In the field of edge computing,achieving low-latency computational task offloading with limited resources is a critical research challenge,particularly in resource-constrained and latency-sensitive vehicular network e...In the field of edge computing,achieving low-latency computational task offloading with limited resources is a critical research challenge,particularly in resource-constrained and latency-sensitive vehicular network environments where rapid response is mandatory for safety-critical applications.In scenarios where edge servers are sparsely deployed,the lack of coordination and information sharing often leads to load imbalance,thereby increasing system latency.Furthermore,in regions without edge server coverage,tasks must be processed locally,which further exacerbates latency issues.To address these challenges,we propose a novel and efficient Deep Reinforcement Learning(DRL)-based approach aimed at minimizing average task latency.The proposed method incorporates three offloading strategies:local computation,direct offloading to the edge server in local region,and device-to-device(D2D)-assisted offloading to edge servers in other regions.We formulate the task offloading process as a complex latency minimization optimization problem.To solve it,we propose an advanced algorithm based on the Dueling Double Deep Q-Network(D3QN)architecture and incorporating the Prioritized Experience Replay(PER)mechanism.Experimental results demonstrate that,compared with existing offloading algorithms,the proposed method significantly reduces average task latency,enhances user experience,and offers an effective strategy for latency optimization in future edge computing systems under dynamic workloads.展开更多
Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence archite...Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence architectures in terms of latency,energy efficiency,and computational power.To achieve this vision,it is of vital importance to scale up the PNNs while simultaneously reducing the high demand on the dimensions required by them.The underlying cause of this strategy is the enormous gap between the scales of photonic and electronic integrated circuits.Here,we demonstrate monolithically integrated optical convolutional processors on thin film lithium niobate(TFLN)that harness inherent parallelism in photonics to enable large-scale programmable convolution kernels and,in turn,greatly reduce the dimensions required by subsequent fully connected layers.Experimental validation achieves high classification accuracies of 96%(86%)on the MNIST(Fashion-MNIST)dataset and 84.6%on the AG News dataset while dramatically reducing the required subsequent fully connected layer dimensions to 196×10(from 784×10)and 175×4(from 800×4),respectively.Furthermore,our devices can be driven by commercial field-programmable gate array systems;a unique advantage in addition to their scalable channel number and kernel size.Our architecture provides a solution to build practical machine learning photonic devices.展开更多
The efficiency of tunnel excavation,rock strength,stability of surrounding rock,and underground engineering disasters are closely related to lithology.Accurately identifying lithology is a necessary prerequisite for i...The efficiency of tunnel excavation,rock strength,stability of surrounding rock,and underground engineering disasters are closely related to lithology.Accurately identifying lithology is a necessary prerequisite for intelligent,safe,and efficient tunnel construction.The design of conventional recognition models heavily relies on experience and extensive calculations.To develop a model suitable for deployment on construction sites and capable of accurate lithology identification,a fast search method for lithology identification models is proposed.This method integrates geological knowledge,apparent feature extraction techniques,and search algorithms.An efficient feature extraction super network using multi-scale geological features of rock surface is constructed,a model evaluation method that comprehensively considers accuracy and latency is developed,and differential evolution algorithm is used to search for the optimal model parameters.Experiments demonstrate that the proposed method enables the model to evolve faster and more accurately,and eventually a model(LithoNet)suitable for lithological classification is found.It only takes 2.10 ms to infer an image of 224×224,which is 57.25%faster than MobileNet v3 and 62.83%faster than ShuffleNet V2.The F1-score of LithoNet is 0.9874,surpassing classical models such as EfficientNetV2-S.LithoNet can be easily deployed on portable devices,effectively promoting the intelligence and accuracy of lithology identification at engineering sites.展开更多
This article investigates the optimization of low latency and high reliability communication mechanisms in 5G URLLC scenarios.Firstly,the key features and challenges of 5G URLLC were outlined,followed by an in-depth a...This article investigates the optimization of low latency and high reliability communication mechanisms in 5G URLLC scenarios.Firstly,the key features and challenges of 5G URLLC were outlined,followed by an in-depth analysis of the implementation mechanisms for low latency and high reliability communication,including physical layer technology,network architecture optimization,and resource scheduling strategies.Through simulation experiments,the effectiveness of the optimization mechanism has been verified,significantly reducing latency and improving reliability.展开更多
