In dynamic 5G network environments,user mobility and heterogeneous network topologies pose dual challenges to the effort of improving performance of mobile edge caching.Existing studies often overlook the dynamic natu...In dynamic 5G network environments,user mobility and heterogeneous network topologies pose dual challenges to the effort of improving performance of mobile edge caching.Existing studies often overlook the dynamic nature of user locations and the potential of device-to-device(D2D)cooperative caching,limiting the reduction of transmission latency.To address this issue,this paper proposes a joint optimization scheme for edge caching that integrates user mobility prediction with deep reinforcement learning.First,a Transformer-based geolocation prediction model is designed,leveraging multi-head attention mechanisms to capture correlations in historical user trajectories for accurate future location prediction.Then,within a three-tier heterogeneous network,we formulate a latency minimization problem under a D2D cooperative caching architecture and develop a mobility-aware Deep Q-Network(DQN)caching strategy.This strategy takes predicted location information as state input and dynamically adjusts the content distribution across small base stations(SBSs)andmobile users(MUs)to reduce end-to-end delay inmulti-hop content retrieval.Simulation results show that the proposed DQN-based method outperforms other baseline strategies across variousmetrics,achieving a 17.2%reduction in transmission delay compared to DQNmethods withoutmobility integration,thus validating the effectiveness of the joint optimization of location prediction and caching decisions.展开更多
The introduction of two-dimensional(2D)perovskite layers on top of three-dimensional(3D)perovskite films enhances the performance and stability of perovskite solar cells(PSCs).However,the electronic effect of the spac...The introduction of two-dimensional(2D)perovskite layers on top of three-dimensional(3D)perovskite films enhances the performance and stability of perovskite solar cells(PSCs).However,the electronic effect of the spacer cation and the quality of the 2D capping layer are critical factors in achieving the required results.In this study,we compared two fluorinated salts:4-(trifluoromethyl)benzamidine hydrochloride(4TF-BA·HCl)and 4-fluorobenzamidine hydrochloride(4F-BA·HCl)to engineer the 3D/2D perovskite films.Surprisingly,4F-BA formed a high-performance 3D/2D heterojunction,while4TF-BA produced an amorphous layer on the perovskite films.Our findings indicate that the balanced intramolecular charge polarization,which leads to effective hydrogen bonding,is more favorable in 4F-BA than in 4TF-BA,promoting the formation of a crystalline 2D perovskite.Nevertheless,4TF-BA managed to improve efficiency to 24%,surpassing the control device,primarily due to the natural passivation capabilities of benzamidine.Interestingly,the devices based on 4F-BA demonstrated an efficiency exceeding 25%with greater longevity under various storage conditions compared to 4TF-BA-based and the control devices.展开更多
The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials off...The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.展开更多
This study presents a novel polyoxometalate(POM)constructed crystalline inorganic framework,featuring a 2D layered architecture with irregular porosity and inherent proton sources.This unique configuration establishes...This study presents a novel polyoxometalate(POM)constructed crystalline inorganic framework,featuring a 2D layered architecture with irregular porosity and inherent proton sources.This unique configuration establishes an intrinsic hydrogen bonding network that facilitates proton hopping(Grotthuss mechanism),achieving a[100]directional proton conductivity of 1.75×10^(-3)S cm^(-1)under a low relative humidity(RH)of 35%at 298 K.Notably,under elevated conditions(338 K,95%RH),it attains a superprotonic conductivity of 1.61 S cm^(-1),representing one of the highest values recorded for framework materials to date.Analysis of the