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The Heart of Education: Being Called to Teach
A calling to teach inspires educators to nurture and challenge students, creating a reciprocal relationship where both students and teachers grow, learn, and contribute to a vibrant, compassionate community of lifelong learners. 2025 Childhood Education International. -
Microstructural evolution and damping response in ARB-processed ZK60 alloy
This study investigates the effect of microstructural evolution on the damping behaviour of ZK60 magnesium alloy processed via Accumulative Roll Bonding (ARB). ARB was employed at 300C for up to four cycles, significantly refining the grain structure and altering dislocation and precipitation behaviour. Comprehensive microstructural analysis revealed the formation of fine equiaxed grains (?6.7 m), dissolution of coarse precipitates, and increased dislocation density. TEM and Selected Area Diffraction (SAD) patterns confirmed dynamic recrystallisation and uniform grain orientation, while XRD patterns exhibited peak broadening and intensity changes, indicating crystallite refinement and texture evolution. Damping results showed substantial improvements in the ARB-processed alloy, particularly at low-to-mid frequencies, with up to 21% higher damping capacity than the base alloy. This enhancement is attributed to increased grain boundary sliding, dislocation interactions, and refined precipitatematrix interfaces. Both alloys exhibited similar damping responses at higher frequencies, suggesting saturation of energy dissipation mechanisms. 2025 Canadian Institute of Mining, Metallurgy and Petroleum. -
Influence of shot peening on microstructure and electrochemical behavior of al-Cu alloy; [Influence du grenaillage sur la microstructure et le comportement.]
The current study explores the effects of shot peening on the microstructural evolution and corrosion behavior of precipitation-hardened Al-Cu alloy. Microstructural analysis revealed significant grain size reduction from 100 m to 6.5 m, and this process improves grain boundary density, reduces precipitate size from 2 m to 0.5 m, and ensures a uniform elemental distribution, effectively mitigating galvanic corrosion risks. Energy-dispersive spectroscopy (EDS) confirms the homogenisation of alloying elements. At the same time, X-ray diffraction (XRD) analysis highlights crystallographic modifications, including refined crystallite size, redistributed secondary phases, and compressive residual stresses, contributing to enhanced strength and fatigue resistance. Corrosion behavior studies reveal a dramatic reduction in weight loss from 0.09 mg to 0.03 mg and a corrosion rate decrease from 3.5 10?3 mpy to 1.5 10?3 mpy, along with a noble shift in corrosion potential from ?1150 mV to ?775 mV. As observed in optical microstructures, grain refinement, residual stress introduction, and uniform surface characteristics lead to a significant shift from severe to mild corrosion attacks. Impedance analysis demonstrated improved corrosion resistance in the shot-peened alloy, evidenced by higher charge transfer resistance (Rct) and lower double-layer capacitance (Cdl). 2025 Canadian Institute of Mining, Metallurgy and Petroleum. -
Real-Time Data Fusion Algorithm for Multi-Modal Environmental Sensor Networks Using Kalman Filtering and IoT Integration
Fusion of heterogeneous, noisy, and asynchronous multimodal data streams is essential to environmental sensor networks, given the computational, memory, and energy constraints of IoT devices. This paper introduces a real-time data fusion framework integrating hybrid adaptive Kalman filtering, distributed edge computing, and seamless IoT connectivity. The proposed framework incorporates three key innovations. First, a hybrid adaptive Kalman filtering mechanism employs the Unscented Kalman Filter (UKF) sigma-point technique, augmented with Long Short-Term Memory (LSTM) neural networks and fuzzy logic, for dynamic noise correction and robust nonlinear state estimation. Second, a three-tier distributed fusion architecture employs edge computing for local data processing, reducing network latency, communication overhead, and energy consumption. Third, a modular Service-Oriented Architecture enables seamless IoT integration, remote data access, and adaptive system reconfiguration. The framework also incorporates multi-criteria fault detection that combines chi-square tests, sequential probability ratio tests, and LSTM-based predictive compensation during sensor failures. Experimental validation employed 150 sensors for urban air-quality monitoring, industrial facility surveillance, and water-quality measurement. Sensor nodes utilized ESP32-S3 microcontrollers with LoRa communication, while Raspberry Pi 4 devices served as edge gateways connected to AWS IoT infrastructure. Compared to standard Kalman filtering, the proposed method achieved: (i) 25.2% reduction in root mean square estimation error, (ii) 41% energy reduction driven by 70% communication savings through predictive transmission and edge compression, (iii) sub-100 ms end-to-end latency representing 54% improvement, and (iv) robust performance maintaining below 10% degradation at 15% sensor failure rates. 2026 Taylor & Francis Group, LLC. -
