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"Hassan, H."
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The interplay between eWOM information and purchase intention on social media: Through the lens of IAM and TAM theory
The maturity and growth of social media have empowered online customers to generate electronic word of mouth (eWOM), on various online websites and platforms, which may influence an individual’s decision-making process. This paper explores eWOM information’s impact on social media users’ purchase intention by applying the information adoption model (IAM) and the technology acceptance model (TAM). PLS-SEM (SmartPLS V.3.3) has been utilized to test the hypotheses using data of 432 respondents. The research findings evinced that eWOM information quality, credibility, usefulness, and ease of use have been critical in determining online consumers’ intention to adopt eWOM and form purchase behavior on social media. The study’s outcomes offer the marketing managers a viewpoint to realize the significance of the effect of eWOM information on online purchase intention among social media users. Furthermore, the study findings will also enlighten marketing and business managers to utilize social media websites by gauging consumer behavior and focusing on characteristics of eWOM information on social media for better consumer insights.
Journal Article
Treasures of the earth : need, greed, and a sustainable future
Would the world be a better place if human societies were somehow able to curb their desires for material goods? Saleem Ali's pioneering book links human wants and needs by providing a natural history of consumption and materialism with scientific detail and humanistic nuance.
Book
Enhanced photocatalytic activity of green synthesized zinc oxide nanoparticles using low-cost plant extracts
Developing stable and highly efficient metal oxide photocatalysts remains a significant challenge in managing organic pollutants. In this study, zinc oxide nanoparticles (ZnO NPs) were successfully synthesized using various plant extracts, pomegranate (P.M), beetroot roots (B.S), and seder, along with a chemical process. The produced ZnO NPs were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), ultraviolet–visible spectroscopy (UV–Vis), Field Emission Scanning Electron Microscope (FESEM), High-Resolution Transmission Electron Microscopy (HRTEM), and Surface Area. For all prepared samples, the results indicated that the composition of the plant extract affects several characteristics of the produced particles, such as their photocatalytic properties, energy bandgap (E
g
), particle size, and the ratio of the two intensity (0 0 2) and (1 0 0) crystalline planes. The particle size of the produced NPs varies between 20 and 30 nm. To examine NPs' photocatalytic activity in the presence of UV light, Methyl Orange (MO) was utilized. The E
g
of ZnO synthesized by the chemical method was 3.16 e. V, whereas it was 2.84, 2.63, and 2.59 for P.M, Seder, and B.S extracts, respectively. The most effective ZnO NPs, synthesized using Beetroots, exhibited a degradation efficiency of 87 ± 0.5% with a kinetic rate constant of 0.007 min
−1
. The ratio of the two intensity (0 0 2) and (1 0 0) crystalline planes was also examined to determine a specific orientation in (0 0 2) that is linked to the production of oxygen vacancies in ZnO, which enhances their photocatalytic efficiency. Furthermore, the increase in photocatalytic effectiveness can be attributed to the improved light absorption by the inter-band gap states and effective charge transfer.
Journal Article
Corrosion Inhibition Using Harmal Leaf Extract as an Eco-Friendly Corrosion Inhibitor
Extract of natural plants is one of the most important metallic corrosion inhibitors. They are readily available, nontoxic, environmentally friendly, biodegradable, highly efficient, and renewable. The present project focuses on the corrosion inhibition effects of Peganum Harmala leaf extract. The equivalent circuit with two time constants with film and charge transfer components gave the best fitting of impedance data. Extraction of active species by sonication proved to be an effective new method to extract the inhibitors. High percent inhibition efficacy IE% of 98% for 283.4 ppm solutions was attained using impedance spectroscopy EIS measurements. The values of charge transfer Rct increases while the double layer capacitance Cdl values decrease with increasing Harmal extract concentration. This indicates the formation of protective film. The polarization curves show that the Harmal extract acts as a cathodic-type inhibitor. It is found that the adsorption of Harmal molecules onto the steel surface followed Langmuir isotherm. Fourier-transform infrared spectroscopy FTIR was used to determine the electron-rich functional groups in Harmal extract, which contribute to corrosion inhibition effect. Scanning electron microscopy SEM measurement of a steel surface clearly proves the anticorrosion effect of Harmal leaves.
