recording approaches to identify a small subpopulation of neurotensin-expressing neurons in the PBN that largely project to the emotional control regions in the forebrain,rather than the medulla.Their activation induces freezing and anxiety-like behaviors,which in turn result in tachypnea.In addition,optogenetic and chemogenetic manipulations of these neurons revealed their function in promoting wakefulness and maintaining sleep architecture.We propose that these neurons comprise a PBN subpopulation with specific gene expression,connectivity,and function,which play essential roles in behavioral and physiological regulation.展开更多
Sound velocities in shock-loaded solids are not only important to determine bulk moduli of solids at high pressures, but are also crucial to inform the shock melting of solids upon loading. In this letter, we first re...Sound velocities in shock-loaded solids are not only important to determine bulk moduli of solids at high pressures, but are also crucial to inform the shock melting of solids upon loading. In this letter, we first report on shock melting of porous solids at high pressures by measuring sound velocities in the porous iron of average density 6.90 g/cm^(3) in the pressure range of 110-180 GPa. The measured sound velocity softens at pressures from 122 to 156 Gpa, which may be attributed to shock melting of the porous iron.展开更多
The power conversion efficiency of all-perovskite tandem solar cells is predominantly constrained by optical absorption losses, especially reflection losses. In this simulation study, we propose the optimization of a ...The power conversion efficiency of all-perovskite tandem solar cells is predominantly constrained by optical absorption losses, especially reflection losses. In this simulation study, we propose the optimization of a dual-interface serrated microstructure to mitigate these optical reflection losses in all-perovskite tandem solar cells. By adjusting the geometry of the periodic serrated structures at both the front interface and the back electrode, we enhance light absorption in the widebandgap perovskite layer and promote light scattering in the narrow-bandgap perovskite layer. The structural modification reduces the reflection-induced photocurrent density loss from 4.47 to 3.65 mA cm^(-2). It is expected to boost the efficiency of all-perovskite tandem solar cells to approximately 31.13%, representing a 3.41% increase. The dual-interface optimization effectively suppresses reflection losses and improves the overall photocurrent of all-perovskite tandem solar cells. These results offer a promising strategy for minimizing optical losses and enhancing device performance in all-perovskite tandem solar cells.展开更多
In the Internet of Things(IoT),a large number of devices are connected using a variety of communication technologies to ensure that they can communicate both physically and over the network.However,devices face the ch...In the Internet of Things(IoT),a large number of devices are connected using a variety of communication technologies to ensure that they can communicate both physically and over the network.However,devices face the challenge of a single point of failure,a malicious user may forge device identity to gain access and jeopardize system security.In addition,devices collect and transmit sensitive data,and the data can be accessed or stolen by unauthorized user,leading to privacy breaches,which posed a significant risk to both the confidentiality of user information and the protection of device integrity.Therefore,in order to solve the above problems and realize the secure transmission of data,this paper proposed EBIAS,a secure and efficient blockchain-based identity authentication scheme designed for IoT devices.First,EBIAS combined the Elliptic Curve Cryptography(ECC)algorithm and the SHA-256 algorithm to achieve encrypted communication of the sensitive data.Second,EBIAS integrated blockchain to tackle the single point of failure and ensure the integrity of the sensitive data.Finally,we performed security analysis and conducted sufficient experiment.The analysis and experimental results demonstrate that EBIAS has certain improvements on security and performance compared with the previous schemes,which further proves the feasibility and effectiveness of EBIAS.展开更多
Dear Editor,The ongoing coronavirus disease 2019(COVID-19)pandemic caused by severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)has lasted for more than four years,resulting in an unprecedented global public h...Dear Editor,The ongoing coronavirus disease 2019(COVID-19)pandemic caused by severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)has lasted for more than four years,resulting in an unprecedented global public health crisis.Progress in halting this pandemic seems slow due to the emergence of variants of concern,such as the B.1.1.7(Alpha),B.1.351(Beta),P.1(Gamma,also known as B.1.1.28.1),B.1.617.2(Delta),and B.1.1.529(Omicron),that appear to be high transmissible and more resistant to neutralizing antibodies(Wang et al.,2021g).New variants are thought to be responsible for re-infections(Hacisuleyman et al.,2021).A general decrease in immune protection against SARS-CoV-2 variants within 6–12 months after the primary infection or vaccination is also observed(Widge et al.,2021).However,not much is known about the immunogenic features of such a booster dose of a COVID-19 vaccine.展开更多
