The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficien...There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.展开更多
Sixth Generation(6G)mobile communication networks will involve sensing as a new function,with the overwhelming trend of Integrated Sensing And Communications(ISAC).Although expanding the serving range of the networks,...Sixth Generation(6G)mobile communication networks will involve sensing as a new function,with the overwhelming trend of Integrated Sensing And Communications(ISAC).Although expanding the serving range of the networks,there exists performance trade-offbetween communication and sensing,in that they have competitions on the physical resources.Different resource allocation schemes will result in different sensing and communication performance,thus influencing the system’s overall performance.Therefore,how to model the system’s overall performance,and how to optimize it are key issues for ISAC.Relying on the large-scale deployment of the networks,cooperative ISAC has the advantages of wider coverage,more robust performance and good compatibility of multiple monostatic and multistatic sensing,compared to the non-cooperative ISAC.How to capture the performance gain of cooperation is a key issue for cooperative ISAC.To address the aforementioned vital problems,in this paper,we analyze the sensing accuracy gain,propose a unified ISAC performance evaluation framework and design several optimization methods in cooperative ISAC systems.The cooperative sensing accuracy gain is theoretically analyzed via Cramér Rao lower bound.The unified ISAC performance evaluation model is established by converting the communication mutual information to the effective minimum mean squared error.To optimize the unified ISAC performance,we design the optimization algorithms considering three factors:base stations’working modes,power allocation schemes and waveform design.Through simulations,we show the performance gain of the cooperative ISAC system and the effectiveness of the proposed optimization methods.展开更多
For the high-precision positioning requirements of UAV formation cooperative operation,a distributed control system based on RTK technology is proposed in this paper.By using the U-blox F9P GNSS module to build an RTK...For the high-precision positioning requirements of UAV formation cooperative operation,a distributed control system based on RTK technology is proposed in this paper.By using the U-blox F9P GNSS module to build an RTK base station/mobile terminal,combined with Pixhawk 6C flight control and MAVESP8266 communication module,centimeter-level(<2 cm)positioning accuracy is achieved.The system adopts the“centralized planning distributed execution”architecture,transmits RTCM differential data and MAVLink messages through the UDP protocol,and integrates ROS to realize status information subscription.Experiments show that the system can effectively support large area surveying and mapping and other complex tasks,and significantly improve the autonomy and reliability of formation operations.展开更多
BACKGROUND Ectonucleoside triphosphate diphosphohydrolase 6(ENTPD6),a member of the ENTPD family,has been implicated in certain cancers,yet a comprehensive analysis across multiple cancer types remains lacking.AIM To ...BACKGROUND Ectonucleoside triphosphate diphosphohydrolase 6(ENTPD6),a member of the ENTPD family,has been implicated in certain cancers,yet a comprehensive analysis across multiple cancer types remains lacking.AIM To systematically evaluate ENTPD6’s expression,prognostic significance,and functions across multiple cancer types.METHODS In this study,we performed a pan-cancer analysis to investigate the correlation between ENTPD6 expression and various factors,including prognosis,genetic alterations,epigenetic modification,immune infiltration,immunotherapy responses,functional enrichment,and drug sensitivity.A tissue microarray of gastrointestinal tumors was used to validate differential ENTPD6 protein expression.RESULTS Pan-cancer analysis revealed that ENTPD6 expression was significantly elevated in many cancers.Immunohistochemistry staining analysis revealed that ENTPD6 expression was significantly higher in esophageal carcinoma,stomach adenocarcinoma,colon adenocarcinoma,rectal adenocarcinoma,and pancreatic adenocarcinoma compared to normal tissues.Furthermore,ENTPD6 expression was strongly associated with immune-infiltrating cells,particularly clusters of differentiation 8+T cells and natural killer cells,and correlated with immune-related genomic features including tumor mutational burden and microsatellite instability.Pathway analysis indicated that ENTPD6 expression was primarily linked to purine and pyrimidine metabolism pathways.Drug sensitivity analysis revealed that high ENTPD6 expression was sensitive to RDEA119,selumetinib,and PD-0325901.CONCLUSION This pan-cancer study elucidates the pivotal role of ENTPD6 in tumor progression and establishes its potential as a therapeutic target for immunotherapeutic approaches in specific malignancies.展开更多
Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication(ISAC)systems,enabling precise navigation in environments where Global Positioning System(GPS)signals are unavailable...Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication(ISAC)systems,enabling precise navigation in environments where Global Positioning System(GPS)signals are unavailable.Existing methods,such as map-based navigation or site-specific fingerprinting,often require intensive data collection and lack generalization capability across different buildings,thereby limiting scalability.This study proposes a cross-site,map-free indoor localization framework that uses low-frequency sub-1 GHz radio signals and a Transformer-based neural network for robust positioning without prior environmental knowledge.The Transformer’s self-attention mechanisms allow it to capture spatial correlations among anchor nodes,facilitating accurate localization in unseen environments.Evaluation across two validation sites demonstrates the framework’s effectiveness.In crosssite testing(Site-A),the Transformer achieved a mean localization error of 9.44 m,outperforming the Deep Neural Network(DNN)(10.76 m)and Convolutional Neural Network(CNN)(12.02 m)baselines.In a real-time deployment(Site-B)spanning three floors,the Transformer maintained an overall mean error of 9.81 m,compared with 13.45 m for DNN,12.88 m for CNN,and 53.08 m for conventional trilateration.For vertical positioning,the Transformer delivered a mean error of 4.52 m,exceeding the performance of DNN(4.59 m),CNN(4.87 m),and trilateration(>45 m).The results confirm that the Transformer-based framework generalizes across heterogeneous indoor environments without requiring site-specific calibration,providing stable,sub-12 m horizontal accuracy and reliable vertical estimation.This capability makes the framework suitable for real-time applications in smart buildings,emergency response,and autonomous systems.By utilizing multipath reflections as an informative structure rather than treating them as noise,this work advances artificial intelligence(AI)-native indoor localization as a scalable and efficient component of future 6G ISAC networks.展开更多
Given the urgency of organic pollutant removal and the low efficiency of advanced oxidation processes(AOPs),a novel Bi-ZFO/BMO-Vo photocatalyst was fabricated via the solvothermal method.A coupling system was construc...Given the urgency of organic pollutant removal and the low efficiency of advanced oxidation processes(AOPs),a novel Bi-ZFO/BMO-Vo photocatalyst was fabricated via the solvothermal method.A coupling system was constructed to combine photocatalysis with peroxymonosulfate(PMS)oxidation processes,which synergistically degrade organic pollutants.Bi-ZFO/BMO-Vo exhibited excellent photocatalytic performance,which could remove 100%RhB in 110 min and degrade 100%MG in 70 min,and 88%H-TC in 50 min.The excellent catalytic performance of Bi-ZFO/BMO-Vo was not only attributed to the synergistic effect of PMS activation and photocatalysis,but also attributed to the SPR effect of Bi nanoparticles,electron capture of oxygen vacancies,and intense contact of Bi-ZFO/BMO-Vo heterojunctions.The active species capture experiments and EPR tests indicated that1 O_(2),SO_(4)^(-)·,·OH,and O_(2)^(-)·worked together for the RhB removal.The degradation intermediates of RhB were identified by LC-MS.Based on the experimental results,the band structure and Z-scheme charge transfer mechanism were proposed.Toxicity evaluation indicated that Bi-ZFO/BMO-Vo-Vis/PMS could significantly reduce RhB toxicity.This efficient and stable catalyst is expected to be used in organic wastewater degradation and practical applications.展开更多
Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth...Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.展开更多
Objective:To elucidate the role and clinical potential of the lncRNA DLX6-AS1/miR-26a/PTEN axis in liver fibrosis.Methods:Systematic studies were conducted using cellular and animal models through causal validation,bi...Objective:To elucidate the role and clinical potential of the lncRNA DLX6-AS1/miR-26a/PTEN axis in liver fibrosis.Methods:Systematic studies were conducted using cellular and animal models through causal validation,bivariate experiments,single-cell sequencing,ROC analysis of clinical samples,and humanized mouse models.Results:LncRNA DLX6-AS1 inhibited PTEN by adsorbing miR-26a,promoting hepatic stellate cell activation in a dose/time-dependent manner;the axis demonstrated excellent diagnostic performance(AUC>0.9),and its inhibitors effectively reversed fibrosis in vivo.Conclusion:This study provides new biomarkers and targeted therapeutic strategies for liver fibrosis.展开更多
