The expansion of subsea industrial activities has increased the demand for reliable robotic systems capable of performing inspection and intervention tasks in deep-water environments. In particular, the integration of high-performance vision systems into autonomous and remotely operated underwater platforms remains a critical engineering challenge due to severe hydrostatic pressure, hydrodynamic loading, and space constraints imposed by robotic manipulators. This work presents the conceptual development, mechanical design, and structural validation of a compact underwater vision module intended for deployment on a robotic arm operating in offshore environments. A systematic engineering design methodology is adopted, beginning with requirement definition and concept generation, followed by a comparative evaluation of alternative configurations using a structured materials and design selection framework. The selected concept is subsequently refined through detailed mechanical design, including material specification, geometric optimization, and sealing strategy definition. Structural integrity is assessed through numerical simulations based on the finite element method, accounting for external pressure loads representative of deep-sea operation. In addition, fluid–structure interaction effects are indirectly evaluated through dynamic analyses aimed at minimizing hydrodynamic resistance. The numerical results confirm that the proposed housing maintains structural safety at operational depths up to 300 m, while achieving a substantial reduction in hydrodynamic loading relative to a previous design generation. The developed solution demonstrates improved robustness, compactness, and hydrodynamic efficiency, supporting its suitability for integration into underwater robotic manipulation systems.

Silicon carbide (SiC)-based polymer nanocomposites have attracted significant attention for advanced electromechanical and optoelectronic applications due to their thermal stability, mechanical robustness, and tunable electronic properties. In this study, one-dimensional SiC nanotubes were successfully synthesized via a high-temperature carbothermal method at 1800 °C and subsequently incorporated into a polyvinylpyrrolidone (PVP) matrix to fabricate SiC/PVP nanocomposites with filler concentrations ranging from 1 to 5 wt%. The structural, morphological, and optical properties of the composites were systematically investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and UV–Vis spectroscopy.

SEM observations confirmed the hollow nanotube structure and rough surface morphology of SiC, while XRD analysis revealed the formation of the cubic 3C-SiC phase and its effective incorporation into the amorphous PVP matrix. At low filler loadings (1–3 wt%), SiC nanotubes were homogeneously dispersed, leading to reduced crystallite sizes, increased microstrain, and higher dislocation densities due to enhanced interfacial interactions and lattice distortion. In contrast, at 5 wt% SiC, aggregation effects became dominant, resulting in increased crystallite size and reduced lattice defects. Optical measurements demonstrated a non-linear band gap behavior, with a minimum value of 5.51 eV observed at 3 wt% SiC/PVP, attributed to interface-induced defect states and enhanced electronic interaction. FTIR spectra further confirmed strong interfacial bonding between SiC surface groups and PVP functional groups.

Based on the combined structural and optical analyses, an optimal filler concentration of approximately 2 wt% was identified, offering balanced crystallinity, defect density, and band gap tunability. These findings highlight the potential of SiC/PVP nanocomposites as promising materials for high-performance optoelectronic and dielectric components in advanced engineering systems.

This paper presents the development and implementation of a computer vision-
based system aimed at improving the reliability and operational safety of an industrial laser-marking process applied to electronic boards. The investigated process involves a board
containing six integrated circuits, over which metallic shields must be correctly positioned
prior to the laser-marking stage to protect sensitive internal components. If a shield is absent
during this operation, the laser may directly affect the chip surface, leading to irreversible
damage, functional degradation, and significant production losses.
To mitigate this risk, an automated visual inspection system was designed to verify,
in a non-invasive manner, the presence or absence of the shield on each individual chip
before authorizing the laser-marking process. The proposed solution was implemented using
the Python programming language and was based on deep learning techniques for object
detection. Specifically, a YOLO-family model in its nano configuration was employed and
trained to classify two distinct conditions: shielded chips and unshielded chips. The use of
a compact model enabled the efficient execution of standard computing hardware,
achieving an average inference time of approximately 300 ms. Although industrial processes
do not impose strict real-time or cycle-time constraints, this inference latency is considered
adequate for reliable integration into the production workflow.
Experimental results demonstrate that the proposed system operates consistently in
an industrial environment, effectively preventing improper laser-marking operations. The
solution acts as an additional layer for fault prevention, contributing to enhanced process
robustness, improved product quality, and increased overall reliability of the manufacturing
system.

Coreless winding designs for stators have gained more interest in the field of electrical machine engineering because of their ability to deliver high-efficiency results, lower electromagnetic losses, and enhanced torque density. Coreless windings successfully reduce iron losses, cogging torque, and magnetic saturation effects by removing the ferromagnetic stator core, making them ideal for applications with low to high speeds and low torque ripple. This resaerch offers a detailed overview of performance metrics related to stator coreless windings, deriving insights from earlier documented analytical, numerical, and experimental research. The key performance indicators analyzed consist of electromagnetic torque capability, winding factor, harmonic distortion, copper loss, thermal behavior, power density, and overall efficiency. The impact of winding topology like toroidal, concentrated or non-concentrated, planar or flat, and printed and flexible PCB-based windings on these performance metrics is examined in depth. Moreover, practical issues concerning mechanical structural support, thermal control, insulation needs, and production tolerances are examined. Comparisons among various machine topologies and operational conditions are emphasized to uncover the inherent trade-offs between efficiency, torque density, and thermal performance. This study offers design-focused insights and highlights essential factors for enhancing stator-less machines by integrating current research results. The findings of this review aim to aid informed design choices for new applications, such as hydro or wind energy systems, electric vehicles, and aerospace propulsion and actuation systems.

