Search Results (593)

Background/Objectives: Collaboration in mental health care is essential for implementing a model oriented towards the psychosocial rehabilitation of people based on multifaceted interventions involving different actors and sectors of society to respond to demands. Despite the benefits presented by the scientific evidence, there are still many barriers to collaborative care, and professionals continue to struggle in reorienting their conduct. The current situation demands organization and the framing of well-founded action plans to overcome challenges, which in turn requires a detailed understanding of collaborative practices in mental health care and their conceptual boundaries. A concept analysis was undertaken to propose a working definition of collaborative practices in mental health care (CPMHC). Methods: This paper used the Walker and Avant concept analysis method. This includes identifying the defining concept attributes, antecedents, consequences, and empirical referents. A literature search was carried out from November 2024 to February 2025 in three databases (Medline, CINAHL, and LILACS), considering studies published between 2010 and 2024. Results: The final sample of literature investigated consisted of 30 studies. The key attributes were effective communication, building bonds, co-responsibility for care, hierarchical flexibility, articulation between services, providers and community, monitoring and evaluating of care processes, and attention to the plurality of sociocultural contexts. Conclusions: This comprehensive analysis contributes to guiding future research and policy development of collaborative practices in mental health, considering the individual, relational, institutional, and social levels. Further research is possible to deepen the understanding of the production of collaborative practices in mental health in the face of the complexity of social relations and structural inequities. Full article

Steel is an important product in many engineering sectors; however, steelmaking remains one of the largest ${\mathrm{CO}}_2$ emitters. Therefore, new governmental policies drive the steelmaking industry toward a cleaner and more sustainable operation such as the gas-based direct reduction–electric arc furnace process. To become carbon neutral, utilizing more scrap is one of the feasible solutions to achieve this goal. Addressing knowledge gaps regarding scrap heterogeneity (size, shape, and composition) is essential to evaluate the effects of increased scrap ratios in basic oxygen furnace (BOF) operations. This review systematically examines heat and mass transfer correlations relevant to scrap melting in BOF steelmaking, with a focus on low Prandtl number fluids (thick thermal boundary layer) and dense particulate systems. Notably, a majority of these correlations are designed for fluids with high Prandtl numbers. Even for the ones tailored for low Prandtl, they lack the introduction of the porosity effect which alters the melting behavior in such high temperature systems. The review is divided into two parts. First, it surveys heat transfer correlations for single elements (rods, spheres, and prisms) under natural and forced convection, emphasizing their role in predicting melting rates and estimating maximum shell size. Second, it introduces three numerical modeling approaches, highlighting that the computational fluid dynamics–discrete element method (CFD–DEM) offers flexibility in modeling diverse scrap geometries and contact interactions while being computationally less demanding than particle-resolved direct numerical simulation (PR-DNS). Nevertheless, the review identifies a critical gap: no current CFD–DEM framework simultaneously captures shell formation (particle growth) and non-isotropic scrap melting (particle shrinkage), underscoring the need for improved multiphase models to enhance BOF operation. Full article

Transonic/supersonic wind tunnels are indispensable equipment for advanced aircraft to operate across subsonic, transonic, and supersonic regimes. The deformation of the flexible nozzle is the key to accurately controlling the Mach number of transonic wind tunnels. However, solving the deformation of flexible wall plates remains challenging due to the highly nonlinear relationship between wall loading and deformation, as well as the lack of simple yet effective mathematical models under complex boundary conditions. To accurately describe the deformation of flexible wall plates and improve computational efficiency, this study systematically investigates the deformation characteristics of flexible walls in two orthogonal directions and proposes an orthogonal beam function (OBF) model for characterizing small-deflection deformations. For large-deflection deformations in a flexible wall, an elliptic integral (EI) solution is introduced, and the OBF model is correspondingly modified. Experimental validation confirms that the OBF model effectively describes large-deflection deformations in a flexible wall. This research contributes to solving large-deflection deformation in flexible wall plates, enhancing both computational efficiency and accuracy. Full article

The escalating climate crisis and global disruptions have prompted a critical re-evaluation of operations management within manufacturing and supply systems. This conceptual article addresses the theoretical and strategic gap in aligning resilience and sustainability by proposing an Integrated Sustainable Operational Strategy (ISOS) framework. Drawing on systems theory, circular economy principles, and sustainability science, the framework synthesizes multiple operational domains—circularity, localization, digital adaptation, and workforce flexibility—across macro (policy), meso (organizational), and micro (process) levels. This study constructs a conceptual model that explains the interdependencies and trade-offs among strategic operational responses in the Anthropocene era. Supported by multi-level logic and a synthesis of domain constructs, the model provides a foundation for empirical investigation and strategic planning. Key propositions for future research are developed, focusing on causal relationships and boundary conditions. The novelty of ISOS lies in its simultaneous integration of three strategic pillars—circularity, localization, and digital resilience—within a unified, multi-scalar architecture that bridges fragmented operational theories. The article advances theory by redefining operational excellence through regenerative logic and adaptive capacity, responding directly to SDG 9 (industry innovation), SDG 12 (responsible consumption and production), and SDG 13 (climate action). This integrative framework offers both theoretical insight and practical guidance for transforming operations into catalysts of sustainable transition. Full article

