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为了探究通过被毛红外光谱特征进行啮齿目（Rodentia）动物种类鉴定的可行性，使用傅里叶红外光谱（FT-IR）及其二阶导数谱（SD-IR）对大仓鼠（Tscherskia triton）背毛和腹毛进行检测与分析。结果表明：大仓鼠的背毛和腹毛均能反映出该物种的特征性成分，背毛和腹毛的红外图谱基本一致，均在621、679、782、846、1562、1637 cm-1附近有明显的吸收峰形成，在3415、3470 cm-1均有明显吸收峰出现，形成W形图谱；二阶导数谱也基本相同，均在683、703、776、786、854 cm-1有明显的吸收峰。尽管存在这些相似性，但红外图谱和二阶导数谱也能明显地反映出背毛和腹毛的特定差异，腹毛吸收峰的峰面积和峰强明显比背毛的大。在红外图谱中，845~848 cm-1和1426~1439 cm-1处，二者出峰位置均有明显差异；在700~727 cm-1，二者的峰形有较大差异。二阶导数谱中，在621~645 cm-1处，腹毛形成2个W形图谱，背毛形成1个W形图谱；在707~718 cm-1处，背毛形成1个W形图谱，腹毛形成1个明显的单峰；在818~835 cm-1处，腹毛形成1个M形图谱，背毛形成2个M形图谱；背毛和腹毛分别在652~655、650~655 cm-1形成1个单峰；背毛在700 cm-1形成1个单峰，腹毛未形成明显的峰。研究认为，大仓鼠背毛和腹毛的红外光谱特征基本一致，但二阶导数谱能更好地反映出二者的差异。故红外光谱可用于大仓鼠不同部位被毛的识别与鉴定工作。

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(School of Mathematics and Computer Science, Anhui Normal University, Wuhu 241003, China)Abstract:With the development of social networks, the influence measurement of nodes has become an important research area. Aiming at the accuracy problem of the traditional random walk PageRank algorithm, we in this paper propose a reverse random walk PageRank algorithm, which is based on the idea of reversely searching dissemination source, each directed edge starts the random walk with probability ε, and the value of PageRank is calculated by iteration. Experimental evaluation on publicly available datasets demonstrates that our algorithm has the improved stability and higher accuracy when there is less iteration. [ABSTRACT FROM AUTHOR]