Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remain...Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.展开更多
Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced tran...Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.展开更多
Tibetan turnip and oilseeds are the most important vegetables cultivated in the Qinghai-Tibet Plateau.Our field observations identified a dominant early-bolting phenotype at the vegetative growth stage in the Tibetan ...Tibetan turnip and oilseeds are the most important vegetables cultivated in the Qinghai-Tibet Plateau.Our field observations identified a dominant early-bolting phenotype at the vegetative growth stage in the Tibetan turnip,which was possibly due to cross-pollination contamination from nearby oilseeds.We performed genetic and molecular experiments to explore the main reason for early bolting.We first analyzed gene expression and genomic sequence variation of turnip and oilseed BraFLC2,a gene that acts as a key repressor of flowering in turnip in a dosage-dependent manner.We found that the differences in flowering time and life habits between turnip and oilseeds were closely correlated with the genetic variations in BraFLC2.We further identified that the early-bolting turnip was the hybrid between turnip and oilseeds by selecting BraFLC2 as a testing gene.Furthermore,using an artificial hybridization experiment,we found that the heterozygote and low levels of BraFLC2 expression promoted early bolting in hybrid plants.These findings indicate that early-bolting in turnip is caused by cross-pollination contamination from oilseeds under human agricultural activities.We propose a strategy of strict seed screening,cultivation isolation and turnip breeding to ensure high quality and yield.展开更多
This study identified castor oil and phosphate ester as effective retarders through setting time,tensile,and flexural tests,and determined their optimal dosages.The mechanism by which phosphate ester affects the setti...This study identified castor oil and phosphate ester as effective retarders through setting time,tensile,and flexural tests,and determined their optimal dosages.The mechanism by which phosphate ester affects the setting time of polyurethane was further investigated using molecular dynamics simulations.Fourier transform infrared spectroscopy was also employed to systematically study the physical and chemical interactions between phosphate esters and polyurethane materials.The results demonstrate that a 1%concentration of phosphate ester provides the most effective retarding effect with minimal impact on the strength of polyurethane.When phosphate ester is added to the B component of the two-component polyurethane system,its interaction energy with component A decreases,as do the diffusion coefficient and aggregation degree of component B on the surface of component A.This reduction in interaction slows the setting time.Additionally,the addition of phosphate ester to polyurethane leads to the disappearance or weakening of functional groups,indicating competitive interactions within the phosphate ester components that inhibit the reaction rate.展开更多
Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the origin...Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.展开更多
To address the problem of multi-missile cooperative interception against maneuvering targets at a prespecified impact time and desired Line-of-Sight(LOS)angles in ThreeDimensional(3D)space,this paper proposes a 3D lea...To address the problem of multi-missile cooperative interception against maneuvering targets at a prespecified impact time and desired Line-of-Sight(LOS)angles in ThreeDimensional(3D)space,this paper proposes a 3D leader-following cooperative interception guidance law.First,in the LOS direction of the leader,an impact time-controlled guidance law is derived based on the fixed-time stability theory,which enables the leader to complete the interception task at a prespecified impact time.Next,in the LOS direction of the followers,by introducing a time consensus tracking error function,a fixed-time consensus tracking guidance law is investigated to guarantee the consensus tracking convergence of the time-to-go.Then,in the direction normal to the LOS,by combining the designed global integral sliding mode surface and the second-order Sliding Mode Control(SMC)theory,an innovative 3D LOS-angle-constrained interception guidance law is developed,which eliminates the reaching phase in the traditional sliding mode guidance laws and effectively saves energy consumption.Moreover,it effectively suppresses the chattering phenomenon while avoiding the singularity issue,and compensates for unknown interference caused by target maneuvering online,making it convenient for practical engineering applications.Finally,theoretical proof analysis and multiple sets of numerical simulation results verify the effectiveness,superiority,and robustness of the investigated guidance law.展开更多