Adaptive Mesh Networking Protocol for Self-Healing Electrochemical Sensor Networks in Environmental Monitoring Applications
Sensor networks for environmental monitoring must be robust, flexible, and long-lasting, and comprehensive reviews and evaluations of adaptive mesh networking protocols for self-healing to enable autonomous operation under challenging environmental conditions are needed. The purpose of this study was to conduct an extensive review and assessment of adaptive mesh networking protocols for the self-healing of electrochemical sensor networks used in environmental monitoring. The Adaptive Mesh Networking Protocols enable the distributed autonomous sensors (distributed over vast areas or through obstructions) to dynamically route their collected data, recover when nodes fail, and extend their life (in real-time). In evaluating adaptive mesh networking protocols, we reviewed several key features, including self-healing mechanisms, adaptive routing algorithms (including their mathematical representations), methods for achieving energy efficiency, and mechanisms for securing data collection from autonomous sensor networks. Our simulation results show that our proposed adaptive mesh networking protocol achieves greater than 98% packet delivery success, even with up to 30% of nodes lost. Furthermore, we have shown that our approach can reduce the energy consumption of autonomous sensors by up to 87.5% compared to existing non-adaptive approaches. Our demonstration of real-time monitoring dashboards and a comprehensive performance analysis of the autonomous sensor networks demonstrates the feasibility of implementing adaptive mesh networking protocols into large-scale environmental monitoring projects. A significant area of focus for future research will be sensor-level self-correction to address bio-fouling remediation. 2026 Taylor & Francis Group, LLC. -
Exploring cultural contexts of dog ownership Mental health and satisfaction with life among university students in India
The rising social value of pet ownership is infuenced by social media and evidence of positive efects on well-being, leading to a rise in dog ownership in younger generations. However, the mental health outcomes of this broader shif, especially in India, have not been studied. The study explored the association between dog owners relationships, mental health, and satisfaction with life among university students. A cross-sectional correlational design was used with 250 students aged 1825 who were either dog owners or without pets. The dog owners responded to the Monash Dog Owner Relationship Scale, apart from the Mental Health Continuum and Satisfaction with Life Scale. Results showed a non-signifcant diference between mental health and satisfaction with life between dog owners and non-pet respondents. A positive relationship could not be established between dog ownership, mental health, and satisfaction with life. The dogs gender and breed infuenced the owners emotional bonding and interactions. Low perceived costs were related to a strong emotional bond with the dog, highlighting the complex nature of the pet ownership experience. Dog ownerships efect on students well-being is not universal and might depend on various individual, cultural, and contextual factors. Exploration of these human-animal interactions is warranted. 2025 John Benjamins Publishing Company. -
Influence of gravity modulation on the initiation of Rayleigh-Bard convection in ferro-nanofluids
The study investigates the influence of sinusoidal (sine wave) and non-sinusoidal (square wave, triangular wave, and sawtooth wave) gravity modulation on Rayleigh-Bard Convection in ferro-nanofluids (FNF) using both linear and nonlinear stability analyses. Controlled fluid systems are important in application situations, and hence, we have considered gravity modulation approach to control. The linear analysis based on the Venezian method is performed to determine the Rayleigh number of the problem, while the nonlinear analysis is carried out by solving the non-autonomous Lorenz equations to evaluate the heat transfer coefficient through the Nusselt number. Free-free and rigid-rigid boundary conditions for both upper and lower plates are considered along with isothermal and iso-nano concentration conditions. The purpose of the present study is to investigate the influence of initiation of convection and heat transfer in FNFs. This research focuses on analyzing the effects of various dimensionless parameters on the onset of convection and heat transfer. The results indicate that the magnetization parameters destabilize the system and enhance heat transfer. Among the four wave forms considered, square wave gravity modulation is found to facilitate greater heat transport compared to other forms of gravity modulation. In addition, the presence of ferro-nanoparticles advances the initiation of convection and enhances heat transfer. The novelty of this study lies in analyzing unconsidered aspects of gravity modulation, together with magnetic effects and nanoparticles, on the onset of convection and heat transfer in FNFs using both linear and nonlinear stability approaches. 2025 Author(s). -