molecular structure,pore geometry characteristics and topological connectivity,and water vapor adsorption experiment(offering proton diffusion coefficient),indicates that the exceptional water-mediated proton dynamics stem from the interlayer S-shaped irregular pore channels,which probably induce a siphon-like effect to significantly enhance the transport of hydrated protons under the vehicle mechanism.This work not only proposes a POM strategy for constructing 2D inorganic frameworks but also reveals the irregular pore channel-enhanced proton dynamics,providing new insights into the optimization of proton conductors.展开更多
[Significance]In alignment with the national germplasm security strategy,current research efforts are accelerating the adoption of precision breeding in sheep.Within the whole-genome selection,accurate phenotyping of ...[Significance]In alignment with the national germplasm security strategy,current research efforts are accelerating the adoption of precision breeding in sheep.Within the whole-genome selection,accurate phenotyping of body morphometrics is critical for assessing growth performance and breeding value.Traditional manual measurements are inefficient,prone to human error,and may cause stress to sheep,limiting their suitability for precision sheep management.By summarizing the applications of sheep body size measurement technologies and analyzing their development directions,this paper provides theoretical references and practical guidance for the research and application of non contact sheep body size measurement.[Progress]This review synthesizes progress across three principal methodological paradigms:two-dimensional(2D)image-based techniques,three-dimensional(3D)point cloud-based approaches,and integrated 2D-3D fusion systems.2D methods,employing either handcrafted geometric features or deep learning-based keypoint detector algorithms,are cost-effective and operationally simple but sensitive to variation in imaging conditions and unable to capture critical circumference metrics.3D point-cloud approaches enable precise reconstruction of full animal morphology,supporting comprehensive body-size acquisition with higher accuracy,yet face challenges including high hardware costs,complex data workflows,and sensitivity to posture variability.Hybrid 2D-3D fusion systems combine semantic richness from RGB imagery with geometric completeness from point clouds.Having been effectively validated in other livestock specise,e.g.,cattle and pigs,these fusion systems have demonstrated excellent performance,providing important technical references and practical insights for sheep body size measurement.[Conclusions and Prospects]Firstly,future research should focus on constructing large-scale,high-quality datasets for sheep body size measurement that encompass diverse breeds,growth stages,and environmental conditions,thereby enhancing model robustness and generalization.Secondly,the development of lightweight artificial intelligence models is essential.Techniques such as model compression,quantization,and algorithmic optimization can substantially reduce computational complexity and storage requirements,facilitating deployment in resource-constrained environments.Thirdly,the 3D point cloud processing pipeline should be streamlined to improve the efficiency of data acquisition,filtering,registration,and segmentation,while promoting the integration of low-cost,high-resilience vision systems into practical farming scenarios.Fourthly,specific emphasis should be placed on improving the accuracy of curved-dimensional measurements,such as chest circumference,abdominal circumference,and shank circumference,through advances in pose standardization,refined 3D segmentation strategies,and multimodal data fusion.Finally,the cross-fertilization of sheep body size measurement technologies with analogous methods for other livestock species offers a promising pathway for mutual learning and collaborative innovation,accelerating the industrialization of automated sheep morphometric systems and supporting the development of intelligent,data-driven pasture management practices.展开更多
