Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.     

Corrosion behavior of Cu–Sn bronze alloys in simulated archeological soil media

The corrosion behavior of synthetic Cu–Sn bronze alloys with six different Sn contents was examined through an electrochemical test and a synthetic test in a simulated corrosive medium. The mechanism of corrosion and the morphology of the corroded surfaces were characterized through field emission scanning electron microscopy equipped with energy-dispersive spectroscopy. At the corrosion potential, the corrosion behavior appears to be determined by the charge transfer step and the diffusion process. It was found that the bronze-IV (Cu–26.8Sn) specimen exhibited the best corrosion resistance, as evidenced by a low corrosion current density and a high impedance. This improvement resulted from an increase in the content of the Cu–Sn solid solution in the alloy, which was conducive to forming a relatively more protective passive film on the surface of the bronze alloy. This finding would be valuable in the anticorrosion protection of archeological artefacts after their excavation.     

Facile construction of composition-tuned ruthenium-nickel nanoparticles on g-C3N4 for enhanced hydrolysis of ammonia borane without base additives

Developing high-efficiency and low-cost catalysts for hydrogen evolution from hydrolysis of ammonia borane (AB) is significant and critical for the exploitation and utilization of hydrogen energy. Herein, the in-situ fabrication of well-dispersed and small bimetallic RuNi alloy nanoparticles (NPs) with tuned compositions and concomitant hydrolysis of AB are successfully achieved by using graphitic carbon nitride (g-C₃N₄) as a NP support without additional stabilizing ligands. The optimized Ru₁Ni_7.5/g-C₃N₄ catalyst exhibits an excellent catalytic activity with a high turnover frequency of 901 min^?1 and an activation energy of 28.46 kJ mol^?1 without any base additives, overtaking the activities of many previously reported catalysts for AB hydrolysis. The kinetic studies indicate that the AB hydrolysis over Ru₁Ni_7.5/g-C₃N₄ is first-order and zero-order reactions with respect to the catalyst and AB concentrations, respectively. Ru₁Ni_7.5/g-C₃N₄ has a good recyclability with 46% of the initial catalytic activity retained even after five runs. The high performance of Ru₁Ni_7.5/g-C₃N₄ should be assigned to the small-sized alloy NPs with abundant accessible active sites and the synergistic effect between the composition-tuned Ru–Ni bimetals. This work highlights a potentially powerful and simple strategy for preparing highly active bimetallic alloy catalysts for AB hydrolysis to generate hydrogen.     

博斯腾湖东泵站电气主接线及主设备选型设计

博斯腾湖泵站分东、西泵站二期建设,本文介绍了博斯腾湖东泵站工程电气一次设计中的接入系统设计、电气主接线、设备选择。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。     

从频谱监测和国际协调探讨短波广播频段扩展的可行性

短波广播能够实现远距离和大范围的覆盖，至今仍是进行地区性、全国性及国际性广播覆盖的最好手段之一。ITU在2001年4月批准的1514建议书《30MHz以下广播频段的数字声音广播系统》，正式确定了DRM系统为全球统一的数字广播系统。在短波广播由模拟向数字化过渡的进程中，如何解决短波广播频谱短缺的问题，本文根据国家相关的频谱监测和国际短波频率协调的情况，对短波广播中4～10MHz频谱的扩展可行性进行初步分析。     

二极管侧面抽运薄片激光器耦合系统研究

设计了二极管侧面抽运Nd:YAG薄片激光器,耦合系统由消像差透镜组和空心光波导组成,对二极管快轴和慢轴方向的抽运光进行压缩和均匀化.采用光线追迹法,同时考虑二极管在快轴和慢轴方向的发散特性及薄片侧面的散射特性,模拟并分析了光线在耦合系统内的传输和薄片内抽运光分布的规律.模拟结果表明耦合系统具有98.1%的耦合效率,同时薄片内具有理想的抽运光分布.     

连续型衍射透镜激光直写技术研究

研究了不同于台阶形式的具有连续浮雕结构的衍射聚光透镜的激光直写工艺,简要描述了光致抗蚀剂的曝光和显影,对激光直写工艺的机理和工艺过程进行阐述.利用CLWS-300W/C极坐标激光直写设备制作出了具有良好面形微结构和较高衍射效率的连续型衍射透镜.研究表明,激光直写技术直写精度高,加工工艺灵活,利用计算机的控制,能够根据光学设计产生的浮雕分布数据制作复杂的、任意形状和外形的微型浮雕结构,非常适合于高精度微光学元件的加工制作.