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Innovation Article
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Driving forces for ongoing northward indentation of India into Asia: insight from 3D numerical modeling of mantle dynamics
- ZHENG Qunfan, SHI Yaolin
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2021, 38 (6):
721-728.
DOI: 10.7523/j.issn.2095-6134.2021.06.001
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Abstract (
623 )
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The collision between the Indian and Asian plates started about 60 Ma ago. It has continued to shorten the Asian side by at least 1 000 km, and thus formed the huge Qinghai-Tibetan Plateau. One important lithospheric dynamical issue is what kind of force could overcome such huge resistance from the Asian plate and from the Qinghai-Tibetan Plateau and drive the Indian plate continuously moving northward for such a long time. We performed 3D numerical modeling to reveal the role of mantle flow for the dynamics of the India-Asia collision by considering the global temperature structure converted from the seismic tomographic model S20RTS as initial temperature and the absolute plate motion velocities as initial surficial velocity boundary conditions. Our results suggest that drags from the moving asthenospheric mantle could be the main cause for transporting Indian plate northward.
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Experimental test of the uncertainty relations for mixed states
- WANG Shuang, LI Junli, WANG Hui, MENG Fangxia, QIAO Congfeng
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2021, 38 (6):
735-740.
DOI: 10.7523/j.issn.2095-6134.2021.06.003
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Abstract (
264 )
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The uncertainty relation lies at the heart of quantum theory and behaves as a trade-off relation between the inherent uncertainties of incompatible observables. Many experiments have been devoted to the test of the various uncertainty relations, where the quantum system are mainly prepared in pure states. Here we present an experimental investigation of the direct sum majorization uncertainty relation optimal majorization uncertainty for mixed states using the coherent light. By measuring the Stokes parameters of the polarized beams, the direct sum majorization uncertainty relation for general mixed states is verified. The experimental results show that the tested majorization uncertainty relation is optimized for the mixed states.
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2D numerical simulations of liquid tin film flows with heat flux on free surface under a perpendicular magnetic field
- ZHUO Qihao, PAN Junhua, NI Mingjiu
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2021, 38 (6):
741-749.
DOI: 10.7523/j.issn.2095-6134.2021.06.004
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Abstract (
273 )
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With capacities of self-cleaning and sustaining high heat load, liquid-metal divertor is one important design of first wall component. Liquid-metal divertor has to be faced with external magnetic fields and high-intensity heat flux, and in devices, existence of low-frequency disturbances is inevitable, which would make liquid-metal film flows develop into capillary solitary waves, in which capillary separation eddies at wave troughs would strengthen heat convection there. In this research, heat transportation of liquid-tin film flows with capillary solitary waves is studied under Re=58. When there is no magnetic field and free-surface heat flux, capillary solitary waves of liquid tin have same features of water waves and Nu number also reaches peak at wave trough. When only applying magnetic field is exerted, Lorentz force has damping effects on waves and accordingly, the enhancement of heat transfer from capillary separation eddies decreases. When only applying free-surface heat flux is exerted, film flows are heated and distribution of Nu number become more uniform. When applying both magnetic field and heat flux are exerted, their effects will be stacked.
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Cytotoxicity of lindane in hepatoma HepG2 cells
- DUAN Shanshan, WANG Yuanli, YANG Jianzheng, DING Wenjun, HE Junhui
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2021, 38 (6):
750-757.
DOI: 10.7523/j.issn.2095-6134.2021.06.005
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Abstract (
366 )
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Lindane, as one of persistent organic pollutants (POPs), has high toxicity, lipophilicity, chemical stability, and bioaccumulation. The use of lindane seriously threatens ecological environment and biosafety in China. Lindane bioaccumulation can cause liver function damage, but its toxic effects on liver have not been fully understood. In this study, we have investigated effects of lindane-induced oxidative stress on inflammation and autophagy in HepG2 cells. HepG2 cells were exposed to lindane for 24 h. Cell viability, intracellular reactive oxygen species (ROS), and autophagy were determined by thiazolyl blue (MTT) assay, 2,7-dichlorofluorescein (DCF) and immunofluorescence, respectively. The expression levels of IL-6, IL-8, IL-1β, TNF-α, NF-κB, Beclin1, ULK1 mRNA and P-P65, IL-1β, P62, LC3 protein were detected by real-time quantitative PCR and Western blot, respectively. We found that high-concentration lindane significantly decreased the cell viability, triggered an increase in both intracellular ROS and lactate dehydrogenase (LDH) levels, and decreased the catalase (CAT) activity. Moreover, the expression levels of TNF-α, IL-6, IL-1β, IL-8, NF-κB mRNA and P-p65, IL-1β, P62, LC3, and NF-κB protein were significantly up-regulated after lindane exposure. These results indicated that the lindane exposure causes oxidative stress and autophagy as well as inflammatory through activating NF-κB signaling pathway in HepG2 cells.
