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  1. Ratnasari A, Syafiuddin A, Boopathy R, Malik S, Aamer Mehmood M, Amalia R, et al.
    Bioresour Technol, 2022 Jan;344(Pt B):126239.
    PMID: 34737137 DOI: 10.1016/j.biortech.2021.126239
    The palm oil mill effluent (POME) from palm milling oil activities is discharged into various water bodies which poses several environmental problems including turbidity, increases COD and BOD, adds oil and grease, increases total nitrogen, and other pollutants. Therefore, it requires effective treatment to remove the pollutants before disposal. The objective was to critically discuss the performance of POME pretreatments along with their limitations. To offer a coverage on the present less efficient technologies, the opportunities and challenges of advanced pretreatments that combine magnetic materials and natural composites as adsorbents are comprehensively reviewed here. Moreover, potential of various magnetic materials for POME pretreatment has been described. Several existing pretreatment methods such as physical pretreatments, chemical pretreatments, coagulation-flocculation, and adsorption can remove pollutant content from POME with certain limitations and the use of magnetic composite adsorbents can enhance the treatment efficiency.
  2. Masood F, Nor NBM, Nallagownden P, Elamvazuthi I, Alam MA, Yusuf M, et al.
    Data Brief, 2021 Dec;39:107630.
    PMID: 34988268 DOI: 10.1016/j.dib.2021.107630
    The combined effect of design control factors on the response variables gives valuable information for geometric design optimization of the compound parabolic concentrator. This study presents the data related to the statistical modeling and analysis of variance for aperture width and height of a low concentration symmetric compound parabolic concentrator designed for photovoltaic applications. The design matrix was generated using the response surface modeling approach. The geometric design equations of the proposed concentrator were developed and solved analytically using MATLAB. The empirical models were developed to establish relationships between the control factors and response variables of the proposed system. The analysis of variance was conducted for two significant response variables. The developed statistical models can be used to predict the selected response variables within the permissible range. The presented data can be used for statistical modeling and design optimization of the two-dimensional symmetric compound parabolic concentrator.
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