This work presents an innovative hydrothermal approach for fabricating flexible piezoelectric PZT thin films on 20 μm titanium foil substrates using TiO₂ and SrTiO₃ (STO) interlayers. Three heterostructures (Ti/PZT, Ti/TiO₂/PZT, and Ti/TiO₂/STO/PZT) were synthesized to enable low-temperature growth and improve ferroelectric performance for advanced flexible MEMS. Characterizations including XRD, PFM, and P–E loop analysis evaluated crystallinity, piezoelectric coefficient d₃₃, and polarization behavior. The results demonstrate that the multilayered Ti/TiO₂/STO/PZT structure significantly enhances performance. XRD confirmed the STO buffer layer effectively reduces lattice mismatch with PZT to ~0.76%, promoting stable morphotropic phase boundary (MPB) composition formation. This optimized film exhibited superior piezoelectric and ferroelectric properties, with a high d₃₃ of 113.42 pm/V, representing an ~8.65% increase over unbuffered Ti/PZT samples, and displayed more uniform domain behavior in PFM imaging. Impedance spectroscopy showed the lowest minimum impedance of 8.96 Ω at 10.19 MHz, indicating strong electromechanical coupling. Furthermore, I–V measurements demonstrated significantly suppressed leakage currents in the STO-buffered samples, with current levels ranging from 10⁻¹² A to 10⁻⁹ A over ±3 V. This structure also showed excellent fatigue endurance through one million electrical cycles, confirming its mechanical and electrical stability. These findings highlight the potential of this hydrothermally engineered flexible heterostructure for high-performance actuators and sensors in advanced MEMS applications. Full article

The COVID-19 pandemic has exposed and intensified structural tensions surrounding work−life balance, precarity, and gender inequalities in academia. This paper examines the spatial, temporal, and emotional disruptions experienced by early-career and precarious researchers in Italy during the first national lockdown (March–April 2020) and their engagement in remote academic work. Adopting an exploratory and qualitative approach, the study draws on ten narrative video interviews and thirty participant-generated images to investigate how structural dimensions—such as gender, class, caregiving responsibilities, and the organizational culture of the neoliberal university—shaped these lived experiences. The findings highlight the implosion of boundaries between paid work, care, family life, and personal space and how this disarticulation exacerbated existing inequalities, particularly for women and caregivers. By interpreting both visual and narrative data through a sociological lens on gender, work, and organizations, the paper contributes to current debates on the transformation of academic labor and the reshaping of temporal work regimes through the everyday use of digital technologies in contemporary neoliberal capitalism. It challenges the individualization of discourses on productivity and flexibility and calls for gender-sensitive, structurally informed policies that support equitable and sustainable transitions in work and family life, in line with European policy frameworks. Full article

In modern vehicles, Autonomous Driving Systems (ADSs) are designed to operate partially or fully without human intervention. The ADS pipeline comprises multiple layers, including sensors, perception, localization, mapping, path planning, and control. The Robot Operating System (ROS) is a widely adopted framework that supports the modular development and integration of these layers. Among them, the path-planning and control layers remain particularly challenging due to several limitations. Classical path planners often struggle with non-smooth trajectories and high computational demands. Meta-heuristic optimization algorithms have demonstrated strong theoretical potential in path planning; however, they are rarely implemented in real-time ROS-based systems due to integration challenges. Similarly, traditional PID controllers require manual tuning and are unable to adapt to system disturbances. This paper proposes a ROS-based ADS architecture composed of eight integrated nodes, designed to address these limitations. The path-planning node leverages a meta-heuristic optimization framework with a cost function that evaluates path feasibility using occupancy grids from the Hector SLAM and obstacle clusters detected through the DBSCAN algorithm. A dynamic goal-allocation strategy is introduced based on the LiDAR range and spatial boundaries to enhance planning flexibility. In the control layer, a modified Pure Pursuit algorithm is employed to translate target positions into velocity commands based on the drift angle. Additionally, an adaptive PID controller is tuned in real time using the Differential Evolution (DE) algorithm, ensuring robust speed regulation in the presence of external disturbances. The proposed system is practically validated on a four-wheel differential drive robot across six scenarios. Experimental results demonstrate that the proposed planner significantly outperforms state-of-the-art methods, ranking first in the Friedman test with a significance level less than 0.05, confirming the effectiveness of the proposed architecture. Full article