Journal Article
Climate change and energy dynamics in the Middle East : modeling and simulation-based solutions
This edited volume presents chapters on the dynamics of global climate change and global warming in the Middle East. In this region, it should be noted that even slightly warmer weather can result in an increased demand of energy along with its lower supply, as well as lower labor productivity. This text focuses on modeling, simulation, system dynamics, and agent-based modeling in dealing with these issues. The latest decision making tools, techniques, and innovative solutions used to overcome these challenges are presented. Many distinguished researchers contribute their work herein. The audience for this volume includes policy makers, researchers, and students unified by the common goal of making better decisions in the sustainable production and consumption of energy. The practical orientation of the chapters within each part is intended to suit the practitioners: managers and decision makers in the energy sector of the Middle East region.
Book
Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy
Neurodegenerative diseases (NDDs), including Alzheimer’s disease (AD) and Parkinson’s disease (PD), are a growing global health concern, especially among the elderly, posing significant challenges to well-being and survival. GSK3β, a serine/threonine kinase, is a key molecular player in the pathogenesis of NDDs. Dysregulated activity of GSK3β has been linked to neurodegenerative complications. Targeting GSK3β with active-site-specific inhibitors presents a promising therapeutic strategy for mitigating its pathological effects and potentially intercepting NDD progression. This study aimed to identify potential GSK3β inhibitors through an integrated in silico approach combining machine learning (ML)-based virtual screening, molecular docking, molecular dynamics (MD) simulations, and MM/GBSA binding free energy calculations. ML models were trained using known GSK3β inhibitors from BindingDB. Among all models, the Random Forest (RF) algorithm had the best prediction accuracy, with a value of 0.6832 on the test set and 0.7432 on the training set, and was employed to screen the target library of 11,032 phytochemicals. The ML-based screening identified 2,898 compounds with potential inhibitory action against GSK3β. Further screening based on Lipinski’s Rule of Five gave 221 drug-like candidates. These compounds were further evaluated for GSK3β interaction via molecular docking. The analyses found ZINC136900288, ZINC7267, and ZINC519549 bind strongly and interact well with key residues in GSK3β active site with their binding scores being − 9.9, -8.8, and − 8.7 kcal/mol, respectively. MD simulations were conducted for both ligand-bound and apo GSK3β to assess structural stability. The simulation results showed that the ligand bound complexes were structurally stable with less fluctuations and higher conformational stability. In addition, (MM/GBSA) binding free energy calculations were carried out to quantify the affinity of the candidate compounds, and the candidate compound ZINC136900288 has the strongest binding affinity (-24.86 kcal/mol) of the three. Notably, these identified compounds feature novel chemical scaffolds that are structurally distinct from previously reported GSK3β inhibitors, emphasizing the originality and therapeutic potential of this study. These results show that ZINC136900288 may serve as suitable GSK3β inhibitors. Nevertheless, the efficacy and safety of these compounds need to be further validated experimentally and further studied in vivo for possible therapeutic application in NDDs.
Journal Article
Recent Advances in Enzymatic and Non-Enzymatic Electrochemical Glucose Sensing
The detection of glucose is crucial in the management of diabetes and other medical conditions but also crucial in a wide range of industries such as food and beverages. The development of glucose sensors in the past century has allowed diabetic patients to effectively manage their disease and has saved lives. First-generation glucose sensors have considerable limitations in sensitivity and selectivity which has spurred the development of more advanced approaches for both the medical and industrial sectors. The wide range of application areas has resulted in a range of materials and fabrication techniques to produce novel glucose sensors that have higher sensitivity and selectivity, lower cost, and are simpler to use. A major focus has been on the development of enzymatic electrochemical sensors, typically using glucose oxidase. However, non-enzymatic approaches using direct electrochemistry of glucose on noble metals are now a viable approach in glucose biosensor design. This review discusses the mechanisms of electrochemical glucose sensing with a focus on the different generations of enzymatic-based sensors, their recent advances, and provides an overview of the next generation of non-enzymatic sensors. Advancements in manufacturing techniques and materials are key in propelling the field of glucose sensing, however, significant limitations remain which are highlighted in this review and requires addressing to obtain a more stable, sensitive, selective, cost efficient, and real-time glucose sensor.
Journal Article