Due to the complex diagenesis process,basalt usually contains defects in the form of amygdales formed by diagenetic bubbles,which affect its mechanical properties.In this study,a synthetic rock mass method(SRM)based o...Due to the complex diagenesis process,basalt usually contains defects in the form of amygdales formed by diagenetic bubbles,which affect its mechanical properties.In this study,a synthetic rock mass method(SRM)based on the combination of discrete fracture network(DFN)and finite-discrete element method(FDEM)is applied to characterizing the amygdaloidal basalt,and to systematically exploring the effects of the development characteristics of amygdales and sample sizes on the mechanical properties of basalt.The results show that with increasing amygdale content,the elastic modulus(E)increases linearly,while the uniaxial compressive strength(UCS)shows an exponential or logarithmic decay.When the orientation of amygdales is between 0°and 90°,basalt shows a relatively pronounced strength and stiffness anisotropy.Based on the analysis of the geometric and mechanical properties,the representative element volume(REV)size of amygdaloidal basalt blocks is determined to be 200 mm,and the mechanical properties obtained on this scale can be regarded as the properties of the equivalent continuum.The results of this research are of value to the understanding of the mechanical properties of amygdaloidal basalt,so as to guide the formulation of engineering design schemes more accurately.展开更多
Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intellig...Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intelligent services to mobile users.However,as the accuracy requirements continue to increase,the components of deep learning models for pedestrian and vehicle detection,such as YOLOv4,become more sophisticated and the computing resources required for model training are increasing dramatically,which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy performance.For addressing this challenge,a cloud-edge collaboration-based pedestrian and vehicle detection framework is proposed in this paper,which enables sufficient training of models by utilizing the abundant computing resources in the cloud,and then deploying the well-trained models on edge devices,thus reducing the computing resource requirements for model training on edge devices.Furthermore,to reduce the size of the model deployed on edge devices,an automatic pruning method combines the convolution layer and BN layer is proposed to compress the pedestrian and vehicle detection model size.Experimental results show that the framework proposed in this paper is able to deploy the pruned model on a real edge device,Jetson TX2,with 6.72 times higher FPS.Meanwhile,the channel pruning reduces the volume and the number of parameters to 96.77%for the model,and the computing amount is reduced to 81.37%.展开更多
Objective: We aimed to study the relationship between clinical effect and surgical methods of inner thigh primary soft tissue sarcomas. Methods: Wide or radical resection were performed in 45 cases of soft tissue sarc...Objective: We aimed to study the relationship between clinical effect and surgical methods of inner thigh primary soft tissue sarcomas. Methods: Wide or radical resection were performed in 45 cases of soft tissue sarcomas, including 20 cases of postoperative recurrence after radiation therapy, 7 cases of first treatment. Thirty-six cases received 4–6 cycles of postoperative chemotherapy. Results: Thirty-eight of 45 cases were followed up for 1–5 years, with 5 case of recurrence and 6 cases of distant metastasis. Conclusion: The inner thigh primary soft tissue sarcoma can be effectively treated with wide or radical resection.展开更多
The zero-valent iron modified biochar materials are widely employed for heavy metals immobilization.However,these materials would be inevitably aged by natural forces after entering into the environment,while there ar...The zero-valent iron modified biochar materials are widely employed for heavy metals immobilization.However,these materials would be inevitably aged by natural forces after entering into the environment,while there are seldom studies reported the aging effects of zero-valent iron modified biochar.In this work,the hydrogen peroxide and hydrochloric acid solution were applied to simulate aging conditions of zero-valent iron modified biochar.According to the results,the adsorption capacity of copper(II)contaminants on biochar,zero-valent iron modified biochar-1,and zero-valent iron modified biochar-2 after aging was decreased by 15.36%,22.65%and 23.26%,respectively.The surface interactions were assigned with chemisorption occurred on multi-molecular layers,which were proved by the pseudo-second-order and Langmuir models.After aging,the decreasing of capacity could be mainly attributed to the inhibition of ion-exchange and zero-valent iron oxidation.Moreover,the plant growth and soil leaching experiments also proved the effects of aging treatment,the zero-valent iron modified biochar reduced the inhibition of copper(II)bioavailability and increased the mobility of copper(II)after aging.All these results bridged the gaps between bio-adsorbents customization and their environmental behaviors during practical agro-industrial application.展开更多
基金the Key Projects of the Yalong River Joint Fund of the National Natural Science Foundation of China(Grant No.U1865203)the Key Program of National Natural Science Foundation of China(Grant No.41931286)the China Postdoctoral Science Foundation(Grant No.2021M691147)。
文摘Due to the complex diagenesis process,basalt usually contains defects in the form of amygdales formed by diagenetic bubbles,which affect its mechanical properties.In this study,a synthetic rock mass method(SRM)based on the combination of discrete fracture network(DFN)and finite-discrete element method(FDEM)is applied to characterizing the amygdaloidal basalt,and to systematically exploring the effects of the development characteristics of amygdales and sample sizes on the mechanical properties of basalt.The results show that with increasing amygdale content,the elastic modulus(E)increases linearly,while the uniaxial compressive strength(UCS)shows an exponential or logarithmic decay.When the orientation of amygdales is between 0°and 90°,basalt shows a relatively pronounced strength and stiffness anisotropy.Based on the analysis of the geometric and mechanical properties,the representative element volume(REV)size of amygdaloidal basalt blocks is determined to be 200 mm,and the mechanical properties obtained on this scale can be regarded as the properties of the equivalent continuum.The results of this research are of value to the understanding of the mechanical properties of amygdaloidal basalt,so as to guide the formulation of engineering design schemes more accurately.
