The performance of photovoltaic (PV) panels is significantly impacted by their operating temperature. As the temperature rises, the ability of solar cells to convert sunlight into electricity decreases, resulting in a drop in electrical efficiency. To mitigate this effect, a passive cooling strategy using RT25 as a phase change material (PCM) combined with aluminum fins was investigated. Numerical simulations were performed in COMSOL Multiphysics using the finite element method, coupling heat transfer in solids and fluids with laminar flow to capture conduction and natural convection within the PCM. The present work focused on three key parameters: the inclination angle of the PV-PCM system, the number of fins, and their location on the panel surface. A numerical analysis was conducted to evaluate the electrical and thermal performance of the PV-PCM system. The investigation considered various fin spacing configurations of different distances (d) to determine the optimal design. The configuration with d = 16 mm showed the lowest temperature compared with all other configurations. At an inclination angle of 60 degrees, the configuration with d = 16 achieved the best cooling performance by reducing the average temperature of the PV panel by 53.20 % and 6.43 % compared with the only PV and PV-PCM, respectively. It exhibited a significant electrical efficiency enhancement, with increases of 18.699 % and 1.84 % compared with the only PV and PV-PCM cases, respectively.
In this work, we present a new analysis for f(R, T) gravity by exploring the energy momentum tensor. We demonstrate that f(R, T) gravity with the form f(R,T)=R+2κ2λT−2Λ is equivalent to Running Vacuum Energy (RVE), which interacts with the components of the cosmic fluid, namely dark matter and radiation. Interestingly, the form of such interaction is inferred from the non-conservation of the stress energy tensor in f(R, T) gravity rather than being introduced in a phenomenological manner. Furthermore, the parameters that distinguish RVE from ΛCDM are fixed once the parameter of f(R, T) gravity, λ, is known. To illustrate our setup, we perform a Markov Chain Monte Carlo analysis of three interaction scenarios using a combination of different data. we find that the parameters characterizing the RVE model are very small as expected. These results give an accuracy to this equivalence between f(R, T) gravity under consideration and support the recent result obtained from a quantum field theory in curved space-time point of view which could open a new relationship between f(R, T) gravity and quantum field theory. Finally, the interaction of the running vacuum increases the current value of the Hubble rate by 3.5% compared to the ΛCDM model, which may be a promising study for the Hubble tension.
Recent advances in the Internet of Medical Things (IoMT) have significantly improved data processing and patient care within Smart Healthcare systems. However, these developments have also expanded the surface of potential cyber threats targeting sensitive medical infrastructures. To address these challenges, a variety of security approaches both traditional and Artificial Intelligence (AI)-based have been proposed to strengthen the resilience of IoMT environments. In particular, Machine Learning (ML) and Deep Learning (DL) techniques have demonstrated strong capabilities in detecting and mitigating abnormal behaviors and malicious activities. This paper provides a comprehensive survey of recent AI-driven methods applied to IoMT security, with a particular focus on intrusion detection systems (IDS), the availability and characteristics of public datasets, and architectural considerations for deploying security solutions across Cloud, Fog, and Edge computing layers. The paper also discusses legal and ethical concerns related to data protection in healthcare contexts. Finally, the study outlines open challenges and future research directions for developing robust, adaptive, and trustworthy security frameworks in the IoMT ecosystem.
The operating temperature of photovoltaic modules critically affects electrical efficiency and long-term reliability, particularly under high solar irradiance. While passive cooling using phase change materials has been widely investigated, most research focuses on single-phase change material systems or has not systematically optimized fin geometry under constant phase change material volume and realistic inclination angles. To address these limitations, this study proposes a fully passive finned photovoltaic-phase change material heat-sink design integrating two phase change materials with different melting temperatures (RT-35 and RT-25HC) arranged in multi-layer configurations. A stepwise numerical optimization is first performed to identify an optimal fin geometry, followed by a comparative analysis against a smooth configuration using the same total phase change material volume. Key geometric parameters, including fin length, fin thickness, and fin number, are systematically evaluated. Results indicate that increasing the fin thickness from 1 mm to 3 mm reduces the maximum photovoltaic operating temperature by about 5.5 degrees C. Based on this optimization, a configuration with seven fins combined with a multiple-phase change material arrangement corresponding to Case 3 (10 mm RT-35 and 30 mm RT-25HC) provides the best overall thermal and electrical performance, reducing photovoltaic temperature by up to 16.29 degrees C and increasing electrical efficiency by 8.21% compared to the smooth system. Overall, optimizing fin geometry, especially fin thickness, significantly enhances passive thermal management in photovoltaic systems with integrated phase change materials.
Let B-a(H) be the collection of bounded antilinear operators on a complex separable Hilbert space H. For R is an element of B-a(H), its numerical range and maximal numerical range are denoted by W(R) and W-0(R), respectively. The numerical radius and the maximal numerical radius of Rare denoted by w(R) and w(0)(R), respectively. This paper answers basic questions concerning maximal numerical ranges of antilinear operators. First, we study the convexity problem of maximal numerical ranges, completely determine those operators in B-a(H) having convex maximal numerical ranges, and prove that they constitute a nowhere dense, closed subset of B-a(H). Second, we study the relation between w(R) and w(0)(R) for R is an element of B-a(H), proving that those R is an element of B-a(H) with w(0)(R) < w(R) constitute an open dense subset of B-a(H) precisely when dim H > 1. Finally, we study the continuity problem of the maximal numerical radius function R is an element of B-a(H) bar right arrow w(0)(R), and completely determine its continuity points. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
