Abstract: Large magnetic fields, either imposed externally or produced spontaneously, are often present in laser-driven high-energy-density systems. In addition to changing plasma conditions, magnetic fields also directly modify laser-plasma interactions (LPI) by changing participating waves and their nonlonear interactions. In this paper, we use two-dimensional particle-in-cell (PIC) simulations to investigate how magnetic fields directly affect crossbeam energy transfer (CBET) from a pump to a seed laser beam, when the transfer is mediated by the ion-acoustic wave (IAW) quasimode. Our simulations are performed in the parameter space where CBET is the dominant process, and in a linear regime where pump depletion, distribution function evolution, and secondary instabilities are insignificant. We use a Fourier filter to separate out the seed signal, and project the seed fields to two electromagnetic eigenmodes, which become nondegenerate in magnetized plasmas. By comparing the seed energy before CBET occurs and after CBET reaches quasi-steady state, we extract CBET energy gains of both eigenmodes for lasers that are initially linearly polarized. Our simulations reveal that starting from a few MG fields, the two eigenmodes have different gains, and magnetization alters how the gains depend on laser detuning. The overall gain decreases with magnetization when the laser polarizations are initially parallel, while a nonzero gain becomes allowed when the laser polarizations are initially orthogonal. These findings qualitatively agree with theoretical expectations.

Abstract: This study tests the Stock Internal Rate of Return Including Price Appreciation (SIRRIPA), derived from the Potential Payback Period (PPP) framework, as both a standardized stress-test and a predictive return metric. For 50 U.S. technology stocks (Sept 5–Nov 3 2025), SIRRIPA correlates positively with subsequent performance (r = 0.26; p = 0.07; ρ = 0.92; p < 0.001), with a 30-point spread between top and bottom deciles. Parallel global research reports r ≈ 0.76–0.82 between PPP-based yields (SIRR/SRP) and realized market returns measured over longer horizons of up to two years. Together, these findings confirm that standardized, yield-based valuation metrics consistently link intrinsic fundamentals to realized performance across both firm and market scales.

Abstract: Cancer is a multifactorial disease influenced by genetic, epigenetic, and environmental determinants, including biological agents such as oncogenic viruses. Among these, hepatitis B virus (HBV), hepatitis C virus (HCV), and hepatitis D virus (HDV) play pivotal roles in the pathogenesis of hepatocellular carcinoma (HCC)—the predominant form of primary liver cancer and a major contributor to global cancer mortality. Chronic infection with these hepatotropic viruses drives hepatocarcinogenesis through both direct mechanisms, including viral genome integration and oncoprotein expression, and indirect pathways involving persistent inflammation, immune evasion, and oxidative stress.Despite substantial advances in HBV vaccination programs and the development of curative therapies for HCV, the global burden of hepatitis-related liver cancer remains high, driven by underdiagnosis, limited access to care, and the absence of a functional cure for HBV.This review critically examines the molecular and pathogenic mechanisms by which HBV, HCV, and HDV contribute to cancer initiation and progression, and summarizes current therapeutic and preventive strategies. It further highlights emerging research directions and translational challenges that must be addressed to improve prevention, early detection, and treatment of virus-induced hepatocellular carcinoma.

Abstract: This mixed-methods study examines the digital readiness of primary school teachers in Greece and Cyprus working in multilingual and multicultural mainstream classrooms. In response to the increasing diversity in European education, it explores how teachers perceive and implement digital competence to support inclusive and quality education. Using the DigCompEdu framework and an extended TPACK model, data were collected from 146 in-service teachers through a structured questionnaire. Cluster analysis revealed three distinct competence profiles—high, moderate, and low—while Kruskal–Wallis tests confirmed significant differences among them. Thematic analysis of open-ended re-sponses, supported by Pearson correlation analysis, highlighted how teachers’ beliefs, infrastructural conditions, and pedagogical practices intersect. Highly competent teachers reported the use of inclusive digital strategies, yet pointed to systemic barriers such as limited training and poor infrastructure. Less confident teachers expressed foundational challenges and dependence on external support. Across all profiles, contextual fac-tors—school resources, time, student digital readiness, and access to professional development—were key. The study concludes that digital competence is not merely technical, but deeply context-sensitive and pedagogical. It calls for differentiated, equity-oriented professional learning pathways aligned with Sustainable Development Goals 4 and 10, contributing to inclusive education and education for sustainability in linguistically diverse classrooms.

