Showing 201 - 220 results of 299 for search '"Ningxia"', query time: 0.05s Refine Results
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    Contribution to the Knowledge of the Genus Linda Thomson, 1864 (Part I), with the Description of Linda (Linda) subatricornis n. sp. from China (Coleoptera, Cerambycidae, Lamiinae) by Mei-Ying Lin, Xing-Ke Yang

    Published 2012-01-01
    “…Linda (Linda) subatricornis n. sp is described from Sichuan (holotype locality), Fujian, Shaanxi, Hebei, Ningxia of China. It is separated from the most similar species L. atricornis Pic by differences in genitalia and antennal insertions. …”
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    Community Integration of Disability: A Bibliometric and Knowledge-Map Analysis by Wang S, Li D, Liu C, Sun X, Shi Y, Wang H, Zhang H

    Published 2025-01-01
    “…Shuaiyou Wang,1 Dingding Li,1 Chenjun Liu,1 Xueting Sun,1 Yage Shi,1 Hongru Wang,2 Huimin Zhang3 1School of Nursing, Xinxiang Medical University, Xinxiang, Henan, People’s Republic of China; 2Nursing of Department, Xinxiang First People’s Hospital, Xinxiang, Henan, People’s Republic of China; 3School of Nursing, Ningxia Medical University, Yinchuan, People’s Republic of ChinaCorrespondence: Huimin Zhang, School of Nursing, Ningxia Medical University, No.1160 Shengli South Street, Xingqing District, Yinchuan, 750001, People’s Republic of China, Email 35290915@qq.comBackground: Community integration (CI) is the ultimate goal of rehabilitation for individuals with disabilities. …”
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    Coordinated Development of Urban Land Use and Ecological Economics in China by Zhiyuan Zhu, Gang Du

    Published 2021-01-01
    “…The level of coordination was high in Beijing, Shanghai, and Tianjin and was low in Gansu, Ningxia, and Xinjiang. Changes in ecoefficiency were not consistent with the degree of coordination, and intensive urban land use was positively correlated with the level of coordination, which showed a mutually reinforcing relationship. …”
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    Imbalanced Data Sets Classification Based on SVM for Sand-Dust Storm Warning by Yonghua Xie, Yurong Liu, Qingqiu Fu

    Published 2015-01-01
    “…The comparative experimental results on the real data sets from Yanchi and Tongxin districts in Ningxia of China show that the SRU-AIBSMOTE method can obtain better classification performance than some traditional classification methods.…”
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