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Interaction between cell penetrating peptide S4(13) and plasma membranes by molecular dynamics simulations
- GAO Jin, CUI Wei
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2021, 38 (6):
758-771.
DOI: 10.7523/j.issn.2095-6134.2021.06.006
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Abstract (
465 )
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The derivatives of cell penetrating peptide S4(13) have been used as good drug carriers carrying nucleic acid into cells to play a therapeutic role, which has potential application value in anti-tumor targeted therapy and other fields. However, the mechanism of membrane penetration of S4(13) is still unclear. In this work, we employed molecular dynamics simulation method for study. Firstly, we built systems of single and multiple S4(13) molecules in different membrane models and aqueous solutions, respectively. Thereafter, we performed classical molecular dynamics simulations as well as umbrella sampling molecular dynamics simulations and we analyzed the trajectory to determine the means of single S4(13) and multiple S4(13) molecules with different plasma membranes. The results suggest that S4(13) binds to the bacterial plasma membrane more strongly than interacting with eukaryotic membrane in the form of a single molecule. In addition, multiple S4(13) molecules trend to aggregate to form tetramers in aqueous solution and eukaryotic model membrane. Our work investigates the mechanism of cell penetrating peptide S4(13) to penetrate membrane at the molecular level, and provides a theoretical basis for the application of S4(13) derivatives as drug carriers in the future.
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Effects of biochar application and water saving drip irrigation on phosphorus leaching in farmland fluvo-aquic soil
- SUN Xiaolei, XIE Zijian, YANG Xiaosong, HU Zhengyi
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2021, 38 (6):
772-781.
DOI: 10.7523/j.issn.2095-6134.2021.06.007
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Abstract (
381 )
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The phosphorus (P) leaching from agricultural soils in Haihe River Basin has polluted groundwater in recent years. It is necessary to develop control measures to improve water quality. In this study, a 2-years soil column test (40 cm×45 cm×80 cm) was conducted to analyze the difference of leaching loss of P in soil between added biochar (+B) and without added biochar (-B) during daylily planting under conventional drip irrigation (CDI) and water-saving drip irrigation (80% of CDI, WSDI) conditions. Under the -B condition, the two-year average leaching loss of P under WSDI was 60.4% lower than that under CDI. Under the +B condition, the average leaching loss of P under WSDI was 65.5% less than that under CDI. Implying that WSDI can reduce leaching loss of P in soils, especially under the condition of biochar application. It could be due to the fact that WSDI was not only unfavorable to soil water infiltration, but also enhanced soil P adsorption by reducing soil pH and increasing soil available Fe, which reduced content of soil leachable P, and then control leaching loss of P in soils. Biochar application had no significant effect on soil P leaching, but there were inter-annual differences. In 2017, biochar application under the same irrigation conditions increased the risk of P leaching while showed a trend of decreasing P leaching in 2018. In 2017, WSDI and biochar application significantly reduced the yield. Irrigation, biochar aplication and their interaction had no significant influence on yield in 2018, which means they were not the key factors for the yield with prolonged planting time. Therefore, water-saving irrigation combined with biochar application is recommended as the control measure of soil P leaching in farmland in this area.
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Research progress and review on spatial differentiation of urban housing price: a bibliometric analysis using CiteSpace
- FU Runde, YANG Degang, JIN Chuanfen, CAI Tianyi, WU Shengqin, WAN Tian
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2021, 38 (6):
782-790.