As Internet of Vehicles(IoV)technology continues to advance,edge computing has become an important tool for assisting vehicles in handling complex tasks.However,the process of offloading tasks to edge servers may expo...As Internet of Vehicles(IoV)technology continues to advance,edge computing has become an important tool for assisting vehicles in handling complex tasks.However,the process of offloading tasks to edge servers may expose vehicles to malicious external attacks,resulting in information loss or even tampering,thereby creating serious security vulnerabilities.Blockchain technology can maintain a shared ledger among servers.In the Raft consensus mechanism,as long as more than half of the nodes remain operational,the system will not collapse,effectively maintaining the system’s robustness and security.To protect vehicle information,we propose a security framework that integrates the Raft consensus mechanism from blockchain technology with edge computing.To address the additional latency introduced by blockchain,we derived a theoretical formula for system delay and proposed a convex optimization solution to minimize the system latency,ensuring that the system meets the requirements for low latency and high reliability.Simulation results demonstrate that the optimized data extraction rate significantly reduces systemdelay,with relatively stable variations in latency.Moreover,the proposed optimization solution based on this model can provide valuable insights for enhancing security and efficiency in future network environments,such as 5G and next-generation smart city systems.展开更多
Low-altitude economy opens up a completely new aerial space for economic growth by enabling brand new services such as fast logistics delivery,timely emergency rescue,and wide-area,high-definition environmental monito...Low-altitude economy opens up a completely new aerial space for economic growth by enabling brand new services such as fast logistics delivery,timely emergency rescue,and wide-area,high-definition environmental monitoring.This new space has many distinct features and therefore faces many new challenges compared with ground-and high-altitude-based information infrastructures.As a result,the rapid and mass development of unmanned aerial vehicles(UAVs)in low-altitude space will inevitably necessitate research on providing ultra-reliable,low-latency,high-capacity.展开更多
Soft fiberoptic choledochoscope is an important tool for the diagnose and surgical treatment of biliary disease.However,the traditional soft fiberoptic choledochoscope is hard to operate,due to the low position accura...Soft fiberoptic choledochoscope is an important tool for the diagnose and surgical treatment of biliary disease.However,the traditional soft fiberoptic choledochoscope is hard to operate,due to the low position accuracy.Based on the conventional soft fiberoptic choledochoscope,an electrical soft fiberoptic choledochoscope robot with a low latency was developed.In order to improve the controllability of the conventional choledochoscope,the wire traction mechanism and the rotation mechanism are used to bend and rotate the scope,so as to control its movement orientation.The dead band compensation model and control algorithm of the wire traction mechanism are developed to improve the accuracy of the orientation control.The human-computer interaction system and complex motion control system are developed based on ARM embedded system and FPGA.Thanks to the high-speed synchronization channel between FPGA and peripheral,the design of low latency whole-procedure surgical mode was established and verified.Combined with a micro image sensor,real-time video back transmission was realized.The performance of the robot prototype was verified by animal experiment in vivo on a pig.The robot has an extremely low operating latency of no more than 0.402 ms,and a high bending positioning accuracy of±1.43°error margin within 99.7%confidence interval,which guarantees the safety of biliary surgery.展开更多
Microservices have revolutionized traditional software architecture. While monolithic designs continue to be common, particularly in legacy applications, there is a growing trend towards the modularity, independent de...Microservices have revolutionized traditional software architecture. While monolithic designs continue to be common, particularly in legacy applications, there is a growing trend towards the modularity, independent deployability, and flexibility offered by microservices, which is further enhanced by developments in cloud technology. This shift towards microservice architecture meets the modern business need for agility, facilitating rapid adaptability in a competitive landscape. Microservices offer an agile framework and, in many cases, can simplify the development process, though the implementation can vary and sometimes introduce complexities. Unlike monolithic systems, which can be cumbersome to modify, microservices enable quicker adjustments and faster deployment times, essential in today’s dynamic environment. This article delves into the essence of microservices and explores their growing prominence in the software industry.展开更多
