A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

Bio-binders are increasingly gaining attention in the pavement community as sustainable alternatives to conventional petroleum-derived asphalt binders. While complete replacement of asphalt binder remains challenging, growing environmental concerns and energy crises demand at least partial substitution with renewable and eco-friendly materials. In this context, this study explores the use of pomegranate molasses (PM), a natural bio-based product, as a novel asphalt binder modifier. A comprehensive experimental program was conducted to evaluate the chemical, thermal, rheological, and mechanical effects of PM incorporation at three dosages (10%, 20%, and 30% by weight of asphalt binder) compared with a reference binder (RB). Fourier Transform

This work involved the successful synthesis of three new Schiff base complexes, including Ni(II), Mn(II), and Cu(II) complexes. The Schiff base ligand was created by reacting the malonyldihydrazide molecule with naphthaldehyde, and the final step involved reacting the ligand with the corresponding metallic chloride yielding pure target complexes. FTIR, 1 H NMR, 13 C NMR, mass, and UV/Vis spectroscopies were used to comprehensively characterize the produced complexes. These substances have been employed in this study to photo-stabilize polystyrene (PS) and lessen the photo-degradation of its polymeric chains. Several methods, including FTIR, weight loss, viscosity average molecular weight, light and atomic force microscopy, and energy disper

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.