The reaction rate constant is a crucial kinetic parameter that governs the charge and discharge performance of batteries,particularly in high-rate and thick-electrode applications.However,conventional estimation or fi...The reaction rate constant is a crucial kinetic parameter that governs the charge and discharge performance of batteries,particularly in high-rate and thick-electrode applications.However,conventional estimation or fitting methods often overestimate the charge transfer overpotential,leading to substantial errors in reaction rate constant measurements.These inaccuracies hinder the accurate prediction of voltage profiles and overall cell performance.In this study,we propose the characteristic time-decomposed overpotential(CTDO)method,which employs a single-layer particle electrode(SLPE)structure to eliminate interference overpotentials.By leveraging the distribution of relaxation times(DRT),our method effectively isolates the characteristic time of the charge transfer process,enabling a more precise determination of the reaction rate constant.Simulation results indicate that our approach reduces measurement errors to below 2%,closely aligning with theoretical values.Furthermore,experimental validation demonstrates an 80% reduction in error compared to the conventional galvanostatic intermittent titration technique(GITT)method.Overall,this study provides a novel voltage-based approach for determining the reaction rate constant,enhancing the applicability of theoretical analysis in electrode structural design and facilitating rapid battery optimization.展开更多
The proper flowering time of rose(Rosa hybrida)is vital for the market value of this horticultural crop,but the mechanism regulating this trait is largely unclear.Here,we found that the transcription factor SQUAMOSA P...The proper flowering time of rose(Rosa hybrida)is vital for the market value of this horticultural crop,but the mechanism regulating this trait is largely unclear.Here,we found that the transcription factor SQUAMOSA PROMOTER BINDING PROTEIN-LIKE4(RhSPL4)positively regulates flowering time in rose.Transient silencing or overexpression transgenic rose plants of RhSPL4 exhibited delayed or early flowering,respectively.Analysis of transcriptome data from transgenic lines overexpressing RhSPL4 compared to the wild type indicated that differentially expressed genes were significantly enriched in the circadian rhythm pathway.Among the proteins encoded by these genes,RhSPL4 binds to the promoter of PSEUDO-RESPONSE REGULATOR 5-LIKE(RhPRR5L),as revealed in yeast one-hybrid,dual-Luciferase/Renilla luciferase reporter,chromatin immunoprecipitation-quantitative PCR and electrophoretic mobility shift assay.Furthermore,RhSPL4 specifically binds to the478 to441 bp region of the RhPRR5L promoter and activates its transcription.The silencing of RhPRR5L delayed flowering time in rose,resembling the phenotype of RhSPL4-silenced plants.Together,these results indicate that the RhSPL4-RhPRR5L module positively regulates flowering time in rose,laying the foundation for the genetic improvement of flowering time in this important horticultural crop.展开更多
The integrated optical true time delay phased array antenna system has the advantages of high bandwidth,small size,low loss and strong antiinterference capability,etc.The high integration of the optically controlled p...The integrated optical true time delay phased array antenna system has the advantages of high bandwidth,small size,low loss and strong antiinterference capability,etc.The high integration of the optically controlled phased array antenna system is a necessary trend for the future development of the phased array,and it is also a major focus and difficulty in the current research of integrated microwave photonics.This paper firstly introduces the basic principle and development history of optical true time delay phased array antenna system based on microwave photonics,and briefly introduces the main implementation methods and integration platform of optical true time delay.Then,the application and development prospect of optical true time delay technology in beam control of phased array antenna system are mainly presented.Finally,according to the current research progress,the possible research directions of integrated optically controlled phased array antenna systems in the future are proposed.展开更多
The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in...The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.展开更多
It is shown that time asymmetry is essential for deriving thermodynamic law and arises from the turnover of energy while reducing its information content and driving entropy increase. A dynamically interpreted princip...It is shown that time asymmetry is essential for deriving thermodynamic law and arises from the turnover of energy while reducing its information content and driving entropy increase. A dynamically interpreted principle of least action enables time asymmetry and time flow as a generation of action and redefines useful energy as an information system which implements a form of acting information. This is demonstrated using a basic formula, originally applied for time symmetry/energy conservation considerations, relating time asymmetry (which is conventionally denied but here expressly allowed), to energy behaviour. The results derived then explained that a dynamic energy is driving time asymmetry. It is doing it by decreasing the information content of useful energy, thus generating action and entropy increase, explaining action-time as an information phenomenon. Thermodynamic laws follow directly. The formalism derived readily explains what energy is, why it is conserved (1st law of thermodynamics), why entropy increases (2nd law) and that maximum entropy production within the restraints of the system controls self-organized processes of non-linear irreversible thermodynamics. The general significance of the principle of least action arises from its role of controlling the action generating oriented time of nature. These results contrast with present understanding of time neutrality and clock-time, which are here considered a source of paradoxes, intellectual contradictions and dead-end roads in models explaining nature and the universe.展开更多
基金This study is financed by the European Union-NextGenerationEU,through the National Recovery and Resilience Plan of the Republic of Bulgaria,Project No.BG-RRP-2.013-0001.