为研发同时预防和控制猪圆环病毒2d基因型(PCV2d)和猪伪狂犬病病毒(PRV)的疫苗,将PCV2dORF2基因克隆到含有绿色荧光蛋白(EGFP)基因的PRV转移质粒pG中BamHⅠ位点,获得重组质粒pG-PCV2d-EGFP。运用转染试剂ZLip2000将其与PRV变异株3基因...为研发同时预防和控制猪圆环病毒2d基因型(PCV2d)和猪伪狂犬病病毒(PRV)的疫苗,将PCV2dORF2基因克隆到含有绿色荧光蛋白(EGFP)基因的PRV转移质粒pG中BamHⅠ位点,获得重组质粒pG-PCV2d-EGFP。运用转染试剂ZLip2000将其与PRV变异株3基因缺失毒株gE^(-)/g^(-)/TK^(-)PRV NY DNA转入ST细胞中,经绿色荧光蚀斑纯化,得到表达EGFP的重组病毒rPRV-PCV2d-EGFP。采用CRISPR/Cas9基因双敲除质粒敲除重组病毒中EGFP基因,经蚀斑纯化,拯救出不表达EGFP的重组病毒rPRV-PCV2d。重组病毒rPRV-PCV2d与亲本株gE^(-)/g^(-)/TK^(-)PRV NY具有相近的遗传稳定性,且能够表达PCV2d衣壳(Cap)蛋白。在6周龄小鼠免疫试验中,与商品化PCV2灭活疫苗相比,rPRV-PCV2d刺激小鼠机体诱导了更高的PCV2特异性抗体,且用PCV2d强毒株攻毒后,rPRV-PCV2d显著降低了小鼠心脏、肝脏、脾脏等组织中PCV2d载量。此外,rPRV-PCV2d在小鼠体内激发PRV特异性免疫应答,并能阻止PRV强毒对小鼠的侵袭。表明rPRV-PCV2d具有良好的免疫原性。展开更多
传统的功率分配算法由于复杂的矩阵运算与迭代所造成的高时延,在实际通信中实时获取信道信息十分困难,当前重要的研究方向是在系统性能和计算复杂度之间找到有效平衡。针对终端直通(Device-to-Device,D2D)用户与蜂窝用户的联合功率分配...传统的功率分配算法由于复杂的矩阵运算与迭代所造成的高时延,在实际通信中实时获取信道信息十分困难,当前重要的研究方向是在系统性能和计算复杂度之间找到有效平衡。针对终端直通(Device-to-Device,D2D)用户与蜂窝用户的联合功率分配问题,提出一种异构功率控制图神经网络(Heterogeneous Power Control Graph Neural Network,HPCGNN)算法,旨在最大化所有用户的加权和速率。首先通过构建干扰的异构图,将信道和噪声等信息嵌入到图的节点和边;再由HPCGNN完成消息传递和更新,采用无监督学习方式优化深度神经网络(Deep Neural Network,DNN)参数,最终得到最佳的功率分配。仿真结果表明,相较于其他深度学习算法,所提算法能够有效提高系统性能,且在损失5%性能下相较分式规划(Fractional Programming,FP)能降低82%~98%的时间复杂度。展开更多
As one of the key technologies for the fifth generation(5G) wireless networks,device-to-device(D2D) communications allow user equipment(UE) in close proximity to communicate with each other directly.Forwarded by a rel...As one of the key technologies for the fifth generation(5G) wireless networks,device-to-device(D2D) communications allow user equipment(UE) in close proximity to communicate with each other directly.Forwarded by a relay,the relay-aided D2D(RA-D2D) communications can not only be applied to communications in much longer distance but also achieve a high quality of service(Qo S) .In this paper,we first propose a two-layer system model allowing RA-D2 D links to underlay traditional cellular uplinks.Then we maximize the energy efficiency of the RA-D2 D link while satisfying the minimum data-rate of the cellular link.The optimal transmit power at both D2 D transmitter and D2 D relay sides is obtained by transforming the nonlinear fractional programming into a nonlinear parameter programming.Simulation results show that our proposed power allocation method is more energy efficient than the existing works,and the proposed RA-D2 D scheme outperformed direct D2 D scheme when the distance between two D2 D users is longer.展开更多
基金supported by the Liaoning Provincial Education Department Fund,grant number JYTZD2023083.
文摘In dynamic 5G network environments,user mobility and heterogeneous network topologies pose dual challenges to the effort of improving performance of mobile edge caching.Existing studies often overlook the dynamic nature of user locations and the potential of device-to-device(D2D)cooperative caching,limiting the reduction of transmission latency.To address this issue,this paper proposes a joint optimization scheme for edge caching that integrates user mobility prediction with deep reinforcement learning.First,a Transformer-based geolocation prediction model is designed,leveraging multi-head attention mechanisms to capture correlations in historical user trajectories for accurate future location prediction.Then,within a three-tier heterogeneous network,we formulate a latency minimization problem under a D2D cooperative caching architecture and develop a mobility-aware Deep Q-Network(DQN)caching strategy.This strategy takes predicted location information as state input and dynamically adjusts the content distribution across small base stations(SBSs)andmobile users(MUs)to reduce end-to-end delay inmulti-hop content retrieval.Simulation results show that the proposed DQN-based method outperforms other baseline strategies across variousmetrics,achieving a 17.2%reduction in transmission delay compared to DQNmethods withoutmobility integration,thus validating the effectiveness of the joint optimization of location prediction and caching decisions.