A Mixed Numerology OFDM(MN-OFDM)system is essential in 6G and beyond.However,it encounters challenges due to Inter-Numerology Interference(INI).The upcoming 6G technology aims to support innovative applications with h...A Mixed Numerology OFDM(MN-OFDM)system is essential in 6G and beyond.However,it encounters challenges due to Inter-Numerology Interference(INI).The upcoming 6G technology aims to support innovative applications with high data rates,low latency,and reliability.Therefore,effective handling of INI is crucial to meet the diverse requirements of these applications.To address INI in MN-OFDM systems,this paper proposes a User-Based Numerology and Waveform(UBNW)approach that uses various OFDM-based waveforms and their parameters to mitigate INI.By assigning a specific waveform and numerology to each user,UBNW mitigates INI,optimizes service characteristics,and addresses user demands efficiently.The required Guard Bands(GB),expressed as a ratio of user bandwidth,vary significantly across different waveforms at an SIR of 25 dB.For instance,OFDM-FOFDM needs only 2.5%,while OFDM-UFMC,OFDM-WOLA,and conventional OFDM require 7.5%,24%,and 40%,respectively.The time-frequency efficiency also varies between the waveforms.FOFDM achieves 85.6%,UFMC achieves 81.6%,WOLA achieves 70.7%,and conventional OFDM achieves 66.8%.The simulation results demonstrate that the UBNW approach not only effectively mitigates INI but also enhances system flexibility and time-frequency efficiency while simultaneously reducing the required GB.展开更多
随着智能电网的快速发展与物联网终端设备的规模化应用部署,互联网协议第6版(Internet Protocol Version 6,IPv6)技术依托其丰富的地址资源和安全特性,已成为网络架构的关键支撑,IPv6地址的管理和日志审计对保障电网安全稳定运行至关重...随着智能电网的快速发展与物联网终端设备的规模化应用部署,互联网协议第6版(Internet Protocol Version 6,IPv6)技术依托其丰富的地址资源和安全特性,已成为网络架构的关键支撑,IPv6地址的管理和日志审计对保障电网安全稳定运行至关重要。系统探讨了智能电网中物联网设备IPv6地址相关技术原理,深入分析了IPv6地址日志审计技术在智能电网中的应用难点与挑战,提出一种IPv6地址日志审计的简易优化方案,并通过实际案例进行分析和可行性验证,为智能电网中的实际应用提供理论依据和实践指导,对推动智能电网网络安全建设具有重要意义。展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
基金supported by the Ecological Conservation and High-Quality Development of the Yellow River Basin Program,China(2022-YRUC-010102)the Second Tibetan Plateau Scientific Expedition and Research Program,China(20190ZKK0405)the Basic Research Fund Project of Innovation Team of Novel Forage Germplasm and Sustainable Utilization of Grassland Resources,China(BR22-12-07)。
文摘There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.
文摘Sixth Generation(6G)mobile communication networks will involve sensing as a new function,with the overwhelming trend of Integrated Sensing And Communications(ISAC).Although expanding the serving range of the networks,there exists performance trade-offbetween communication and sensing,in that they have competitions on the physical resources.Different resource allocation schemes will result in different sensing and communication performance,thus influencing the system’s overall performance.Therefore,how to model the system’s overall performance,and how to optimize it are key issues for ISAC.Relying on the large-scale deployment of the networks,cooperative ISAC has the advantages of wider coverage,more robust performance and good compatibility of multiple monostatic and multistatic sensing,compared to the non-cooperative ISAC.How to capture the performance gain of cooperation is a key issue for cooperative ISAC.To address the aforementioned vital problems,in this paper,we analyze the sensing accuracy gain,propose a unified ISAC performance evaluation framework and design several optimization methods in cooperative ISAC systems.The cooperative sensing accuracy gain is theoretically analyzed via Cramér Rao lower bound.The unified ISAC performance evaluation model is established by converting the communication mutual information to the effective minimum mean squared error.To optimize the unified ISAC performance,we design the optimization algorithms considering three factors:base stations’working modes,power allocation schemes and waveform design.Through simulations,we show the performance gain of the cooperative ISAC system and the effectiveness of the proposed optimization methods.
基金The 2023 Scientific and Technological Project in Henan Province of China(Grant No.232102220098)。
文摘For the high-precision positioning requirements of UAV formation cooperative operation,a distributed control system based on RTK technology is proposed in this paper.By using the U-blox F9P GNSS module to build an RTK base station/mobile terminal,combined with Pixhawk 6C flight control and MAVESP8266 communication module,centimeter-level(<2 cm)positioning accuracy is achieved.The system adopts the“centralized planning distributed execution”architecture,transmits RTCM differential data and MAVLink messages through the UDP protocol,and integrates ROS to realize status information subscription.Experiments show that the system can effectively support large area surveying and mapping and other complex tasks,and significantly improve the autonomy and reliability of formation operations.