Hyperchaos in a three-dimensional non-autonomous system
This paper extends the weakly nonlinear stability analysis reported by Francis et al. [J. Eng. Math. 139, 5 (2023)] to cover post-convective regimes of the gravity-modulated Rayleigh-Bard convection in a Newtonian liquid, bounded by rigid-free isothermal boundaries. Weakly nonlinear stability analysis is performed by considering second harmonics in the Fourier series expansion of temperature, while the second harmonics in the velocity field is neglected owing to the assumption of small-scale convective motions. The occurrence of hyperchaos within the three-dimensional non-autonomous system is observed, induced by modulation, emerging for varying, random combinations of frequency and amplitude values. This result has not been reported in the literature before, to the best of the authors' knowledge. Bifurcation analysis is carried out for varying combinations of modulation parameters. It is found that gravity modulation, in general, stabilizes the convective system under consideration. 2025 Author(s). -
Global stability analysis of thermofluid convection in an inclined porous layer with viscous dissipation, throughflow, and local thermal non-equilibrium effects
The onset of thermal convection in an inclined porous medium under the effect of viscous dissipation with throughflow, using a local thermal non-equilibrium model, is investigated. Darcy's law is used to describe the flow. The stability of the flow is analyzed through linear and nonlinear analyses. A linear instability analysis of disturbances in the form of rolls is performed through the normal mode technique, while the energy method is applied for nonlinear stability analysis by defining an energy functional. The boundary eigenvalue problem that emerges in the two analyses is solved using the boundary value problem solver (bvp4c) in MATLAB R2023a. The impact of the inter-phase heat transfer parameter, H, the porosity-modified conductivity ratio, ? , inclination angle, ? , and the stability parameter, ? ? , on the critical Rayleigh value, R a c ? , is systematically analyzed. The accuracy of the linear instability thresholds are validated with those reported in the existing literature. The results of linear and nonlinear theories have been compared. The study reveals that the inter-phase heat transfer parameter enhances flow stability, while the inclination angle serves as a stabilizing factor in the linear analysis but as a destabilizing factor in the nonlinear analysis, indicating the possibility of sub-critical motion. The stability across all inclination angles depends on ? ? ; specifically, ? ? acts as a stabilizing influence at smaller inclinations but exhibits a monotonic destabilizing effect at larger inclination angles. 2025 Author(s). -
Regulation of axisymmetric Rayleigh-Bard convection using boundary temperature coupling of the two circular plates
Controlled delay of regular, chaotic, and periodic regimes of instabilities is studied in the problem of axisymmetric Rayleigh-Bard convection in a vertical cylinder. A feedback control is assumed at the boundaries, which leads to a coupling of the two boundary temperatures. A classical type solution is impossible in such a situation. Hence, a novel series solution procedure is adopted to arrive at the generalized Lorenz model. Due to feedback control, delayed onset of regular convection is observed and the percentage of such a delay as a function of the controller gain parameter, K , is reported. The changes in the pitchfork bifurcation point, the homoclinic orbit, and the Hopf bifurcation point due to feedback control are highlighted with the help of a bifurcation diagram. This diagram shows that the influence of feedback control is to advance the onset of homoclinic bifurcation and delay the onset of Hopf bifurcation. The results indicate that feedback control shows preference for Hopf bifurcation and is antagonistic toward homoclinic bifurcation. The shortening of the time of existence of the strange attractor intermittent with a periodic/quasi-periodic state, which is preceded by the fully periodic motion as K increases is observed using the largest-Lyapunov-exponent plot, the bar-code plot, and the bifurcation diagram. The results coming out of the Kaplan-Yorke dimension reiterates the results depicted by other indicators concerning the influence of K on chaos. The practical importance of the control strategy that is used in the paper is also mentioned in the paper. 2025 Author(s). -
Soret-driven thermosolutal convection in bidispersive porous medium with vertical throughflow
