Bladder cancer(BC)is a common malignancy and among the leading causes of cancer death worldwide.Analysis of BC cells is of great significance for clinical diagnosis and disease treatment.Current approaches rely mainly...Bladder cancer(BC)is a common malignancy and among the leading causes of cancer death worldwide.Analysis of BC cells is of great significance for clinical diagnosis and disease treatment.Current approaches rely mainly on imaging-based technology,which requires complex staining and sophisticated instrumentation.In this work,we develop a label-free method based on artificial intelligence(AI)-assisted impedance-based flow cytometry(IFC)to differentiate between various BC cells and epithelial cells at single-cell resolution.By applying multiple-frequency excitations,the electrical characteristics of cells,including membrane and nuclear opacities,are extracted,allowing distinction to be made between epithelial cells,low-grade,and high-grade BC cells.Through the use of a constriction channel,the electro-mechanical properties associated with active deformation behavior of cells are investigated,and it is demonstrated that BC cells have a greater capability of shape recovery,an observation that further increases differentiation accuracy.With the assistance of a convolutional neural network-based AI algorithm,IFC is able to effectively differentiate various BC and epithelial cells with accuracies of over 95%.In addition,different grades of BC cells are successfully differentiated in both spiked mixed samples and bladder tumor tissues.展开更多
This paper presents the influences of plasma layer on the oscillatory flow inarterial stenosis. The analysis demonstrates that the existence of the plasma layer mayobviously change the characteristics of flow such as ...This paper presents the influences of plasma layer on the oscillatory flow inarterial stenosis. The analysis demonstrates that the existence of the plasma layer mayobviously change the characteristics of flow such as velocity-profiles, longitudinalimpedance and pressure gradient, but hardly change the phase of longitudinalimpedance and pressure gradient. Besides. such influences vary with a and degree ofstenosis. These analyses have Special physiological significance in blood circulationsystem.展开更多
The transmission-line-circuit model of the Z accelerator, developed originally by W. A. STYGAR, P. A. CORCORAN, et al., is revised. The revised model uses different calculations for the electron loss and flow impedanc...The transmission-line-circuit model of the Z accelerator, developed originally by W. A. STYGAR, P. A. CORCORAN, et al., is revised. The revised model uses different calculations for the electron loss and flow impedance in the magnetically insulated transmission line system of the Z accelerator before and after magnetic insulation is established. By including electron pressure and zero electric field at the cathode, a closed set of equations is obtained at each time step, and dynamic shunt resistance （used to represent any electron loss to the anode） and flow impedance are solved, which have been incorporated into the transmission line code for simulations of the vacuum section in the Z accelerator. Finally, the results are discussed in comparison with earlier findings to show the effectiveness and limitations of the model.展开更多
The sand-conglomerate fans are the major depositional systems in the lower third member of Shahejie Formation in Shengtuo area, which formed in the deep lacustrine environment characterized by steep slope gradient, ne...The sand-conglomerate fans are the major depositional systems in the lower third member of Shahejie Formation in Shengtuo area, which formed in the deep lacustrine environment characterized by steep slope gradient, near sources and intensive tectonic activity. This work was focused on the sedimentary feature of the glutenite segment to conduct the seismic sedimentology research. The near-shore subaqueous fans and its relative gravity channel and slump turbidite fan depositions were identified according to observation and description of cores combining with the numerous data of seismic and logging. Then, the depositional model was built depending on the analysis of palaeogeomorphology. The seismic attributes which are related to the hydrocarbon but relative independent were chosen to conduct the analysis, the reservoir area of the glutenite segment was found performing a distribution where the amplitude value is relatively higher, and finally the RMS amplitude attribute was chosen to conduct the attribute predicting. At the same time, the horizontal distribution of the sedimentary facies was analyzed qualitatively. At last, the sparse spike inversion method was used to conduct the acoustic impedance inversion, and the inversion result can distinguish glutenite reservoir which is greater than 5 m. This method quantitatively characterizes the distribution area of the favorable reservoir sand.展开更多
基金financial support from the National Natural Science Foundation of China(NSFC Grant No.22076138)the National Natural Science Foundation of China(NSFC Grant No.62174119).
文摘Bladder cancer(BC)is a common malignancy and among the leading causes of cancer death worldwide.Analysis of BC cells is of great significance for clinical diagnosis and disease treatment.Current approaches rely mainly on imaging-based technology,which requires complex staining and sophisticated instrumentation.In this work,we develop a label-free method based on artificial intelligence(AI)-assisted impedance-based flow cytometry(IFC)to differentiate between various BC cells and epithelial cells at single-cell resolution.By applying multiple-frequency excitations,the electrical characteristics of cells,including membrane and nuclear opacities,are extracted,allowing distinction to be made between epithelial cells,low-grade,and high-grade BC cells.Through the use of a constriction channel,the electro-mechanical properties associated with active deformation behavior of cells are investigated,and it is demonstrated that BC cells have a greater capability of shape recovery,an observation that further increases differentiation accuracy.With the assistance of a convolutional neural network-based AI algorithm,IFC is able to effectively differentiate various BC and epithelial cells with accuracies of over 95%.In addition,different grades of BC cells are successfully differentiated in both spiked mixed samples and bladder tumor tissues.
文摘This paper presents the influences of plasma layer on the oscillatory flow inarterial stenosis. The analysis demonstrates that the existence of the plasma layer mayobviously change the characteristics of flow such as velocity-profiles, longitudinalimpedance and pressure gradient, but hardly change the phase of longitudinalimpedance and pressure gradient. Besides. such influences vary with a and degree ofstenosis. These analyses have Special physiological significance in blood circulationsystem.
基金supported by National Natural Science Foundation of China (No. 50637010)
文摘The transmission-line-circuit model of the Z accelerator, developed originally by W. A. STYGAR, P. A. CORCORAN, et al., is revised. The revised model uses different calculations for the electron loss and flow impedance in the magnetically insulated transmission line system of the Z accelerator before and after magnetic insulation is established. By including electron pressure and zero electric field at the cathode, a closed set of equations is obtained at each time step, and dynamic shunt resistance （used to represent any electron loss to the anode） and flow impedance are solved, which have been incorporated into the transmission line code for simulations of the vacuum section in the Z accelerator. Finally, the results are discussed in comparison with earlier findings to show the effectiveness and limitations of the model.
基金Project(41172109)supported by the National Natural Science Foundation of ChinaProject(20110003110014)supported by the ResearchFoundation for the Doctoral Program of Higher Education,China
文摘The sand-conglomerate fans are the major depositional systems in the lower third member of Shahejie Formation in Shengtuo area, which formed in the deep lacustrine environment characterized by steep slope gradient, near sources and intensive tectonic activity. This work was focused on the sedimentary feature of the glutenite segment to conduct the seismic sedimentology research. The near-shore subaqueous fans and its relative gravity channel and slump turbidite fan depositions were identified according to observation and description of cores combining with the numerous data of seismic and logging. Then, the depositional model was built depending on the analysis of palaeogeomorphology. The seismic attributes which are related to the hydrocarbon but relative independent were chosen to conduct the analysis, the reservoir area of the glutenite segment was found performing a distribution where the amplitude value is relatively higher, and finally the RMS amplitude attribute was chosen to conduct the attribute predicting. At the same time, the horizontal distribution of the sedimentary facies was analyzed qualitatively. At last, the sparse spike inversion method was used to conduct the acoustic impedance inversion, and the inversion result can distinguish glutenite reservoir which is greater than 5 m. This method quantitatively characterizes the distribution area of the favorable reservoir sand.