DOI: 10.7523/j.issn.2095-6134.2021.06.008
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Abstract (
458 )
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Spatial differentiation of urban housing price is an important issue in current urban development researches, also an important topic of urban geography and social economics. Based on the Citespace econometric analysis visualization tool and the papers related to the spatial differentiation of urban housing price published in Web of Science Core Collection databases, this paper analyzed the time characteristics of literature publication, subject distribution, collaboration network, co-citation network, literature research progress and characteristics. The research suggests that:1) The number of publications on the spatial differentiation of urban housing price study has been increasing since 1970s, and presented a significant two-stage development process. Mainly, studies focus on subjects of economics, environmental ecology, geography and urban management. 2)The United States and China are the countries with the largest number of publications. Among institutes, Chinese scientific research institutions are more closely linked. The largest research institution is Zhejiang University. The papers of Sherwin Rosen, Luc Anselin, et al provided an important knowledge source for existing researches. 3) Factors that affect the spatial differentiation of urban housing price can be divided into internal and external factors. And, the influence degree and mechanism of various factors are different. 4) Hedonic Pricing model is the most classic research method. With the development of spatial metrology and GIS, the combination of multiple methods becomes the general analysis framework of spatial differentiation of urban housing price studies. The development of network information technology has given birth to new research tools and directions. Through the analysis of the spatial differentiation of urban housing price research status, this paper proposes that future research should pay more attention to the general affect mechanism of regional and the combination effect of influence factors. The model should be constructed with both interpretability and efficiency when applying multiple sources of Spatio-temporal big data.
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Calibration method to the impact of antenna scanning on TOPSAR
- YIN Di, HAN Bing, SUN Jili, ZHAO Liangbo, HONG Wen, HU Yuxin
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2021, 38 (6):
791-799.
DOI: 10.7523/j.issn.2095-6134.2021.06.009
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Abstract (
344 )
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TOPSAR is an earth-imaging technique which can provide wide swath coverage. Its products have been widely applied in quantitative remote sensing applications such as ocean wind inversion and ocean current inversion. Depending on TOPSAR characteristics, this paper made several adaptive corrections to the expression of classical radar equation. Based on this, several radiation calibration methods for TOPSAR were proposed, and a complete processing flowchart was given. In the end, the effectiveness of the methods was verified by using the measured data of GF-3 TOPSAR test-mode.
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Multi-scale large well building object detection based on deep learning
- MENG Xiting, JI Luyan, ZHAO Yongchao, YANG Weitun
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2021, 38 (6):
800-808.
DOI: 10.7523/j.issn.2095-6134.2021.06.010
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Abstract (
582 )
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Large well building is important remote sensing object, and the research on object detection of large well buildings is of great significance to national defense. At the data level, due to the small number of large well buildings samples, there is currently no valid data set available for the object detection. Building effective datasets is of great value for the research in related fields. At the algorithm level,the different resolutions of the remote sensing images result in multi-scale characteristics of the large well buildings, which is one of the difficulties in solving the object detection problem. Based on the above analysis, firstly, this article built the first large well buildings object detection dataset using Google Earth. Then an effective detection model was designed for large well building object detection task. The model in this paper fully integrates the object's multi-scale features and contextual information, and detects the object through the multi-stage cascade network. The model can effectively detect large well buildings, and the detection effect is better than the results of the current mainstream algorithms.
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Analysis and correction of ionospheric dispersion effect in spaceborne bistatic InSAR system
- LIN Shiming, ZHANG Yi, WANG Jili, ZHAO Shuang
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2021, 38 (6):
809-816.
DOI: 10.7523/j.issn.2095-6134.2021.06.011
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Abstract (
373 )
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The images of single-pass InSAR are acquired at the same time, so it has been claimed that the images of spaceborne bistatic single-pass InSAR system is not affected by the ionosphere since the ionospheric phase can be removed by the interferometric processing. However, it has been revealed that the images of spaceborne bistatic single-pass InSAR system are still affected by the ionosphere in recent researches, such as group delay, phase advance, scintillation, and Faraday rotation. It is different from the repeat-pass system that the ionosphere effect in bistatic single-pass InSAR system is caused by the slight incidence angle difference in the two SAR and the TEC gradient. In this paper, we first analyzed the ionospheric dispersion effects in bistatic single-pass InSAR system, and then improved and simulated the range split-spectrum method in the bistatic single-pass InSAR system. It is found that the ionospheric phase in interferogram can be removed by the range split-spectrum method, and this research result has high practical value for the Lutan-1 which will be launched soon.