The discovery of G-protein coupled receptor(GPCR)accessory proteins has fundamentally redefined the pharmacological concept of GPCR signaling,demonstrating a more complex molecular basis for receptor specificity on th...The discovery of G-protein coupled receptor(GPCR)accessory proteins has fundamentally redefined the pharmacological concept of GPCR signaling,demonstrating a more complex molecular basis for receptor specificity on the plasma membrane and impressionable downstream intracellular cascades.GPCR accessory proteins not only contribute to the proper folding and trafficking of receptors but also exhibit selectable receptor preferences.展开更多
With the advancement of deep learning techniques,the number of model parameters has been increasing,leading to significant memory consumption and limits in the deployment of such models in real-time applications.To re...With the advancement of deep learning techniques,the number of model parameters has been increasing,leading to significant memory consumption and limits in the deployment of such models in real-time applications.To reduce the number of model parameters and enhance the generalization capability of neural networks,we propose a method called Decoupled MetaDistil,which involves decoupled meta-distillation.This method utilizes meta-learning to guide the teacher model and dynamically adjusts the knowledge transfer strategy based on feedback from the student model,thereby improving the generalization ability.Furthermore,we introduce a decoupled loss method to explicitly transfer positive sample knowledge and explore the potential of negative samples knowledge.Extensive experiments demonstrate the effectiveness of our method.展开更多
基金supported by the National Key R&D Program of China,No.2019YFA0110300(to ZG)the National Natural Science Foundation of China,Nos.81773302(to YF),32070862(to ZG).
文摘Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.
文摘The performance of a material is directly affected by its microstructural development during the solidification phase. Discrete cellular automaton (CA) models are widelyused in materials science to simulate and predict microstructural growth. This review comprehensively explains the developments and applications of CA in solidification structure simulation, including the theoretical underpinnings, computational procedures, software development, and recent advances. Summarizes the potential and limitations of cellular automata in understanding microstructure evolution during solidification, explores the evolution of microstructures during solidification, and adds to our existing knowledge of cellular automaton theory. Finally, the research trend in simulating the evolution of the solidification microstructure using cellular automaton theory is explored.
基金supported by the Major Innovation Project for the Integration of Science,Education,and Industry of Qilu University of Technology(Shandong Academy of Sciences)(Nos.2023HYZX01,2023JBZ02)the Open Project of Key Laboratory of Computing Power Network and Information Security,Ministry of Education,Qilu University of Technology(Shandong Academy of Sciences)(No.2023ZD007)+2 种基金the Talent Research Projects of Qilu University of Technology(Shandong Academy of Sciences)(No.2023RCKY136)the Technology and Innovation Major Project of the Ministry of Science and Technology of China(No.2022ZD0118600)the Jinan‘20 New Colleges and Universities’Funded Project(No.202333043)。
文摘Accurate wind speed measurements on maritime vessels are crucial for weather forecasting,sea state prediction,and safe navigation.However,vessel motion and challenging environmental conditions often affect measurement precision.To address this issue,this study proposes an innovative framework for correcting and predicting shipborne wind speed.By integrating a main network with a momentum updating network,the proposed framework effectively extracts features from the time and frequency domains,thereby allowing for precise adjustments and predictions of shipborne wind speed data.Validation using real sensor data collected at the Qingdao Oceanographic Institute demonstrates that the proposed method outperforms existing approaches in single-and multi-step predictions compared to existing methods,achieving higher accuracy in wind speed forecasting.The proposed innovative approach offers a promising direction for future validation in more realistic maritime onboard scenarios.
基金supported by National Key Research and Development Program of China under Grant 2024YFE0210800National Natural Science Foundation of China under Grant 62495062Beijing Natural Science Foundation under Grant L242017.
