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.
Abstract This article traces the transformation of modern American anthropology through its Moroccan field, examining the discipline’s passage from colonial representation to dialogical encounter. Emerging from anthropology’s postwar crisis of conscience, the interpretive and literary turns displaced claims to objectivity with reflexivity and recast fieldwork as a moral and relational practice. Rather than presenting this shift as a linear disciplinary advance, the article situates it within enduring structures of coloniality, where epistemic authority, voice, and representation remained deeply contested. While Clifford Geertz and Paul Rabinow provided key theoretical frameworks for this reorientation, the analysis centers on six American ethnographers whose Moroccan works most vividly enacted it in practice: Dale F. Eickelman, Vincent Crapanzano, Kevin Dwyer, Henry Munson, Daisy Hilse Dwyer, and Deborah A. Kapchan. Their ethnographies—ranging from social biography and psychological portraiture to oral history, dialogical exchange, and gendered performance—redefined fieldwork as an art of listening, negotiation, and co-creation. Through close textual and theoretical reading of these works, the article treats their monographs as both ethnographic experiments and disciplinary interventions, situating them within the broader epistemological debates that reshaped twentieth-century American anthropology. By reading Morocco as both an ethnographic site and a crucible of theoretical renewal, the article shows how encounter itself became a mode of interpretation. At the same time, it argues that dialogical and ethical anthropology did not mark a clean rupture from colonial epistemologies, but rather a critical reworking of their legacies within new textual, ethical, and institutional frameworks. Collectively, these case studies reveal how anthropology’s moral and narrative reconfiguration unfolded from empire to encounter, culminating in an ethics of voice that reshaped what it means to write—and to know—the Other.
Background: This study investigated the hypolipidemic and hepatoprotective effects of refined soybean oil supplemented with an Ocimum basilicum L. extract, characterized by HPLC and found to be rich in caftaric, caffeic, chicoric, and rosmarinic acids. Methods: After a 12-week model of diet-induced hyperlipidemia, we examined the plasma levels of TC, TG, Glucose, HDL-C, and LDL-C and the LDL-C/HDL-C ratio using enzymatic kits. The Plasma Hepatic and Biliary Marker Analysis was analysed following standardized hospital protocols with quality-controlled instrumentation. Results: The supplementation with Basil-Enriched Oil (BEO) resulted in a notable redistribution of lipids, significantly reducing the plasma total cholesterol (-75%), triglycerides (-96%), and glucose (-22%), while enhancing their hepatic sequestration. This was accompanied by a marked improvement in the LDL-C/HDL-C ratio and a reduction in hepatic oxidative stress (measured by MDA). Importantly, BEO preserved liver structure and prevented steatosis, despite inducing an increase in adaptive hepatomegaly. Conclusions: The results reveal a dual mechanism whereby the antioxidant properties of BEO collaborate with reprogrammed lipid metabolism, promoting safe hepatic storage rather than harmful circulating levels. These findings strongly advocate for the extract's potential as a nutraceutical for addressing hyperlipidemia and related metabolic disorders by targeting both oxidative stress and lipid imbalance. Further research is required to confirm these effects in clinical settings and to confirm its long-term efficacy.
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.
