Electrocatalytic Oxidation of Venlafaxine at a Multiwall Carbon Nanotubes-Ionic Liquid Gel Modified Glassy Carbon Electrode and Its Electrochemical Determination

The electrocatalytic oxidation of venlafaxine (VEN) was investigated at a glassy carbon electrode (GCE), the modified electrode by a gel containing multiwall carbon nanotubes (MWCNTs) and a room-temperature ionic liquid (RTIL), 1-butyl-3-methylimidazolium hexafluorophate (BMIMPF6) in 0.10 mol L−1 phosphate buffer solution (PBS, pH 6.8). It was found that an irreversible anodic oxidation peak of VEN with the peak potential (Epa) as 0.780 V appeared at MWCNTs-RTIL/GCE. The electrode reaction process was a diffusion-controlled one and the electrochemical oxidation involved two electrons transferring and two protons participation. Furthermore, the charge-transfer coefficient (α), and the electrode reaction rate constant (kf) of VEN were found to be 0.91 and 3.04×10−2 s−1, respectively. Under the optimized conditions, the electrocatalytic oxidation peak currents were linearly dependent on the concentration of VEN in the concentration range from 2.0×10−6 mol L−1 ~ 2.0×10−3 mol L−1 with the limit of detection (S / N = 3) as 1.69×10−6 mol L−1. The proposed method has been successfully applied in the electrochemical quantitative determination of VEN content in commercial venlafaxine hydrochloride capsules and the determination results could meet the requirement of the quantitative determination

Image Super-resolution with An Enhanced Group Convolutional Neural Network

CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image super-resolution, which may increase computational cost in general. In this paper, we present an enhanced super-resolution group CNN (ESRGCNN) with a shallow architecture by fully fusing deep and wide channel features to extract more accurate low-frequency information in terms of correlations of different channels in single image super-resolution (SISR). Also, a signal enhancement operation in the ESRGCNN is useful to inherit more long-distance contextual information for resolving long-term dependency. An adaptive up-sampling operation is gathered into a CNN to obtain an image super-resolution model with low-resolution images of different sizes. Extensive experiments report that our ESRGCNN surpasses the state-of-the-arts in terms of SISR performance, complexity, execution speed, image quality evaluation and visual effect in SISR. Code is found at https://github.com/hellloxiaotian/ESRGCNN

A self-supervised CNN for image watermark removal

Popular convolutional neural networks mainly use paired images in a supervised way for image watermark removal. However, watermarked images do not have reference images in the real world, which results in poor robustness of image watermark removal techniques. In this paper, we propose a self-supervised convolutional neural network (CNN) in image watermark removal (SWCNN). SWCNN uses a self-supervised way to construct reference watermarked images rather than given paired training samples, according to watermark distribution. A heterogeneous U-Net architecture is used to extract more complementary structural information via simple components for image watermark removal. Taking into account texture information, a mixed loss is exploited to improve visual effects of image watermark removal. Besides, a watermark dataset is conducted. Experimental results show that the proposed SWCNN is superior to popular CNNs in image watermark removal

Crustal evolution of a continental magmatic arc from subduction to collision: a case study in the Gangdese arc, southern Tibetan Plateau

Magmatic arcs are the main environment where continental crust is created on the post-Archean Earth; however, how juvenile arc crust evolves into mature continental crust is still controversial. In this study, we report new bulk-rock major and trace elements, Sr-Nd isotopes, and zircon U-Pb ages and Hf isotopes from a large suite of granites collected from the eastern segment of the Gangdese arc, southern Tibetan Plateau, which record a complete history of arc crust evolution from Mesozoic subduction to Cenozoic collision. These new data show that Gangdese crust-derived granites generated during the subduction to collisional stages record significant geochemical changes with age, indicating that the bulk composition, lithological makeup, and thicknesses of the arc crust evolved over time. Here, we propose that the Gangdese arc had a thick juvenile crust with a small volume of ancient crustal components during late-stage subduction of the Neo-Tethys Ocean, a thin juvenile crust with heterogeneously distributed ancient crustal materials during early collision, and a thick juvenile crust with minor proportions of ancient rocks during late collision. This implies that the arc experienced episodes of crustal thickening during the Late Cretaceous and Eocene, interspersed by periods of thinning during the Paleocene and Miocene, and several discrete episodes of partial melting in the lower arc crust, and cycling or recycling of juvenile and ancient crustal materials within the arc crust and between the crust and mantle. We suggest that shallow subduction of the Neo-Tethys during the Late Cretaceous promoted tectonic thickening of the arc crust, partial melting of lower crust, and formation of high Sr/Y granites. After the onset of the Indo-Asian collision, breakoff of the subducted Neo-Tethyan oceanic slab during the Paleocene/early Eocene allowed thinning of the overlying arc crust and generation of granites derived from juvenile and ancient crustal sources. Continued underthrusting of the Indian continental crust and subsequent delamination of thickened lithospheric mantle led to thickening and thinning of the arc crust, respectively, and partial melting of thickened lower crust and generation of high Sr/Y granites during the Oligocene and Miocene. Using the Gangdese as an analogue for post-Archean continental margins, we suggest that the repeated thickening and thinning of arc crust, and associated multistage remelting of the lower arc crust, and material cycling or recycling within the crust and between the crust and mantle from subduction to collision are common processes that drive maturation of juvenile arc crust