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    A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity by Wesam S. Ahmed (10170053)

    Published 2024
    “…Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable <u>bioluminescence </u>activity of NLuc in living cells and in vitro. …”
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    Deep random vector functional link transformer network with multiple output layers for significant wave height forecasting by Aryan Bhambu (18767731)

    Published 2025
    “…This paper introduces a novel random vector functional link transformer (RFT) and ensemble deep random vector functional link transformer (edRFT) networks to capture the dynamic characteristics of significant wave heights. The model employs hidden blocks based on transformer encoders to effectively capture complex sequential dependencies in the data. …”
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    The Impact of Inquiry-based Learning on the Critical Thinking of high School Students by AZZAM, LILIAN ABDELNASSER

    Published 2021
    “…Explanatory sequential mixed-methods approach was utilized in the current study in which the data are collected and analyzed quantitatively first, and then qualitative data were collected in order to fully explain the quantitative data results The current study found that inquiry-based learning approach has a statistically significant positive impact on the high school students’ critical thinking in where the independent T-test results were for t (90) = 7 with a P value equals to 0.000 ˂ 0.05. …”
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    The Anti-Tumor Agent Sodium Selenate Decreases Methylated PP2A, Increases GSK3βY216 Phosphorylation, Including Tau Disease Epitopes and Reduces Neuronal Excitability in SHSY-5Y Neu... by Wesal Habbab (17346961)

    Published 2019
    “…Somewhat surprisingly, the catalytically active form, methylated PP2A (mePP2A) was significantly decreased. In close correlation to these data, the phosphorylation state of two substrate proteins, sensitive to PP2A activity, GSK3β and Tau were found to be increased. …”
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    Development and Validation of the Motivation for Tutoring Questionnaire in Problem-Based Learning Programs by Salah Eldin, Kassab

    Published 2017
    “…PurposeThere are no published instruments, which measure tutor motivation for conducting small group tutorials in problem-based learning programs. Therefore, we aimed to develop a motivation for tutoring questionnaire in problem-based learning (MTQ-PBL) and evaluate its construct validity. …”
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    Remote Labs and Game-Based Learning for Process Control by Zaulkerman, Imran

    Published 2013
    “…This paper explores the use of game-based learning in the context of an undergraduate chemical engineering remote laboratory. …”
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    Investigating Educators’ Perceptions of the Impact of STEM Project-Based Learning on 21st Century Skills by AL-TIMANI, SANAA

    Published 2024
    “…This study investigates educators' perspectives on STEM Project-Based Learning (PBL) implementation and its effectiveness in fostering 21st century skills in private American schools in Ajman, UAE. …”
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    Students’ perceptions of Kahoot!: An exploratory mixed-method study in EFL undergraduate classrooms in the UAE by Alawadhi, Azza

    Published 2021
    “…, with the highest influence reported on increased motivation, improved classroom engagement, and enhanced learning experience. However, the effect on academic performance was not significant as perceived by Emirati students. …”
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    PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

    Published 2023
    “…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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    PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

    Published 2023
    “…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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