Abstract: This work presents an energy efficient implementation for UAV-based systems over 5G networks with on-boarded accelerated processing capabilities and provides a preliminary evaluation analysis of the integrated solution. A two-fold comparative study focused on connectivity and edge processing for UAVs, realizes two discrete deployment scenarios, where standard 5G configuration with Artificial Neural Networks processing is evaluated against 5G RedCap connectivity paired with Spiking Neural Networks. Both proposed alternative energy efficient solutions, are designed to offer significant energy saving, and this paper examines if they are fit candidates for energy stringent environments, i.e., UAVs, and also quantify the impact on the overall energy consumption of the system. The integrated solution with 5G RedCap/SNN realizes energy-use reductions approaching 60%, which translated to approximately 35% of increased flight time. The experimental evaluations were performed in a real-world deployment using a 5G equipped UAV with edge processing capabilities based on NVIDIA’s Jetson Orin.

Abstract: Efgartigimod is a novel neonatal Fc receptor (FcRn) antagonist that reduces pathogenic IgG autoantibodies, offering a targeted therapeutic approach for generalized myasthenia gravis (gMG) and other antibody-mediated autoimmune diseases. This narrative review synthesizes clinical trial data, pharmacological insights, and real-world evidence to evaluate efgartigimod's efficacy, safety, and emerging applications. Phase 3 randomized controlled trials and extension studies demonstrate rapid and sustained improvements in muscle strength and patient-reported outcomes with a favorable safety profile, including reduced reliance on corticosteroids and intravenous immunoglobulin. Additionally, observational studies highlight its expanding utility in diverse IgG-mediated disorders such as immune thrombocytopenia and autoimmune encephalitis. Efgartigimod thus represents a paradigm shift in autoimmune disease management, enabling precision immunomodulation with the potential for broad clinical impact and improved patient quality of life (QOL).

Abstract: This study investigates the classification of nine sitting postures using pressure distribution data from hard and soft seat surfaces. Three neural network architectures (FNN, CNN, ResNet) were evaluated under single-surface and mixed-domain training regimes. While all models achieved high accuracy (>96%) when trained on mixed-domain dataset, significant performance degradation occurred in cross-domain testing. CNN demonstrated superior capability in leveraging spatial pressure features under mixed training conditions, while FNN exhibited relatively better cross-domain robustness. Results indicate model performance highly depends on architectural inductive biases and training data diversity. These findings underscore the importance of employing representative multi-surface datasets for ensuring generalization in practical sitting posture recognition systems.

Abstract: Cultural family leisure refers to participation in cultural events, visits to museums, attending concerts, and/or any other activity with an artistic or cultural component. Its characteristics shape family coexistence, bonds, lived experiences, memories, and quality family moments. Several authors argue that it influences children’s development and the adolescent stage, as it provides a safe space to explore interests, express emotions, strengthen self-esteem, develop creativity, and foster positive bonds with culture and art. Social changes, globalization and immediacy, and the shortage of time needed to “do it all” (work, studies, health, family, friends, etc.) are reducing its presence, thereby decreasing the quality of family time. This study, in compliance with the ethical principles of research with human beings, analyzes adolescents’ perception of cultural family leisure. The participating sample consists of 1,054 Spanish students aged 11–16 who answered an ad hoc questionnaire composed of 48 items. The study is descriptive, correlational, cross-sectional, and non-experimental. The results show that adolescents perceive that little time is shared as a family and that little importance is attached to family leisure, and that, for the most part, it is organized by external agents rather than within the family itself. However, they underscore the importance of family leisure for communication and personal development. In conclusion, the study proposes socio-educational and cultural actions within the family sphere to promote cultural leisure.