文摘The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous fluid density distributions over time.It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems.The Sunway Bluelight II supercomputer,as a new generation of China’s developed supercomputer,possesses powerful computational capabilities.Porting and optimizing industrial software on this platform holds significant importance.For the optimization of the DDFT algorithm,based on the Sunway Bluelight II supercomputer and the unique hardware architecture of the SW39000 processor,this work proposes three acceleration strategies to enhance computational efficiency and performance,including direct parallel optimization,local-memory constrained optimization for CPEs,and multi-core groups collaboration and communication optimization.This method combines the characteristics of the program’s algorithm with the unique hardware architecture of the Sunway Bluelight II supercomputer,optimizing the storage and transmission structures to achieve a closer integration of software and hardware.For the first time,this paper presents Sunway-Dynamical Density Functional Theory(SW-DDFT).Experimental results show that SW-DDFT achieves a speedup of 6.67 times within a single-core group compared to the original DDFT implementation,with six core groups(a total of 384 CPEs),the maximum speedup can reach 28.64 times,and parallel efficiency can reach 71%,demonstrating excellent acceleration performance.
基金supported in part by the National Natural Science Foundation of China(62293511 and 62402256)in part by the Shandong Provincial Natural Science Foundation of China(ZR2024MF100)+1 种基金in part by the Taishan Scholars Program(tsqn202408239)in part by the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(ICT2025B13).
文摘1.Data security in smart manufacturing The global manufacturing sector is undergoing a digital transformation as traditional systems-reliant on physical assets such as raw materials and labor-struggle to meet demands for greater flexibility and efficiency.The integration of advanced information technology facilitates smart manufacturing(SM),which optimizes production,management,and supply chains[1].
基金supported by the National Natural Science Foundation of China(Nos.62175076,62105028,62475085)the Natural Science Foundation of Hubei Province of China(Nos.2024AFA016,2024AFB612)the Open Project Program of Hubei Optical Fundamental Research Center.
文摘The integrated waveguide polarizer is essential for photonic integrated circuits,and various designs of waveguide polarizers have been developed.As the demand for dense photonic integration increases rapidly,new strategies to minimize the device size are needed.In this paper,we have inversely designed an integrated transverse electric pass(TE-pass)polarizer with a footprint of 2.88μm×2.88μm,which is the smallest footprint ever achieved.A direct binary search algorithm is used to inversely design the device for maximizing the transverse electric(TE)transmission while minimizing transverse magnetic(TM)transmission.Finally,the inverse-designed device provides an average insertion loss of 0.99 dB and an average extinction ratio of 33 dB over a wavelength range of 100 nm.
基金supported by the National Natural Science Foundation of China(No.32271165)the Interdisciplinary Project in Ocean Research of Tongji University(No.2022-2-ZD-02),China.
文摘Imprinted genes play a key role in regulating mammalian placental and embryonic development.Here,we generated glutaminyl-peptide cyclotransferase-knockout(Qpct^(-/-))mice utilizing the clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein 9(Cas9)platform and identified Qpct as a novel anti-angiogenic factor in regulating mouse placentation.Compared with Qpct^(+/+)mice,placentae and embryos(Qpct^(-/+)and Qpct^(-/-))showed significant overgrowth at embryonic Day 12.5(E12.5),E15.5,and E18.5.Using single-cell transcriptome analysis of 32309 cells from Qpct^(+/+)and Qpct^(-/-)mouse placentae,we identified 13 cell clusters via single-nucleus RNA sequencing(snRNA-seq)(8880 Qpct^(+/+)and 13577 Qpct^(-/-)cells)and 20 cell clusters via single-cell RNA sequencing(scRNA-seq)(6567 Qpct^(+/+)and 3285 Qpct^(-/-)cells).Furthermore,we observed a global up-regulation of pro-angiogenic genes in the Qpct^(-/-)background.Immunohistochemistry assays revealed a notable increase in the number of blood vessels in the decidual and labyrinthine layers of E15.5 Qpct^(-/+)and Qpct^(-/-)mice.Moreover,the elevation of multiple pairs of ligand-receptor interactions was observed in decidual cells,endothelial cells,and macrophages,promoting angiogenesis and inflammatory response.Our findings indicate that loss of maternal Qpct leads to altered phenotypic characteristics of placentae and embryos and promotes angiogenesis in murine placentae.
基金partially supported by the National Natural Science Foundation of China under Grants 62471493 and 62402257(for conceptualization and investigation)partially supported by the Natural Science Foundation of Shandong Province,China under Grants ZR2023LZH017,ZR2024MF066,and 2023QF025(for formal analysis and validation)+1 种基金partially supported by the Open Foundation of Key Laboratory of Computing Power Network and Information Security,Ministry of Education,Qilu University of Technology(Shandong Academy of Sciences)under Grant 2023ZD010(for methodology and model design)partially supported by the Russian Science Foundation(RSF)Project under Grant 22-71-10095-P(for validation and results verification).
