An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of a...An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.展开更多
BACKGROUND Inadequately controlled hypertension often leads to an increased cardiovascular death rate in type 2 diabetes mellitus(T2DM).It remains unclear whether systolic blood pressure(SBP)status of hypertension is ...BACKGROUND Inadequately controlled hypertension often leads to an increased cardiovascular death rate in type 2 diabetes mellitus(T2DM).It remains unclear whether systolic blood pressure(SBP)status of hypertension is related to coronary inflammation and plaques in T2DM.AIM To evaluate whether SBP variability(SBPV)and levels of hypertension are related to coronary inflammation and plaques in T2DM patients using coronary computed tomography angiography(CCTA).METHODS This retrospective study involved 881 T2DM patients with CCTA images,including 668 hypertension and 213 normotension patients.Hypertension patients were subgroup based on SBP status:(1)SBPV:Low(<8.96 mmHg)and high(≥8.96 mmHg)groups;and(2)SBP levels:Controlled(<140 mmHg)and uncontrolled(≥140 mmHg)groups.Pericoronary adipose tissue(PCAT)attenuation,high-risk plaques(HRPs)and obstructive stenosis(OS)were evaluated by CCTA.Propensity score matching was utilized to compare these CCTA findings for these groups.The impact of SBPV and SBP levels of hypertension on these CCTA findings in T2DM patients were evaluated by multivariate logistic regression and multivariable linear regression.RESULTS PCAT attenuation of the left anterior descending artery(LAD),any low attenuation plaque(LAP),any spotty calcification(SC),any positive remodeling(PR),and OS had significant differences between the hypertension group and the normotension group,as well as between the high SBPV or uncontrolled SBP group and the low SBPV or controlled SBP group(all P<0.05).Hypertension was independently positively correlated with LADPCAT attenuation(β=1.815,P=0.010),LAP(OR=1.612,P=0.019),SC(OR=1.665,P=0.013),PR(OR=1.549,P=0.033),and OS(OR=1.928,P=0.036)in all T2DM patients.Additionally,high SBPV and uncontrolled SBP were independently positively correlated with LAD-PCAT attenuation(high SBPV:β=1.673,P=0.048;uncontrolled SBP:β=2.370,P=0.004)and PR(high SBPV:OR=1.903,P=0.048;uncontrolled SBP:OR=2.230,P=0.013)in T2DM patients with hypertension.CONCLUSION Inadequately controlled hypertension,including high SBPV and/or uncontrolled SBP levels,may be related to increased coronary artery inflammation,HRPs,and OS in T2DM,leading to increased cardiovascular risk.Achieving both low SBPV and controlled SBP levels simultaneously,especially in individuals with T2DM and hypertension,warrants clinical attention.展开更多
Hydrogen,as a clean and versatile energy carrier,plays a vital role in the global transition toward carbon neutrality.Achieving a sustainable hydrogen economy requires safe,efficient,and cost‐effective technologies a...Hydrogen,as a clean and versatile energy carrier,plays a vital role in the global transition toward carbon neutrality.Achieving a sustainable hydrogen economy requires safe,efficient,and cost‐effective technologies across production,storage,transportation,and utilization.On the production side,electrolysis and solar‐driven photocatalysis are rapidly advancing toward industrial adoption,yet remain constrained by electrolysis efficiency,cost,and electrolyzer durability.For storage and transportation,lowering costs and energy consumption,improving system efficiency,and deploying safe,high‐capacity hydrogen storage and transportation solutions are key priorities.Regarding hydrogen utilization,particularly hydrogen fuel cells and hydrogen‐based power systems,require further enhancement in their durability,reliability,and integration flexibility to enable widespread deployment across sectors.Therefore,this review provides a comprehensive overview of green hydrogen technologies,emphasizing recent advances,key challenges,and industrial demonstrations.By integrating insights from electrochemical and photochemical production,solid‐state and liquid‐phase storage,and hydrogen end‐use pathways,we propose a roadmap toward the scalable deployment of green hydrogen infrastructure.Coordinated progress across these domains will position hydrogen as a cornerstone of a sustainable,secure,and decarbonized global energy solution.展开更多
