Usha Martin (India)

Based on the methods discussed, a framework for integrating blockchain technology into networking protocols was created in this study. Some of the difficulties that conventional networking protocols face when integrating blockchain technology into communication networks are covered in this paper. This paper also provides case studies and examples to provide a clearer picture of how blockchain technology might be utilised to enhance security, privacy, and decentralisation in networking protocols. Based on the open and unchangeable nature of blockchain technology, this article offered suggestions for communication networks to achieve higher levels of integrity and trust while lowering any dangers related to centralised control and single points of failure. Furthermore, the study looks at advanced security feature which is SHA-256 cryptographic hashing to show how blockchain can maintain data integrity and guard against malicious attacks.

Abstract: Niosomes (Niosomes), as Non-Ionic Surfactant (NIOs)-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 NIOs in the formulation of Niosomes, emphasizing their influence on clinical efficacy, pharma-cokinetics, and targeted drug delivery. It also explores the emerging patent landscape and transla-tional potential of Niosomes 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 20202025 onwards. The relevant studies, clinical trials, and granted patents involving Niosomes formulations with NIOs were systematically analyzed for their for-mulation design, therapeutic outcomes, and disease-specific applications. The study showed a no-table rise in research and patents on Niosomes drug delivery using NIOs 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 tar-geting. The recent patents highlight advances in combination therapies, responsive systems, and ligand-based targeting, reflecting a trend toward personalized medicine. NIOs play a critical role in modulating the performance of Niosomes 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 NIO-based Niosomes formulations toward clinical use.

The measurement of ECG-derived heart rate variability (HRV) provides early diagnosis and prevention of cardiac events such as coronary artery disease (CAD) and myocardial infarction (MI). The disease severity causes ECG shape deformation, leading to difficulty in R-wave detection required for heart rate variability (HRV) analysis. Therefore, the study aimed to optimize R-wave threshold filters at 50%, 60%, 70%, and 80% within the framework of HRV analysis for better diagnosis of MI and CAD. Lead-II ECG was recorded from CAD (n=15), MI (n=15), and Control (n=10) group participants using an MP45 amplifier (Biopac Systems Inc., USA). The ECG morphologic features were extracted to analyze the change in R-wave amplitude. The R-R interval time series was extracted at different threshold filters (50%, 60%, 70%, and 80%) and used for heart rate variability (HRV) analysis. The HRV features extracted using Kubios V2.0 in time, frequency, and nonlinear domains at different threshold filters were compared. The obtained findings revealed that R-wave amplitude was suppressed under the CAD and MI groups in comparison to the control subjects. The observed results also suggested 70% threshold filters for optimum detection of R-wave under CAD and MI. Further, the time and frequency domains presented the best result in comparison to the nonlinear HRV domain. The present study suggested that HRV analysis may be made more predictive for various cardiac diseases by optimizing R-wave threshold filters.

The extensive use of smokeless tobacco and the worldwide occurrence of diabetes mellitus (DM) poses significant public health obstacles. A comprehensive review of the literature was undertaken to assess epidemiological research, clinical trials, and meta-analyses that examine the link between smokeless tobacco use and DM. The key results indicate that the biological constituents of smokeless tobacco may interfere with the process of glucose metabolism and lead to an increase in insulin resistance. An association between consumption levels and diabetes risk is evident, with higher levels of usage being positively correlated with an increased chance of developing diabetes. Smokeless tobacco usage is identified as a significant risk factor for DM. This highlights the need to implement focused public health initiatives and policies aimed at decreasing the usage of smokeless tobacco and its influence on the incidence of diabetes. Future research should prioritize elucidating the processes behind this correlation and developing efficacious preventative methods to mitigate the worldwide burden of diabetes.

This research focuses on utilizing deep learning and natural language processing (NLP) to design an AI-powered chatbot for emotional support. The primary objective is to establish a supportive platform for individuals dealing with emotional challenges. By leveraging NLP, the chatbot will identify and interpret users’ emotional states, generating tailored and empathetic responses. Deep learning techniques will enable the system to learn from past interactions, adapting its responses to meet the unique needs of each user. The platform aims to deliver personalized, scalable support while incorporating features like sharing uplifting content, such as cute cat images. This study emphasizes the potential of AI-driven solutions in enhancing mental well-being through empathetic and meaningful interactions.

The National Education Policy (NEP) 2020 introduces transformative reforms aimed at fostering inclusive education in India, ensuring that every child, regardless of background, receives equitable access to quality education. This policy emphasizes providing support for socio-economically disadvantaged groups (SEDGs), including girls, children with disabilities, and marginalized communities. “NEP 2020 seeks to overhaul the traditional educational framework by promoting multilingual education, enhancing early childhood care and education (ECCE), and integrating technology to bridge educational gaps. Additionally, teacher training is prioritized to equip educators with the skills needed to create inclusive classrooms. However, despite these promising provisions, several challenges exist in the implementation, such as inadequate infrastructure, limited teacher training, and the digital divide. The policy highlights the importance of community involvement and collaboration with various stakeholders to achieve true inclusivity. This paper explores the key policies of NEP 2020 for inclusive education, the challenges of implementation, and strategies to overcome these barriers, ultimately evaluating the potential of NEP 2020 to transform India’s educational landscape into one that embraces diversity and inclusivity. The study also compares successful case studies and international best practices to provide a comprehensive understanding of how inclusive education can be effectively realized in India under the framework of NEP 2020.