文摘To address the challenge of missing modal information in entity alignment and to mitigate information loss or bias arising frommodal heterogeneity during fusion,while also capturing shared information acrossmodalities,this paper proposes a Multi-modal Pre-synergistic Entity Alignmentmodel based on Cross-modalMutual Information Strategy Optimization(MPSEA).The model first employs independent encoders to process multi-modal features,including text,images,and numerical values.Next,a multi-modal pre-synergistic fusion mechanism integrates graph structural and visual modal features into the textual modality as preparatory information.This pre-fusion strategy enables unified perception of heterogeneous modalities at the model’s initial stage,reducing discrepancies during the fusion process.Finally,using cross-modal deep perception reinforcement learning,the model achieves adaptive multilevel feature fusion between modalities,supporting learningmore effective alignment strategies.Extensive experiments on multiple public datasets show that the MPSEA method achieves gains of up to 7% in Hits@1 and 8.2% in MRR on the FBDB15K dataset,and up to 9.1% in Hits@1 and 7.7% in MRR on the FBYG15K dataset,compared to existing state-of-the-art methods.These results confirm the effectiveness of the proposed model.
基金supported by the National Natural Science Foundation of China under Grant 62471493 and 62402257partially supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066 and 2023QF025+2 种基金partially supported by the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-12)partially supported by the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),the Ministry of Education(No.EIN2024C006)partially supported by the Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE(No.202306).
文摘As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.
基金Supported by the National Natural Science Foundation of China(Nos.42006018,42276009,42376199)the Open Fund Project of the Key Laboratory of Ocean Observation and Information of Hainan Province(No.HKLOOI-OF-2023-03)the Tianjin Natural Science Foundation(Nos.21JCYBJC00500,21JCQNJC00590)。
文摘Frequent typhoons can significantly change the temperature,nutrient availability,and phytoplankton biomass in marginal seas.The oceanic response to typhoons is usually influenced by the features of the typhoon,among which the translational speed is critically important.By using a high resolution coupled physical-biological model,we investigated the response of the Yellow and East China seas(YECS)to two typhoons at different translational speeds,Muifa in August 2011 and Bolaven in August 2012.The model well reproduced the spatial and temporal variations of temperature,chlorophyll-a concentration over the YECS.Results show that typhoons with slower translational speeds uplift more deep water,leading to a more significant oceanic response.Divergence and convergence caused nutrient fluxes in opposite directions in the surface and bottom layers.Moreover,the nutrient flux in the bottom layer was greater than that in the surface layer.These phenomena are closely related to the spatial distribution of nutrients.Further studies show that the degree of ocean response to typhoons is highly correlated with the initial conditions of physical and biological elements of the upper ocean before the typhoon,as well as with ocean structure.Pretyphoon initial conditions of oceanic physical and ecological elements,mixed layer depth,and potential energy anomalies can all alter the degree of typhoon-induced oceanic response.This study emphasizes the important roles of the translational speed of typhoons and the initial oceanic conditions in the oceanic response to typhoons.
基金supported by Shandong Provincial Key Research and Development Program of China(2021CXGC010107,2020CXGC010107)the Shandong Provincial Natural Science Foundation of China(ZR2020KF035)the New 20 Project of Higher Education of Jinan,China(202228017).
文摘Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain.Due to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many scenarios.To improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling technology.Nevertheless,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected aim.This paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction distribution.Bymitigating crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the blockchain.Therefore,the scheme can achieve a high-frequency transaction as well as a better blockchain scalability.Experiments results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.
基金supported in part by the Shandong Provincial Natural Science Foundation(ZR2021QF057)Taishan Scholars Program(tsqn202211203)+3 种基金Shandong Provincial Higher Education Youth Innovation Team Development Project(2022KJ 290)“20 New Universities”Project of Jinan City(202228077)QLU/SDAS Computer Science and Technology Fundamental Research Enhancement Program(2021JC02023)QLU/SDAS Pilot Project for Integrated Innovation of Science,Education,and Industry(2022JBZ01-01).