基金supported by the National Key Research and Development Programs-Intergovernmental International Cooperation in Science and Technology Innovation Project(Grant No.2022YFE0118400)the Natural Science Foundation of Hunan Province(2023JJ50132)+1 种基金Shenzhen Science and Technology Innovation Committee(Grants Nos.JCYJ20220818100211025,and KCXST20221021111616039)Shenzhen Science and Technology Program(No.20231128110928003)。
文摘The introduction of two-dimensional(2D)perovskite layers on top of three-dimensional(3D)perovskite films enhances the performance and stability of perovskite solar cells(PSCs).However,the electronic effect of the spacer cation and the quality of the 2D capping layer are critical factors in achieving the required results.In this study,we compared two fluorinated salts:4-(trifluoromethyl)benzamidine hydrochloride(4TF-BA·HCl)and 4-fluorobenzamidine hydrochloride(4F-BA·HCl)to engineer the 3D/2D perovskite films.Surprisingly,4F-BA formed a high-performance 3D/2D heterojunction,while4TF-BA produced an amorphous layer on the perovskite films.Our findings indicate that the balanced intramolecular charge polarization,which leads to effective hydrogen bonding,is more favorable in 4F-BA than in 4TF-BA,promoting the formation of a crystalline 2D perovskite.Nevertheless,4TF-BA managed to improve efficiency to 24%,surpassing the control device,primarily due to the natural passivation capabilities of benzamidine.Interestingly,the devices based on 4F-BA demonstrated an efficiency exceeding 25%with greater longevity under various storage conditions compared to 4TF-BA-based and the control devices.
基金supported by the IITP(Institute of Information & Communications Technology Planning & Evaluation)-ITRC(Information Technology Research Center) grant funded by the Korea government(Ministry of Science and ICT) (IITP-2025-RS-2024-00437191, and RS-2025-02303505)partly supported by the Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education. (No. 2022R1A6C101A774)the Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia, through Large Research Project under grant number RGP-2/527/46
文摘The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.
基金supported by the National Natural Science Foundation of China(22271075,22171071)。
文摘This study presents a novel polyoxometalate(POM)constructed crystalline inorganic framework,featuring a 2D layered architecture with irregular porosity and inherent proton sources.This unique configuration establishes an intrinsic hydrogen bonding network that facilitates proton hopping(Grotthuss mechanism),achieving a[100]directional proton conductivity of 1.75×10^(-3)S cm^(-1)under a low relative humidity(RH)of 35%at 298 K.Notably,under elevated conditions(338 K,95%RH),it attains a superprotonic conductivity of 1.61 S cm^(-1),representing one of the highest values recorded for framework materials to date.Analysis of the molecular structure,pore geometry characteristics and topological connectivity,and water vapor adsorption experiment(offering proton diffusion coefficient),indicates that the exceptional water-mediated proton dynamics stem from the interlayer S-shaped irregular pore channels,which probably induce a siphon-like effect to significantly enhance the transport of hydrated protons under the vehicle mechanism.This work not only proposes a POM strategy for constructing 2D inorganic frameworks but also reveals the irregular pore channel-enhanced proton dynamics,providing new insights into the optimization of proton conductors.
文摘[Significance]In alignment with the national germplasm security strategy,current research efforts are accelerating the adoption of precision breeding in sheep.Within the whole-genome selection,accurate phenotyping of body morphometrics is critical for assessing growth performance and breeding value.Traditional manual measurements are inefficient,prone to human error,and may cause stress to sheep,limiting their suitability for precision sheep management.By summarizing the applications of sheep body size measurement technologies and analyzing their development directions,this paper provides theoretical references and practical guidance for the research and application of non contact sheep body size measurement.[Progress]This review synthesizes progress across three principal methodological paradigms:two-dimensional(2D)image-based techniques,three-dimensional(3D)point cloud-based approaches,and integrated 2D-3D fusion systems.2D methods,employing either handcrafted geometric features or deep learning-based keypoint detector algorithms,are cost-effective and operationally simple but sensitive to variation in imaging conditions and unable to capture critical circumference metrics.3D point-cloud approaches enable precise reconstruction of full animal morphology,supporting comprehensive body-size acquisition with higher accuracy,yet face challenges including high hardware costs,complex data workflows,and sensitivity to posture variability.Hybrid 2D-3D fusion systems combine semantic richness from RGB imagery with geometric completeness from point clouds.Having been effectively validated in other livestock specise,e.g.,cattle and pigs,these fusion systems have demonstrated excellent performance,providing important technical references and practical insights for sheep body size measurement.[Conclusions and Prospects]Firstly,future research should focus on constructing large-scale,high-quality datasets for sheep body size measurement that encompass diverse breeds,growth stages,and environmental conditions,thereby enhancing model robustness and generalization.Secondly,the development of lightweight artificial intelligence models is essential.Techniques such as model compression,quantization,and algorithmic optimization can substantially reduce computational complexity and storage requirements,facilitating deployment in resource-constrained environments.Thirdly,the 3D point cloud processing pipeline should be streamlined to improve the efficiency of data acquisition,filtering,registration,and segmentation,while promoting the integration of low-cost,high-resilience vision systems into practical farming scenarios.Fourthly,specific emphasis should be placed on improving the accuracy of curved-dimensional measurements,such as chest circumference,abdominal circumference,and shank circumference,through advances in pose standardization,refined 3D segmentation strategies,and multimodal data fusion.Finally,the cross-fertilization of sheep body size measurement technologies with analogous methods for other livestock species offers a promising pathway for mutual learning and collaborative innovation,accelerating the industrialization of automated sheep morphometric systems and supporting the development of intelligent,data-driven pasture management practices.
