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With the development of the times, computer, information technology gradually penetrated into all walks of life. Textile and clothing design, production, consumption integration of machine vision, graphic image recognition technology development have become a trend. At present, the intelligence degree of the textile and clothing industry has reached an unprecedented new height. In the production and identification of fabrics, the machine vision gradually replaces the manual work, and realizes the automatic and accurate production line. In the design, manufacturing, consumption and other aspects of clothing, image recognition technology has assumed the historical responsibility. Combined with the Internet of things, cloud computing and other technologies, it has improved the production efficiency and achieved intelligent design and production.

Oral English teaching is an important form of cultivating students' English accomplishment and improving their English learning effect. In the context of intelligent education, by giving full play to the advantages of computer network and actively reconstructing the new mode of Oral English teaching, we will, on the basis of optimizing the form of oral English teaching and by integrating high-quality oral English teaching resources, to promote students to participate in oral English learning and speaking practice in a conscious and spontaneous way. Based on the analysis of the existing problems in spoken English teaching, this paper puts forward the construction and implementation of a new spoken English teaching model based on computer network.

Uranium bioleaching has been rapidly developed in China during recent years. However, some problems during bioleaching, such as low uranium leaching efficiency for rocks lacking pyrite, remain to be solved. A granite type uranium deposit from southern China was selected for the study of U bioleaching with addition of pyrite. Experiments using four approaches, including (i) pyrite ores mixing with culture, (ii) pyrite tiled on the surface of ores with culture, (iii) no pyrite ores with culture, and (iv) pyrite ores without culture were examined in this study. Results showed that bacteria can improve U leaching efficiency, particularly by adding pyrite into ore. Approach (i) pyrite ores mixing with culture had the highest U concentration and the highest recovery rate of the four approaches. No significant difference was observed between approaches (ii) pyrite tiled on the surface of ores with culture and (iii) no pyrite ores with culture.