基金Supported by the Science and Technology Program of Gansu Province,No.23JRRA1015the International Science and Technology Cooperation Project of Gansu Provincial Science and Technology Department,No.2023YFWA0009the Innovation and Entrepreneurship Project for Young Talents of Lanzhou Science and Technology Bureau,No.2023-4-18.
文摘BACKGROUND Ectonucleoside triphosphate diphosphohydrolase 6(ENTPD6),a member of the ENTPD family,has been implicated in certain cancers,yet a comprehensive analysis across multiple cancer types remains lacking.AIM To systematically evaluate ENTPD6’s expression,prognostic significance,and functions across multiple cancer types.METHODS In this study,we performed a pan-cancer analysis to investigate the correlation between ENTPD6 expression and various factors,including prognosis,genetic alterations,epigenetic modification,immune infiltration,immunotherapy responses,functional enrichment,and drug sensitivity.A tissue microarray of gastrointestinal tumors was used to validate differential ENTPD6 protein expression.RESULTS Pan-cancer analysis revealed that ENTPD6 expression was significantly elevated in many cancers.Immunohistochemistry staining analysis revealed that ENTPD6 expression was significantly higher in esophageal carcinoma,stomach adenocarcinoma,colon adenocarcinoma,rectal adenocarcinoma,and pancreatic adenocarcinoma compared to normal tissues.Furthermore,ENTPD6 expression was strongly associated with immune-infiltrating cells,particularly clusters of differentiation 8+T cells and natural killer cells,and correlated with immune-related genomic features including tumor mutational burden and microsatellite instability.Pathway analysis indicated that ENTPD6 expression was primarily linked to purine and pyrimidine metabolism pathways.Drug sensitivity analysis revealed that high ENTPD6 expression was sensitive to RDEA119,selumetinib,and PD-0325901.CONCLUSION This pan-cancer study elucidates the pivotal role of ENTPD6 in tumor progression and establishes its potential as a therapeutic target for immunotherapeutic approaches in specific malignancies.
基金funded by the Ministry of Science and Technology,Taiwan,under grant number MOST 114-2224-E-A49-002was received by En-Cheng Liou.
文摘Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication(ISAC)systems,enabling precise navigation in environments where Global Positioning System(GPS)signals are unavailable.Existing methods,such as map-based navigation or site-specific fingerprinting,often require intensive data collection and lack generalization capability across different buildings,thereby limiting scalability.This study proposes a cross-site,map-free indoor localization framework that uses low-frequency sub-1 GHz radio signals and a Transformer-based neural network for robust positioning without prior environmental knowledge.The Transformer’s self-attention mechanisms allow it to capture spatial correlations among anchor nodes,facilitating accurate localization in unseen environments.Evaluation across two validation sites demonstrates the framework’s effectiveness.In crosssite testing(Site-A),the Transformer achieved a mean localization error of 9.44 m,outperforming the Deep Neural Network(DNN)(10.76 m)and Convolutional Neural Network(CNN)(12.02 m)baselines.In a real-time deployment(Site-B)spanning three floors,the Transformer maintained an overall mean error of 9.81 m,compared with 13.45 m for DNN,12.88 m for CNN,and 53.08 m for conventional trilateration.For vertical positioning,the Transformer delivered a mean error of 4.52 m,exceeding the performance of DNN(4.59 m),CNN(4.87 m),and trilateration(>45 m).The results confirm that the Transformer-based framework generalizes across heterogeneous indoor environments without requiring site-specific calibration,providing stable,sub-12 m horizontal accuracy and reliable vertical estimation.This capability makes the framework suitable for real-time applications in smart buildings,emergency response,and autonomous systems.By utilizing multipath reflections as an informative structure rather than treating them as noise,this work advances artificial intelligence(AI)-native indoor localization as a scalable and efficient component of future 6G ISAC networks.
基金supported by the Project of Development Plan of Science and Technology of Jilin Province(Nos.YDZJ202201ZYTS629 and 20220201151GX)the National Natural Science Foundation(Nos.21576112,21906062,and 61705079)+3 种基金the Natural Science Foundation Project of Jilin Province(Nos.YDZJ202101ZYTS073,YDZJ202201ZYTS356,20180623042TC,20180101181JC,and 20170520147JH)the Project of Development and Reform Commission of Jilin Province(No.2019C044-2)the Project of Ecological Environment Department of Jilin Province(2019-01-07)the Project of Education Department of Jilin Province(Nos.JJKH20220431KJ and JJKH20230508KJ).
