Transylvania University of Brașov

Classical thermoelastic-diffusion theories are inadequate at micro- and nanoscales because they assume instantaneous local response of heat and mass fluxes, predict infinite propagation speeds, and completely neglect long-range microstructural interactions. This paper introduces the first thermodynamically consistent theoretical framework that simultaneously overcomes all three limitations: it extends the Lord–Shulman generalized theory by incorporating nonlocal heat conduction of Guyer–Krumhansl type with its own thermal length scale, a newly proposed nonlocal mass-diffusion law governed by an independent diffusive length scale, and separate phase-lag relaxation times for thermal and chemical-potential gradients. The model is analytically solved for an infinite isotropic solid containing a traction-free spherical cavity subjected to a pulsed thermal shock and an exponentially decaying chemical potential at the inner surface. Numerical results for copper reveal three striking physical effects that are entirely absent in all previous local and single-nonlocality models: temperature and concentration disturbances penetrate far deeper into the material while their spatial gradients become remarkably smoother; peak displacements and thermoelastic stresses are reduced by more than half; and the coupled thermo-elasto-diffusive waves experience significantly stronger attenuation throughout the medium. These distinctive size-dependent phenomena originate from long-range interactions among energy carriers and diffusing species. The proposed framework therefore enables accurate performance prediction and deliberate microstructural tailoring in modern nanoscale devices, offering substantially improved reliability for MEMS thermal actuators, faster hydrogen charging in metallic microspheres, safer laser-triggered drug-release nanocapsules, and reduced thermoelastic losses in high-frequency nanoresonators.

Integral inequalities, in general, serve as powerful tools for various applications. Specifically, when an integral operator is used as a predictive tool, an integral inequality can play a key role in defining, quantifying, and analyzing such processes. Real-valued functions over a fuzzy domain, also referred to as real-valued fuzzy functions, offer a valuable approach for incorporating uncertainty into prediction models. In this paper, using a straightforward proof method over a newly defined triangular LPL_PLP​ fuzzy space, we establish several new refinements for integral forms of the classical Hölder’s and newly defined triangular Hölder’s-like inequality. Numerous existing inequalities linked with the triangular Hölder’s-like inequality over a fuzzy domain can be improved through the newly obtained ones, as illustrated through applications such as the triangular Hölder’s power-mean-like integral inequality, triangular Cauchy–Schwarz-like inequality, triangular Minkowski’s-like inequality, and triangular Beckenbach’s-like inequality over a fuzzy domain. Additionally, our outcomes represent significant progressions in the field of mathematics.

The implication of buoyancy reveals complex, non-linear behavior in numerous mass and thermal transfer processes. Quadratic thermal and solutal buoyancy effects become significant in high-temperature and high-concentration systems where density variations are strongly non-linear. Additionally, cross thermo-solutal buoyancy interactions play a crucial role in alloy solidification, geophysical flows, and oceanography, where the stability and density of the flow are influenced by the combined action of thermal and solutal gradients. This study aims to investigate quadratic thermal and solutal buoyancy effects in nanofluid convection through a vertical frustum of a cone, emphasizing the Soret phenomenon. The partial differential equations derived from the mathematical formulation using non-similarity variables were solved numerically. The governing non-similar partial differential equations are solved numerically using the bivariate pseudo-spectral local linearization method, which combines quasi-linearization and spectral collocation for enhanced accuracy. The results are compared to asymptotic series solutions in order to evaluate the reliability of the proposed methodology. Graphical results illustrate how quadratic and mixed buoyancy parameters influence momentum, heat, and mass transfer characteristics. The findings provide new insights into the physics of non-linear buoyancy-driven nanofluid convection in conical geometries relevant to thermal, geophysical, and chemical systems.

Fast growing species such as willow have been found to be a viable alternative for bio-energy production. Establishment of willow crops requires a series of operations, among which planting is important for their success. Partly mechanized planting has been studied lately in terms of productivity and costs, and it was found to be a viable alternative for small and dispersed plots. However, no research has addressed its suitability in terms of work intensity. One important assumption is that physical strain would be higher in such operations, mainly due to an intense use of the upper limbs, probably leading to a high cardiovascular workload. This study evaluated the level of physical workload in partly mechanized willow planting operations by heart rate measurements taken on six subjects, which were observed during all the common planting tasks. Close to 65 hours of observations were taken at a rate of one second, and the heart rate increment was used as the main indicator to characterize the workload of planting work. The findings indicate that there was a task-based variability in cardiovascular response (ca. 87 to 96 bpm) and in the heart rate increment among the subjects (ca. 14 to 28%). In addition, there was a differentiation in terms of heart rate increment among the planting tasks. Nevertheless, most of the data indicated a low to moderate cardiovascular workload. Although these results validate partly mechanized planting as a suitable alternative in terms of cardiovascular output, future studies should evaluate other ergonomic conditions such as the biomechanical exposure and the risks of developing musculoskeletal disorders.

This systematic review investigates the integration of artificial intelligence (AI) and information and communication technologies (ICT) in physical education across all educational levels. Physical education is uniquely centered on motor skill development, physical activity engagement, and health promotion—outcomes that require tailored technological approaches. Through the analysis of recent empirical studies, the main areas where digital technologies contribute to pedagogical innovation are highlighted—such as personalized learning, real-time feedback, student motivation, and educational inclusion. The findings show that AI-assisted tools facilitate differentiated instruction and self-regulated learning by adapting to students’ individual performance levels. Technologies such as wearables and augmented reality (AR)/virtual reality (VR) systems increase engagement and support the participation of students with special educational needs. Furthermore, AI contributes to more efficient and objective assessment of motor performance, coordination, and movement quality. However, significant structural and ethical challenges persist, such as unequal access to digital infrastructure, lack of teacher training, and concerns related to personal data protection. Teachers’ perceptions reflect both openness to the educational potential of AI and caution regarding its practical implementation. The review concludes that AI and ICT can substantially transform physical education, provided that coherent policies, clear ethical frameworks, and investments in teachers’ professional development are in place.