Under the dual-carbon goals, with the rapid increase in the proportion of fluctuating power sources such as wind and solar energy, the regulatory capacity of traditional thermal power generation can no longer meet the demand for intra-day fluctuations. There is an urgent need to tap into the potential of flexible load-side regulatory resources. To this end, this paper proposes a low-carbon economic optimal dispatching strategy for virtual power plants (VPPs), considering the aggregation of diverse flexible and adjustable resources with the integration of wind and solar power. Firstly, the method establishes mathematical models by analyzing the dynamic response characteristics and flexibility regulation boundaries of adjustable resources such as photovoltaic (PV) systems, wind power, energy storage, charging piles, interruptible loads, and air conditioners. Subsequently, considering the aforementioned diverse adjustable resources and aggregating them into a VPP, a low-carbon economic optimal dispatching model for the VPP is constructed with the objective of minimizing the total system operating costs and carbon costs. To address the issue of slow convergence rates in solving high-dimensional state variable optimization problems with the traditional plant growth simulation algorithm, this paper proposes an improved plant growth simulation algorithm through elite selection strategies for growth points and multi-base point parallel optimization strategies. The improved algorithm is then utilized to solve the proposed low-carbon economic optimal dispatching model for the VPP, aggregating diverse adjustable resources. Simulations conducted on an actual VPP platform demonstrate that the proposed method can effectively coordinate diverse load-side adjustable resources and achieve economically low-carbon dispatching, providing theoretical support for the optimal aggregation of diverse flexible resources in new power systems. Full article

This paper examines the epistemological transformation prompted by the integration of generative artificial intelligence technologies into social science research, proposing the “adaptive epistemology” paradigm. In today’s post-digital era—characterized by pervasive infrastructures and non-human agents endowed with generative capabilities—traditional research approaches have become inadequate. Through a critical review of historical and discursive paradigms (positivism, interpretivism, critical realism, pragmatism, transformative paradigms, mixed and digital methods), here I show how the advent of digital platforms and large language models reconfigures the boundaries between data collection, analysis, and interpretation. Employing a theoretical–conceptual framework that draws on sociotechnical systems theory, platform studies, and the philosophy of action, the core features of adaptive epistemology are identified: dynamism, co-construction of meaning between researcher and system, and the capacity to generate methodological solutions in response to rapidly evolving contexts. The findings demonstrate the need for reasoning in terms of an adaptive epistemology that could offer a robust theoretical and methodological framework for guiding social science research in the post-digital society, emphasizing flexibility, reflexivity, and ethical sensitivity in the deployment of generative tools. Full article

The mechanical characteristics of soil–rock mixtures (S-RMs) are essential for ensuring geotechnical engineering stability and are significantly influenced by the microstructure’s contact network configuration. Due to the irregularity of particle shapes and the variability in particle grading with S-RMs, their macro-mechanical characteristics and mesoscopic contact skeleton distribution exhibit increased complexity. To further elucidate the macro-mesoscopic mechanical behavior of S-RMs, this study employed the DEM to develop a model incorporating irregular specimens representing various states, based on CT scan outlines, and applied flexible boundary conditions. A main skeleton system of contact force chains is an effective methodology for characterizing the dominant structural features that govern the mechanical behavior of soil–rock mixture specimens. The results demonstrate that the strength of S-RMs was significantly influenced by gravel content and consolidation state; however, the relationship is not merely linear but rather intricately associated with the strength and distinctiveness of the contact force chain skeleton. In the critical state, the mechanical behavior of S-RMs was predominantly governed by the characteristics of the principal contact force skeleton: the contact force skeleton formed by gravel–gravel, despite having fewer contact forces, exhibits strong contact characteristics and an exceptionally high-density distribution of weak contacts, conferring the highest shear strength to the specimens. Conversely, the principal skeleton formed through gravel–sand exhibits contact characteristics that are less distinct compared to those associated with strong contacts. Simultaneously, the probability density distribution of weak contacts diminishes, resulting in reduced shear strength. The contact skeleton dominated by sand–sand contact forces displays similar micro-mechanical characteristics yet possesses the weakest macroscopic behavior strength. Consequently, the concept of the main skeleton of contact force chains utilized in this study presents a novel research approach for elucidating the macro- and micro-mechanical characteristics of multiphase media. Full article

Graphene exhibits exceptional electronic properties, superior mechanical strength, and remarkable flexibility, driving significant advances in flexible electronics. However, achieving high-precision patterned graphene via in situ fabrication for such applications remains challenging, limiting the development of graphene-based flexible devices. In this study, we successfully synthesized patterned graphene with high precision by substrate surface oxidation technology. The effect of substrate surface oxidation on patterned graphene growth was deeply investigated. By regulating the oxidation time, we precisely controlled the oxidation degree of the substrate and characterized the boundary precision between oxidized and unoxidized regions. Finally, we achieved the high-precision in situ fabrication of patterned graphene with a feature size of 0.5 μm on selectively oxidized substrates. Furthermore, we fabricated a flexible fluorescent device based on patterned graphene, demonstrating the pronounced fluorescence quenching effect of graphene (I_Gr-free/I_Gr-cov ≈ 3). Full article