This article investigates thermosolutal convection in bidispersive porous medium with Soret effect and vertical throughflow. The Oberbeck-Boussinesq approximation assumed and fluid flow obeys Darcy's law. Local thermal equilibrium is considered between solid and fluid phases. We analyze the system stability through linear instability, nonlinear stability (energy method), and weak nonlinear analysis. The expression for Ra is derived analytically, using the Galerkin orthogonalization technique. The Ginzburg-Landau equation is derived to get deep insight into convective amplitudes, also we explore the heat and mass transfer in the system by defining Nusselt and Sherwood numbers. The research delves into the influence of various physical parameters on the system's stability. The solutal Rayleigh number and Soret number have destabilizing property, whereas the Lewis number, momentum transfer coefficient, and permeability ratio have the stabilizing nature. The sub-critical region decreases as the Soret number increases. The strong buoyancy force delays the heat transfer and mass transfer by disrupting existing mass transfer. The critical Rayleigh number maintains symmetry over the upward and downward throughflow. The less area under the curve for average Nusselt and Sherwood number over permeability ratio implies total heat and mass transfer alleviating. 2025 Author(s). -
Prediction of CFRP and NSM-Wrapped Composite Column Capacities Using Experimentation and an Ensemble Machine-Learning Approach with SHAP Interpretation
Column capacity is an essential parameter in structural design, and its accurate determination is critical for a safe load-Transfer mechanism in structures. Also, experimental and accurate model-based assessments are critical to the column capacity evaluation. The main objective of this study is to experimentally and analytically investigate near-surface mounted (NSM) wrapped columns of different configurations and compare their capacity enhancements with the capacity enhancements of carbon fiber-reinforced polymer (CFRP). The study is also focused on developing a statistical regression model and extreme gradient boost (XG Boost), an ensemble machine-learning (ML) approach-based model, and examining both models developed for the experimental results by Shapley additive explanations (SHAP) interpretations. Therefore, the study experimentally reviewed the behavior of 24 composite columns to gain insights into experimental and code-recommended column capacities, stress-strain responses, axial stiffness, ductility factors, and failure modes. NSM-wrapped columns gained 10% strength increments, and, in comparison, the full-wrapped CFRP columns achieved 22% strength enhancement. The structural columns in a structure typically require various levels or types of strengthening, depending on their loading conditions, geometry, and material properties. With a 10% increment, the NSM technique suits columns needing lesser strength enhancements. Therefore, a key finding of the study is that the contribution of NSM longitudinal wrapping to column capacity is significant and cannot be ignored. A statistical regression model is developed for column capacity with four key parameters: percentage steel reinforcement, the extent of epoxy adhesion, the weight of the specimen, and the concrete clear cover. A model based on XG Boost, an ensemble ML approach, is also developed for the same four key parameters. The models developed are evaluated by SHAP interpretations. The SHAP analysis technique interpreted this improved model for various input-output features. The XG Boost machine-learning algorithm, developed with a coefficient of determination of 0.99, is found to be a refined regression model. Also, the study establishes that the ensemble ML approach used in tandem with SHAP analysis is a robust prediction and model interpretation tool, highlighting the significance of the percentage of steel reinforcement and the extent of epoxy adhesion over the other variables for the experimental dataset. 2026 American Society of Civil Engineers. -
Hybrid Analytical-Machine Learning Framework for SH-Wave Dispersion in Piezo-Flexoelectric Layered Structures with Imperfect Interfaces
This study presents a hybrid analytical-machine learning (ML) framework for modeling shear-horizontal (SH) wave propagation in piezo-flexoelectric (PFE) layered structures with imperfect interfacial bonding. The governing dispersion relations were derived using mechanical, electrical, and flexoelectric continuity conditions, establishing explicit links among phase velocity, wave number, layer thickness ratio, and flexoelectric coefficients. Analytical results revealed that nanoscale flexoelectricity and interfacial imperfections significantly influence wave behavior: electrically open (EO) boundaries amplify electromechanical coupling and enhance dispersion, whereas electrically shorted (ES) conditions suppress these effects, leading to reduced phase velocities. To address the computational cost associated with evaluating high-dimensional parametric spaces, ML surrogate models were incorporated. Convolutional neural network (CNN) and k-nearest