文摘Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.
基金research was funded by Science and Technology Project of State Grid Corporation of China under grant number 5200-202319382A-2-3-XG.
文摘Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.
基金supported by the National Natural Science Foundation of China(no.32200306,32170385 and 32070362)the Postdoctoral Directional Training Foundation of Yunnan Province,and the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(no.2019QZKK0502).
文摘Tibetan turnip and oilseeds are the most important vegetables cultivated in the Qinghai-Tibet Plateau.Our field observations identified a dominant early-bolting phenotype at the vegetative growth stage in the Tibetan turnip,which was possibly due to cross-pollination contamination from nearby oilseeds.We performed genetic and molecular experiments to explore the main reason for early bolting.We first analyzed gene expression and genomic sequence variation of turnip and oilseed BraFLC2,a gene that acts as a key repressor of flowering in turnip in a dosage-dependent manner.We found that the differences in flowering time and life habits between turnip and oilseeds were closely correlated with the genetic variations in BraFLC2.We further identified that the early-bolting turnip was the hybrid between turnip and oilseeds by selecting BraFLC2 as a testing gene.Furthermore,using an artificial hybridization experiment,we found that the heterozygote and low levels of BraFLC2 expression promoted early bolting in hybrid plants.These findings indicate that early-bolting in turnip is caused by cross-pollination contamination from oilseeds under human agricultural activities.We propose a strategy of strict seed screening,cultivation isolation and turnip breeding to ensure high quality and yield.
基金Funded by the National Natural Science Foundation of China(No.52370128)the Fundamental Research Funds for the Central Universities(No.2572022AW54)。
文摘This study identified castor oil and phosphate ester as effective retarders through setting time,tensile,and flexural tests,and determined their optimal dosages.The mechanism by which phosphate ester affects the setting time of polyurethane was further investigated using molecular dynamics simulations.Fourier transform infrared spectroscopy was also employed to systematically study the physical and chemical interactions between phosphate esters and polyurethane materials.The results demonstrate that a 1%concentration of phosphate ester provides the most effective retarding effect with minimal impact on the strength of polyurethane.When phosphate ester is added to the B component of the two-component polyurethane system,its interaction energy with component A decreases,as do the diffusion coefficient and aggregation degree of component B on the surface of component A.This reduction in interaction slows the setting time.Additionally,the addition of phosphate ester to polyurethane leads to the disappearance or weakening of functional groups,indicating competitive interactions within the phosphate ester components that inhibit the reaction rate.
基金supported in part by the Interdisciplinary Project of Dalian University(DLUXK-2023-ZD-001).
文摘Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.
文摘To address the problem of multi-missile cooperative interception against maneuvering targets at a prespecified impact time and desired Line-of-Sight(LOS)angles in ThreeDimensional(3D)space,this paper proposes a 3D leader-following cooperative interception guidance law.First,in the LOS direction of the leader,an impact time-controlled guidance law is derived based on the fixed-time stability theory,which enables the leader to complete the interception task at a prespecified impact time.Next,in the LOS direction of the followers,by introducing a time consensus tracking error function,a fixed-time consensus tracking guidance law is investigated to guarantee the consensus tracking convergence of the time-to-go.Then,in the direction normal to the LOS,by combining the designed global integral sliding mode surface and the second-order Sliding Mode Control(SMC)theory,an innovative 3D LOS-angle-constrained interception guidance law is developed,which eliminates the reaching phase in the traditional sliding mode guidance laws and effectively saves energy consumption.Moreover,it effectively suppresses the chattering phenomenon while avoiding the singularity issue,and compensates for unknown interference caused by target maneuvering online,making it convenient for practical engineering applications.Finally,theoretical proof analysis and multiple sets of numerical simulation results verify the effectiveness,superiority,and robustness of the investigated guidance law.
基金supported by the National Key R&D Program of China 2022YFB2404300the National Natural Science Foundation of China U22B2069the China Postdoctoral Science Foundation 2024M761006。
文摘The reaction rate constant is a crucial kinetic parameter that governs the charge and discharge performance of batteries,particularly in high-rate and thick-electrode applications.However,conventional estimation or fitting methods often overestimate the charge transfer overpotential,leading to substantial errors in reaction rate constant measurements.These inaccuracies hinder the accurate prediction of voltage profiles and overall cell performance.In this study,we propose the characteristic time-decomposed overpotential(CTDO)method,which employs a single-layer particle electrode(SLPE)structure to eliminate interference overpotentials.By leveraging the distribution of relaxation times(DRT),our method effectively isolates the characteristic time of the charge transfer process,enabling a more precise determination of the reaction rate constant.Simulation results indicate that our approach reduces measurement errors to below 2%,closely aligning with theoretical values.Furthermore,experimental validation demonstrates an 80% reduction in error compared to the conventional galvanostatic intermittent titration technique(GITT)method.Overall,this study provides a novel voltage-based approach for determining the reaction rate constant,enhancing the applicability of theoretical analysis in electrode structural design and facilitating rapid battery optimization.