SI:Agentic AI for 6G Networks.Introduction.6G networks are poised to provide full coverage across air,land,and sea,deliver terabit-per-second data rates,and achieve microsecond-level latency.They promise comprehensive...SI:Agentic AI for 6G Networks.Introduction.6G networks are poised to provide full coverage across air,land,and sea,deliver terabit-per-second data rates,and achieve microsecond-level latency.They promise comprehensive upgrades across industries through embedded intelligence,ushering in an era of intelligent interconnection of all things.However,managing real-time interactions among devices,infrastructure,and services in 6G networks is much more complex than in previous generations.Massive data streams from terrestrial nodes(e.g.,edge devices,sensors,distributed computing)and non-terrestrial nodes(LEO/MEO/GEO satellites)demand more intelligent and efficient processing.展开更多
Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple dat...Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance.展开更多
Aim: To assess the psychometric properties of the Chinese Index of Premature Ejaculation (CIPE). Methods: The sexual function of 167 patients with and 114 normai controls without premature ejaculation (PE) were evalua...Aim: To assess the psychometric properties of the Chinese Index of Premature Ejaculation (CIPE). Methods: The sexual function of 167 patients with and 114 normai controls without premature ejaculation (PE) were evaluated with CIPE. All subjects were married and had regular sexual activity. The CIPE has 10 questions, focusing on libido, erectile function, ejaculatory latency, sexual satisfaction and difficulty in delaying ejaculation, self-confi dence and depression. Each question was responded to on a 5 point Likert-type scale. The individual question score and the total scale score were analyzed between the two groups. Results: There were no significant differences between the age, duration of marriage and educational level (P > 0.05) of patients with and vvithout PE and normai controls. The mean latency of patients with PE and normai controls were 1.6±1.2 and 10.2±9.5 minutes, respectively. Significant differences between patients with (26.7±4.6) PE and normai controls (41.9±4.0) were observed on the total score of CIPE (P < 0.01). Using binary logistic regression analysis, PE was significantly related to five questions of the original measure. They are the so-called the CIPE-5 and include: ejaculatory latency, sexual satisfaction of patients and sexual partner, difficulty in delaying ejaculation, anxiety and depression. Receiver Operat ing Characteristic (ROC) curve analysis of CIPE-5 questionnaire indicated that the sensitivity and specificity of CIPE were 97.60 % and 94.74 %, respectively. Employing the total score of CIPE-5, patients with PE could be divided into three groups: mild (>15 point) 19.8 %, moderate (10-14 point) 62.8 % and severe (< 9 point) 16.7 %. Conclusion: The CIPE-5 is a useful method for the evaluation of sexual function of patients with PE and can be used as a clinical endpoint for clinical trials studying the efficacy of pharmacologica] intervention.展开更多
This study examined the effect of electro-acupuncture (EA) combined with transcranial magnetic stimulation (TMS) therapy at different time windows on learning and memory ability of rats with cerebral infarction and th...This study examined the effect of electro-acupuncture (EA) combined with transcranial magnetic stimulation (TMS) therapy at different time windows on learning and memory ability of rats with cerebral infarction and the underlying mechanism.Two hundred SD rats were randomly divided into four groups:normal group,sham-operated group,model group and EA+TMS group,and each group was then divided into five sub-groups in terms of the different time to start treatment post operation:6,12,24,48 and 72 h.Cerebral infarction models were established in the model and the EA+TMS groups by left middle cerebral artery occlusion/reperfusion (MCAO/R).After treatment for 14 d,the Morris water maze test was applied to examine the spatial learning and memory abilities of rats.In infarcted area,the expression of caspase-3 was immunohistochemically detected,and real-time fluorescent quantitative PCR was used to measure the expression of Bcl-2 mRNA.The results showed that in EA+TMS group compared with model group at the same treatment time windows,the escape latency was substantially shortened,the expression of caspase-3 was considerably decreased and the expression level of Bcl-2 mRNA significantly increased (P<0.05).In the EA+TMS sub-groups,the escape latency was shortest,the expression level of caspase-3 lowest,and the expression level of Bcl-2 mRNA highest at the treatment time window of 24 h.It was concluded that EA combined with TMS can promote neurological function of rats with cerebral infarction by increasing the expression level of Bcl-2 mRNA and decreasing the expression of caspase-3.The best time window is 24 h after perfusion treatment to ischemia.展开更多
Sparse code multiple access(SCMA) is a novel non-orthogonal multiple access scheme proposed to meet the challenging demand of the future 5G communications, especially in support of the massive connections. The coded b...Sparse code multiple access(SCMA) is a novel non-orthogonal multiple access scheme proposed to meet the challenging demand of the future 5G communications, especially in support of the massive connections. The coded bits from each data stream will be directly mapped as multi-dimensional SCMA codeword in complex domain and then spread onto the physical resource elements in a sparse manner. The number of codewords that can be nonorthogonally multiplexed in one SCMA block can be made much larger than the number of orthogonal resource elements therein, resulting in an overloaded system. The sparsity in the spreading pattern and the design in the multidimensional modulator jointly ensure the SCMA codewords can be robustly decoded with low complexity. In this paper, we focus on the low complexity receiver design and verified the superior of an SCMA system via simulations and real-time prototyping. Lab tests and field tests all show that SCMA is a promising candidate for 5G non-orthogonal multiple access which can provide up to 300% overloading that triples the whole system throughput while still enjoying the link performance close to orthogonal transmissions.展开更多
