The roots of Wireless Sensor Networks (WSNs) are tracked back to US military developments, and, currently, WSNs have paved their way into a vast domain of civil applications, especially environmental, critical infrastructure, habitat monitoring, etc. In the majority of these applications, WSNs have been deployed to monitor critical and inaccessible terrains; however, due to their unique and resource-constrained nature, WSNs face many design and deployment challenges in these difficult-to-access working environments, including connectivity maintenance, topology management, reliability, etc. However, for WSNs, topology management and connectivity still remain a major concern in WSNs that hampers their operations, with a direct impact on the overall application performance of WSNs. To address this issue, in this paper, we propose a new topology management and connectivity maintenance scheme called a Tolerating Fault and Maintaining Network Connectivity using Array Antenna (ToMaCAA) for WSNs. ToMaCAA is a system designed to adapt to dynamic structures and maintain network connectivity while consuming fewer network resources. Thereafter, we incorporated a Phase Array Antenna into the existing topology management technologies, proving ToMaCAA to be a novel contribution. This new approach allows a node to connect to the farthest node in the network while conserving resources and energy. Moreover, data transmission is restricted to one route, reducing overheads and conserving energy in various other nodes’ idle listening state. For the implementation of ToMaCAA, the MATLAB network simulation platform has been used to test and analyse its performance. The output results were compared with the benchmark schemes, i.e., Disjoint Path Vector (DPV), Adaptive Disjoint Path Vector (ADPV), and Pickup Non-Critical Node Based k-Connectivity (PINC). The performance of ToMaCAA was evaluated based on different performance metrics, i.e., the network lifetime, total number of transmitted messages, and node failure in WSNs. The output results revealed that the ToMaCAA outperformed the DPV, ADPV, and PINC schemes in terms of maintaining network connectivity during link failures and made the network more fault-tolerant and reliable.

This paper presents ANS-V2X, an Adaptive Network Selection framework tailored for latency-aware V2X systems operating under varying vehicle densities and heterogeneous network conditions. Modern vehicular environments demand low-latency and high-throughput communication, yet real-time network selection is hindered by diverse application requirements and the coexistence of multiple Radio Access Technologies (RATs) such as 4G, 5G, and ad hoc links. ANS-V2X employs a heuristic-driven approach to assign vehicles to networks by considering application sensitivity, latency, computational load, and directionality constraints. The framework is benchmarked against a Mixed-Integer Linear Programming (MILP) formulation for optimal solutions and a Q-learning-based method representing reinforcement learning. Simulation results demonstrate that ANS-V2X achieves near-optimal performance, typically within 5 to 10% of the utility achieved by MILP-V2X, while reducing execution time by more than 85%. Although MILP-V2X offers globally optimal results, its computation time often exceeds 100 milliseconds, making it unsuitable for real-time applications. The Q-learning-based method is more adaptable but requires extensive training and converges slowly in dynamic scenarios. In contrast, ANS-V2X completes decisions in under 15 milliseconds and consistently delivers lower latency than both alternatives. This confirms its suitability for real-time, edge-level deployment in latency-critical V2X systems.

Rowing is a popular sport across the globe which involves both skill and strength. The aim of the present investigation is to examine the somatotype and physical fitness of the Pakistani rowers. Data was collected from (n = 08) lightweight, and (n = 14) heavyweight Pakistani national rowers. Age, height, body mass, skinfold of triceps, subscapular, supraspinal, and calf, breadths of elbow and knee were measurement for somatotype as guided by (Norton & Olds, 1996). Push up, anaerobic, 2000 meter of maximal rowing ergometer, and set and reach for flexibility. Pearson product of correlation and t-test was applied for statistical analysis. The result showed there was a slight difference among light and heavyweight rowers in their somatotype measurements. On the other hand, the vertical jump was significantly correlated with rowing performance. It was concluded the leg power is associated with the performance of rower. It is proposed that rowers would improve their leg strength through training that enhances rowing performance.

The purpose of the study is to determine the relationship between financial leverage and the financial performance of companies in the insurance industry in Jordan, taking into account the influence of market concentration and product diversity. It analyzes data from 20 Jordanian insurance companies over 15 years (2005-2019). The study reveals a positive connection between financial leverage and insurance company profitability, with product diversification enhancing this relationship. Initially, market concentration had a negative impact on return on equity, but product diversification turned it into a positive influence. Additionally, the study highlights the positive mediating role of market concentration in the financial leverage-financial performance relationship. These findings have practical implications for insurers, emphasizing the need for diversified product portfolios and effective financial leverage strategies in a competitive market. This research contributes to understanding capital structure dynamics in emerging markets, specifically in the Jordanian insurance sector, by providing empirical evidence of the mediating and moderating effects of market concentration and product diversity.