文摘Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)protocol.More specifically,to reduce the communication burden,a TOD protocol with novel update rules on protocol weights is designed for scheduling measurement outputs.In addition,unknown nonlinear functions vulnerable to DoS attacks are considered due to the openness and vulnerability of the network.
基金Supported by Shandong Province Key R and D Program,No.2021SFGC0504Shandong Provincial Natural Science Foundation,No.ZR2021MF079Science and Technology Development Plan of Jinan(Clinical Medicine Science and Technology Innovation Plan),No.202225054.
文摘Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression assessment.Non-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively utilized.Specialized physicians usually require extensive training and experience to capture changes in these features.Advancements in deep learning technology have provided technical support for capturing non-biological markers.Several researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression screening.This article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.
基金supported by the University of Michigan startup funds and the NIH Grants R01 AT011652 and R01 HL156989.
文摘The parabrachial nucleus(PBN)integrates interoceptive and exteroceptive information to control various behavioral and physiological processes including breathing,emotion,and sleep/wake regulation through the neural circuits that connect to the forebrain and the brainstem.However,the precise identity and function of distinct PBN subpopulations are still largely unknown.Here,we leveraged molecular characterization,retrograde tracing,optogenetics,chemogenetics,and electrocortical recording approaches to identify a small subpopulation of neurotensin-expressing neurons in the PBN that largely project to the emotional control regions in the forebrain,rather than the medulla.Their activation induces freezing and anxiety-like behaviors,which in turn result in tachypnea.In addition,optogenetic and chemogenetic manipulations of these neurons revealed their function in promoting wakefulness and maintaining sleep architecture.We propose that these neurons comprise a PBN subpopulation with specific gene expression,connectivity,and function,which play essential roles in behavioral and physiological regulation.
基金Supported by the National Natural Science Foundation of China under Grant No.10032040。
文摘Sound velocities in shock-loaded solids are not only important to determine bulk moduli of solids at high pressures, but are also crucial to inform the shock melting of solids upon loading. In this letter, we first report on shock melting of porous solids at high pressures by measuring sound velocities in the porous iron of average density 6.90 g/cm^(3) in the pressure range of 110-180 GPa. The measured sound velocity softens at pressures from 122 to 156 Gpa, which may be attributed to shock melting of the porous iron.
基金supported by National Key R&D Program of China (2023YFB3608900)the Innovation Project of Optics Valley Laboratory (OVL2024ZD002)+6 种基金the University of New South Wales-Huazhong University of Science and Technology Strategic Partnership Research Seed Fundthe State Key Laboratory of Photoelectric Conversion and Utilization of Solar Energy (Innovation Fund Project SKLPCU24OP007)Wuhan Science and Technology Innovation Bureau (2024010702020023)Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization (2023B1212060012)Hubei Optical Fundamental Research Centerthe National Natural Science Foundation of China (62174064)the Analytical and Testing Center of Huazhong University of Science and Technology for their support
文摘The power conversion efficiency of all-perovskite tandem solar cells is predominantly constrained by optical absorption losses, especially reflection losses. In this simulation study, we propose the optimization of a dual-interface serrated microstructure to mitigate these optical reflection losses in all-perovskite tandem solar cells. By adjusting the geometry of the periodic serrated structures at both the front interface and the back electrode, we enhance light absorption in the widebandgap perovskite layer and promote light scattering in the narrow-bandgap perovskite layer. The structural modification reduces the reflection-induced photocurrent density loss from 4.47 to 3.65 mA cm^(-2). It is expected to boost the efficiency of all-perovskite tandem solar cells to approximately 31.13%, representing a 3.41% increase. The dual-interface optimization effectively suppresses reflection losses and improves the overall photocurrent of all-perovskite tandem solar cells. These results offer a promising strategy for minimizing optical losses and enhancing device performance in all-perovskite tandem solar cells.
基金supported by the National Science Foundation of China(62272256,62202250)the Major Program of Shandong Provincial Natural Science Foundation for the Fundamental Research(ZR2022ZD03)+3 种基金the National Science Foundation of Shandong Province(ZR2021QF079)the Talent Cultivation Promotion Program of Computer Science and Technology in Qilu University of Technology(Shandong Academy of Sciences)(2023PY059)the Pilot Project for Integrated Innovation of Science,Education and Industry of Qilu University of Technology(Shandong Academy of Sciences)(2022XD001)the Colleges and Universities 20 Terms Foundation of Jinan City(202228093).
