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Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As traditional geographical distances diminish, new patterns of regional spatial configuration continuously emerge and develop, with the dominance of flow space shaping the new landscape of regional spatial networks. From the viewpoint of passenger flows, and with the help of the social network analysis method, the present paper constructed a comprehensive passenger flow matrix based on passenger frequency data. It analyzed the characteristics of the passenger transport network of the Pearl River Delta Urban Agglomeration from three aspects, namely network nodes, connection flow lines, and the overall network. and then explored its influencing factors. The results showed that: (1) From the point of network nodes, the Pearl River Delta urban agglomeration passenger transportation network shows the characteristics of multiple levels and regional differentiation as a whole, plays a leading role as the first level of Guangzhou. (2) From the point of connection flow lines, passenger flows between cities are led by Guangzhou and Shenzhen, which plays a core leading role in their hinterland. The connection between cities is strong along the axis from northwest to southeast along the Pearl River. (3) From the perspective of the overall network, its development level is relatively high in the Pearl River Delta Urban Agglomeration, and the network centralization degree is relatively high as well. (4) From the perspective of influencing factors, policy and natural factors will have an impact on passenger flow. Through quantitative analysis of economic and social factors, it is found that R&D input, GDP, fixed asset investment and urbanization rate show a positive impact on passenger network, while resident population and foreign direct investment show a negative impact on passenger network. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Surfactant Detergent & Cosmetics (2097-2806) is the property of China Surfactant Detergent & Cosmetics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Feed Research is the property of Editorial Board of Feed Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Science Technology & Industry / Keji he Chanye is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Apple is one of the main producing fruits and the main economic crops in many areas. Detecting and grading apples through the image of apple trees under natural environment is helpful to promote the modernization of fruit industry. Combining deep learning with traditional methods, this paper proposes a fruit detection and grading method combining color and apple diameter. In order to improve the detection rate of unobvious targets and the precision of bounding boxes when illumination or fruit coloration is uneven, the convolutional neural network is used to construct an apple detection model and detect apple on feature maps of two scales, b货，(1. 8b-- L*) color components of the image in bounding boxes in CIELAB color space are extracted, the image is binarized, and the target contour is accurately extracted to correct the bounding boxes. Experimental results show that the precision is 91. 60% and the Fl-score value is 87. 62%. According to the image and actual size mapping method, the apple diameter is calculated to achieve the apple grading. Experimental results show that the grading accuracy is 90%. [ABSTRACT FROM AUTHOR]

Copyright of Acta Edulis Fungi is the property of Acta Edulis Fungi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)