基金supported by Yunnan Province Agricultural Joint Key Project(Grant No.202401BD070001-016)the National Natural Science Foundation of China(Grant No.32202530)+3 种基金Talent Introduction and Training Project of Yunnan Academy of Agricultural Sciences(Grant No.2024RCYP-09)Fundamental Research Project(Grant No.202401CF070046)Xingdian Talent support program(XDYC-QNRC-2023-0457)Yunnan Technology Innovation Center of Flower Technique.
文摘The proper flowering time of rose(Rosa hybrida)is vital for the market value of this horticultural crop,but the mechanism regulating this trait is largely unclear.Here,we found that the transcription factor SQUAMOSA PROMOTER BINDING PROTEIN-LIKE4(RhSPL4)positively regulates flowering time in rose.Transient silencing or overexpression transgenic rose plants of RhSPL4 exhibited delayed or early flowering,respectively.Analysis of transcriptome data from transgenic lines overexpressing RhSPL4 compared to the wild type indicated that differentially expressed genes were significantly enriched in the circadian rhythm pathway.Among the proteins encoded by these genes,RhSPL4 binds to the promoter of PSEUDO-RESPONSE REGULATOR 5-LIKE(RhPRR5L),as revealed in yeast one-hybrid,dual-Luciferase/Renilla luciferase reporter,chromatin immunoprecipitation-quantitative PCR and electrophoretic mobility shift assay.Furthermore,RhSPL4 specifically binds to the478 to441 bp region of the RhPRR5L promoter and activates its transcription.The silencing of RhPRR5L delayed flowering time in rose,resembling the phenotype of RhSPL4-silenced plants.Together,these results indicate that the RhSPL4-RhPRR5L module positively regulates flowering time in rose,laying the foundation for the genetic improvement of flowering time in this important horticultural crop.
基金supported by Fund of State Key Laboratory of IPOC(BUPT)(No.IPOC2021ZT16),China.
文摘The integrated optical true time delay phased array antenna system has the advantages of high bandwidth,small size,low loss and strong antiinterference capability,etc.The high integration of the optically controlled phased array antenna system is a necessary trend for the future development of the phased array,and it is also a major focus and difficulty in the current research of integrated microwave photonics.This paper firstly introduces the basic principle and development history of optical true time delay phased array antenna system based on microwave photonics,and briefly introduces the main implementation methods and integration platform of optical true time delay.Then,the application and development prospect of optical true time delay technology in beam control of phased array antenna system are mainly presented.Finally,according to the current research progress,the possible research directions of integrated optically controlled phased array antenna systems in the future are proposed.
基金supported in part by National Key R&D Program of China(Grant No.2022YFC3803700)in part by the National Natural Science Foundation of China(Grant No.92067102)in part by the project of Beijing Laboratory of Advanced Information Networks.
文摘The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.
文摘It is shown that time asymmetry is essential for deriving thermodynamic law and arises from the turnover of energy while reducing its information content and driving entropy increase. A dynamically interpreted principle of least action enables time asymmetry and time flow as a generation of action and redefines useful energy as an information system which implements a form of acting information. This is demonstrated using a basic formula, originally applied for time symmetry/energy conservation considerations, relating time asymmetry (which is conventionally denied but here expressly allowed), to energy behaviour. The results derived then explained that a dynamic energy is driving time asymmetry. It is doing it by decreasing the information content of useful energy, thus generating action and entropy increase, explaining action-time as an information phenomenon. Thermodynamic laws follow directly. The formalism derived readily explains what energy is, why it is conserved (1st law of thermodynamics), why entropy increases (2nd law) and that maximum entropy production within the restraints of the system controls self-organized processes of non-linear irreversible thermodynamics. The general significance of the principle of least action arises from its role of controlling the action generating oriented time of nature. These results contrast with present understanding of time neutrality and clock-time, which are here considered a source of paradoxes, intellectual contradictions and dead-end roads in models explaining nature and the universe.