文摘In the Internet of Things(IoT),a large number of devices are connected using a variety of communication technologies to ensure that they can communicate both physically and over the network.However,devices face the challenge of a single point of failure,a malicious user may forge device identity to gain access and jeopardize system security.In addition,devices collect and transmit sensitive data,and the data can be accessed or stolen by unauthorized user,leading to privacy breaches,which posed a significant risk to both the confidentiality of user information and the protection of device integrity.Therefore,in order to solve the above problems and realize the secure transmission of data,this paper proposed EBIAS,a secure and efficient blockchain-based identity authentication scheme designed for IoT devices.First,EBIAS combined the Elliptic Curve Cryptography(ECC)algorithm and the SHA-256 algorithm to achieve encrypted communication of the sensitive data.Second,EBIAS integrated blockchain to tackle the single point of failure and ensure the integrity of the sensitive data.Finally,we performed security analysis and conducted sufficient experiment.The analysis and experimental results demonstrate that EBIAS has certain improvements on security and performance compared with the previous schemes,which further proves the feasibility and effectiveness of EBIAS.
基金supported by the Ministry of Science and Technology of China (CPL-1233 and SPRG22-003)CAS (YSBR-010)+2 种基金the National Science Foundation Grants (12034006,32325004 and T2394482)supported by National Science Fund for Distinguished Young Scholar (No. 32325004)the NSFS Innovative Research Group (No. 81921005)
文摘Dear Editor,The ongoing coronavirus disease 2019(COVID-19)pandemic caused by severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)has lasted for more than four years,resulting in an unprecedented global public health crisis.Progress in halting this pandemic seems slow due to the emergence of variants of concern,such as the B.1.1.7(Alpha),B.1.351(Beta),P.1(Gamma,also known as B.1.1.28.1),B.1.617.2(Delta),and B.1.1.529(Omicron),that appear to be high transmissible and more resistant to neutralizing antibodies(Wang et al.,2021g).New variants are thought to be responsible for re-infections(Hacisuleyman et al.,2021).A general decrease in immune protection against SARS-CoV-2 variants within 6–12 months after the primary infection or vaccination is also observed(Widge et al.,2021).However,not much is known about the immunogenic features of such a booster dose of a COVID-19 vaccine.
基金supported by the National Natural Science Foundation of China(Grant No.32271165)Shanghai Clinical Research Center of Plastic and Reconstructive Surgery supported by the Science and Technology Commission of Shanghai Municipality(Grant No.22MC1940300)+2 种基金the Innovative Research Team of High-level Local Universities in Shanghai(Grant No.SHSMU-ZDCX20210400)the Key Laboratory Program of the Education Commission of Shanghai Municipality(No.ZDSYS14005)China Postdoctoral Science Foundation(Grant No.2022M722127).
文摘The discovery of G-protein coupled receptor(GPCR)accessory proteins has fundamentally redefined the pharmacological concept of GPCR signaling,demonstrating a more complex molecular basis for receptor specificity on the plasma membrane and impressionable downstream intracellular cascades.GPCR accessory proteins not only contribute to the proper folding and trafficking of receptors but also exhibit selectable receptor preferences.
基金supported by the Key R&D Program of Shandong Province,China(2022CXGC20106)the Pilot Project for Integrated Innovation of Science,Education,and Industry of Qilu University of Technology(Shandong Academy of Sciences)(2022JBZ01-01)+1 种基金Joint Fund of Shandong Natural Science Foundation(ZR2022LZH010)Shandong Provincial Natural Science Foundation(ZR2021LZH008).
文摘With the advancement of deep learning techniques,the number of model parameters has been increasing,leading to significant memory consumption and limits in the deployment of such models in real-time applications.To reduce the number of model parameters and enhance the generalization capability of neural networks,we propose a method called Decoupled MetaDistil,which involves decoupled meta-distillation.This method utilizes meta-learning to guide the teacher model and dynamically adjusts the knowledge transfer strategy based on feedback from the student model,thereby improving the generalization ability.Furthermore,we introduce a decoupled loss method to explicitly transfer positive sample knowledge and explore the potential of negative samples knowledge.Extensive experiments demonstrate the effectiveness of our method.
