Browsing by Author "Zhou J"

Now showing 1 - 5 of 5
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    Combining data from consumers and traditional medicine practitioners to provide a more complete picture of Chinese bear bile markets
    (John Wiley and Sons Ltd on behalf of British Ecological Society, 2021-10-07) Hinsley A; Hu S; Chen H; Garshelis D; Hoffmann M; Lee TM; Moyle B; Qiu Y; Ruan X; Wan AKY; Zhou J; Milner-Gulland EJ; Friant S
    1. Understanding wildlife consumption is essential for the design and evaluation of effective conservation interventions to reduce illegal trade. This requires understanding both the consumers themselves and those who influence their behaviour. For example, in markets for wildlife-based medicines, both consumers and medical practitioners have a role in which products are consumed. 2. We used mixed methods to triangulate data on bear bile consumption from 3,646 members of the public, 80 pharmacy workers and 38 Traditional Chinese Medicine (TCM) doctors in four provincial capital cities across China. Bear bile can be sold legally in packaged TCM products made from farmed bile, or sold illegally, often as raw gallbladders from wild bears. We interviewed medical practitioners, and surveyed the public using both direct questions (DQ) and the Unmatched Count Technique (UCT), an indirect method used to improve reporting of sensitive behaviours. We applied a ‘combined’ UCT-DQ analysis to produce a more robust consumption estimate. 3. In all, 140 (3.8%) survey respondents directly reported recent (<3 years) bile consumption, but the combined UCT-DQ estimate was 11.2%. In total, 14 survey respondents (0.4% sample and 10% recent consumers) self-reported recent wild bile consumption. Almost a quarter of doctors and half of pharmacy workers had ever prescribed bile. 4. Around half of doctors and over a quarter of pharmacy workers said that bear bile was the best medicine in certain situations. More than half of doctors and over a third of pharmacy workers thought wild bile was more effective than farmed, although we found no evidence of wild bile being formally prescribed. Consumers could name specific treatment uses of bile but almost half of recent consumers did not know the source of bile they had consumed. 5. We show that gathering perspectives from different wildlife market actors can generate a more complete picture of trade. In China, bile consumption may be limited by its specific TCM treatment uses, but whether practitioner views on the greater effectiveness of wild bile are passed to consumers must be investigated further. With potential overlap between farmed and wild consumption, any interventions to change these markets must carefully consider how both consumers and practitioners may react.
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    Influences of nitrogen input forms and levels on phosphorus availability in karst grassland soils
    (Frontiers Media S.A., 2024-01-18) Zhou J; Yang F; Zhao X; Gu X; Chen C; Chen J
    The availability of soil phosphorus (P), a crucial nutrient influencing plant productivity and ecosystem function, is impacted by continuously increasing nitrogen (N) enrichment, which changes the soil P cycle. The effect of varying forms of N input on soil P dynamics in P-limited karst grassland ecosystems remains unclear. To address this knowledge gap, we conducted a greenhouse experiment to explore the effects of various forms of N addition [Ca(NO3)2, NH4Cl, NH4NO3, Urea] on soil P fractions in these ecosystems, applying two levels (N1: 50 mg N kg−1soil, N2: 100 mg N kg−1soil) of N input in two soils (yellow soil, limestone soil). Results indicated that P fractions in both soil types were significantly affected by N additions, with yellow soil demonstrating a higher sensitivity to these additions, and this effect was strongly modulated by the form and level of N added. High N addition, rather than low N, significantly affect the P fractions in both soil types. Specially, except for Ca(NO3)2, high N addition significantly increased the available P in both soils, following the order: Urea and NH4NO3 > NH4Cl > Ca(NO3)2, and decreased NaHCO3-Pi in both soils. High N addition also significantly reduced NaOH-Po and C.HCl-Po fractions in yellow soil. Additionally, the response of root biomass and alkaline phosphatase activity in both soils to N input paralleled the trends observed in the available P fractions. Notably, changes in soil available P were strongly correlated with plant root biomass and soil alkaline phosphatase activity. Our study highlights that the N addition form significantly influences soil P availability, which is closely tied to plant root biomass and alkaline phosphatase activity. This finding underscores the importance of considering N input form to boost soil fertility and promote sustainable agriculture.
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    Initialization-similarity clustering algorithm
    (Springer Science+Business Media, LLC, 2019-12) Liu T; Zhu J; Zhou J; Zhu Y; Zhu X
    Classic k-means clustering algorithm randomly selects centroids for initialization to possibly output unstable clustering results. Moreover, random initialization makes the clustering result hard to reproduce. Spectral clustering algorithm is a two-step strategy, which first generates a similarity matrix and then conducts eigenvalue decomposition on the Laplacian matrix of the similarity matrix to obtain the spectral representation. However, the goal of the first step in the spectral clustering algorithm does not guarantee the best clustering result. To address the above issues, this paper proposes an Initialization-Similarity (IS) algorithm which learns the similarity matrix and the new representation in a unified way and fixes initialization using the sum-of-norms regularization to make the clustering more robust. The experimental results on ten real-world benchmark datasets demonstrate that our IS clustering algorithm outperforms the comparison clustering algorithms in terms of three evaluation metrics for clustering algorithm including accuracy (ACC), normalized mutual information (NMI), and Purity.
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    Joint Spectral Clustering based on Optimal Graph and Feature Selection
    (Springer Nature Switzerland AG, 2021-02) Zhu J; Jang-Jaccard J; Liu T; Zhou J
    Redundant features and outliers (noise) included in the data points for a machine learning clustering model heavily influences the discovery of more distinguished features for clustering. To solve this issue, we propose a spectral new clustering method to consider the feature selection with the L2 , 1-norm regularization as well as simultaneously learns orthogonal representations for each sample to preserve the local structures of data points. Our model also solves the issue of out-of-sample, where the training process does not output an explicit model to predict unseen data points, along with providing an efficient optimization method for the proposed objective function. Experimental results showed that our method on twelve data sets achieves the best performance compared with other similar models.
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    Weighted adjacent matrix for K-means clustering
    (Springer Science+Business Media, LLC, 2019-12) Zhou J; Liu T; Zhu J
    K-means clustering is one of the most popular clustering algorithms and has been embedded in other clustering algorithms, e.g. the last step of spectral clustering. In this paper, we propose two techniques to improve previous k-means clustering algorithm by designing two different adjacent matrices. Extensive experiments on public UCI datasets showed the clustering results of our proposed algorithms significantly outperform three classical clustering algorithms in terms of different evaluation metrics.