Due to the rapid development of the maritime networks, there has been a growing demand for computation-intensive applications which have various energy consumption, transmission bandwidth and computing latency require...Due to the rapid development of the maritime networks, there has been a growing demand for computation-intensive applications which have various energy consumption, transmission bandwidth and computing latency requirements. Mobile edge computing(MEC) can efficiently minimize computational latency by offloading computation tasks by the terrestrial access network. In this work, we introduce a space-air-ground-sea integrated network architecture with edge and cloud computing components to provide flexible hybrid computing service for maritime service. In the integrated network, satellites and unmanned aerial vehicles(UAVs) provide the users with edge computing services and network access. Based on the architecture, the joint communication and computation resource allocation problem is modelled as a complex decision process, and a deep reinforcement learning based solution is designed to solve the complex optimization problem. Finally, numerical results verify that the proposed approach can improve the communication and computing efficiency greatly.展开更多
Various factors/pathways including hormonal regulation have been suggested to control herpes simplex virus type 1 （HSV-1） latency and reactivation. Our computer analysis identified a DNA repeat containing thyroid ho...Various factors/pathways including hormonal regulation have been suggested to control herpes simplex virus type 1 （HSV-1） latency and reactivation. Our computer analysis identified a DNA repeat containing thyroid hormoneresponsive elements （TRE） in the regulatory region of HSV-1 latency-associated transcript （LAT）. Thyroid hormone （triiodothyronine, T3） functions via its receptor TR （thyroid hormone receptor）, a transcription factor. Present study investigated the roles of TR and T3 in HSV-1 gene expression using cultured neuoroblastoma cell lines. We demonstrated that liganded TR activated LAT transcription, but repressed infected cell protein no. 0 （ICP0） transcription in the presence of LAT TRE. Chromatin immunoprecipitation （CHIP） assays showed that TRs were recruited to LAT TREs independently of T3 and hyperacetylated H4 was associated with the LAT promoter that was transcriptionally active. In addition, ChIP results showed that the chromatin insulator protein CCCTC-binding factor was enriched at the LAT TREs in the presence of TR and T3. In addition, the BRG1 chromatin remodeling complex is found to participate in the T3/TR-mediated LAT activation since overexpression of BRG1 enhanced the LAT transcription and the dominant-negative mutant K785R abolished the activation. This is the first report revealing that TR elicits epigenetic regulation on HSV-1 ICP0 expression in neuronal cells and could have a role in the complex processes of HSV-1 latency/reactivation.展开更多
Varicella zoster virus(VZV) is the causative agent of varicella(chicken pox) and herpes zoster(shingles). After primary infection, the virus remains latent in sensory ganglia, and reactivates upon weakening of the cel...Varicella zoster virus(VZV) is the causative agent of varicella(chicken pox) and herpes zoster(shingles). After primary infection, the virus remains latent in sensory ganglia, and reactivates upon weakening of the cellular immune system due to various conditions, erupting from sensory neurons and infecting the corresponding skin tissue. The current varicella vaccine(v-Oka) is highly attenuated in the skin, yet retains its neurovirulence and may reactivate and damage sensory neurons. The reactivation is sometimes associated with postherpetic neuralgia(PHN), a severe pain along the affected sensory nerves that can linger for years, even after the herpetic rash resolves. In addition to the older population that develops a secondary infection resulting in herpes zoster, childhood breakthrough herpes zoster affects a small population of vaccinated children. There is a great need for a neuro-attenuated vaccine that would prevent not only the varicella manifestation, but, more importantly, any establishment of latency, and therefore herpes zoster. The development of a genetically-defined live-attenuated VZV vaccine that prevents neuronal and latent infection, in addition to primary varicella, is imperative for eventual eradication of VZV, and, if fully understood, has vast implications for many related herpesviruses and other viruses with similar pathogenic mechanisms.展开更多
基金supported by the National Natural Science Foundation of China(62202215)Liaoning Province Applied Basic Research Program(Youth Special Project,2023JH2/101600038)+4 种基金Shenyang Youth Science and Technology Innovation Talent Support Program(RC220458)Guangxuan Program of Shenyang Ligong University(SYLUGXRC202216)the Basic Research Special Funds for Undergraduate Universities in Liaoning Province(LJ212410144067)the Natural Science Foundation of Liaoning Province(2024-MS-113)the science and technology funds from Liaoning Education Department(LJKZ0242).
