Search Results (221)

Federated learning (FL) is a promising approach for training distributed machine learning models while preserving clients’ data privacy. However, in real-world FL systems, data are often not independent and identically distributed (non-IID). This heterogeneity can slow convergence, degrade model performance, and increase client drift. To address these challenges, numerous methods have been proposed to mitigate non-IID data effects by optimizing client selection, local training, and model aggregation strategies. Despite their effectiveness in improving performance and efficiency, these methods rarely consider fairness across clients. Improving global accuracy does not guarantee balanced participation, influence, or outcomes, which may lead to biased model behavior across clients. In this survey, we review existing non-IID mitigation methods in FL from a fairness perspective and provide a systematic analysis of their implicit impact on client participation and influence. Unlike prior surveys that treat fairness as a separate research direction, this work analyzes how these methods designed for non-IID mitigation implicitly shape fairness outcomes across clients. Our taxonomy classifies existing methods into three categories—fairness-aware, semi-fairness-aware, and fairness-unaware—based on their design strategies for client selection and model aggregation. Using this taxonomy, we analyze the advantages, trade-offs, and limitations of each category and highlight that mitigating non-IID data does not guarantee fairness across clients. Finally, we identify open challenges and outline future directions, including system-level FL design that jointly considers non-IID mitigation and fairness and the development of standardized fairness evaluation metrics. Overall, this survey aims to provide a structured perspective on the relationship between non-IID mitigation and fairness and support the development of more balanced and scalable FL systems under non-IID conditions. Full article

Protein chromatography, the process of separating desired proteins from other elements in a chemical solution, is used widely in the manufacturing of biotherapeutics. Many parameters involved in this process must be tested extensively during process development, which results in higher costs of the biotherapeutics. Modeling and simulation of the chromatography process could reduce the amount of time and resources spent on running live experiments, potentially lowering therapeutic costs. In this work, we consider the transport equation coupled with adsorption isotherm equations to model the process using a porous membrane as the medium for protein adsorption. For the adsorption isotherm models, we consider both an explicit function and an implicitly defined relationship. We use a semi-implicit, finite element solution implemented in FEniCS to solve the modeling equations and simulate the adsorption phase of membrane chromatography. We conduct an initial parameter space investigation to establish acceptable ranges on each parameter and then apply numerical optimization methods to determine optimal parameter values for the modeling equations. We solve the single-parameter optimization problem by applying a line search algorithm and a multi-parameter optimization problem using built-in functionality in FEniCS which applies the adjoint method. The single-parameter optimization algorithm is applied with an explicit adsorption model while the multi-parameter optimization algorithm is applied to both the explicitly and implicitly defined adsorption models. Both algorithms yield optimal parameter values that provide much more accurate simulation results. Last, we conduct a sensitivity analysis to establish which parameters most affect the model solution in an effort to reduce computational effort in the multi-parameter optimization problem. Results indicate that two parameters most affect the optimization results and suggest that the multi-objective optimization could be modified to adjust certain parameter values at different simulation times to reduce the computation time. Full article

Background/Objectives: Collaboration between medical and dental professionals is essential for comprehensive, patient-centred healthcare, yet the two fields often remain separate in education and practice. This study explored attitudes, experiences, and perceptions of interprofessional relationships among medical and dental faculty and students at a Croatian university. Methods: A qualitative study using semi-structured interviews was conducted. Thirty-nine participants, including faculty members and students from medicine and dentistry, were interviewed. Data were analyzed using thematic analysis to identify patterns and themes related to interprofessional perceptions and collaboration. Results: Participants generally reported mutual respect, although their accounts revealed subtle hierarchies, persistent stereotypes, and implicit biases. Overt animosity was rare, often limited to humour, though instances of disrespect and status differentiation were described. Educational collaboration was minimal, with siloed curricula and few structured initiatives, while clinical collaboration was described as largely case-dependent and centred on referral rather than coordinated care. Personal exposure to the other profession mitigated some biases, suggesting that social proximity influences professional perceptions. Conclusions: Despite overall respect, participants identified structural, cultural, and educational factors that limited opportunities for interprofessional engagement within the studied setting. The findings suggest that creating opportunities for structured interprofessional learning and collaborative clinical practice may strengthen professional understanding, support more integrated models of care, and ultimately contribute to improved patient-centred healthcare. Full article