To overcome the challenges of poor real-time performance,limited scalability,and low intelligence in conventional jamming pattern recognition methods,this paper proposes a method based on Wavelet Packet Decomposition(...To overcome the challenges of poor real-time performance,limited scalability,and low intelligence in conventional jamming pattern recognition methods,this paper proposes a method based on Wavelet Packet Decomposition(WPD)and enhanced deep learning techniques.In the proposed method,an agent at the receiver processes the received signal using WPD to generate an initial Spectrogram Waterfall(SW),which is subsequently segmented using a sliding window to serve as the input for the jamming recognition network.The network employs a bilateral filter to preprocess the input SW,thereby enhancing the edge features of the jamming signals.To extract abstract features,depthwise separable convolution is utilized instead of traditional convolution,thereby reducing the network’s parameter count and enhancing real-time performance.A pyramid pooling layer is integrated before the fully connected layer to enable the network to process input SW of varying sizes,thus enhancing scalability.During network training,adaptive moment estimation is employed as the optimizer,allowing the network to dynamically adjust the learning rate and accelerate convergence.A comprehensive comparison between the proposed jamming recognition network and six other models is conducted,along with Ablation Experiments(AE)based on numerical simulations.Simulation results demonstrate that the proposed method based on WPD and enhanced deep learning achieves high-precision recognition of various jamming patterns while maintaining a favorable balance among prediction accuracy,network complexity,and prediction time.展开更多
基金support of the National Natural Science Foundation of China(No.52274176)the Guangdong Province Key Areas R&D Program(No.2022B0101070001)+5 种基金Chongqing Elite Innovation and Entrepreneurship Leading talent Project(No.CQYC20220302517)the Chongqing Natural Science Foundation Innovation and Development Joint Fund(No.CSTB2022NSCQ-LZX0079)the National Key Research and Development Program Young Scientists Project(No.2022YFC2905700)the Chongqing Municipal Education Commission“Shuangcheng Economic Circle Construction in Chengdu-Chongqing Area”Science and Technology Innovation Project(No.KJCX2020031)the Fundamental Research Funds for the Central Universities(No.2024CDJGF-009)the Key Project for Technological Innovation and Application Development in Chongqing(No.CSTB2025TIAD-KPX0029).
文摘An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.
基金Supported by Natural Science Foundation of Hubei Province,No.2023AFB848.
文摘BACKGROUND Inadequately controlled hypertension often leads to an increased cardiovascular death rate in type 2 diabetes mellitus(T2DM).It remains unclear whether systolic blood pressure(SBP)status of hypertension is related to coronary inflammation and plaques in T2DM.AIM To evaluate whether SBP variability(SBPV)and levels of hypertension are related to coronary inflammation and plaques in T2DM patients using coronary computed tomography angiography(CCTA).METHODS This retrospective study involved 881 T2DM patients with CCTA images,including 668 hypertension and 213 normotension patients.Hypertension patients were subgroup based on SBP status:(1)SBPV:Low(<8.96 mmHg)and high(≥8.96 mmHg)groups;and(2)SBP levels:Controlled(<140 mmHg)and uncontrolled(≥140 mmHg)groups.Pericoronary adipose tissue(PCAT)attenuation,high-risk plaques(HRPs)and obstructive stenosis(OS)were evaluated by CCTA.Propensity score matching was utilized to compare these CCTA findings for these groups.The impact of SBPV and SBP levels of hypertension on these CCTA findings in T2DM patients were evaluated by multivariate logistic regression and multivariable linear regression.RESULTS PCAT attenuation of the left anterior descending artery(LAD),any low attenuation plaque(LAP),any spotty calcification(SC),any positive remodeling(PR),and OS had significant differences between the hypertension group and the normotension group,as well as between the high SBPV or uncontrolled SBP group and the low SBPV or controlled SBP group(all P<0.05).Hypertension was independently positively correlated with LADPCAT attenuation(β=1.815,P=0.010),LAP(OR=1.612,P=0.019),SC(OR=1.665,P=0.013),PR(OR=1.549,P=0.033),and OS(OR=1.928,P=0.036)in all T2DM patients.Additionally,high SBPV and uncontrolled SBP were independently positively correlated with LAD-PCAT attenuation(high SBPV:β=1.673,P=0.048;uncontrolled SBP:β=2.370,P=0.004)and PR(high SBPV:OR=1.903,P=0.048;uncontrolled SBP:OR=2.230,P=0.013)in T2DM patients with hypertension.CONCLUSION Inadequately controlled hypertension,including high SBPV and/or uncontrolled SBP levels,may be related to increased coronary artery inflammation,HRPs,and OS in T2DM,leading to increased cardiovascular risk.Achieving both low SBPV and controlled SBP levels simultaneously,especially in individuals with T2DM and hypertension,warrants clinical attention.