文摘In the field of edge computing,achieving low-latency computational task offloading with limited resources is a critical research challenge,particularly in resource-constrained and latency-sensitive vehicular network environments where rapid response is mandatory for safety-critical applications.In scenarios where edge servers are sparsely deployed,the lack of coordination and information sharing often leads to load imbalance,thereby increasing system latency.Furthermore,in regions without edge server coverage,tasks must be processed locally,which further exacerbates latency issues.To address these challenges,we propose a novel and efficient Deep Reinforcement Learning(DRL)-based approach aimed at minimizing average task latency.The proposed method incorporates three offloading strategies:local computation,direct offloading to the edge server in local region,and device-to-device(D2D)-assisted offloading to edge servers in other regions.We formulate the task offloading process as a complex latency minimization optimization problem.To solve it,we propose an advanced algorithm based on the Dueling Double Deep Q-Network(D3QN)architecture and incorporating the Prioritized Experience Replay(PER)mechanism.Experimental results demonstrate that,compared with existing offloading algorithms,the proposed method significantly reduces average task latency,enhances user experience,and offers an effective strategy for latency optimization in future edge computing systems under dynamic workloads.
基金supported by the National Natural Science Foundation of China (Grant Nos.12192251,12334014,62335019,12134001,1230441812474378)+1 种基金the Quantum Science and Technology National Science and Technology Major Project(Grant No.2021ZD0301403)the Shanghai Municipal Science and Technology Major Project (Grant No.2019SHZDZX01)。
文摘Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence architectures in terms of latency,energy efficiency,and computational power.To achieve this vision,it is of vital importance to scale up the PNNs while simultaneously reducing the high demand on the dimensions required by them.The underlying cause of this strategy is the enormous gap between the scales of photonic and electronic integrated circuits.Here,we demonstrate monolithically integrated optical convolutional processors on thin film lithium niobate(TFLN)that harness inherent parallelism in photonics to enable large-scale programmable convolution kernels and,in turn,greatly reduce the dimensions required by subsequent fully connected layers.Experimental validation achieves high classification accuracies of 96%(86%)on the MNIST(Fashion-MNIST)dataset and 84.6%on the AG News dataset while dramatically reducing the required subsequent fully connected layer dimensions to 196×10(from 784×10)and 175×4(from 800×4),respectively.Furthermore,our devices can be driven by commercial field-programmable gate array systems;a unique advantage in addition to their scalable channel number and kernel size.Our architecture provides a solution to build practical machine learning photonic devices.
基金financial support from the National Natural Science Foundation of China(Grant Nos.52279103 and 52379103)the Natural Science Foundation of Shandong Province(Grant No.ZR2023YQ049).