基金supported by Key-Area Research and Development Program of Guangdong Province(2021B0101420002)the Major Key Project of PCL(PCL2021A09)+3 种基金National Natural Science Foundation of China(62072187)Guangdong Major Project of Basic and Applied Basic Research(2019B030302002)Guangdong Marine Economic Development Special Fund Project(GDNRC[2022]17)Guangzhou Development Zone Science and Technology(2021GH10,2020GH10).
文摘Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intelligent services to mobile users.However,as the accuracy requirements continue to increase,the components of deep learning models for pedestrian and vehicle detection,such as YOLOv4,become more sophisticated and the computing resources required for model training are increasing dramatically,which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy performance.For addressing this challenge,a cloud-edge collaboration-based pedestrian and vehicle detection framework is proposed in this paper,which enables sufficient training of models by utilizing the abundant computing resources in the cloud,and then deploying the well-trained models on edge devices,thus reducing the computing resource requirements for model training on edge devices.Furthermore,to reduce the size of the model deployed on edge devices,an automatic pruning method combines the convolution layer and BN layer is proposed to compress the pedestrian and vehicle detection model size.Experimental results show that the framework proposed in this paper is able to deploy the pruned model on a real edge device,Jetson TX2,with 6.72 times higher FPS.Meanwhile,the channel pruning reduces the volume and the number of parameters to 96.77%for the model,and the computing amount is reduced to 81.37%.
文摘Objective: We aimed to study the relationship between clinical effect and surgical methods of inner thigh primary soft tissue sarcomas. Methods: Wide or radical resection were performed in 45 cases of soft tissue sarcomas, including 20 cases of postoperative recurrence after radiation therapy, 7 cases of first treatment. Thirty-six cases received 4–6 cycles of postoperative chemotherapy. Results: Thirty-eight of 45 cases were followed up for 1–5 years, with 5 case of recurrence and 6 cases of distant metastasis. Conclusion: The inner thigh primary soft tissue sarcoma can be effectively treated with wide or radical resection.
基金The authors appreciate the support from the National Natural Science Foundation of China(Grant No.22264025)the Yunnan Province Education Department Scientific Research Foundation Project(Grant No.2022J0136)the Applied Basic Research Foundation of Yunnan Province(Grant Nos.202201AS070020,202201AU070061).
文摘The zero-valent iron modified biochar materials are widely employed for heavy metals immobilization.However,these materials would be inevitably aged by natural forces after entering into the environment,while there are seldom studies reported the aging effects of zero-valent iron modified biochar.In this work,the hydrogen peroxide and hydrochloric acid solution were applied to simulate aging conditions of zero-valent iron modified biochar.According to the results,the adsorption capacity of copper(II)contaminants on biochar,zero-valent iron modified biochar-1,and zero-valent iron modified biochar-2 after aging was decreased by 15.36%,22.65%and 23.26%,respectively.The surface interactions were assigned with chemisorption occurred on multi-molecular layers,which were proved by the pseudo-second-order and Langmuir models.After aging,the decreasing of capacity could be mainly attributed to the inhibition of ion-exchange and zero-valent iron oxidation.Moreover,the plant growth and soil leaching experiments also proved the effects of aging treatment,the zero-valent iron modified biochar reduced the inhibition of copper(II)bioavailability and increased the mobility of copper(II)after aging.All these results bridged the gaps between bio-adsorbents customization and their environmental behaviors during practical agro-industrial application.