neighbor (KNN) regressors accurately reproduced analytical dispersion surfaces with errors below 3% and drastically reduced computation time by more than two orders of magnitude. Classification models provided >90% accuracy in distinguishing EO and ES boundary-condition regimes, and generative artificial intelligence (AI) variational autoencoder/generative adversarial network (VAE/GAN) architectures successfully synthesized dispersion surfaces for previously unseen flexoelectric parameter ranges. The proposed hybrid framework combines the physical rigor of analytical modeling with the efficiency of modern ML surrogates, enabling rapid parametric exploration and high-fidelity prediction of SH-wave characteristics. The outcomes support accelerated design of advanced surface acoustic wave (SAW) devices, micro-electro-mechanical systems (MEMS) components, and nanoscale electromechanical systems. Future work will extend the approach to experimental validation and uncertainty-aware modeling for real-world applications. 2026 American Society of Civil Engineers. -
Generative AI: fuelling e-commerce revenue growth
Generative AI (GenAI) is a novel technology that has transformed businesses across various industries. E-commerce companies are increasingly using cutting-edge technologies, such as GenAI, that could drive revenue growth. This study leverages the lens of social-technical systems and dynamic capabilities theories to examine how e-commerce companies adopt GenAI and its subsequent impact on their revenue generation capabilities. This study investigated the factors influencing the adoption of GenAI in e-commerce companies. This study considers both Social factorstop management support, organizational readiness, competitive pressure, and vendor support) and Technical factors (security concerns, technological readiness, and AI explainability). Further, it investigates how the use of GenAI affects the development of technological capabilities and leads to financial performance, particularly in sales growth, revenue generation, profitability, and cost reduction. To validate the proposed model, we surveyed e-commerce company managers and analyzed the collected data using PLS-SEM. These findings offer valuable insights for e-commerce companies and their managers, enabling them to leverage GenAI for revenue generation. This novel study makes a significant contribution to the academic understanding of GenAI adoption and how it can be adopted for successful revenue generation. The Author(s), under exclusive licence to Springer Nature Limited 2025. -
Examining humanized bot interaction for the retail revenue growth
The increasing popularity of conversational artificial intelligence (chatbot) in retail has fuelled consumer purchase decisions. The present study measures humanbot interaction through anthropomorphism, social presence, personalization, media richness, and its role in customer engagement and continuous purchase intention for retail revenue growth. Data were collected from 366 respondents and analyzed using PLS-SEM-ANN integrated approach. To overcome the limitation of establishing only the linear relationship among variables for prediction, the study deploys nonlinear complex artificial neural network (ANN) models to determine the relative importance of the significant predictors identified through structural equation modeling (PLS-SEM). The findings of the study confirm the role of anthropomorphism, personalization, and media richness in customer engagement and customer engagement leading to continuous purchase intention. Furthermore, Chatbots in the electronic commerce space strengthen involvement, but trust and price fairness also play a positive moderating influence in shaping consumer purchase intentions. Study implications highlight the role of anthropomorphic design in the desired social presence for sustained engagement and its contribution to revenue. This study enriches the AI literature and guides organizations leveraging chatbots to create more natural and personalized interactions so retailers can better meet customer needs, foster loyalty, and stay competitive in an increasingly digital marketplace. The Author(s), under exclusive licence to Springer Nature Limited 2025. -
Probing the formation of megaparsec-scale giant radio galaxies II. Continuum and polarization behavior from magneto-hydrodynamic simulations