The adaptive regulation of student productivity remains a challenging problem in technology-enhanced learning environments due to the continuous and uncertain nature of cognitive effort, attention, and behavioral fluctuations. While existing educational intervention models are predominantly based on discrete-time decision frameworks, they often provide limited support for the representation of stochastic productivity dynamics and continuous effort adaptation. This paper proposes a continuous-time stochastic optimal control framework for adaptive effort allocation in student productivity regulation. The learner productivity level is modeled as a bounded stochastic diffusion process evolving on the interval ([0, 1]), where the drift and diffusion coefficients depend on both effort allocation and learner-specific psychological characteristics. The control objective is formulated as the maximization of an expected cumulative productivity reward penalized by excessive cognitive effort over a finite study horizon. Using the Hamilton–Jacobi–Bellman (HJB) framework, we derive an optimal state-dependent feedback policy that dynamically adjusts effort allocation according to the current productivity level, the remaining study horizon, and the learner profile. We establish the well-posedness of the controlled stochastic dynamics and show that the productivity state remains invariant within the admissible interval. The resulting HJB equation is solved numerically using a semi-implicit finite-difference approximation combined with iterative feedback updates. Simulation experiments conducted on synthetic learner profiles illustrate the qualitative behavior of the proposed controller under heterogeneous psychological configurations. Compared with constant-effort and threshold-based heuristic strategies, the adaptive feedback policy produces smoother productivity trajectories and more stable effort allocation patterns under stochastic perturbations. The proposed framework provides a mathematically grounded approach for studying adaptive productivity regulation under uncertainty and establishes a foundation for future data-driven calibration and personalized intervention systems. Full article

This study conducted a numerical simulation of laminar flow within a cylindrical pipe using a semi-implicit method. The full Navier–Stokes equations in cylindrical coordinates were solved, with modifications to the SIMPLE algorithm to handle pressure-linked equations. We evaluated three key thermophysical parameters—dynamic viscosity, specific heat capacity, and thermal conductivity—under both constant and variable conditions in the entrance region. Due to the process’s two-dimensional, time-dependent nature, third-kind boundary conditions were used to accurately model the effects of ambient temperature, external wind, and the pipe’s geometric and physical features. From the numerical results, we analyzed the velocity field, pressure distribution, surface friction coefficient, and temperature distribution at various pipe cross-sections. These findings are of practical and scientific importance: they offer insights into the hydrodynamics and thermal behavior of the internal flow and enhance understanding of fluid flow and heat transfer, improving predictive models. This advancement supports better design and operational control in pipeline systems. Full article

Aiming at the challenging issue of nonlinear coupling control between cooling intensity and solidification rate in the secondary cooling zone of round billet continuous casting, this study proposes an efficient 3D temperature field modeling method that integrates hybrid coordinate systems with equal-area meshing. The model is applicable to the temperature range of 800–1520 °C during the continuous casting process. With the modeling strategies of constructing an r-θ-z hybrid coordinate system and designing a dynamic equal-area meshing method, and combined with a topological structure optimization algorithm, the geometric adaptability and numerical stability of the model are significantly improved. Based on this, an explicit-semi-implicit dual-mode finite difference solution model is developed, where the explicit scheme meets real-time online calculation requirements, and the semi-implicit scheme combined with preconditioned Gauss–Seidel iteration enables high-precision offline simulation. Furthermore, a boundary condition model incorporating adaptive mold heat flux correction and multi-mechanism heat transfer in the secondary cooling zone is established. Based on Microsoft Visual Studio 2019 (Version 16.11) C++ development, SIMD vectorization and temperature gradient threshold optimization technologies are employed, resulting in a 35% improvement in computational efficiency. Industrial validation results show that, taking 42CrMo steel with a casting speed of 0.24 m/min and a cross-section of φ600 mm as an example, the deviation between the calculated surface temperature (887 °C) and the measured value (876 °C) of the round billet in the straightening zone is only 11 °C, and the calculation error of the cold billet diameter is only 0.325% (with a calculated value of 597.548 mm and a measured average value of 599.5 mm), both meeting the accuracy requirements for engineering applications. The model breaks through the limitations of traditional empirical formulas and provides theoretical support for digital control of continuous casting processes and quality optimization of high-alloy steels. Full article

