Building automation and electrical control systems are pivotal in enhancing the efficiency, sustainability, and comfort of modern buildings. These systems integrate a variety of technologies that optimize the use of energy, improve operational efficiency, and provide a comfortable environment for building occupants. This review paper explores the fundamental components and types of building automation systems (BAS), the role of electrical control systems, their applications in residential and commercial buildings, and the benefits they bring in terms of energy efficiency, cost reduction, and enhanced operational control. Moreover, the paper discusses emerging trends, challenges, and future directions, such as the integration of IoT, smart grids, and advanced control strategies in building automation.

The exponential growth of digital data has created new opportunities for organizations to enhance decision-making and gain strategic advantage. This paper presents a framework for leveraging Big Data Analytics (BDA) to drive business growth through data-driven insights and predictive intelligence. The proposed model integrates distributed data processing tools such as Apache Hadoop and Apache Spark with machine learning algorithms for real-time analysis of large and heterogeneous datasets. Using case-based evaluation, the study demonstrates how effective deployment of BDA improves organizational performance across key metrics such as customer engagement, operational efficiency, and profitability. Experimental results indicate that businesses employing data-driven strategies experience a significant increase in decision accuracy and market responsiveness compared to traditional analytics approaches. The findings highlight the critical role of big data technologies in achieving competitive advantage and advancing digital transformation in modern enterprises.

The oil and gas industry is considered a high-risk industry worldwide due to its constant exposure to various physical, chemical, and ergonomic hazards. The research focused on assessing occupational exposure and safety hazards among employees in four allied oil and gas companies in Warri, Nigeria, with the intention of measuring the level of exposure, determining the health outcomes associated with it, and evaluating safety compliance. It employed a cross-sectional descriptive study design, which incorporated environmental surveillance and a survey of the workers. Structured questionnaires and standardized tools were used to collect data from 380 employees, including CEL-6X0 Noise Level Meters, Aerocet 531S Dust Monitors, and RKI GX-2009 Multi-Gas Determiners. Results indicated a high prevalence of 62.4% of high noise exposure, 55.8% of exposure to welding fumes or dust, and 38.2% of exposure to chemical or gaseous emissions, with 21.8% of respondents experiencing work-related injuries in the previous year. Ear protection and respiratory masks were used frequently (37.4% and 35.8%, respectively), despite the fact that safety training had been completed by 72.1% of them. The noise levels exceeded the OSHA 85 dBA standard at major workplaces, including generator houses (99.3 dBA), welding areas (94.6 dBA), and maintenance workshops (93.9 dBA). The air quality analysis revealed that the concentrations of particulate matter (PM2.5: 81.3 μg/m³ and PM10: 145.1 μg/m³) exceeded the safe limits established by the WHO, and CO (26.8ppm) approached the 35ppm limit recommended by NIOSH. The reported symptoms included headaches (41.6%), respiratory irritation (37.4%), fatigue (35.8%), and temporary hearing loss (31.6%). Correlation analysis revealed strong relationships between noise exposure/hearing symptoms (r = 0.73, p < 0.001) and between PM 2.5/respiratory symptoms (r = 0.69, p = 0.002). The research concludes that occupational exposures are still at a lethally high level and advises increasing engineering measures, persistent monitoring, and stricter policy enforcement through regulations to protect the health of workers.

This study evaluates classic and modern machine-learning methods for email spam detection using term frequency and inverse document frequency (TF-IDF) features and a public dataset of ham and spam emails. Nineteen classifiers were trained and compared with accuracy, precision, recall, F1, and variance-based stability. While several models (e.g., Gradient Boosting, Ridge Classifier CV, Bernoulli Naive Bayes) achieved high test accuracy, robustness analysis shows Random Forest and Logistic Regression with cross-validation provide steadier performance and reduced overfitting. Standard-deviation results and train-test gaps expose variance issues in single trees and highlight the practical value of ensembles and regularized linear models. The work underscores that deployment choices should favor consistent, generalizable behavior over peak scores alone.

The blood-borne malaria pathogen is a fatal infectious disease that is especially endemic in sub-Saharan Africa and has a high death rate there. However, no advanced mathematical model is available to comprehend the complex relationship among the parasite and its human host during the blood and liver stages. Red blood cell and immune cell interactions were integrated into an in-host mathematical model of Plasmodium falciparum malaria dynamics at the liver level in this study. Both graphical interpretations and numerical simulations are provided and examined. The research results indicate that immunology plays a major role in eliminating infected red blood cells. Additionally, as the density of merozoites in the blood increases, so do the number of infected erythrocytes and, consequently, the severity of malaria. The outcome showed that reducing the density of merozoites in circulation and the rate at which they invade healthy erythrocytes should be the main goals of intervention during a malaria infection.

A thorough review on the seismic behavior of rocking wall systems with additional damping in reinforced masonry structures has been given in this paper. Rocking walls are the walls that are created in order to uplift and sway to and fro during the occurrence of an earthquake and dissipating the energy using the additional damping devices and the restriction of the damage to the general building parts. Experimental works, quasi-static tests and shake table tests, numerical simulations and comparisons with fixed-base systems are analyzed in the review. Its non-destructive quasi-static tests were carried out in order to characterise the low-cycle fatigue properties and to determine the behaviour of rocking wall systems subject to cyclic loading. Shake table testing had been carried out to check the dynamic performance and earthquake behavior of rocking walls under even earthquake forces. The experiment outcomes showed that rocks wall systems with additional damping performed very well with a smaller base shear forces, small remaining drifts, and better energy dissipation compared to those systems with fix base. Finite element analysis and numerical models were generated to mimic and model the behavior of rocking wall system and improve design parameters. The effects of post-tensioning, energy dissipation devices as well as uplift behavior fell into the models. The seismic capacity of rocking wall systems was also assessed with the help of pushover analysis to find possible sources of weaknesses. The review has emphasized the drawbacks and shortcomings of available models including the inability to better predict the fractures strands of post-tensioning and lateral-torsional buckling of slender fuses plates and nonlinear and complex interactions during dynamic loading. The results indicate that rocking wall systems that are supplementally damped are an attractive seismic design concept to be applied on reinforced masonry buildings, which provide an increased performance, damage protection, and self-center capacity relative to usual fixed-based systems. It is proposed to conduct further studies and improve the design and implementation of the rocking wall systems in practice to overcome the named difficulties.