Abstract: The proliferation of smartphones and social media has reshaped journalistic practices across South Asia, particularly in Bangladesh, where “selfie stick journalism” has emerged as a symbolic and practical marker of the new media age. This paper investigates how the democratization of media tools—mobile phones, selfie sticks, livestream platforms, and algorithmic news feeds—has redefined the boundaries of journalism, eroding traditional professional hierarchies and raising critical questions: Who qualifies as a journalist in a networked society? What constitutes journalistic authority, authenticity, and accountability when anyone can broadcast to millions? Drawing upon case studies from Bangladesh, India, and Pakistan, this study explores the identity crisis confronting professional journalists amidst the rise of “content creators,” “citizen reporters,” and “social influencers.” The research combines theoretical frameworks from Pierre Bourdieu’s field theory, Manuel Castells’s network society, and media convergence literature to examine shifts in professional legitimacy and epistemic authority. Empirical data are drawn from interviews with professional journalists, digital content creators, and social media analysts, as well as content analysis of viral “selfie journalism” incidents during major political and humanitarian events in 2024–2025. The findings suggest a profound transformation of journalistic identity: a movement from institutional to performative, from gatekeeping to self-branding, and from public service to algorithmic visibility. In South Asia’s hybrid media ecology, the selfie stick becomes not just a tool but a metaphor for the spectacle, precariousness, and personalization of journalism itself.

Abstract: We model conscient entities as vertices of a Graph; and its edges, as the interaction between the them. We further introduce a two-layer multiplex network structure coupling the micro-level soul graph with a macro-level nation graph, enabling the study of how individual interactions aggregate to shape inter-nation relationships, and conversely, how geopolitical events influence individual states. The model includes concepts such as cultural entanglement, and virtue field restoration, providing a unified graph-theoretic treatment of both spiritual and geopolitical evolution. By combining deterministic evolution laws with graph Laplacian operators, the model captures the cyclical patterns of cooperation, fragmentation, and reunification across epochs. This work not only bridges ancient spiritual narratives with modern mathematical formalisms but also lays the foundation for quantitative simulations of the socio-political dynamics of humanity across Time.

Abstract: As the climate continues to warm, the incidence of extreme weather events is increasing on a global scale. Presently, flooding remains a complex challenge for urban environments. Certain regions and countries are limited by geographic and historical urban planning factors, resulting in heightened flooding in some historic districts that are affected throughout the year. Since the mid-20th century, nations have initiated comprehensive research into flood protection measures, evolving from the initial construction of flood control dykes to the development of floodplains. However, with the escalation of climatic issues, traditional flood prevention strategies, such as floodplain management, are no longer sufficient to address current flooding phenomena. Consequently, this study will focus on the cities of Carlisle in northern England and New Orleans in the United States. These two cities have been selected due to their similar causes of flooding. The research aims to compare the underlying factors contributing to flooding in New Orleans and Carlisle in order to assess why conventional flood control strategies are becoming increasingly ineffective.

Abstract: This study presents an optimal bearing arrangement for the propulsion shafting system of ships equipped with multiple strut bearings, ensuring both structural stability and cost-effectiveness under shallow-draft conditions where the propeller must remain fully submerged. To this end, the shafting flexibility, alignment characteristics, and whirling vibration responses were analyzed for various bearing arrangements. The analysis results show that removing the stern tube bearing and supporting the shaft using only the Y-type and I-type strut bearings, with the bearing span adjusted so that the L/d ratio remains within 15 to 18, minimizes the reaction influence number, shaft bending moments, and variations in bearing loads. At this configuration, the first natural frequency corresponding to the propeller blade order is also more than 30 percent higher than the service speed, thereby avoiding resonance caused by transverse vibration. Accordingly, this study confirms that adjusting the layout of strut bearings can simultaneously enhance both the structural reliability and dynamic stability of the propulsion shafting system.

Abstract: This essay commemorates Henri Ciriani (1936–2025), tracing his architectural work and influential teaching as a defender of ethical modernism. Through his built projects and his pedagogy at Studio UNO, Ciriani advanced a spatial language rooted in light, proportion, and human dignity, shaping generations of architects and reaffirming architecture’s civic role.

