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The bound acrylonitrile content in nitrile rubber (NBR) was determined by pyrolysis-gas chromatography/mass spectrometry, and the effects of furnace temperature and sample amount on pyrolysis were investigated. The butadiene and acrylonitrile fragments were identified by mass spectrometry, and the relationship between peak height ratio of acrylonitrile to butadiene and content ratio of acrylonitrile to butadiene was also established. Furthermore, the test results were compared with those determined by Kjeldahl method. The experiment results showed that the butadiene and acrylonitrile fragments in NBR had good chromatographic peak shape and recognition under the conditions of pyrolysis temperature of 600 ℃ and sample mass of 0.3-0.6 mg. The peak height of acrylonitrile with extracted ion M/Z 53 was positively correlated with the content of bound acrylonitrile in NBR, and the linear correlation coefficient of quantitative curve was above 0.99. Compared with Kjeldahl method, the absolute deviation of this method for determination of bound acrylonitrile content was not more than 0.7%.

Objective: This study focuses on solving the problems of large memory consumption, low recognition accuracy and slow recognition speed in the classification process of peanut quality. Methods: A method for classification of peanut quality based on deep learning and image processing was proposed. The Coordinate Attention module was firstly introduced to encode the obtained feature graph into a pair of direction-aware and position-sensitive attention graph, which improved the ability to obtain the information of the region of interest of the graph. Then, Gradient Centralization was used to improve the optimizer. By modifying the parameters of the last fire layer and the convolution layer. An improved model, CG-SqueezeNet, was applied to peanut pod quality grading. Results: The classical convolutional network models VGG16, AlexNet, DenseNet121, ResNet50, Squeezenet were improved, and five different base classifier models were trained by transfer learning. By comparing with the classic model, it was found that the CG-SqueezeNet model could better learn the features of the region of interest in the image. The detection accuracy of the actual peanut pod image database was 97.83%, and the parameter memory was only 2.52 MB. Conclusion: The method is suitable for deployment on embedded resource-limited devices such as mobile terminals, which helps to realize real-time and accurate identification of peanut pod quality.

The Wutonggou iron deposit is located in the well-known iron metallogenic belt in the eastern Tianshan, NW China, and has been regarded as a sedimentary iron deposit. Although hydrothermal overprinting could play indispensable roles in the formation of high-grade iron ores in sedimentary iron deposits, previous studies mainly focused on sedimentary-related iron mineralization, while the nature and contribution of hydrothermal fluids are poorly constrained. Accordingly, an integrated study of ore geology, H-O-C isotopes and 40Ar-39Ar dating, is conducted on the Wutonggou deposit, in order to reveal the features, source, and timing of hydrothermal mineralization. The studied deposit includes two mining sections namely the Jianshan and Wutonggou. The δ18O values of early magnetite from the Jianshan section range from +3.0‰ to +5.8‰ that nearly consistent with classic magmatic magnetite, while increase to 6.3‰–8.0‰ in the late stage. Quartz from the two sections shows comparable H-O isotopic compositions and identical fractionation trends, and is plotted in or periphery to the primary magmatic water area. Calcites from the two sections are broadly similar in carbon and oxygen isotopic compositions, and siderite from the Wutonggou section is plotted in the same region. Thus, comparable stable isotopic compositions and evolution trends indicate similar magmatic fluids contributed hydrothermal iron mineralization in the two mining sections. Moreover, water-rock interactions of varying degrees generated distinct mineralization styles in the Jianshan and Wutonggou sections, and caused the isotopic fractionation in late stages. Biotite extracted from a hydrothermal siderite ore yielded a 40Ar-39Ar plateau age of 299.5 ± 2.0 Ma, indicates the timing of hydrothermal iron mineralization is corresponding to the emplacement of vicinity granitoids. Taken together, the hydrothermal mineralization in the Wutonggou iron deposit was the product of remobilization and upgrading of early sedimentary iron ores, and ore-forming fluids were most probably originated from regional granitic magmatism. [ABSTRACT FROM AUTHOR]