Makerspaces can serve as distributed urban infrastructures for repair, reuse, tool sharing, and peer learning, yet their contributions to circular economy (CE) goals often occur without being explicitly recognized or framed as CE practices. Inspired by practice theory and the literature on quiet sustainability, this study introduces implicit circularity as circular practices enacted without an explicit sustainability/CE framing by participants, and examines how such practices shape bottom-up circular transitions. Using reflexive thematic analysis informed by constructivist grounded theory procedures, we examined three linked questions: which circular practices occur in makerspaces and how they cluster into domains, how these practices vary across makerspace types, and which barriers and governance arrangements shape makerspaces’ consolidation as circular urban infrastructure. A qualitative multi-method design was employed in Czechia, combining field mapping with in-depth qualitative inquiry. Data included 40 semi-structured interviews with makerspace founders and operators, documentary analysis based on websites, social media, event listings, rules, and other documents, and 21 observations. Using reflexive thematic analysis informed by constructivist grounded theory procedures, we analyzed how circular practices cluster into domains, how implicit versus explicit circularity varies across makerspace types, which barriers constrain makerspaces’ consolidation as circular urban infrastructure, and what governance arrangements could mitigate them. Circularity was dominated by implicit, routine practices rather than formal, CE-branded programs. Three practice domains were identified: repair and maintenance, material flows, and learning/education. Explicit programming was comparatively less common and context-dependent. Barriers formed a reinforcing system spanning institutional fragmentation and coordination deficits, capability gaps, infrastructural constraints, and tensions around autonomy and legitimacy, which together kept many circular contributions low-visibility. Makerspaces constitute an under-recognized form of circular micro-infrastructure that couples technical capacity with social learning and can translate CE ambitions into everyday practice. To mobilize these latent capacities, cities need hybrid governance, especially light-touch coordination platforms, long-horizon operational support, and integration of makerspaces into municipal material-flow systems and repair/reuse strategies. The study offers a practice-based framework and a cross-case typology to support comparative research and grounded urban CE policy design. Full article

In this paper, we propose and numerically investigate a fractional T system. As a fractional generalization of the classical T model, the fractional order serves as a memory parameter governing the system dynamics. By employing the fractional stability criterion, the local stability of the equilibrium points is analyzed, and the existence of Hopf bifurcation is characterized. To efficiently simulate the long-time dynamics induced by fractional memory, a linear semi-implicit numerical scheme accelerated by a sum-of-exponentials approximation of the Caputo derivative is developed. The proposed scheme is shown to be stable and enables a significant reduction in computational cost compared with classical L1 and Grünwald–Letnikov methods. Numerical experiments, including time series, phase portraits, Lyapunov exponent computations, and bifurcation diagrams, demonstrate that varying the fractional order leads to transitions among stable, periodic, and chaotic regimes. In particular, pronounced transient dynamics are observed as the fractional order approaches its critical value, highlighting the memory-induced effects inherent in fractional-order systems. Full article

