Itraconazole is an oral triazole antifungal medication used to treat superficial and systemic fungal infections in the mouth, throat, lungs, and nails. Certain brands may not be appropriate for treating nail infections. It may be prepared for topical and systemic use and is well-known for its antimycotic qualities. The goal of this review is to gather the national and international literature on itraconazole estimation in pharmaceutical formulations and bulk, with a focus on UV spectrophotometric and high performance liquid chromatography (HPLC) techniques, High performance thin layer chromatography (HPTLC), Gas chromatography (GC), Gas chromatography-Mass spectroscopy (GC-MS) and Liquid chromatography Mass Spectroscopy (LC-MS). For UV spectroscopy, the important parameters analyzed are λmax and solvent, and for HPLC and HPTLC, the stationary phase, mobile phase, retention period, and column specifications. Validation of an analytical method is a requirement to demonstrate that the method is suitable and appropriate for the intended use, often a prerequisite for analytical purposes. This paper reviews different analytical methods for the determination of itraconazole and its combinations in pharmaceutical drug. It also involves the validation of itraconazole and development of various analytical methods used for different dosage forms.
Red mud/bauxite residue is an industrial waste product of Bayer's process and because of its alkalinity poses a significant environmental problem. However, it is a potential source from which valuable metals such as iron, alumina, titanium, caustic soda, gallium and rare earth elements (REEs) especially scandium can be extracted. The aim of this article is to systematically review, research on metal and rare earth extraction from red mud from the year 2000 to 2024. Extraction methods by hydrometallurgy, pyrometallurgy and bioleaching have been reviewed in the paper. It is seen that in any extraction process, the different operational parameters, such as reagent concentrations, temperature and pH influence the extraction efficiency of metals and rare earths. The recovery challenges and limitations presented in this document highlights, above all, the underlying complexities. The paper also discusses the problems associated with the recovery processes, particularly because of the complex composition of the red mud.
Modern cyber-attacks grow tougher that motivates the need for advanced protection methods. A real-time attack detection system operates through analysis of SIP signals by implementing CNN-based approaches according to the concept. The automated traffic analysis of the system uses a detection mechanism which detects potential attacks with both precision and speed. The CNN model uses network analysis to generate threat-based protection better than traditional signature approaches that need manual rulemaking. A dynamic real-time streaming system operates within the system framework to process SIP signals in real-time. The proposed detection approach succeeds in security tests which establishes exceptional results while reducing false warning occurrences. The approach works through deep learning techniques that promote automatic real-time attack detection which functions with high efficiency.
In order to increase drivetrain fidelity and adaptability in MATLAB/Simulink environments, this research attempts to create a next-generation electric vehicle (EV) simulation framework that blends artificial intelligence (AI) with physics-based modeling. Neuro-adaptive machine learning algorithms were used in the design of a modular AI-Integrated Drivetrain Emulator (AIDE), which dynamically modifies torque, battery state-of-charge (SOC), and regenerative braking in response to driving patterns, terrain, and environmental conditions. AIDE is a reliable simulation tool for intelligent EV system design in both academic and industrial contexts. The suggested system showed a 22% improvement in drivetrain response accuracy and a 17% increase in energy efficiency when compared to traditional static models.1
With the outbreak of Corona pandemic throughout the world in the year 2020, the importance of online and virtual learning and teaching has increased manifold in connecting students to the teachers at all levels of education i.e. school and colleges. In the era of science and Technology and with the increasing usability of Internet online and virtual learning has become possible in a country like India with a huge population. But can traditionally teaching methods be wholly replaced by online and virtual means of teaching learning is a matter of concern in professional courses like engineering education. Over the past few years lots of research is going on to find the effectiveness of online and virtual learning in various courses. This paper is an attempt to give an overview of process of online and virtual learning in engineering education, its resources, their advantages and disadvantages in engineering education.
