Publications by authors named "A S Kareem"
Precise estimation of rock petrophysical parameters are seriously important for the reliable computation of hydrocarbon in place in the underground formations. Therefore, accurately estimation rock saturation exponent is necessary in this regard. In this communication, we aim to develop intelligent data-driven models of decision tree, random forest, ensemble learning, adaptive boosting, support vector machine and multilayer perceptron artificial neural network to predict rock saturation exponent parameter in terms of rock absolute permeability, porosity, resistivity index, true resistivity, and water saturation based on acquired 1041 field data.
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- The study examines the effectiveness of various nanocages (C, Ge, AlP, Ni-C, Ni-Ge, Cr-C, and Cr-AlP) in delivering the anticancer drugs flutamide and cyclophosphamide, factoring in adsorption parameters and recovery times.
- Results indicate that Ni-Ge and Cr-AlP nanocages show superior drug delivery capacity, with significantly lower recovery times compared to other nanostructures previously studied.
- The research employs advanced computational methods to optimize the nanocage structures and calculate thermodynamic parameters, revealing enhanced capabilities due to the incorporation of Ni and Cr atoms.
This study comprehensively investigates the stress distribution and aging effects in Ethylene Propylene Diene Monomer (EPDM) and Liquid Silicone Rubber (LSR) gasket materials through a novel integration of hyperelastic modeling and advanced machine learning techniques. By employing the Mooney-Rivlin, Ogden, and Yeoh hyperelastic models, we evaluated the mechanical behavior of EPDM and LSR under conditions of no aging, heat aging, and combined heat- and sulfuric-acid exposure. Each model revealed distinct sensitivities to stress distribution and material deformation, with peak von Mises stress values indicating that LSR experiences higher internal stress than EPDM across all conditions.
View Article and Find Full Text PDFlncRNAs'p potential roles in the pathogenesis of cancer via interacting with signaling pathways; special focus on lncRNA-mediated signaling dysregulation in lung cancer.
Med Oncol
November 2024
Article Synopsis
- Lung cancer is a highly lethal disease with a significant rate of occurrence and mortality, primarily due to its ability to metastasize, leading to treatment challenges and poor outcomes.
- Current treatments involve chemotherapy and targeted therapies; however, resistance to these methods commonly develops in patients.
- Long non-coding RNAs (lncRNAs), which are important non-protein-coding RNA molecules, play a key role in cancer biology by regulating gene expression and influencing various cancer-related processes, making them potential targets for therapy and biomarkers in lung cancer.