Context. The persistence of radiative signatures in giant radio galaxies (GRGs & 700 kpc) remains a frontier topic of research, with contemporary telescopes revealing intricate features that require investigation. Aims. This study aims to examine the emission characteristics of simulated GRGs, and correlate them with their underlying three-dimensional dynamical properties. Methods. Sky-projected continuum and polarization maps at 1 GHz were computed from five 3D relativistic magnetohydrodynamical (RMHD) simulations by integrating the synthesized emissivity data along the line of sight, with the integration path chosen to reflect the GRG evolution in the sky plane. The emissivities were derived from these RMHD simulations, featuring FR-I and FR-II jets injected at different locations of the large-scale environment and with propagation along varying jet frustration paths. Results. Morphologies, such as widened lobes from low-power jets and collimated flows from high-power jets, are strongly shaped by the triaxiality of the environment, resulting in features such as wings and asymmetric cocoons, thereby making morphology a crucial indicator of GRG formation mechanisms. The decollimation of the bulk flow in GRG jets gives rise to intricate cocoon features, most notably filamentary structuresmagnetically dominated threads with lifespans of a few mega-year. High jet power cases frequently display enhanced emission zones at mid-cocoon distances (alongside warmspots around the jet head), contradicting the interpretations of the GRG as a restarting source. In such cases, examining the lateral intensity variation of the cocoon may reveal the sources state, with a gradual decrease in emission suggesting a low active stage. This study highlights that applying a simple radio powerjet power relation to a statistical GRG sample is unfeasible, as it depends on growth conditions of individual GRGs. Effects such as inverse-Compton cooling due to cosmic microwave background photons and matter entrainment significantly impact the long-term emission persistence of GRGs. The diminishing fractional polarization with GRG evolution reflects increasing turbulence, underscoring the importance of modeling this characteristic further, particularly for even larger-scaled sources. The Authors 2025. -
Euclid: Early Release Observations of ram-pressure stripping in the Perseus cluster: Detection of parsec-scale star formation within the low surface brightness stripped tails of UGC 2665 and MCG +07-07-070
Euclid is delivering optical and near-infrared imaging data over 14 000 deg2 on the sky at spatial resolution and surface brightness levels that can be used to understand the morphological transformation of galaxies within groups and clusters. Using the Early Release Observations (ERO) of the Perseus cluster, we demonstrate the capability offered by Euclid in studying the nature of perturbations for galaxies in clusters. Filamentary structures are observed along the discs of two spiral galaxies, UGC 2665 and MCG +07-07-070, with no extended diffuse emission expected from tidal interactions at surface brightness levels of a30 mag arcseca 2. The detected features exhibit a good correspondence in morphology between optical and near-infrared wavelengths, with a surface brightness of a25 mag arcseca 2, and the knots within the features have sizes of a 100 pc, as observed through IE imaging. Using the Euclid, CFHT, UVIT, and LOFAR 144 MHz radio continuum observations, we conducted a detailed analysis to understand the origin of the detected features. We constructed the Euclid IEaYE, YEaHE, and CFHT u ar, g ai colour-colour plane and show that these features contain recent star formation events, which are also indicated by their H? and NUV emissions. Euclid colours alone are insufficient for studying stellar population ages in unresolved star-forming regions, which require multi-wavelength optical imaging data. There are features with red colours that can be explained by dust being stripped along with the gas in these regions. The morphological shape, orientation, and mean age of the stellar population, combined with the presence of extended radio continuum cometary tails can be consistently explained if these features formed during a recent ram-pressure stripping event. This result further confirms the exceptional qualities of Euclid in the study of galaxy evolution in dense environments. 2025 EDP Sciences. All rights reserved. -
The birth of Be star disks: I. from localized ejection to circularization
Context. Classical Be stars are well known to eject mass to build up a disk, but the details governing the initial distribution and subsequent evolution of this matter into a disk are in general poorly constrained through observations. Aims. By combining high-cadence time-series spectroscopy with contemporaneous space photometry from the Transiting Exoplanet Survey Satellite (TESS), we have sampled about 30 mass ejection events in 13 Be stars. Our goal is to constrain the geometrical and kinematic properties of the ejecta as early as possible, facilitating the investigation into the material's initial conditions and evolution, and understanding its interactions with preexisting material. Methods. The photometric variability is analyzed together with measurements of the at-times rapidly changing emission features in order to identify the onset of outburst events and obtain information about the geometry of the ejecta and how it changes over time. Short-lived line asymmetries display oscillation cycles (tefl frequencies), which are compared to photometric and stable spectroscopic frequencies. Results. All Be stars observed with sufficiently high cadence during an outburst are found to exhibit rapid