文摘The efficiency of tunnel excavation,rock strength,stability of surrounding rock,and underground engineering disasters are closely related to lithology.Accurately identifying lithology is a necessary prerequisite for intelligent,safe,and efficient tunnel construction.The design of conventional recognition models heavily relies on experience and extensive calculations.To develop a model suitable for deployment on construction sites and capable of accurate lithology identification,a fast search method for lithology identification models is proposed.This method integrates geological knowledge,apparent feature extraction techniques,and search algorithms.An efficient feature extraction super network using multi-scale geological features of rock surface is constructed,a model evaluation method that comprehensively considers accuracy and latency is developed,and differential evolution algorithm is used to search for the optimal model parameters.Experiments demonstrate that the proposed method enables the model to evolve faster and more accurately,and eventually a model(LithoNet)suitable for lithological classification is found.It only takes 2.10 ms to infer an image of 224×224,which is 57.25%faster than MobileNet v3 and 62.83%faster than ShuffleNet V2.The F1-score of LithoNet is 0.9874,surpassing classical models such as EfficientNetV2-S.LithoNet can be easily deployed on portable devices,effectively promoting the intelligence and accuracy of lithology identification at engineering sites.
文摘This article investigates the optimization of low latency and high reliability communication mechanisms in 5G URLLC scenarios.Firstly,the key features and challenges of 5G URLLC were outlined,followed by an in-depth analysis of the implementation mechanisms for low latency and high reliability communication,including physical layer technology,network architecture optimization,and resource scheduling strategies.Through simulation experiments,the effectiveness of the optimization mechanism has been verified,significantly reducing latency and improving reliability.
基金supported in part by the National Natural Science Foundation of China under Grant No.61701197in part by the National Key Research and Development Program of China under Grant No.2021YFA1000500(4)in part by the 111 project under Grant No.B23008.
文摘As Internet of Vehicles(IoV)technology continues to advance,edge computing has become an important tool for assisting vehicles in handling complex tasks.However,the process of offloading tasks to edge servers may expose vehicles to malicious external attacks,resulting in information loss or even tampering,thereby creating serious security vulnerabilities.Blockchain technology can maintain a shared ledger among servers.In the Raft consensus mechanism,as long as more than half of the nodes remain operational,the system will not collapse,effectively maintaining the system’s robustness and security.To protect vehicle information,we propose a security framework that integrates the Raft consensus mechanism from blockchain technology with edge computing.To address the additional latency introduced by blockchain,we derived a theoretical formula for system delay and proposed a convex optimization solution to minimize the system latency,ensuring that the system meets the requirements for low latency and high reliability.Simulation results demonstrate that the optimized data extraction rate significantly reduces systemdelay,with relatively stable variations in latency.Moreover,the proposed optimization solution based on this model can provide valuable insights for enhancing security and efficiency in future network environments,such as 5G and next-generation smart city systems.
文摘Low-altitude economy opens up a completely new aerial space for economic growth by enabling brand new services such as fast logistics delivery,timely emergency rescue,and wide-area,high-definition environmental monitoring.This new space has many distinct features and therefore faces many new challenges compared with ground-and high-altitude-based information infrastructures.As a result,the rapid and mass development of unmanned aerial vehicles(UAVs)in low-altitude space will inevitably necessitate research on providing ultra-reliable,low-latency,high-capacity.
基金the Science and Technology Commission of Shanghai Municipality(No.18441900500)。
文摘Soft fiberoptic choledochoscope is an important tool for the diagnose and surgical treatment of biliary disease.However,the traditional soft fiberoptic choledochoscope is hard to operate,due to the low position accuracy.Based on the conventional soft fiberoptic choledochoscope,an electrical soft fiberoptic choledochoscope robot with a low latency was developed.In order to improve the controllability of the conventional choledochoscope,the wire traction mechanism and the rotation mechanism are used to bend and rotate the scope,so as to control its movement orientation.The dead band compensation model and control algorithm of the wire traction mechanism are developed to improve the accuracy of the orientation control.The human-computer interaction system and complex motion control system are developed based on ARM embedded system and FPGA.Thanks to the high-speed synchronization channel between FPGA and peripheral,the design of low latency whole-procedure surgical mode was established and verified.Combined with a micro image sensor,real-time video back transmission was realized.The performance of the robot prototype was verified by animal experiment in vivo on a pig.The robot has an extremely low operating latency of no more than 0.402 ms,and a high bending positioning accuracy of±1.43°error margin within 99.7%confidence interval,which guarantees the safety of biliary surgery.