Understanding the coupled dynamics of groundwater flow and salinity transport is essential for the sustainable management of aquifer systems, particularly in irrigated and semi-arid regions where evaporation, recharge variability, and groundwater abstraction strongly influence hydrogeological regimes. In multilayer porous media, groundwater-level fluctuations and salt migration processes are closely interconnected, since hydraulic gradients control solute transport while salinity variations may affect flow behaviour through density-related mechanisms. In this study, a nonlinear mathematical model is developed to describe groundwater-level evolution and salt transport within a two-layer porous medium consisting of a phreatic layer and an underlying confined aquifer. The model accounts for filtration processes, interlayer hydraulic exchange, density-dependent effects, and external forcing factors including surface recharge, evaporation, and pumping. For numerical implementation, the governing equations are discretized using a finite-difference scheme with central spatial approximations and an implicit Crank–Nicolson-type temporal formulation. A hybrid second-order time approximation is introduced for the main-layer equation to improve numerical smoothness and stability. The resulting tridiagonal algebraic systems are solved using the Thomas algorithm within an iterative quasi-linearization framework, ensuring both computational efficiency and numerical robustness. Simulation results reveal a clear difference in the dynamical behaviour of the two layers. The phreatic aquifer exhibits rapid and high-amplitude responses to external forcing, whereas the confined aquifer demonstrates slower and smoother hydraulic and geochemical adjustments. Sensitivity analysis further identifies the filtration coefficient, transmissivity, porosity, density-related parameters, surface flux, and pumping intensity as the dominant factors governing groundwater dynamics and salinity redistribution. The proposed modelling framework provides a reliable tool for analysing coupled groundwater–salinity processes and offers a scientifically grounded basis for groundwater monitoring, salinization risk assessment, and sustainable aquifer management. Full article

Existential, spiritual, and religious themes often evoke strong emotions in therapy, yet little is known about how clients’ emotion regulation relates to these aspects. Spiritual psychotherapy for inpatient residential and intensive treatment (SPIRIT) integrates meaning in life within a cognitive-behavioral treatment (CBT) framework in acute and intensive mental health care and provides an appropriate context for examining this. This qualitative study explores: (1) clients’ beliefs about expressing, managing, or suppressing emotions related to meaning in life, spirituality, or religion (MSR); (2) how emotion regulation strategies (e.g., reappraisal, acceptance, and distress tolerance) are influenced by addressing MSR in therapy; and (3) whether engaging with MSR activates emotion regulation mechanisms for clients’ experienced distress. We analyzed 118 client evaluation forms and 19 semi-structured client interviews using a thematic approach informed by emotion regulation theory. SPIRIT-CBT made implicit beliefs about (MSR-related) emotion regulation explicit, and group interactions sometimes led to changes. Clients showed various regulation strategies, for example: MSR-based reappraisal, connectedness, reflection, and positive refocusing. However, emotional tension and suppression were also reported. Particularly from the interviews, it emerged that the therapy facilitated regulation mechanisms, including narrative processing, perspective shifting, sense-making, and social belonging. Focusing on MSR and existential themes addresses an important gap in mental health care and may contribute to supporting clients’ emotional recovery and overall well-being. Full article

This paper investigates co-continuous structures in immiscible polymer blends through three-dimensional (3D) computational calculations based on a multiphase phase-field equation for fluid flow. The mathematical model describes phase separation with the Cahn–Hilliard (CH) equation and fluid motion with the incompressible Navier–Stokes (NS) equations. Both polymers are treated as Newtonian viscous fluids, and the model includes surface tension, viscosity, and volume fraction effects. A semi-implicit finite difference method (FDM) solves the CH equation, and a projection method maintains the incompressibility of the flow field. Multigrid techniques solve the nonlinear systems efficiently. In addition, a connectivity-based detection algorithm determines whether a phase forms a connected structure that reaches all boundaries of the numerical domain. The numerical results show that the morphology changes from a droplet–matrix structure to a co-continuous structure as the volume fraction increases. The interfacial area per unit volume reaches a local maximum near the transition between these two regimes. Full article

This paper develops a two-dimensional fully Lagrangian meshless fluid–structure interaction solver by integrating the Moving Particle Semi-implicit (MPS) method with continuum mechanics to investigate the nonlinear interaction between waves and floating bodies. The stability and accuracy of the proposed model are validated through several benchmark cases. Furthermore, the solver is employed to analyze the dynamic response of a flat plate floating body in waves. The numerically generated waves exhibit a minimum error of approximately −0.5% and a period consistent with theoretical values, maintaining a smooth and continuous free surface. Due to the inherent limitations of the two-dimensional wave-floating body simulation, the Root Mean Square Error (RMSE) of the interaction results ranges from 5.4% to 15.2%. These findings indicate that the proposed method provides a valuable reference for the design and analysis of floating structures in ocean engineering. Full article