African megacities demonstrate economic pulsing as well as increased exposure to occupational risks and security threats, with their urban transport-market corridors and manifolds. This paper used a multidisciplinary approach with a mixed-methods design of the Ojota-Ketu-Mile 12 axis of Lagos with the involvement of surveys (n = 283), key informant interviews (n = 30), and focus group discussions (n = 9), and advanced statistics and artificial intelligence (AI). In descriptive results of occupational hazards, musculoskeletal strain was reported as the most frequent hazard (44.9%), whereas respiratory stress was the second most frequent hazard (38.2%). In descriptive results of security, most frequently reported security hazards were theft (42.4%), followed by harassment (33.6%). Findings in the use of a chi-square and regression model were education, occupation, and gender as crucial predictors, and a three-factor exploratory factor analysis identified occupational strain, exposure to the environment, and vulnerability of security. The Random Forest stratifiers were ~86% accurate, and the AUC was 0.91, with stratification identifying 28.6% of respondents as high-risk and 41.3% as medium-risk, thus highlighting systemic vulnerability. These trends were supported by the qualitative evidence, which revealed how many people feel the strain, visibility, accidents, and insecurity, narrating how people feel cautious about adopting AI in society. The study concludes that mitigation must be an integrated intervention of environmental, ergonomics, and security interventions in combination with participatory and ethically-governed AI systems. These findings present practical directions to policymakers, civic administrators, and even market institutions that desire safer, healthier, and more resilient urban market spaces.

Transition metal complexes play a vital role in modern catalysis due to their unique ability to facilitate a wide range of chemical transformations with high efficiency, selectivity, and sustainability. This study explores the fundamental mechanisms by which transition metal complexes function as catalysts and highlights their extensive industrial applications. The catalytic activity of these complexes arises from the variable oxidation states, coordination geometries, and electronic properties of transition metals, which enable them to activate substrates and stabilize reactive intermediates during chemical reactions. Mechanistic pathways such as oxidative addition, reductive elimination, insertion, and ligand exchange are central to the catalytic cycles of many metal-based systems. Well-known examples include palladium-catalyzed cross-coupling reactions, rhodium- and ruthenium-based hydrogenation and hydroformylation, and vanadium or molybdenum complexes used in oxidation reactions. These reactions are foundational in the synthesis of pharmaceuticals, polymers, agrochemicals, and fine chemicals. From an industrial perspective, transition metal catalysts contribute significantly to green chemistry by reducing energy consumption, minimizing waste, and improving atom economy. Homogeneous and heterogeneous catalytic systems utilizing metals such as nickel, cobalt, platinum, and copper have revolutionized large-scale processes like petroleum refining, ammonia synthesis, and polymer production. This paper emphasizes the importance of understanding catalytic mechanisms at the molecular level to design more efficient and environmentally friendly catalysts. Continued research in this area holds promise for the development of novel catalytic systems tailored to meet the demands of sustainable chemical manufacturing and energy transformation.

In today’s connected world, choosing the right broadband technology is key to delivering fast and reliable internet. This paper takes a closer look at three major players in the field: DSL (Digital Subscriber Line), DOCSIS (Data Over Cable Service Interface Specification), and PON (Passive Optical Network). Each of these technologies uses a different kind of infrastructure—DSL runs over traditional telephone lines, DOCSIS relies on cable TV networks, and PON uses cutting-edge fiber-optic cables. DSL is widely available and cost-effective but struggles with speed over long distances. DOCSIS offers better speeds and is commonly used in cities, though bandwidth is shared among users. PON, on the other hand, delivers ultra-fast speeds and is ideal for future internet demands, but comes with higher installation costs. By comparing their performance, scalability, and costs, this paper helps understand where each technology fits best and how they can meet the growing demands of digital life.

Biomedical engineering is an interdisciplinary field that merges the principles of engineering and medical sciences to develop innovative solutions for healthcare challenges. Over the past decade, rapid technological advancements have transformed the way health conditions are diagnosed, monitored, and treated. This research provides a comprehensive review of recent developments in biomedical technologies, focusing on four primary areas: wearable medical devices, advanced medical imaging, robotic-assisted surgery, and tissue engineering. The study employs a thematic qualitative methodology based on a systematic review of peer-reviewed literature, analyzing key innovations, their clinical impacts, and integration challenges. The findings reveal that wearable devices have significantly improved chronic disease management through real-time physiological monitoring, while imaging technologies, enhanced by artificial intelligence, have elevated diagnostic precision and early disease detection. Robotic-assisted surgeries have led to reduced complications and faster recovery times, and tissue engineering shows promising potential in regenerative medicine despite ongoing challenges in scalability and biocompatibility. However, the study also identifies persistent issues such as device interoperability, cybersecurity risks, and regulatory constraints. This paper concludes that biomedical engineering will continue to play a critical role in shaping the future of healthcare. The integration of AI, nanotechnology, and personalized medicine is expected to further accelerate innovation. Addressing existing barriers through multidisciplinary collaboration will be essential in maximizing the benefits of biomedical technologies and ensuring equitable access to advanced healthcare solutions globally.