文摘Microservices have revolutionized traditional software architecture. While monolithic designs continue to be common, particularly in legacy applications, there is a growing trend towards the modularity, independent deployability, and flexibility offered by microservices, which is further enhanced by developments in cloud technology. This shift towards microservice architecture meets the modern business need for agility, facilitating rapid adaptability in a competitive landscape. Microservices offer an agile framework and, in many cases, can simplify the development process, though the implementation can vary and sometimes introduce complexities. Unlike monolithic systems, which can be cumbersome to modify, microservices enable quicker adjustments and faster deployment times, essential in today’s dynamic environment. This article delves into the essence of microservices and explores their growing prominence in the software industry.
文摘SI:Agentic AI for 6G Networks.Introduction.6G networks are poised to provide full coverage across air,land,and sea,deliver terabit-per-second data rates,and achieve microsecond-level latency.They promise comprehensive upgrades across industries through embedded intelligence,ushering in an era of intelligent interconnection of all things.However,managing real-time interactions among devices,infrastructure,and services in 6G networks is much more complex than in previous generations.Massive data streams from terrestrial nodes(e.g.,edge devices,sensors,distributed computing)and non-terrestrial nodes(LEO/MEO/GEO satellites)demand more intelligent and efficient processing.
文摘Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance.
文摘Aim: To assess the psychometric properties of the Chinese Index of Premature Ejaculation (CIPE). Methods: The sexual function of 167 patients with and 114 normai controls without premature ejaculation (PE) were evaluated with CIPE. All subjects were married and had regular sexual activity. The CIPE has 10 questions, focusing on libido, erectile function, ejaculatory latency, sexual satisfaction and difficulty in delaying ejaculation, self-confi dence and depression. Each question was responded to on a 5 point Likert-type scale. The individual question score and the total scale score were analyzed between the two groups. Results: There were no significant differences between the age, duration of marriage and educational level (P > 0.05) of patients with and vvithout PE and normai controls. The mean latency of patients with PE and normai controls were 1.6±1.2 and 10.2±9.5 minutes, respectively. Significant differences between patients with (26.7±4.6) PE and normai controls (41.9±4.0) were observed on the total score of CIPE (P < 0.01). Using binary logistic regression analysis, PE was significantly related to five questions of the original measure. They are the so-called the CIPE-5 and include: ejaculatory latency, sexual satisfaction of patients and sexual partner, difficulty in delaying ejaculation, anxiety and depression. Receiver Operat ing Characteristic (ROC) curve analysis of CIPE-5 questionnaire indicated that the sensitivity and specificity of CIPE were 97.60 % and 94.74 %, respectively. Employing the total score of CIPE-5, patients with PE could be divided into three groups: mild (>15 point) 19.8 %, moderate (10-14 point) 62.8 % and severe (< 9 point) 16.7 %. Conclusion: The CIPE-5 is a useful method for the evaluation of sexual function of patients with PE and can be used as a clinical endpoint for clinical trials studying the efficacy of pharmacologica] intervention.
基金supported by a grant from the National Natural Science Foundation of China (No.30640010)
文摘This study examined the effect of electro-acupuncture (EA) combined with transcranial magnetic stimulation (TMS) therapy at different time windows on learning and memory ability of rats with cerebral infarction and the underlying mechanism.Two hundred SD rats were randomly divided into four groups:normal group,sham-operated group,model group and EA+TMS group,and each group was then divided into five sub-groups in terms of the different time to start treatment post operation:6,12,24,48 and 72 h.Cerebral infarction models were established in the model and the EA+TMS groups by left middle cerebral artery occlusion/reperfusion (MCAO/R).After treatment for 14 d,the Morris water maze test was applied to examine the spatial learning and memory abilities of rats.In infarcted area,the expression of caspase-3 was immunohistochemically detected,and real-time fluorescent quantitative PCR was used to measure the expression of Bcl-2 mRNA.The results showed that in EA+TMS group compared with model group at the same treatment time windows,the escape latency was substantially shortened,the expression of caspase-3 was considerably decreased and the expression level of Bcl-2 mRNA significantly increased (P<0.05).In the EA+TMS sub-groups,the escape latency was shortest,the expression level of caspase-3 lowest,and the expression level of Bcl-2 mRNA highest at the treatment time window of 24 h.It was concluded that EA combined with TMS can promote neurological function of rats with cerebral infarction by increasing the expression level of Bcl-2 mRNA and decreasing the expression of caspase-3.The best time window is 24 h after perfusion treatment to ischemia.
