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    AICpred: Machine Learning-Based Prediction of Potential Anti-Inflammatory Compounds Targeting TLR4-MyD88 Binding Mechanism by Lucindah N. Fry-Nartey, Cyril Akafia, Ursula S. Nkonu, Spencer B. Baiden, Ignatus Nunana Dorvi, Kwasi Agyenkwa-Mawuli, Odame Agyapong, Claude Fiifi Hayford, Michael D. Wilson, Whelton A. Miller, Samuel K. Kwofie

    Published 2025-01-01
    “…Predictive models were trained using random forest, adaptive boosting (AdaBoost), eXtreme gradient boosting (XGBoost), k-nearest neighbours (KNN), and decision tree models. …”
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    Towards Better Perovskite Absorber Materials: Cu+ Doping Improves Photostability and Radiation Hardness of Complex Lead Halides by Marina I. Ustinova, Maxim N. Sarychev, Nikita A. Emelianov, Yiqun Li, Yuling Zhuo, Tongjun Zheng, Sergey D. Babenko, Evgeniy D. Tarasov, Pavel P. Kushch, Nadezhda N. Dremova, Galina A. Kichigina, Alexandra V. Rasmetyeva, Andrey I. Kukharenko, Dmitry P. Kiryukhin, Ernst Z. Kurmaev, Xueqing Xu, Pavel A. Troshin, Lyubov A. Frolova, Ivan S. Zhidkov

    Published 2025-01-01
    “…The discovered possibility of controlling the electronic properties and major materials degradation pathways through minor modification of their chemical composition (e.g., replacing 1% of Pb2+ with Cu+) opens up tremendous opportunities for engineering new perovskite absorber compositions with significantly improved properties for both terrestrial and aerospace applications.…”
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    Serum IL-18 Is Increased at Early Postburn Period in Moderately Burned Patients

    Published 2006-01-01
    “…These three parameters were highly correlated with each other (<mml:math alttext="$r<0.9$"><mml:mrow><mml:mi>r</mml:mi><mml:mo>&#x003E;</mml:mo><mml:mn>0.9</mml:mn> </mml:mrow></mml:math> and <mml:math alttext="$P>.001$"><mml:mrow><mml:mi>P</mml:mi><mml:mo>&#x003C;</mml:mo><mml:mn>.001</mml:mn></mml:mrow></mml:math>). …”
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