Dam-break flows over erodible beds represent a complex fluid–solid interaction problem characterized by extreme turbulence and rapid morphological changes. This study investigates the dynamics of such flows over inclined granular beds by integrating an advanced Moving Particle Semi-implicit (MPS) method. To accurately resolve the transition between static and kinetic granular regimes, I introduce a state-dependent tangential friction model that explicitly distinguishes between sticking and sliding conditions based on local force balance. Furthermore, the momentum exchange between the fluid and solid phases is rigorously modeled using the porosity-dependent drag formulation. The numerical results demonstrate a distinct regime shift in energy dissipation: while low-inclination beds (0–$4\%$) promote distributed sediment transport, steep-inclination beds (8–$12\%$) trigger a localized “Shielding Effect”. In this regime, the surge’s horizontal kinetic energy is rapidly converted into vertical potential energy and frictional work, forming a deep sacrificial scour hole that acts as a topographical energy sink. This mechanism effectively mitigates the destructive potential of the surge in downstream areas. The proposed method provides a robust tool for predicting morphological feedback and designing topographical countermeasures for disaster mitigation in hydraulic and coastal environments. Full article

Brushless motors are characterized by extreme power density, thermal management and steady dynamic performance which are commonly utilized in aerospace, high-end robotics and precision medical equipment. The nonlinear solutions and the corresponding stabilities in the brushless DC motor system reveal the inherent current-speed properties. In this study, the semi-analytical solutions and the corresponding stabilities in the brushless DC motor system are obtained via a discretized mapping method. The governing equations are discretized into nonlinear polynomials through an implicit mid-point scheme. The semi-analytical solution trees from period-1 to period-2 and period-1 to period-4 are obtained. Some independent periodic solutions are observed. The stability and bifurcations are obtained quantitatively where the period-doubling bifurcations trigger the bifurcation trees and saddle-node bifurcations bound the independent solutions. Interestingly, unstable bifurcation trees are also observed. For verification, numerical simulation is conducted. The stable and unstable properties of current–velocity coupling dynamics are discussed finally. Full article

This paper presents a computational study of wave–bathymetry and wave–structure interaction problems using advanced numerical techniques based on high-fidelity, two-phase Navier–Stokes (TpNS) flow and reduced-order, fully nonlinear potential flow models. For high-fidelity simulations, the TpNS equations are discretized using the finite-element method, with free-surface evolution captured through a hybrid level-set (LS) and volume-of-fluid (VOF) formulation. A monolithic, phase-conservative LS equation is introduced to mitigate mass loss and interface smearing, combined with a semi-implicit projection scheme. Hydrodynamic forces are resolved using a high-order, phase-resolving cut finite-element method (CutFEM), which enables the representation of complex solid geometries within a fixed background mesh. An equivalent polynomial of Heaviside and Dirac distributions ensures accurate evaluation of surface and volume integrals. Hence, no explicit generation of cut cell meshes, adaptive quadrature, or local refinement is required. For reduced-order modeling, a fast regularized boundary integral method (RBIM) is employed to solve the fully nonlinear potential flow. Singular and near-singular integrals are treated using a subtract-and-addition technique based on auxiliary functions derived from Stokes’ theorem, allowing direct application of high-order quadrature without conventional boundary element discretization. An arbitrary Lagrangian–Eulerian (ALE) formulation is adopted to enforce free-surface boundary conditions while avoiding excessive mesh distortion. The proposed approaches are applied to investigate highly nonlinear wave transformation over complex bathymetry and wave-induced dynamics of floating structures, including eddy-making damping effects. Numerical results are validated against experimental measurements. These two modeling approaches represent complementary levels of physical fidelity and computational efficiency, and their systematic comparison clarifies the trade-offs between computational accuracy, efficiency, and cost for practical marine problems. Full article