Awadhesh Pratap Singh University is a public university in Rewa city, Madhya Pradesh. The university was named after Captain Awadhesh Pratap Singh, a politician and an activist. It is a teaching-cum-affiliating institution with its jurisdiction over 65 colleges in the districts of Rewa, Satna, Sidhi, Shahdol, Umariya and Singrauli besides 21 Sanskrit colleges and 85 Sanskrit schools spread all over Madhya Pradesh.Awadhesh Pratap Singh University is a non-profit public higher education institution located in the urban setting of the small city of Rewa (population range of 2,50,000-3,00,000 inhabitants), Madhya Pradesh. Officially recognized by the University Grants Commission of India, Awadhesh Pratap Singh University (APSU) is a co-educational Indian higher education institution. Awadhesh Pratap Singh University (APSU) offers courses and programs leading to officially recognized higher education degrees such as bachelor degrees, master degrees in several areas of study.APSU also provides several academic and non-academic facilities and services to students including a library, online courses and distance learning opportunities, as well as administrative services.
Plant-derived essential oils are attractive corrosion inhibitors due to their low cost, availability,::::and eco-friendliness. In this work, essential oil of Zingiber mioga (ZM), obtained by hydro-distillation, was studied as a green inhibitor for mild steel in 1 M HCl. The oil was characterized by FTIR and GC–MS, while its inhibition performance was evaluated by gravimetric studies and electrochemical techniques (EIS and PDP). Surface morphology was examined using SEM, SEM–EDS, and FTIR, and density functional theory (DFT) was applied to assess the reactivity of key phytochemicals. Results revealed that inhibition efficiency increased with concentration and reached a maximum at 5 g/L (93
Niosomes (NIOs), as non-ionic surfactant based vesicles, have emerged as versatile nanocarriers in the targeted delivery of drugs due to their biocompatibility, chemical stability, and ability to encapsulate both hydrophilic and lipophilic drugs. Their utility has gained significant traction in addressing challenges associated with conventional therapies, for chronic and resistant diseases, Tuberculosis (TB), and cancer. This review critically evaluates the role of non-ionic surfactant in the formulation of NIOs, emphasizing their influence on clinical efficacy, pharmacokinetics, and targeted drug delivery. It also explores the emerging patent landscape and translational potential of NIOs systems in TB and oncology. A comprehensive literature and patent database search was conducted using PubMed, Google Scholar, ScienceDirect, Scopus, Elsevier, SpringerLink, and ClinicalTrials.gov, as well as Google Patents, USPTO, and WIPO, covering publications and patents from 2020-2025 onwards. The relevant studies, clinical trials, and granted patents involving NIOs formulations with non-ionic surfactant were systematically analyzed for their formulation design, therapeutic outcomes, and disease-specific applications. The study showed a notable rise in research and patents on NIOs drug delivery using non-ionic surfactant categories. In TB, these systems enhanced Bioavailability (BA), sustained drug release, and targeted macrophages. In cancer therapy, they enabled controlled release, minimized side effects, and improved tumor targeting. The recent patents highlight advances in combination therapies, responsive systems, and ligand-based targeting, reflecting a trend toward personalized medicine. Non-ionic surfactant play a critical role in modulating the performance of NIOs drug carriers. Their strategic application in TB and oncology represents a promising avenue for improving therapeutic outcomes. Continued research and innovation in this field, as reflected by patent trends, highlight the translational potential of non-ionic surfactant-based NIOs formulations toward clinical use.
Nagod State, a former princely state situated in the modern Satna district of Madhya Pradesh, possesses a remarkably rich historical and archaeological legacy. Despite its modest territorial extent, the state contains a rich assemblage of monuments spanning ancient Buddhist civilization, Gupta-era art and architecture, medieval Rajput statecraft, and the colonial era. The historical sites of Nagod State—most notably Nagod Fort, Unchehara, Naro Fort, Bharhut, Bhumara, Khoh, Pataini Devi, Lal Pahar, Shankargarh, and Kotara—collectively depict over two millennia of dynamic cultural evolution. This paper examines these key historical locations and evaluates their pivotal contributions to the political, religious, artistic, and archaeological landscape of Central India
PurposeThis study aims to examine the global research on information retrieval (IR) research from 2015 to 2024, focusing on research trends, institute and author collaboration, leading sources, keyword analysis and future research direction.Design/methodology/approachThis study uses the combined method of bibliometrics and topic modeling analysis. The bibliographic data were retrieved from the Scopus database. Analysis tools such as Biblioshiny (primary analysis), Word Cloud, VOSviewer (data visualization), LDAShiny and BERTopic (topic modeling) have been used. A structured keyword string used to collect the data from the database limited to selected bibliographic details. A total of 3,457 details are limited to the journals finally selected between 2025 and 2024 for thematic analysis and conceptual structure evaluations.FindingsThe inconsistent research growth found during the study period in IR is driven by technological advancements and changes in information dynamics. Bradford's law indicates 22 journals in Zone 1 (core) contributing 33% of publications, and author productivity is found similar to Lotka's law. The collaboration pattern indicates a limited global institutional collaboration. Keyword co-occurrence analysis indicates a total of four key clusters related to digital IR, teaching methodologies, technical frameworks and IR systems. The analysis of topic modeling using LDAShiny and BERTopic suggests future research must focus on cognitive science, multilingual retrieval, natural language processing, tailored search engines, semantic search, etc.Practical implicationsThis study examines the global research profile of IR using bibliometric and topic modeling analysis. Future implications include user-centered search, user behavior analysis, multimedia retrieval, big data processing, predictive analytics, semantic search, mobile access and context-aware retrieval.Originality/valueThis study uniquely identified research in IR using advanced analysis tools, offering valuable insights and methodology to conduct studies in different domains.
This study presents an automated approach for the early detection and diagnosis of COVID-19 using multimodal medical imaging, including chest X-ray and computed tomography scans. The proposed framework utilizes a hybrid deep learning architecture that combines convolutional neural networks for spatial feature extraction with transformer-based encoders to capture contextual information. A multimodal fusion module integrates features from both imaging modalities to improve diagnostic robustness and accuracy. The dataset consists of 12,000 chest X-ray images and 8,000 CT images, which are preprocessed using adaptive normalization and data augmentation techniques. Experimental results show that the proposed model achieves an accuracy of 98.7%, sensitivity of 97.9%, and specificity of 98.5%, outperforming existing methods. Additionally, Grad-CAM visualization enhances interpretability by highlighting clinically relevant regions, supporting reliable and efficient COVID-19 screening in healthcare environments.