Abstract: In the continuous quest to enhance the efficiency and sustainability of flight, the natural world offers a plethora of strategies and adaptations that can be harnessed in aviation technology. This review paper explores the multifaceted approaches of energy harvesting and drag reduction observed in nature, emphasizing their potential applications in modern aircraft and drone design. It delves into the study of micro and macro structures in various species, such as the drag-reducing micro-structures of riblets on bird feathers. The paper further investigates the broader morphological adaptations in birds and insects, including topics such as beak shape, coloration, flight configurations, materials, molting, and airfoil design for their contributions to aerodynamic proficiency. In addition, this review highlights various energy harvesting techniques observed in nature, such as soaring and ground effect exploitation, and their potential integration into aircraft design for improved endurance. Through a comprehensive review of these natural phenomena, this work aims to provide valuable insights for the development of innovative, eco-friendly aviation technologies, contributing to the global effort to reduce the environmental impact of air travel while improving the viability of drones in the nano to micro range.

Abstract: This study explores the digital transformation and public value created through Taiwan’s smart city Mobile Payment APP and digital city token system within the context of sustainable governance. Using a mixed-methods approach, the research integrates Importance-Performance Analysis (IPA) surveys of users with in-depth stakeholder interviews to assess service quality, user satisfaction, and cross-sector collaboration effects. The findings reveal that the mobile payment platform significantly enhances digital service delivery, fosters user engagement, and supports sustainable urban development goals, including net-zero carbon emissions. Key challenges identified include limited merchant acceptance and technical usability issues, which suggest areas for policy and technological improvement. This study contributes empirical evidence on the integration of financial technology and public service innovation as a means to advance smart governance and sustainable urban ecosystems. The results provide actionable insights for policymakers, city planners, and service designers focused on promoting digital public services that facilitate economic vitality, environmental sustainability, and collaborative governance.

Abstract: Canonical market microstructure theories, validated in liquid financial markets, are often misapplied to illiquid power futures. This study introduces the Impact-Inventory Parity (IIP) parameter Ψ, bridging the Kyle (information-based) and Ho-Stoll (inventory-based) models, and uses agent-based simulations to test its validity in thin markets. We uncover a critical asymmetry: while competition consistently pushes markets towards inventory dominance, the countervailing effect of non-linear inventory costs systematically weakens as markets thin due to lower inventory variance. This creates a structural bias toward inventory dominance Ψ=1 that persists despite strong convex penalties. Adaptive behaviour revealed a stability paradox, causing severe parity breakdown that was amplified by liquidity, not thinness. Parameter space analysis showed market stability rests equally on three structural pillars: participation, liquidity, and information quality. Among stable markets, information quality dominates regime outcomes, while adaptative behaviour acts as a critical threshold where small changes can trigger immediate market collapse. Across the physically plausible parameter space, inventory-dominated regimes comprise the vast majority (73%) of configurations, while the balanced-risk conditions predicted by classical theory are rare (8%), confirming parity as a narrow, fragile equilibrium. The framework proves robust in thin, fragmented markets—precisely where canonical models fail, while becoming unreliable in the liquid, centralized venues where those models were validated.

Abstract: The weather has a significant impact on various aspects of lives. The consequences of severe weather conditions are manifold and detrimental, posing significant risks to human survival. In this paper we aim to develop a database for capturing weather data and to predict severe weather condition. The dataset used to achieve this aim was a secondary dataset collected from OpenWeather from 2/21/2024 to 2/27/2024. The weather dataset was analyzed quantitatively using descriptive statistic and correlation analysis. Furthermore, three supervised machine learning model (logistic regression, random forest, and neural network) was trained to predict the severity of the weather situation. Temperature exhibited a strong negative correlation with pressure (-0.640), moderate negative correlation with humidity (-0.296) and wind degree (-0.002), weak positive correlation with ground level (0.260) and wind speed (0.221). Also, pressure was found to have a weak negative correlations with humidity (-0.083), ground level (-0.387), and wind speed (-0.015), wind degree (-0.322) and cloud cover (-0.075). humidity showed a strong positive correlation with ground level (0.662) and wind degree (0.642). Wind degree had a moderate positive correlation with humidity (0.642) and ground level (0.528). The performance metric of the model was evaluated in three different instances (train, testing, all). On the training dataset NN achieved an accuracy of 1(95% CI: 0.9997 to 1), RF with an accuracy of 1.0(95% CI: 0.9998 to 1), logistic with an accuracy of 0.9651(95% CI: 0.9625 to 0.9676). On a new dataset (i.e., test dataset), RF maintained its accuracy of 1.0(95% CI: 0.9984 to 1), while NN had a slightly lower accuracy of 0.9996(95% CI: 0.9975 to 1), and LR achieved accuracy of 0.9663(95% CI: 0.958 to 0.973). Across the entire dataset, RF 1.0(95% CI: 0.9998 to 1) accuracy, The NN model performed nearly as well, with accuracy of 0.9999(95% CI: 0.9997 to 1), while LR maintained consistent but lower scores, recording accuracy of 0.9652(95% CI: 0.9628 to 0.9676). The results suggest that our weather prediction system was stable across the three instances effectively classifies weather conditions indicating its potential for real-world applications in weather prediction systems.

