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Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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 Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography 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 Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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 Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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 Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering 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.)

COVID-19 is spreading rapidly around the world. In order to diagnose it quickly and accurately and thus block the chain of epidemic transmission, the study proposed a deep learning-based classification network DLDA-A-DenseNet. Firstly, DenseNet-201 combined deep layer dense aggregation to aggregate feature information at different stages to enhance its ability to identify and localize lesions. Secondly, this paper proposed efficient multi-scale long-range attention to refine the aggregated features. Moreover, this paper used a balanced sampling training strategy to eliminate the bias for the class imbalance problem of CT image dataset. Testing on the China consortium of chest CT image investigation dataset, the method improved 2.24%,3.09%,2.09%,2.60% and 3.48% in accuracy, recall, precision, F1 score and Kappa coefficient compared with DenseNet-201,and achieved an optimal accuracy of 99.50% on COVID-CISet image dataset. The results show that the proposed COVID-19 CT image classification method can fully extract the lesion features of CT slices compared with other methods, and has higher classification accuracy and good generalizability. [ABSTRACT FROM AUTHOR]

Copyright of Evaluation & Analysis of Drug-Use in Hospitals of China is the property of Evaluation & Analysis of Drug-Use in Hospitals of China Editorial Board 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 Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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.)

Considering the existing spinal Computer Tomography（CT） and Magnetic Resonance（MR） image segmentation models have limitations in segmentation performance, this paper proposes a spinal segmentation method MAU-Net based on U-shaped network. Frist, this paper introduces coordinate attention module into the encoder of Ushaped network, which enables the network accurately capture the spatial position information and embed it into the channel attention. Second, this paper proposes dual-branch channel cross fusion module based on Transformer, it can replace the skip connection for multi-scale feature fusion. Finally, this paper proposes a feature fusion attention module to better fuse the semantic differences between Transformer and convolution network. On scoliosis CT dataset, Dice reached 0.9296, IoU reached 0.8597. On the public MR dataset SpineSagT2 Wdataset3, compared with FCN, Dice improved by 14.46%. Experimental results show that this method can effectively reduce the false segmentation area of vertebrae. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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 Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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.)

Bone age assessment is a common method to detect endocrine and growth abnormalities in children. But in deep learning methods, low-quality hand X-ray images reduce the final evaluation accuracy. To solve this problem, this paper proposed an alignment network that increases the area of interest in hand X-ray images. This network uses the Swin Transformer structure as the backbone network to learn image hand similarity and obtain affine coefficients and does not require large-scale hand annotation during the training process. In the bone age assessment network, for the improvement of efficient channel attention and spatial attention mechanism. This paper proposed dual-pool efficient channel attention and asymmetric convolution spatial attention method and combines these two methods in the form of dual attention and Xception network proposes DA-Xception. This paper tested the RSNA dataset, which achieved a mean absolute error of 5.37 months for this bone age assessment method. Compared with other deep learning methods, this method can fully extract features and optimize the evaluation results. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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.)

目的 探讨子宫颈小细胞神经内分泌癌（SCNEC）乳腺转移的诊治方法。方法 回顾性分析1例SCNEC 乳腺转移患者的临床资料。结果 患者女，29岁，最初被诊断为SCNEC，进行根治性子宫切除手术及术后辅助放化 疗的综合治疗。术后 2年发现右乳腺肿块及肿大的腋窝淋巴结，病理证实为 SCNEC乳腺转移。接受化疗+抗血管 生成药物+程序性细胞死亡受体1/程序性细胞死亡配体1抑制剂联合治疗+放疗，最终于发现乳腺转移后9个月因 肿瘤全身多处转移、呼吸衰竭而死亡。结论 SCNEC乳腺转移临床罕见，诊断主要依靠病理检查结合病史及免疫 组化检查，患者预后较差，早期主要以根治性手术及术后放疗和（或）化疗为主，晚期可采取化疗和局部放疗或局部 病灶切除术治疗。 [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University 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 Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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 Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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.)

The construction and operation of reservoir project will have an important impact on regional land use and ecosystem stability. The analysis of spatial and temporal dynamic changes of land use in reservoir area can provide technical support for the protection of land resources and ecological environment in reservoir area. Taking the first tributary of the upper reaches of the reservoir in the upper reaches of the reservoir area above the dam to 92 m of the Chushandian Reservoir as an example, by interpreting, calculating and analyzing satellite remote sensing images from different periods of the reservoir area, the land use transfer matrix could he generated, and a single type dynamic degree and comprehensive type dynamic degree model could be constructed to qualitatively analyze the spatial and temporal characteristics of land use in the reservoir area. The results show that from 2000 to 2018, the land use structure of Chushandian Reservoir has been changed significantly, and the spatial dynamic degree of different land use types in different periods is obviously different, hut the spatial pattern has been changed little. Reservoir construction will play a leading role in regional economic and social development. Land use structure should he adjusted in time to strengthen the protection of land resources and ecological environment in reservoir area. [ABSTRACT FROM AUTHOR]

Copyright of Yellow River is the property of Editorial Board of Yellow River 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 Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology 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 Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology 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 Journal of Agro-Environment Science is the property of Journal of Agro-Environment Science Editorial Board 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 Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering 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.)