文摘为研发同时预防和控制猪圆环病毒2d基因型(PCV2d)和猪伪狂犬病病毒(PRV)的疫苗,将PCV2dORF2基因克隆到含有绿色荧光蛋白(EGFP)基因的PRV转移质粒pG中BamHⅠ位点,获得重组质粒pG-PCV2d-EGFP。运用转染试剂ZLip2000将其与PRV变异株3基因缺失毒株gE^(-)/g^(-)/TK^(-)PRV NY DNA转入ST细胞中,经绿色荧光蚀斑纯化,得到表达EGFP的重组病毒rPRV-PCV2d-EGFP。采用CRISPR/Cas9基因双敲除质粒敲除重组病毒中EGFP基因,经蚀斑纯化,拯救出不表达EGFP的重组病毒rPRV-PCV2d。重组病毒rPRV-PCV2d与亲本株gE^(-)/g^(-)/TK^(-)PRV NY具有相近的遗传稳定性,且能够表达PCV2d衣壳(Cap)蛋白。在6周龄小鼠免疫试验中,与商品化PCV2灭活疫苗相比,rPRV-PCV2d刺激小鼠机体诱导了更高的PCV2特异性抗体,且用PCV2d强毒株攻毒后,rPRV-PCV2d显著降低了小鼠心脏、肝脏、脾脏等组织中PCV2d载量。此外,rPRV-PCV2d在小鼠体内激发PRV特异性免疫应答,并能阻止PRV强毒对小鼠的侵袭。表明rPRV-PCV2d具有良好的免疫原性。
文摘传统的功率分配算法由于复杂的矩阵运算与迭代所造成的高时延,在实际通信中实时获取信道信息十分困难,当前重要的研究方向是在系统性能和计算复杂度之间找到有效平衡。针对终端直通(Device-to-Device,D2D)用户与蜂窝用户的联合功率分配问题,提出一种异构功率控制图神经网络(Heterogeneous Power Control Graph Neural Network,HPCGNN)算法,旨在最大化所有用户的加权和速率。首先通过构建干扰的异构图,将信道和噪声等信息嵌入到图的节点和边;再由HPCGNN完成消息传递和更新,采用无监督学习方式优化深度神经网络(Deep Neural Network,DNN)参数,最终得到最佳的功率分配。仿真结果表明,相较于其他深度学习算法,所提算法能够有效提高系统性能,且在损失5%性能下相较分式规划(Fractional Programming,FP)能降低82%~98%的时间复杂度。
基金supported by the ZTE Corp under Grant CON1412150018the Natural Science Foundation of China under Grant 61572389 and 61471361
文摘As one of the key technologies for the fifth generation(5G) wireless networks,device-to-device(D2D) communications allow user equipment(UE) in close proximity to communicate with each other directly.Forwarded by a relay,the relay-aided D2D(RA-D2D) communications can not only be applied to communications in much longer distance but also achieve a high quality of service(Qo S) .In this paper,we first propose a two-layer system model allowing RA-D2 D links to underlay traditional cellular uplinks.Then we maximize the energy efficiency of the RA-D2 D link while satisfying the minimum data-rate of the cellular link.The optimal transmit power at both D2 D transmitter and D2 D relay sides is obtained by transforming the nonlinear fractional programming into a nonlinear parameter programming.Simulation results show that our proposed power allocation method is more energy efficient than the existing works,and the proposed RA-D2 D scheme outperformed direct D2 D scheme when the distance between two D2 D users is longer.