Abstract: Introduction: Chronic Obstructive Pulmonary Disease (COPD), a respiratory pathology primarily linked to smoking, appears to exacerbate oral health problems through systemic and local mechanisms. This study evaluates the impact of COPD on the oral health of smoking patients in an Algerian context.​Methods: A descriptive cross-sectional study was conducted from January to June 2023 at the University Hospital Center of Sidi Bel Abbès, Algeria. A total of 138 male smoking patients were included. Each participant answered a standardized questionnaire, underwent a thorough clinical oral examination, and spirometry to confirm the diagnosis of COPD (FEV/FVC < 0.7 post-bronchodilator).​Results: Out of 138 patients, 62 (44.9%) had confirmed COPD. Tooth loss was significantly more frequent among COPD patients (88.7%) than among non-COPD patients (77.6%, p = 0.03). Dental caries were also more prevalent in the COPD group (85.5%) compared to the non-COPD group (70.1%, p = 0.02). Gum disease (93.5% vs. 91.3%, p = 0.65) and bad breath (79.0% vs. 76.0%, p = 0.70) showed similar prevalences in both groups.​Conclusion: COPD is associated with a significant deterioration of oral health, particularly regarding tooth loss and dental caries. A multidisciplinary management approach involving pulmonologists and dentists is crucial to improve clinical outcomes and patient quality of life.

Abstract: Words matter in science, particularly when they define technologies with distinct biological mechanisms. High-Intensity Laser Therapy (HILT) is often conflated with High-Power Laser Therapy or High-Level Laser Therapy (HPLT/HLLT), despite these terms referring to laser systems with very different capabilities. Whereas many therapeutic lasers can elicit photochemical and photothermal effects, only devices delivering high-peak, short-duration pulses at very low duty cycles are able to generate acoustic pressure waves and thus qualify as true HILT systems. These photoacoustic effects uniquely activate mechanotransduction pathways involved in cellular differentiation, extracellular matrix remodeling, and long-term tissue regeneration. This review highlights the widespread misclassification in the laser therapy literature, where devices lacking genuine photoacoustic capability are nonetheless described as HILT. Such semantic ambiguity undermines biological specificity, inflates clinical claims, and delays technological progress. Within the laser science community, it is well recognized that average power alone is insufficient to characterize a therapeutic mechanism and provides no indication of the ability to induce pressure waves. We therefore propose a mechanism-based classification that clearly separates photochemical, photothermal, and photoacoustic effects, and call for greater rigor in reporting technical parameters such as peak power, pulse duration, and duty cycle. Correct terminology will advance scientific rigor and enable meaningful comparisons across regenerative medicine studies.

Abstract: Proteins exist as multiple chemical and sequence-specific proteoforms, each of which may serve as a critical mediator of physiological or pathological signaling. This diversity arises from processes such as alternative splicing of gene transcripts, translation into amino acid sequences, and various post-translational modifications (PTMs), leading to an exponential increase in biological complexity. This manuscript provides an overview of the mechanisms underlying proteoform generation in biological systems and highlights strategies for their analysis using mass spectrometry (MS)-based proteomics and bioinformatics. Additionally, it focuses on recent findings linking PTMs to cardiovascular disease (CVD), highlighting the MS-based methods and workflows that have been used to study uncommon PTMs and their role in CVD. This review provides a comprehensive collection of tools and knowledge to explore the breadth of proteoforms, particularly PTMs, within their specific areas of interest in cardiovascular physiology.