oscillations of line asymmetry with a single frequency in the days following the start of the event. For a given star this circumstellar frequency may differ only slightly from event to event even when the outbursts they are associated with have different properties. These circumstellar frequencies are typically between 0.5 to 2 d- 1, and are generally near photometric frequencies. They are slightly below prominent (generally stable) spectroscopic frequencies seen in photospheric absorption lines. The emission asymmetry cycles break down after roughly 5- 10 cycles, with the emission line profile converging toward approximate symmetry shortly thereafter. In photometry, several frequencies typically emerge at relatively high amplitude at some point during the mass ejection process. Conclusions. In all observed cases, freshly ejected material was initially constrained within a narrow azimuthal range, indicating it was launched from a localized region on the stellar surface. The material orbits the star with a frequency consistent with the near-surface Keplerian orbital frequency. This material circularizes into a disk configuration after several orbital timescales. This is true whether or not there was a preexisting disk at the time of the observed outburst. We find no evidence for precursor phases prior to the ejection of mass in our sample. The several photometric frequencies that emerge during outburst are at least partially stellar in origin. The Authors 2025. -
Probing the formation of megaparsec-scale giant radio galaxies: I. Dynamical insights from magnetohydrodynamic simulations
Context. Constituting a relatively small fraction of the extended-jetted population, giant radio galaxies (GRGs) form in a wide range of jet and environment configurations. This observed diversity complicates the identification of the growth factors that facilitate their attainment of megaparsec scales. Aims. This study aims to numerically investigate the hypothesized formation mechanisms of GRGs extending ?1 Mpc in order to assess their general applicability. Methods. We employed tri-axial ambient medium settings to generate varying levels of jet frustration and simulated jets with a low and a high power from different locations in the environment. This approach formulated five representations evolving under a relativistic magnetohydrodynamic framework. Results. The emergence of distinct giant phases in all five simulated scenarios suggests that GRGs may be more common than previously believed. This prediction can be verified with contemporary and forthcoming radio telescopes. We find that different combinations of jet morphology, power, and evolutionary age of the formed structure hold the potential to elucidate different formation scenarios. In all of these cases, the lobes are overpressured, prompting further investigation into pressure profiles when jet activity ceases, potentially distinguishing between relic and active GRGs. We observed a potential phase transition in GRGs marked by differences in lobe expansion speed and pressure variations compared to their smaller evolutionary phases. This suggests the need for further investigation across a broader parameter space to determine if lobe evolution in GRGs fundamentally differs from smaller radio galaxies. The axial ratio analysis reveals self-similar expansion in rapidly propagating jets, while there is a notable deviation when the jet forms wider lobes. Overall, this study emphasizes that multiple growth factors simultaneously at work can better elucidate the current-day population of GRGs, including scenarios such as the growth of GRGs in dense environments, GRGs extending several megaparsecs, development of GRGs in low-powered jets, and the formation of morphologies such as GRG-XRGs. The Authors 2025. -
Fe doped ZnO nanomaterials for energy storage applications as high-capacitance supercapacitor electrodes
Enhancing the performance of electrode materials is essential for developing high-capacitance supercapacitors, and transition-metal-doped metal oxides have shown particular promise in this regard. In this work, Fe-doped ZnO nanostructures were synthesized using a sonochemical method and systematically examined through XRD, SEM, TEM, XPS and UVvis analyses to verify Fe incorporation and the resulting changes in crystallinity, morphology and optical behaviour. The structural modifications induced by Fe were evident in the electrochemical response, with the optimized ZnOFe sample delivering a specific capacitance of 11.4 F g?1 at 0.1 A g?1 in the two-electrode system and 462 F g?1 in the three-electrode system, both measured in 3 M KOH electrolyte. A CR2032 coin cell assembled with this material achieved an energy density of 1.6 Wh kg?1 and a power density of 2890.93 W kg?1, demonstrating an effective balance between energy storage and power output. These findings highlight the suitability of Fe-doped ZnO as a tunable electrode material and support its further exploration in advanced supercapacitor systems. This journal is The Royal Society of Chemistry, 2026.