The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections an...The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and convergence.In this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration.Due to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions.Regarding the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the flows.In addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+MADDPG.Introducing a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network environment.The LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.展开更多
Listening is the primary method to access language information.It is an essential part of L2(second language)teaching but also the most difficult skill to master for L2 learners.Based on this,it is necessary to analyz...Listening is the primary method to access language information.It is an essential part of L2(second language)teaching but also the most difficult skill to master for L2 learners.Based on this,it is necessary to analyze learners’needs in listening.This article aims to conduct a needs analysis of a selected learner from Iraq and describe course material selection and design.Methods including questionnaires,interviews,and observation were used to collect data.Additionally,targeted 60-minute online listening activities were designed.It was found that listening activities can improve both listening and speaking skills.Thus,language teaching should be student-oriented,and subsequent course materials and activity design should be selected based on the analysis of students’needs.展开更多
Among the emitters in powder dusting to visualize the latent fingerprints(LFPs),aggregation-induced emission luminogens(AIEgens)are well employed for their high brightness and resistance to photobleaching.However,the ...Among the emitters in powder dusting to visualize the latent fingerprints(LFPs),aggregation-induced emission luminogens(AIEgens)are well employed for their high brightness and resistance to photobleaching.However,the serious background interference and low resolution still limit their fast development.Therefore,to further enhance the signal-to-noise ratio in LFPs imaging,especially to improve the analysis for level 3 details,donor-acceptor(D-A)typed AIEgens of DTPA-2,3-P,DTPA-2,5-P and DTPA-2,6-P are designed here.It is observed that strong emission covering from 450nm to 650nm can be obtained for all these molecules,especially that a high PLQY value of 10.06%in solids is achieved in DTPA-2,3-P.This is much higher than that of the other two cases(0.80%and 0.51%).By utilizing the DTPA-2,3-P in powder dusting,fluorescence imaging of LFPs can be clearly captured on both smooth and rough substrates.Moreover,confocal laser scanning microscope(CLSM)enables us to achieve high-resolution LFPs imaging in both 2D and 3D views,providing more detailed information of fingerprints pores in width,distance,distribution,and shapes.The results here demonstrate that highly emissive AIEgen of DTPA-2,3-P could be an excellent candidate for the visualization of fingerprints,thus providing the potential application in criminal investigation in the future.展开更多
文摘The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and convergence.In this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration.Due to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions.Regarding the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the flows.In addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+MADDPG.Introducing a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network environment.The LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.
文摘Listening is the primary method to access language information.It is an essential part of L2(second language)teaching but also the most difficult skill to master for L2 learners.Based on this,it is necessary to analyze learners’needs in listening.This article aims to conduct a needs analysis of a selected learner from Iraq and describe course material selection and design.Methods including questionnaires,interviews,and observation were used to collect data.Additionally,targeted 60-minute online listening activities were designed.It was found that listening activities can improve both listening and speaking skills.Thus,language teaching should be student-oriented,and subsequent course materials and activity design should be selected based on the analysis of students’needs.
基金The authors are thankful for the financial support from the National Natural Science Foundation of China(No.21975197)Shaanxi Province Key R&D Program-International Science and Technology Cooperation Project(No.2022KW-40)the Innovation Capability Support Program of Shaanxi(No.2021TD-57).
文摘Among the emitters in powder dusting to visualize the latent fingerprints(LFPs),aggregation-induced emission luminogens(AIEgens)are well employed for their high brightness and resistance to photobleaching.However,the serious background interference and low resolution still limit their fast development.Therefore,to further enhance the signal-to-noise ratio in LFPs imaging,especially to improve the analysis for level 3 details,donor-acceptor(D-A)typed AIEgens of DTPA-2,3-P,DTPA-2,5-P and DTPA-2,6-P are designed here.It is observed that strong emission covering from 450nm to 650nm can be obtained for all these molecules,especially that a high PLQY value of 10.06%in solids is achieved in DTPA-2,3-P.This is much higher than that of the other two cases(0.80%and 0.51%).By utilizing the DTPA-2,3-P in powder dusting,fluorescence imaging of LFPs can be clearly captured on both smooth and rough substrates.Moreover,confocal laser scanning microscope(CLSM)enables us to achieve high-resolution LFPs imaging in both 2D and 3D views,providing more detailed information of fingerprints pores in width,distance,distribution,and shapes.The results here demonstrate that highly emissive AIEgen of DTPA-2,3-P could be an excellent candidate for the visualization of fingerprints,thus providing the potential application in criminal investigation in the future.
