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"Ahmad"
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Islamic law : cases, authorities and worldview
\"Introducing undergraduate students to Islamic law, this accessible textbook does not presume legal or technical knowledge. Drawing on a comparative approach, it encourages students to think through the issues of the application of Islamic law in majoritarian and minority Islamic legal contexts, including the USA, Saudia Arabia, Egypt and Malaysia. The book surveys the historical development as well as the contemporary contexts of Islamic law. In distilling the history of Islamic law for non-specialists, the author covers important topics such as the development and transformation of Islamic Institutions during and following colonialism. Coverage of Islamic law across contemporary contexts draws on real case material, and allows for discussion of Islam as a legal as well as ethical and moral code that is activated both inside and outside the court. Shariʻa (an Arabic word that simply means water-source or 'law') is explained, and the book also covers the two sources of 'authority' of Islamic Law, the Qurʼan, and the State. Readers will learn about rituals, dietary restrictions, family, contracts and property, lawful and unlawful gain, criminal law and punishments, and what makes a government legitimate in the eyes of Muslim individuals and authorities. \"-- Provided by publisher.
Book
Dielectric relaxation, XPS and structural studies of polyethylene oxide/iodine complex composite films
Polyethylene oxide (PEO) complexed with molecular iodine (
I
2
) forming PEO/
I
2
complex composites stand‐free films were investigated using dielectric relaxation, X-ray photoelectron spectroscopy (XPS), UV–Vis spectrophotometry, structural and morphological techniques. Scanning electron microscopy was used to monitor the variation in the surface morphology and the related roughness. 2D Energy-dispersive X-ray spectroscopy (EDX) measurements enabled to observe the distribution of iodine on the film surface. High resolution XPS measurements were used to define the iodine anion types and the metallic iodine existence, as well as the relevant concentrations based on the binding energies. The dielectric relaxation measurements were carried out over the frequency range from 0.1 to 10
7
Hz and temperature range from 155 to 330 K. Dielectric loss (ε′′) curves were fitted to the Havriliak–Negami (HN) model for one and/or two relaxation peaks (α and β), with and without the electrical conductivity contribution term, in order to deduce the relaxation time (τ) and the dielectric strengths (Δ
ε
), in addition to the electrical conductivities (
σ
). The temperature-dependent data of β- and σ- relaxations follow the law of Arrhenius thermal activation indicating the presence of typical glass-forming polymers. Δ
ε
of α-relaxation obeys the curvature pattern of Vogel-Tammann-Fulcher (VTF) thermal activation law. The electrical conductivity of the system increases 6000 folds by doping PEO with 5 wt% of iodine at the same temperature (293 K).
Journal Article
Review on Methylene Blue: Its Properties, Uses, Toxicity and Photodegradation
The unavailability of clean drinking water is one of the significant health issues in modern times. Industrial dyes are one of the dominant chemicals that make water unfit for drinking. Among these dyes, methylene blue (MB) is toxic, carcinogenic, and non-biodegradable and can cause a severe threat to human health and environmental safety. It is usually released in natural water sources, which becomes a health threat to human beings and living organisms. Hence, there is a need to develop an environmentally friendly, efficient technology for removing MB from wastewater. Photodegradation is an advanced oxidation process widely used for MB removal. It has the advantages of complete mineralization of dye into simple and nontoxic species with the potential to decrease the processing cost. This review provides a tutorial basis for the readers working in the dye degradation research area. We not only covered the basic principles of the process but also provided a wide range of previously published work on advanced photocatalytic systems (single-component and multi-component photocatalysts). Our study has focused on critical parameters that can affect the photodegradation rate of MB, such as photocatalyst type and loading, irradiation reaction time, pH of reaction media, initial concentration of dye, radical scavengers and oxidising agents. The photodegradation mechanism, reaction pathways, intermediate products, and final products of MB are also summarized. An overview of the future perspectives to utilize MB at an industrial scale is also provided. This paper identifies strategies for the development of effective MB photodegradation systems.
Journal Article
Machine Learning and Big Data - Concepts, Algorithms, Tools and Applications
Currently many different application areas for Big Data (BD) and Machine Learning (ML) are being explored. These promising application areas for BD/ML are the social sites, search engines, multimedia sharing sites, various stock exchange sites, online gaming, online survey sites and various news sites, and so on. To date, various use-cases for this application area are being researched and developed. Software applications are already being published and used in various settings from education and training to discover useful hidden patterns and other information like customer choices and market trends that can help organizations make more informed and customer-oriented business decisions. Combining BD with ML will provide powerful, largely unexplored application areas that will revolutionize practice in Videos Surveillance, Social Media Services, Email Spam and Malware Filtering, Online Fraud Detection, and so on. It is very important to continuously monitor and understand these effects from safety and societal point of view.
eBook
The influence of UV-visible light, microwave radiation, argon laser, and heating and aging processes on silicone oil utilized as intravitreal implants: Experimental exposure with clinical correlation
The emulsification of silicone oil (SO) remains poorly understood. In the present study, we investigated the physical properties of unused pharmaceutical SO samples under various conditions. Moreover, clinical correlations with the patients' SO samples were assessed.
Unused pharmaceutical ophthalmic SO samples and four explanted SO samples from previously vitrectomized patients with rhegmatogenous retinal detachment were analyzed. To assess the stability of SO, the samples were exposed to UV light, visible light, a green argon laser, microwave radiation, heat, and were aged. Following exposure, the samples were investigated using Fourier-transform infrared spectroscopy, optical transmittance and absorbance, and micro-viscometry measurements. Two patients underwent argon laser retinopexy while SO tamponaded the vitreous cavity postoperatively.
The physical properties of SO exposed to heat, UV light, microwave radiation, and aging did not change. However, SO irradiated by the green argon laser demonstrated a significant breakdown of atomic bonding and a transmittance loss. These results are consistent with the analyses of SO samples provided by patients. In those who underwent laser retinopexy, the SO exhibited clinical emulsification necessitating earlier removal, which was confirmed by physical tests.
It may be postulated that patients exposed to the argon laser experienced more emulsification than the other two groups, leading to the earlier removal of the SO implants from the eyes. This investigation did not consider the biological effects of inflammatory biomarkers; however, it may provide valuable insights for optimizing the use of SO in ophthalmic surgery and other potential applications.
Journal Article
Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils
The integration of Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs), has transformed predictive modeling in structural and durability engineering. This study investigates the use of ANN-based approaches to predict the corrosion rates of mild steel reinforcement embedded in cementitious composites subjected to clay-dominated soil environments. Key environmental parameters, sodium chloride (NaCl) content (0-4%), inhibitor dosage (DOI) (0-5%), and exposure duration (30-180 days), were selected as input variables. Two ANN architectures, Feedforward Backpropagation (FFBP) and Cascadeforward Backpropagation (CFBP), were developed and trained using 72 experimental data points extracted from the literature. The FFBP model outperformed CFBP in terms of predictive accuracy, achieving a correlation coefficient (R) of 0.998, a mean absolute percentage error (MAPE) of 30.43%, and a root mean square error (RMSE) of 0.071 during testing. Sensitivity analysis revealed that inhibitor dosage had the most significant influence on corrosion behavior, followed by NaCl concentration and exposure duration. The findings confirm that ANN models can effectively capture the nonlinear interactions governing corrosion progression, even under complex environmental conditions associated with clayey soils. This research provides a reliable and practical AI-driven framework for assessing corrosion risk, guiding material design, and enhancing long-term infrastructure durability in aggressive subsurface conditions. The study underscores the growing relevance of machine learning in simulating time-dependent deterioration processes in geotechnical and structural materials.
Journal Article