This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,wher...This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.展开更多
AIM:To identify a possible role of home echocardiography for monitoring chronic heart failure(CHF)patients.METHODS:We prospectively investigated 118 patients hospitalized during the last year for CHF who could not eas...AIM:To identify a possible role of home echocardiography for monitoring chronic heart failure(CHF)patients.METHODS:We prospectively investigated 118 patients hospitalized during the last year for CHF who could not easily reach the pertaining District Healthcare Center.The patients were followed up with 2 home management programs:one including clinical and electrocardiographic evaluations and also periodic home echocardiographic examinations(group A),the other including clinical and electrocardiographic evaluations only(group B).RESULTS:At the end of the 18-mo follow-up no significant differences were observed between the 2 groups as regards the primary endpoint:rehospitalization occurred in 4 patients of the group A and in 6 patients of the group B;major cardiovascular events occurred in 2 and in 3 patients,respectively.No significant differences were observed with respect to the secondary endpoints:one vascular event appeared in both the groups,3 cardiovascular deaths occurred in group A and 2 in group B.No significant differences were observed between the 2 groups as regards the composite endpoint of death plus hospitalization.CONCLUSION:Home echocardiography for monitoring of CHF patients does not improve the cardiovascular endpoints.In our CHF patients,a low incidence of vascular events was observed.展开更多
基金funded by the project of the China Geological Survey(DD20211364)the Science and Technology Talent Program of Ministry of Natural Resources of China(grant number 121106000000180039–2201)。
文摘This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.
文摘AIM:To identify a possible role of home echocardiography for monitoring chronic heart failure(CHF)patients.METHODS:We prospectively investigated 118 patients hospitalized during the last year for CHF who could not easily reach the pertaining District Healthcare Center.The patients were followed up with 2 home management programs:one including clinical and electrocardiographic evaluations and also periodic home echocardiographic examinations(group A),the other including clinical and electrocardiographic evaluations only(group B).RESULTS:At the end of the 18-mo follow-up no significant differences were observed between the 2 groups as regards the primary endpoint:rehospitalization occurred in 4 patients of the group A and in 6 patients of the group B;major cardiovascular events occurred in 2 and in 3 patients,respectively.No significant differences were observed with respect to the secondary endpoints:one vascular event appeared in both the groups,3 cardiovascular deaths occurred in group A and 2 in group B.No significant differences were observed between the 2 groups as regards the composite endpoint of death plus hospitalization.CONCLUSION:Home echocardiography for monitoring of CHF patients does not improve the cardiovascular endpoints.In our CHF patients,a low incidence of vascular events was observed.