文摘Given the urgency of organic pollutant removal and the low efficiency of advanced oxidation processes(AOPs),a novel Bi-ZFO/BMO-Vo photocatalyst was fabricated via the solvothermal method.A coupling system was constructed to combine photocatalysis with peroxymonosulfate(PMS)oxidation processes,which synergistically degrade organic pollutants.Bi-ZFO/BMO-Vo exhibited excellent photocatalytic performance,which could remove 100%RhB in 110 min and degrade 100%MG in 70 min,and 88%H-TC in 50 min.The excellent catalytic performance of Bi-ZFO/BMO-Vo was not only attributed to the synergistic effect of PMS activation and photocatalysis,but also attributed to the SPR effect of Bi nanoparticles,electron capture of oxygen vacancies,and intense contact of Bi-ZFO/BMO-Vo heterojunctions.The active species capture experiments and EPR tests indicated that1 O_(2),SO_(4)^(-)·,·OH,and O_(2)^(-)·worked together for the RhB removal.The degradation intermediates of RhB were identified by LC-MS.Based on the experimental results,the band structure and Z-scheme charge transfer mechanism were proposed.Toxicity evaluation indicated that Bi-ZFO/BMO-Vo-Vis/PMS could significantly reduce RhB toxicity.This efficient and stable catalyst is expected to be used in organic wastewater degradation and practical applications.
基金supported by the National Natural Science Foundation of China(62122064,62331021,62371410)the Natural Science Foundation of Fujian Province of China(2023J02005 and 2021J011184)+1 种基金the President Fund of Xiamen University(20720220063)the Nanqiang Outstanding Talents Program of Xiamen University.
文摘Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.
基金Study on the Correlation between the Regulation of the miR-26a/PTEN Axis by lncRNA DLX6-AS1 and Post-Hepatitis Liver Fibrosis(Project No.:YKK22233)。
文摘Objective:To elucidate the role and clinical potential of the lncRNA DLX6-AS1/miR-26a/PTEN axis in liver fibrosis.Methods:Systematic studies were conducted using cellular and animal models through causal validation,bivariate experiments,single-cell sequencing,ROC analysis of clinical samples,and humanized mouse models.Results:LncRNA DLX6-AS1 inhibited PTEN by adsorbing miR-26a,promoting hepatic stellate cell activation in a dose/time-dependent manner;the axis demonstrated excellent diagnostic performance(AUC>0.9),and its inhibitors effectively reversed fibrosis in vivo.Conclusion:This study provides new biomarkers and targeted therapeutic strategies for liver fibrosis.
文摘A Mixed Numerology OFDM(MN-OFDM)system is essential in 6G and beyond.However,it encounters challenges due to Inter-Numerology Interference(INI).The upcoming 6G technology aims to support innovative applications with high data rates,low latency,and reliability.Therefore,effective handling of INI is crucial to meet the diverse requirements of these applications.To address INI in MN-OFDM systems,this paper proposes a User-Based Numerology and Waveform(UBNW)approach that uses various OFDM-based waveforms and their parameters to mitigate INI.By assigning a specific waveform and numerology to each user,UBNW mitigates INI,optimizes service characteristics,and addresses user demands efficiently.The required Guard Bands(GB),expressed as a ratio of user bandwidth,vary significantly across different waveforms at an SIR of 25 dB.For instance,OFDM-FOFDM needs only 2.5%,while OFDM-UFMC,OFDM-WOLA,and conventional OFDM require 7.5%,24%,and 40%,respectively.The time-frequency efficiency also varies between the waveforms.FOFDM achieves 85.6%,UFMC achieves 81.6%,WOLA achieves 70.7%,and conventional OFDM achieves 66.8%.The simulation results demonstrate that the UBNW approach not only effectively mitigates INI but also enhances system flexibility and time-frequency efficiency while simultaneously reducing the required GB.
文摘随着智能电网的快速发展与物联网终端设备的规模化应用部署,互联网协议第6版(Internet Protocol Version 6,IPv6)技术依托其丰富的地址资源和安全特性,已成为网络架构的关键支撑,IPv6地址的管理和日志审计对保障电网安全稳定运行至关重要。系统探讨了智能电网中物联网设备IPv6地址相关技术原理,深入分析了IPv6地址日志审计技术在智能电网中的应用难点与挑战,提出一种IPv6地址日志审计的简易优化方案,并通过实际案例进行分析和可行性验证,为智能电网中的实际应用提供理论依据和实践指导,对推动智能电网网络安全建设具有重要意义。
