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  1. Article: Detection of Environmentally Harmful Malathion Pesticides Using a Bimetallic Oxide of CuO Nanoparticles Dispersed over a 3D ZnO Nanoflower.

    Gurusamy, Lakshmanan / Cheng, Ru-Wen / Anandan, Sambandam / Liu, Cheng-Hua / Wu, Jerry J

    Materials (Basel, Switzerland)

    2023  Volume 16, Issue 22

    Abstract: Super-sensitive malathion detection was achieved using a nonenzymatic electrochemical sensor based on a CuO/ZnO-modified glassy carbon electrode (GCE). Due to the high affinity between the Cu element and the sulfur groups in malathion, the developed CuO- ... ...

    Abstract Super-sensitive malathion detection was achieved using a nonenzymatic electrochemical sensor based on a CuO/ZnO-modified glassy carbon electrode (GCE). Due to the high affinity between the Cu element and the sulfur groups in malathion, the developed CuO-ZnO/GCE sensor may bond malathion with ease, inhibiting the redox signal of the Cu element when malathion is present. In addition to significantly increasing the ability of electron transfer, the addition of 3D-flower-like ZnO enhances active sites of the sensor interface for the high affinity of malathion, giving the CuO-ZnO/GCE composite an exceptional level of sensitivity and selectivity. This enzyme-free CuO-ZnO/GCE malathion sensor demonstrates outstanding stability and excellent detection performance under optimal operating conditions with a wide linear range of malathion from 0 to 200 nM and a low detection limit of 1.367 nM. A promising alternative technique for organophosphorus pesticide (OP) determination is offered by the analytical performance of the proposed sensor, and this method can be quickly and sensitively applied to samples that have been contaminated with these pesticides.
    Language English
    Publishing date 2023-11-07
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2487261-1
    ISSN 1996-1944
    ISSN 1996-1944
    DOI 10.3390/ma16227065
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: The Analysis on Similarity of Spectrum Analysis of Landslide and Bareland through Hyper-Spectrum Image Bands

    Wan, Shiuan / Cheng, Ru Wen / Lei, Tsu Chiang / Ma, Hong Lin

    Water. 2019 Nov. 17, v. 11, no. 11

    2019  

    Abstract: Landslides of Taiwan occur frequently in high mountain areas. Soil disturbance causes by the earthquake and heavy rainfall of the typhoon seasons often produced the earth and rock to landslide in the upper reaches of the catchment area. Therefore, the ... ...

    Abstract Landslides of Taiwan occur frequently in high mountain areas. Soil disturbance causes by the earthquake and heavy rainfall of the typhoon seasons often produced the earth and rock to landslide in the upper reaches of the catchment area. Therefore, the landslide near the hillside has an influence on the catchment area. The hyperspectral images are effectively used to monitor the landslide area with the spectral analysis. However, it is rarely studied how to interpret it in the image of the landslide. If there are no elevation data on the slope disaster, it is quite difficult to identify the landslide zone and the bareland area. More specifically, this study used a series of spectrum analysis to identify the difference between them. Therefore, this study conducted a spectrum analysis for the classification of the landslide, bareland, and vegetation area in the mountain area of NanXi District, Tainan City. On the other hand, this study used the following parallel study on Support Vector Machine (SVM) for error matrix and thematic map for comparison. The study simultaneously compared the differences between them. The spectral similarity analysis reaches 85% for testing data, and the SVM approach has 98.3%.
    Keywords landslides ; support vector machines ; thematic maps
    Language English
    Dates of publication 2019-1117
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2521238-2
    ISSN 2073-4441
    ISSN 2073-4441
    DOI 10.3390/w11112414
    Database NAL-Catalogue (AGRICOLA)

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