The presented research introduces a novel hybrid deep learning approach for the dynamic prediction of the attitude and position of super-large diameter shields-a critical consideration for construction safety and tunn...The presented research introduces a novel hybrid deep learning approach for the dynamic prediction of the attitude and position of super-large diameter shields-a critical consideration for construction safety and tunnel lining quality.This study proposes a hybrid deep learning approach for predicting dynamic attitude and position prediction of super-large diameter shield.The approach consists of principal component analysis(PCA)and temporal convolutional network(TCN).The former is used for employing feature level fusion based on features of the shield data to reduce uncertainty,improve accuracy and the data effect,and 9 sets of required principal component characteristic data are obtained.The latter is adopted to process sequence data in predicting the dynamic attitude and position for the advantages and potential of convolution network.The approach’s effectiveness is exemplified using data from a tunnel construction project in China.The obtained results show remarkable accuracy in predicting the global attitude and position,with an average error ratio of less than 2 mm on four shield outputs in 97.30%of cases.Moreover,the approach displays strong performance in accurately predicting sudden fluctuations in shield attitude and position,with an average prediction accuracy of 89.68%.The proposed hybrid model demonstrates superiority over TCN,long short-term memory(LSTM),and recurrent neural network(RNN)in multiple indexes.Shapley additive exPlanations(SHAP)analysis is also performed to investigate the significance of different data features in the prediction process.This study provides a real-time warning for the shield driver to adjust the attitude and position of super-large diameter shields.展开更多
This paper presents a case study of the clogging of a slurry-shield tunnel-boring machine(TBM)experienced during tunnel operations in clay-rich argillaceous siltstones under the Ganjiang River,China.The clogging exper...This paper presents a case study of the clogging of a slurry-shield tunnel-boring machine(TBM)experienced during tunnel operations in clay-rich argillaceous siltstones under the Ganjiang River,China.The clogging experienced during tunneling was due to special geological conditions,which had a considerably negative impact on the slurry-shield TBM tunneling performance.In this case study,the effect of clogging on the slurry-shield TBM tunneling performance(e.g.,advance speed,thrust,torque,and penetration per revolution)was fully investigated.The potential for clogging during tunnel operations in argillaceous siltstone was estimated using an existing empirical classification chart.Many improvement measures have been proposed to mitigate the clogging potential of two slurry-shield TBMs during tunneling,such as the use of an optimum cutting wheel,a replacement cutting tool,improvements to the circulation flushing system and slurry properties,mixed support integrating slurry,and compressed air to support the excavation face.The mechanisms and potential causes of clogging are explained in detail,and the contributions of these mitigation measures to tunneling performance are discussed.By investigating the actual operational parameters of the slurry-shield TBMs,these mitigation measures were proven to be effective in mitigating the clogging potential of slurry-shield TBMs.This case study provides valuable information for slurry-shield TBMs involving tunneling in clay-rich sedimentary rocks.展开更多
As a powerful cell-based therapeutic approach,CAR-T therapy was originally designed for treating acquired immunodeficiency syndrome(AIDS)(Baker et al.,2023),but had been strikingly successful in curing hematologic mal...As a powerful cell-based therapeutic approach,CAR-T therapy was originally designed for treating acquired immunodeficiency syndrome(AIDS)(Baker et al.,2023),but had been strikingly successful in curing hematologic malignancies and multiple solid tumors.Numerous evidence has expanded the medical application of CAR-T therapy for the treatment of many other human diseases beyond cancer.In this article,we discuss the principle of CAR-T and enumerate the current application and limitation in oncology.Finally,we provide a comprehensive perspective of current advance and future directions of CAR-T in treating multiple non-tumoral diseases.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52078304,51938008,52090084,and 52208354)Guangdong Province Key Field R&D Program Project(Grant Nos.2019B111108001 and 2022B0101070001)+1 种基金Shenzhen Fundamental Research(Grant No.20220525163716003)the Pearl River Delta Water Resources Allocation Project(CD88-GC022020-0038).
文摘The presented research introduces a novel hybrid deep learning approach for the dynamic prediction of the attitude and position of super-large diameter shields-a critical consideration for construction safety and tunnel lining quality.This study proposes a hybrid deep learning approach for predicting dynamic attitude and position prediction of super-large diameter shield.The approach consists of principal component analysis(PCA)and temporal convolutional network(TCN).The former is used for employing feature level fusion based on features of the shield data to reduce uncertainty,improve accuracy and the data effect,and 9 sets of required principal component characteristic data are obtained.The latter is adopted to process sequence data in predicting the dynamic attitude and position for the advantages and potential of convolution network.The approach’s effectiveness is exemplified using data from a tunnel construction project in China.The obtained results show remarkable accuracy in predicting the global attitude and position,with an average error ratio of less than 2 mm on four shield outputs in 97.30%of cases.Moreover,the approach displays strong performance in accurately predicting sudden fluctuations in shield attitude and position,with an average prediction accuracy of 89.68%.The proposed hybrid model demonstrates superiority over TCN,long short-term memory(LSTM),and recurrent neural network(RNN)in multiple indexes.Shapley additive exPlanations(SHAP)analysis is also performed to investigate the significance of different data features in the prediction process.This study provides a real-time warning for the shield driver to adjust the attitude and position of super-large diameter shields.
基金gratefully acknowledge the support of funds from the National Natural Science Foundation of China(Grant Nos.52090084,52208400).
文摘This paper presents a case study of the clogging of a slurry-shield tunnel-boring machine(TBM)experienced during tunnel operations in clay-rich argillaceous siltstones under the Ganjiang River,China.The clogging experienced during tunneling was due to special geological conditions,which had a considerably negative impact on the slurry-shield TBM tunneling performance.In this case study,the effect of clogging on the slurry-shield TBM tunneling performance(e.g.,advance speed,thrust,torque,and penetration per revolution)was fully investigated.The potential for clogging during tunnel operations in argillaceous siltstone was estimated using an existing empirical classification chart.Many improvement measures have been proposed to mitigate the clogging potential of two slurry-shield TBMs during tunneling,such as the use of an optimum cutting wheel,a replacement cutting tool,improvements to the circulation flushing system and slurry properties,mixed support integrating slurry,and compressed air to support the excavation face.The mechanisms and potential causes of clogging are explained in detail,and the contributions of these mitigation measures to tunneling performance are discussed.By investigating the actual operational parameters of the slurry-shield TBMs,these mitigation measures were proven to be effective in mitigating the clogging potential of slurry-shield TBMs.This case study provides valuable information for slurry-shield TBMs involving tunneling in clay-rich sedimentary rocks.
基金supported by the National Key Research and Development Program of China(Grant no.2019YFA0111400,2022YFE0200100)the National Natural Science Foundation of China(Grant no.32271165,82070144,82270155)the Interdisciplinary Project of Central Universities(Grant no.2022-2-ZD-02).
文摘As a powerful cell-based therapeutic approach,CAR-T therapy was originally designed for treating acquired immunodeficiency syndrome(AIDS)(Baker et al.,2023),but had been strikingly successful in curing hematologic malignancies and multiple solid tumors.Numerous evidence has expanded the medical application of CAR-T therapy for the treatment of many other human diseases beyond cancer.In this article,we discuss the principle of CAR-T and enumerate the current application and limitation in oncology.Finally,we provide a comprehensive perspective of current advance and future directions of CAR-T in treating multiple non-tumoral diseases.
