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When Synthetic Aperture Radar (SAR) observes complex structural targets such as oil tanks, it is easily interfered with by multipath signals, resulting in a large number of multipath ghost images in the SAR image, which seriously affect the image clarity. To address this problem, this paper proposes a multi-aspect multipath suppression method. This method observes complex structural targets from different azimuth angles to obtain a multi-aspect image sequence and then uses the difference in sequence features between the target image and the multipath ghost image with respect to aspect angle to separate them. This paper takes a floating-roof oil tank as an example to analyze the propagation path and the ghost image characteristics of multipath signals under different observation aspects. We conclude that the scattering center of the multipath ghost image changes with the radar observation aspect, whereas the scattering center of the target image does not. This paper uses the Robust Principal Component Analysis (RPCA) method to decompose the image sequence matrix into two parts: a sparse matrix and a low-rank matrix. The low-rank matrix represents the aspect-stable principal component in the image sequence; that is, the real scattering center. The sparse matrix represents the part of the image sequence that deviates from the principal component; that is, the signal that varies with aspect, mainly including multipath signals, sidelobes, anisotropic signals, etc. By reconstructing the low-rank matrix and the sparse matrix, respectively, we can obtain the image after multipath signal suppression and also the multipath ghost image. Both the target and the multipath signal provide useful information. The image after multipath signal suppression is useful for obtaining the structural information of the target, and the multipath ghost image is useful for analyzing the multipath phenomenon of the complex structure target. This paper conducts experimental verification using real airborne SAR data of an external floating roof oil tank and compares three methods: RPCA, PCA, and sub-aperture fusion method. The experiment shows that the RPCA method can better separate the target image and the multipath ghost image. [ABSTRACT FROM AUTHOR]

Flexible electrolyte-gated graphene field effect transistors (Eg-GFETs) are widely developed as sensors because of fast response, versatility and low-cost. However, their sensitivities and responding ranges are often altered by different gate voltages. These bias-voltage-induced uncertainties are an obstacle in the development of Eg-GFETs. To shield from this risk, a machine-learning-algorithm-based LgGFETs' data analyzing method is studied in this work by using Ca2+ detection as a proof-of-concept. For the as-prepared Eg-GFET-Ca2+ sensors, their transfer and output features are first measured. Then, eight regression models are trained with the use of different machine learning algorithms, including linear regression, support vector machine, decision tree and random forest, etc. Then, the optimized model is obtained with the random-forest-method-treated transfer curves. Finally, the proposed method is applied to determine Ca2+ concentration in a calibration-free way, and it is found that the relation between the estimated and real Ca2+ concentrations is close-to y = x. Accordingly, we think the proposed method may not only provide an accurate result but also simplify the traditional calibration step in using Eg-GFET sensors. [ABSTRACT FROM AUTHOR]

Background: The plant Euphorbia esula has been used by ancient Chinese people to treat cancer and other ailments and is used by present doctors or folks as an assistant treatment for some kind of cancers, but the mode of action is unclear. Objective: To investigate the influence of E. esula full extract on chemoresistance, cell migration/invasion, and apoptosis of multidrug-resistant human stomach cancer cells. Materials and Methods: After treating multidrug-resistant human stomach cancer SGC7901/VCR cells with E. esula extract at varying concentrations, the inhibition of cell proliferation was detected using thiazolyl blue. Sensitivity to the chemotherapeutic drugs, adriamycin and paclitaxel, was evaluated using half maximal inhibitory concentration. Cell cycle progression was analyzed by flow cytometry. The inhibitions of cell migration and invasion were examined by Transwell method. The induction of apoptosis and the apoptotic rate were studied by electron microscopy and flow cytometry, respectively. Activation of caspase 3 enzyme was inspected by ultraviolet spectrophotometry. Results: E. esula extract could increase the sensitivity of SGC7901/VCR cells to the chemotherapeutic drugs, adriamycin and paclitaxel. The proliferation, migration, and invasion of SGC7901/VCR cells were significantly inhibited by E. esula extract (P < 0.01 compared with negative control), which showed time- and dose-dependent manners (P < 0.05 and P < 0.01, respectively). Cell cycle was arrest at the S phase. E. esula extract also induced apoptosis in SGC7901/VCR cells, and the apoptotic rate was increased significantly with drug concentration and with treatment time (P < 0.01 compared with negative control, P < 0.05 between concentrations and time points). E. esula extract upregulated enzymatic activity of caspase 3. Conclusion: E. esula extract could reverse SGC7901/VCR cell's resistance to chemotherapeutic drugs and could inhibit cell proliferation, migration, and invasion, interfere with cell cycle progression, and induce apoptosis in SGC7901/VCR cells. Abbreviations used: E. esula: Euphorbia Esula; FCS: fetal calf serum; IC50: half maximal inhibitory concentration; OD: optical density. [ABSTRACT FROM AUTHOR]