Considered as the heart of electrical power transmission and distribution networks, power transformers are essential part of the electricity transmission grid. Among the condition monitoring and fault diagnosis tools for these machines, dissolved gas analysis (DGA) has proven its effectiveness in their early detection and classification of faults. Up to date, many methods have been proposed in the literature for the interpretation of DGA data, classified into traditional and intelligent methods. This paper proposes a two-steps hybrid method, which uses the strengths of both methods. The approach uses the evolutionary k-means clustering algorithm based on the genetic algorithm for subset formation and subset analysis by human expertise. In the diagnostic procedure, to determine the condition of a sample, the subset to which it belongs is first identified and then the corresponding diagnostic sub-model is applied. The proposed method has been implemented with 595 DGA data, tested on 254 DGA data and validated on the International Electrotechnical Commission (IEC) TC10 database. Their performances were evaluated and compared with existing traditional, intelligent and hybrid methods. From the results obtained with the IEC TC10 database, the newly proposed approach depicts the best overall diagnosis accuracies. Indeed, the best performance is achieved with the proposed method compared to other models in the literature, with diagnostic accuracy of 98.29% compared to 88.89% of the Gouda triangle method, to 88.03% of the Hyosun Corporation gas ratio method or to 86.32% of the three ratios technique.

Dengue Fever remains a pressing public health concern in the Global South, including in Africa, where limited resources, inadequate surveillance, weak health systems, climate change, and urbanization exacerbate the threat. This review study focuses on strategies to strengthen preparedness, capacity building efforts on surveillance, vector control, health system strengthening, community engagement, and research. Investing in training programs, research initiatives, and regional collaboration is vital. Advocacy for increased political commitment and resource allocation is necessary to drive policy support. African nations are actively contributing to global Dengue control efforts, showcasing resilience amidst adversity. There are promising prospects for improvement. Enhanced surveillance, capacity building, community engagement, research, and regional collaboration are identified as crucial strategies. Strengthening surveillance systems can provide accurate data for targeted interventions, while investing in healthcare infrastructure and training can improve diagnosis and treatment capabilities. Community engagement and education efforts can promote preventive behaviours, and research initiatives drive progress in Dengue prevention and control. Additionally, regional collaboration fosters knowledge exchange and resource sharing. By addressing these challenges and capitalizing on emerging opportunities, Africa can further strengthen its contribution to global Dengue control efforts. Through sustained investment, collaboration, and innovation, Africa has the potential to mitigate Dengue's impact and inspire similar efforts worldwide. Advocacy for increased political commitment and resource allocation is essential to drive policy support. By prioritizing Dengue control and implementing sustainable interventions tailored to local contexts, Africa can enhance public health resilience and contribute significantly to the global fight against Dengue.

Introduction: The integration of genomics and proteomics, two cornerstone omics technologies, has transformed our understanding of biological systems, enabling deeper insights into disease mechanisms, biomarker discovery, and the development of personalised medicine. While genomics uncovers genetic blueprints, proteomics reveals functional protein expressions, making their combined use essential for a holistic view of biological processes. This narrative review explores the current state, advantages, challenges, and prospects of integrating genomics and proteomics in biological research, particularly in the context of translational medicine and global health applications. Methods: A systematic literature search was conducted across four databases—PubMed, Scopus, Web of Science, and Google Scholar, for English-language peer-reviewed articles published between January 2015 and May 2025. A PRISMA-based approach guided article screening and selection. Inclusion criteria focused on studies addressing multi-omics integration, relevant technologies, clinical applications, and associated ethical concerns. The findings were synthesised using thematic analysis. Synthesis: The review highlights the growing synergy between genomics and proteomics in enhancing disease diagnosis, drug discovery, and precision medicine. Advances in next-generation sequencing and mass spectrometry, coupled with computational tools such as MOFA+ and AlphaFold, have improved data integration. However, challenges persist, including high data complexity, computational demands, ethical/legal concerns, and limited access in low-resource settings. Conclusion: Integrated omics approaches hold immense potential to revolutionise healthcare and biological discovery. Addressing current barriers and fostering global collaboration, particularly in underrepresented regions, are critical to realising the full benefits of genomics and proteomics integration.

The accuracy of a knowledge extraction algorithm in a large database depends on the quality of the data preprocessing and the methods used. The massive amounts of data that we collect every day are putting storage capacity at a premium. In reality, many databases are characterized by attributes with outliers, redundant, and even more missing values. Missing data and outliers are ubiquitous in our databases, and imputation techniques will help us mitigate their influence. To solve this problem, as well as the problem of data size, this paper proposes a data preprocessing approach based on the k-nearest neighbor (KNN) completion for imputation of missing data and principal component analysis (PCA) for processing redundant data, thus reducing the data size by generating a significant quality sample after imputation of missing and outlier data. A rigorous comparison is made between our approach and two others. The dissolved gas data from Rio Tinto Alcans transformer T0001 were imputed by KNN, where k equals 5. For 6 imputed gases, the average percentage error is about 2, 17.5 after average imputation, and 23.65 after multiple imputations. For data compression, 2 axes were selected based on the elbow rule and the Kaiser threshold.

Measles remains a significant public health challenge in Nigeria, contributing to substantial morbidity and mortality among children despite the availability of effective vaccines. This narrative review aims to synthesize current literature on the epidemiological trends, drivers, barriers, and public health interventions related to measles control in Nigeria. A comprehensive search was conducted across Google Scholar, Scopus, and PubMed for articles published between 2008 and 2024. The search strategy utilized keywords such as “measles,” “Nigeria,” “epidemiology,” “vaccination,” and “public health interventions.” Articles were selected based on predetermined inclusion and exclusion criteria, focusing on studies that specifically addressed measles and its control measures in Nigeria. The review highlights fluctuating measles incidence with periodic outbreaks exacerbated by low immunization coverage, population displacement, and rapid urbanization. Suboptimal vaccination rates for both the first (MCV1) and second (MCV2) doses leave many children vulnerable. Barriers to effective control include misinformation, vaccine hesitancy, insecurity in conflict-affected regions, and logistical challenges in vaccine distribution. Public health interventions, including enhanced immunization campaigns, community engagement, and integrated health services, are essential for improving vaccination coverage and combating measles. Achieving effective measles control in Nigeria requires sustained commitment, adequate funding, and international collaboration to ensure the health and well-being of Nigerian children.