As the urban underground natural gas pipeline network expands, the explosion risk arising from methane accumulation in drainage ditches due to pipeline leakage has increased severely. A two-dimensional numerical model—9.7 m in length (including a 1-m obstacle section), 0.1 m in diameter, and with a water volume fraction of 0.2—was developed to address the flexible boundary characteristics of urban underground ditches. The investigation examined the influence of methane concentration on explosion propagation characteristics. Results indicated that, at a methane concentration of 11%, the peak pressure attained 157.9 kPa, and the peak temperature exceeded 3100 K—all of which were significantly higher than the corresponding values at 10%, 13%, and 16% concentrations. Explosion-induced water motion exerted a cooling effect that inhibited heat and pressure transfer, while obstacles imposed partial restrictions on flame propagation. Temporal profiles of temperature and pressure exhibited three distinct stages: “initial stability–rapid rise–attenuation”. Notably, at a methane concentration of 16%, the water column formed by fluid vibration demonstrated a pronounced cooling effect, causing faster decreases in measured temperatures and pressures compared to other concentrations. Full article

This paper addresses the issue of practical fixed-time tracking control for a class of strict-feedback nonlinear systems subject to external disturbances, while ensuring flexible prescribed performance. First, a fixed-time disturbance observer is designed to estimate the unknown external disturbances. The primary advantage of the proposed fixed-time disturbance observer lies in its capability to estimate both the disturbance itself and its higher-order derivatives in fixed time. In addition, various prescribed performance behaviors can be realized via a set of function transformations, merely by modifying certain critical parameters, without the need to redesign the controller. It is shown that, under the proposed control strategy, the system output can track the reference signal in fixed time, and the tracking error always remains within the prescribed performance boundaries. Finally, the simulation results are provided to demonstrate the feasibility and effectiveness of the proposed control scheme. Full article

Computational limitations of computers have emerged as a critical barrier to the advancement of Computational Fluid Dynamics (CFD). Consequently, exploring novel accelerator architectures tailored for large-scale CFD applications and closely integrated with CFD algorithmic characteristics holds significant value. Through an in-depth analysis of the finite difference method (FDM) for solving Navier–Stokes (N-S) equations, we propose a specialized accelerator architecture for FDM-based CFD (FAcc). Implemented on a 28 nm process, FAcc integrates 16,384 differential computing cores (FCores). Experimental validation demonstrates FAcc’s capability to solve N-S equations of varying complexities by flexibly configuring boundary conditions. Compared to conventional approaches, FAcc achieves significant acceleration performance, with its programmability underscoring adaptability to high-precision, large-scale CFD simulations. As the first CFD-focused accelerator designed from the instruction set architecture (ISA) level, FAcc bridges a critical gap in domain-specific hardware for CFD, offering a paradigm shift in high-performance fluid dynamics computation. Full article

This research evaluates the performance of six metaheuristic algorithms in the active and reactive power management of wind turbines (WTs) integrated into an AC microgrid (MG). The population-based genetic algorithm (PGA) is proposed as the primary optimization strategy and is rigorously compared against five benchmark techniques: Monte Carlo (MC), particle swarm optimization (PSO), the JAYA algorithm, the generalized normal distribution optimizer (GNDO), and the multiverse optimizer (MVO). This study aims to minimize, through independent optimization scenarios, the operating costs, power losses, or CO₂ emissions of the microgrid during both grid-connected and islanded modes. To achieve this, a coordinated control strategy for distributed generators is proposed, offering flexible adaptation to economic, technical, or environmental priorities while accounting for the variability of power generation and demand. The proposed optimization model includes active and reactive power constraints for both conventional generators and WTs, along with technical and regulatory limits imposed on the MG, such as current thresholds and nodal voltage boundaries. To validate the proposed strategy, two scenarios are considered: one involving 33 nodes and another one featuring 69. These configurations allow evaluation of the aforementioned optimization strategies under different energy conditions while incorporating the power generation and demand variability corresponding to a specific region of Colombia. The analysis covers two-time horizons (a representative day of operation and a full week) in order to capture both short-term and weekly fluctuations. The variability is modeled via an artificial neural network to forecast renewable generation and demand. Each optimization method undergoes a statistical evaluation based on multiple independent executions, allowing for a comprehensive assessment of its effectiveness in terms of solution quality, average performance, repeatability, and computation time. The proposed methodology exhibits the best performance for the three objectives, with excellent repeatability and computational efficiency across varying microgrid sizes and energy behavior scenarios. Full article