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Fingerprinting localization of cross-temporal transferred and multi-source wireless signal fusion
- SHI Daheng, LIU Ligang, ZHOU Bin, BU Zhiyong
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2021, 38 (6):
817-824.
DOI: 10.7523/j.issn.2095-6134.2021.06.012
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Abstract (
357 )
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To address the problem of limited coverage area of wireless signals and difficulty in dealing with time-varying characteristics of wireless signals in traditional fingerprinting localization, we propose a method of using multi-source wireless signals for fingerprinting localization, and the accuracy of positioning, which is affected by the time varying of signals, is mitigated by geodesic flow kernel. Firstly, we construct our datasets by a multi-round random sampling of multiple wireless signal sources, which provides a richer and more diverse fingerprint features. Secondly, we fuse geodesic flow kernels from fingerprint features of different times, so that we extend transferring methods from two domains to multiple domains. Finally, base classifiers are trained on multiple datasets, and the predicted position are obtained from all base classifiers, so as to elevate the generalization of the model. Simulation results show that the proposed method outperforms the traditional approaches in terms of positioning accuracy.
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A method for deinterleaving based on JANET
- JIANG Zaiyang, SUN Siyue, LI Huawang, LIANG Guang
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2021, 38 (6):
825-831.
DOI: 10.7523/j.issn.2095-6134.2021.06.013
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Abstract (
317 )
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Radar signal deinterleaving process is a method of classifying intensive pulse streams. The performance of signal classifiers requires to be improved when being confronted with the large amount of data and mode-switch emitters. Recurrent neural network is appropriate as a classifier for pulse streams. However it is weak of long-term dependencies. The forget gate which is a custom function in JANET overcomes the problem. In this paper, JANET is introduced as a classifier for mining the long-term temporal patterns, and the result proves the breathtaking performance of the proposed method.
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Analysis and optimization of single event upset on neural network
- WANG Huiling, XIE Zhuochen, LIANG Xuwen
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2021, 38 (6):
832-840.
DOI: 10.7523/j.issn.2095-6134.2021.06.014
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Abstract (
343 )
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When the DNN (deep neural network) chip is used in a satellite system as a space-borne chip, it will be affected by space radiation. The interference of single event upset (SEU) on the storage unit will cause the parameters of the memory unit to be wrong. The error mapping to the neural network will affect the output results. This paper analyzes the accuracy of the network inference which combines the SEU probability model to inject the error on the network weight parameters. From the analysis of the nonlinear characteristics of the activation function and experimental verification, it is found that the activation function with bilateral inhibition is more fault-tolerant. Furthermore, we add the BN layer after the network convolution layer and consider L2 regularization during training to improve the network's fault tolerance, and verify its feasibility through experiments.
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Improving pseudo-labeling semi-supervised learning based on prototype learning
- YANG Yulong, GUO Tiande, HAN Congying
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2021, 38 (6):
841-851.
DOI: 10.7523/j.issn.2095-6134.2021.06.015
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Abstract (
912 )
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In recent years, semi-supervised learning (SSL) methods based on image augmentation and consistency regularization have been widely used and have achieved great success. However, little attention has been paid to pseudo-labeling (PL)-based semi-supervised learning methods because of the "confirmation bias" problem, i.e., errors in the model are accumulated by wrong pseudo-labels and thus difficult to be corrected. In this paper, we propose a feature refinement model based on the feature space graph. The model learns a graph attention model on the feature space mapped by the neural network. We apply this model to the feature space to make use of the information of the prototypes to refine the features. The pseudo-labels generated by the refined features are randomly and linearly combined with the pseudo-labels generated by the prototypes assignment to obtain new pseudo-labels. In this paper, we apply this module to two pseudo-labeling semi-supervised learning frameworks and achieve significant accuracy improvements in several CIFAR-10 and CIFAR-100 semi-supervised classification problems. In particular, we apply our feature refinement model to the pseudo-labeling semi-supervised learning framework PLCB and add the proposed mutual mix supervision techniques to achieve good results on this framework. By applying the proposed feature refinement module to several pseudo-labeling semi-supervised learning frameworks and conducting experiments on several datasets, the proposed algorithm is demonstrated to be universal and effective as an add-on module.