基金supported by the National Key R&D Program of China(no.2022YFB3803700)the National Natural Science Foundation(52401386)the SINOPEC Research Institute of Petroleum Processing Co.Ltd.Fund(25H010102119).
文摘Hydrogen,as a clean and versatile energy carrier,plays a vital role in the global transition toward carbon neutrality.Achieving a sustainable hydrogen economy requires safe,efficient,and cost‐effective technologies across production,storage,transportation,and utilization.On the production side,electrolysis and solar‐driven photocatalysis are rapidly advancing toward industrial adoption,yet remain constrained by electrolysis efficiency,cost,and electrolyzer durability.For storage and transportation,lowering costs and energy consumption,improving system efficiency,and deploying safe,high‐capacity hydrogen storage and transportation solutions are key priorities.Regarding hydrogen utilization,particularly hydrogen fuel cells and hydrogen‐based power systems,require further enhancement in their durability,reliability,and integration flexibility to enable widespread deployment across sectors.Therefore,this review provides a comprehensive overview of green hydrogen technologies,emphasizing recent advances,key challenges,and industrial demonstrations.By integrating insights from electrochemical and photochemical production,solid‐state and liquid‐phase storage,and hydrogen end‐use pathways,we propose a roadmap toward the scalable deployment of green hydrogen infrastructure.Coordinated progress across these domains will position hydrogen as a cornerstone of a sustainable,secure,and decarbonized global energy solution.
基金supported by National Natural Science Foundation of China under Grant U23A20279China Electronics Tian’ao Innovation Theory and Technology Group Fund under Grand 20221193-04-04.
文摘To overcome the challenges of poor real-time performance,limited scalability,and low intelligence in conventional jamming pattern recognition methods,this paper proposes a method based on Wavelet Packet Decomposition(WPD)and enhanced deep learning techniques.In the proposed method,an agent at the receiver processes the received signal using WPD to generate an initial Spectrogram Waterfall(SW),which is subsequently segmented using a sliding window to serve as the input for the jamming recognition network.The network employs a bilateral filter to preprocess the input SW,thereby enhancing the edge features of the jamming signals.To extract abstract features,depthwise separable convolution is utilized instead of traditional convolution,thereby reducing the network’s parameter count and enhancing real-time performance.A pyramid pooling layer is integrated before the fully connected layer to enable the network to process input SW of varying sizes,thus enhancing scalability.During network training,adaptive moment estimation is employed as the optimizer,allowing the network to dynamically adjust the learning rate and accelerate convergence.A comprehensive comparison between the proposed jamming recognition network and six other models is conducted,along with Ablation Experiments(AE)based on numerical simulations.Simulation results demonstrate that the proposed method based on WPD and enhanced deep learning achieves high-precision recognition of various jamming patterns while maintaining a favorable balance among prediction accuracy,network complexity,and prediction time.