文摘Sparse code multiple access(SCMA) is a novel non-orthogonal multiple access scheme proposed to meet the challenging demand of the future 5G communications, especially in support of the massive connections. The coded bits from each data stream will be directly mapped as multi-dimensional SCMA codeword in complex domain and then spread onto the physical resource elements in a sparse manner. The number of codewords that can be nonorthogonally multiplexed in one SCMA block can be made much larger than the number of orthogonal resource elements therein, resulting in an overloaded system. The sparsity in the spreading pattern and the design in the multidimensional modulator jointly ensure the SCMA codewords can be robustly decoded with low complexity. In this paper, we focus on the low complexity receiver design and verified the superior of an SCMA system via simulations and real-time prototyping. Lab tests and field tests all show that SCMA is a promising candidate for 5G non-orthogonal multiple access which can provide up to 300% overloading that triples the whole system throughput while still enjoying the link performance close to orthogonal transmissions.
基金the National Natural Science Foundation of China under Grant No. U1805262
文摘Due to the rapid development of the maritime networks, there has been a growing demand for computation-intensive applications which have various energy consumption, transmission bandwidth and computing latency requirements. Mobile edge computing(MEC) can efficiently minimize computational latency by offloading computation tasks by the terrestrial access network. In this work, we introduce a space-air-ground-sea integrated network architecture with edge and cloud computing components to provide flexible hybrid computing service for maritime service. In the integrated network, satellites and unmanned aerial vehicles(UAVs) provide the users with edge computing services and network access. Based on the architecture, the joint communication and computation resource allocation problem is modelled as a complex decision process, and a deep reinforcement learning based solution is designed to solve the complex optimization problem. Finally, numerical results verify that the proposed approach can improve the communication and computing efficiency greatly.
文摘Various factors/pathways including hormonal regulation have been suggested to control herpes simplex virus type 1 （HSV-1） latency and reactivation. Our computer analysis identified a DNA repeat containing thyroid hormoneresponsive elements （TRE） in the regulatory region of HSV-1 latency-associated transcript （LAT）. Thyroid hormone （triiodothyronine, T3） functions via its receptor TR （thyroid hormone receptor）, a transcription factor. Present study investigated the roles of TR and T3 in HSV-1 gene expression using cultured neuoroblastoma cell lines. We demonstrated that liganded TR activated LAT transcription, but repressed infected cell protein no. 0 （ICP0） transcription in the presence of LAT TRE. Chromatin immunoprecipitation （CHIP） assays showed that TRs were recruited to LAT TREs independently of T3 and hyperacetylated H4 was associated with the LAT promoter that was transcriptionally active. In addition, ChIP results showed that the chromatin insulator protein CCCTC-binding factor was enriched at the LAT TREs in the presence of TR and T3. In addition, the BRG1 chromatin remodeling complex is found to participate in the T3/TR-mediated LAT activation since overexpression of BRG1 enhanced the LAT transcription and the dominant-negative mutant K785R abolished the activation. This is the first report revealing that TR elicits epigenetic regulation on HSV-1 ICP0 expression in neuronal cells and could have a role in the complex processes of HSV-1 latency/reactivation.
文摘Varicella zoster virus(VZV) is the causative agent of varicella(chicken pox) and herpes zoster(shingles). After primary infection, the virus remains latent in sensory ganglia, and reactivates upon weakening of the cellular immune system due to various conditions, erupting from sensory neurons and infecting the corresponding skin tissue. The current varicella vaccine(v-Oka) is highly attenuated in the skin, yet retains its neurovirulence and may reactivate and damage sensory neurons. The reactivation is sometimes associated with postherpetic neuralgia(PHN), a severe pain along the affected sensory nerves that can linger for years, even after the herpetic rash resolves. In addition to the older population that develops a secondary infection resulting in herpes zoster, childhood breakthrough herpes zoster affects a small population of vaccinated children. There is a great need for a neuro-attenuated vaccine that would prevent not only the varicella manifestation, but, more importantly, any establishment of latency, and therefore herpes zoster. The development of a genetically-defined live-attenuated VZV vaccine that prevents neuronal and latent infection, in addition to primary varicella, is imperative for eventual eradication of VZV, and, if fully understood, has vast implications for many related herpesviruses and other viruses with similar pathogenic mechanisms.