The rapidly increasing demand for standalone photovoltaic (PV) system deployment requires not only highly efficient control methods under rapidly changing environmental conditions but also methods that are economically affordable for real-world applications. In the PV field, conventional techniques may fail in the face of these significant challenging events, making their practical execution on low-cost hardware boards demanding. This study investigates the real-time implementation feasibility of a Nonlinear Backstepping Control (NBC) method for a standalone PV system, using an Arduino Due platform, within MATLAB/Simulink software. The applied system integrates a PV generator based on Kyocera 200GT (KC200GT) modules, linked to a DC–DC boost converter supplying a DC load. The proposed Maximum Power Point Tracking (MPPT) ensures stable, controlled extraction of the PV power under abrupt atmospheric conditions. The obtained results demonstrate a superior tracking efficiency that exceeds 97%, without exhibiting significant oscillations. In contrast to classic control strategies such as Perturb & Observe (P&O), which produce high fluctuations, leading to poor MPPT efficiency, especially under Standard Test Conditions (STC), the Arduino-in-the-loop evaluation of this nonlinear technique establishes high consistency between embedded and simulation results, indicating its superior accuracy, rapid convergence, and smooth power extraction, showing its suitability for real-world standalone PV system applications under cost-effective embedded systems.

Introduction

Effective rehabilitation of the ankle joint is critical for maintaining mobility and functional independence, particularly among elderly individuals and patients undergoing post-injury or post-surgical recovery. Many existing robotic rehabilitation devices rely on rigid mechanical architectures, which may increase weight, reduce adaptability, and compromise user comfort. Cable-driven actuation offers a flexible and lightweight alternative, capable of safely assisting complex joint motions. This work introduces CABLEAnkle, a cable-driven device developed to support assisted and rehabilitative ankle movements.

Methods

CABLEAnkle consists of a foot-shaped platform actuated by four Dynamixel servo motors that modulate cable tension routed through a knee-mounted brace. The mechanical architecture is designed to reproduce the three primary rotational degrees of freedom of the ankle: dorsiflexion/plantarflexion, inversion/eversion, and adduction/abduction. A detailed CAD model was developed to define geometry, cable routing, and motor placement. Kinematic modelling was carried out to relate motor rotation to cable length variation. Finite element analysis was performed to assess the structural feasibility of a lightweight PMMA foot platform under representative loading conditions. A preliminary prototype was then assembled.

Results

The kinematic analysis confirmed that coordinated cable actuation enables physiologically relevant ankle rotations. Structural simulations demonstrated that a 5 mm thick PMMA platform withstands symmetric and asymmetric loads representative of assisted ankle motion without exceeding material stress limits. The assembled prototype successfully reproduced the intended ankle movements, validating the feasibility of the proposed mechanical and actuation design.

Conclusions

The results demonstrate that CABLEAnkle is a compact, lightweight, and adaptable cable-driven solution capable of replicating essential ankle kinematics. The proposed design provides a promising foundation for future experimental validation and clinical evaluation in rehabilitative and assistive applications.

Additive Manufacturing (AM), particularly polymer 3D printing, enables the production of structural components with complex geometries; however, predicting mechanical stiffness and strength directly from manufacturing conditions remains a major challenge. In Material Extrusion (MEX) processes, as defined by ISO/ASTM standards, the layer-by-layer deposition strategy introduces process-dependent structural features that strongly influence the resulting mechanical response. This work presents an analytical, experimental and numerical investigation of the flexural behavior of PLA components manufactured by material extrusion, following ISO 178 guidelines, with the objective of linking processing characteristics to effective mechanical properties. For components subjected to bending-dominated loading, flexural response provides a representative framework to assess stiffness and strength while activating interlayer interactions that are not captured by uniaxial tests. Three-point bending experiments were conducted on specimens produced with different filament deposition orientations to validate analytically derived estimates of flexural stiffness and load-bearing capacity. Scanning electron microscopy (SEM) was used to characterize process-induced structural features, including voids, filament morphology and layer interfaces, providing a physical basis for interpreting the observed mechanical behavior. In parallel, finite element analysis (FEA) was employed to complement the experimental results by analyzing stress and shear distributions under bending. The combined analytical, experimental and numerical approach highlights the role of manufacturing-induced structure in governing flexural performance and demonstrates how process-informed modeling can be used to estimate stiffness and strength in material-extruded polymer components. The results contribute to a clearer understanding of process–structure–property relationships in additive manufacturing and support the development of predictive mechanical descriptions for 3D-printed structures, reducing reliance on extensive experimental testing.

The partial shading phenomenon is one of the most critical issues in off-grid photovoltaic systems that may decrease their performance. Therefore, the utilization of efficient and robust maximum power point tracking (MPPT) methods is crucial in these systems, especially under highly abrupt variations. In the domain, several researchers developed classic control techniques such as Incremental Conductance (IC) algorithms that often exhibit high fluctuations and slow convergence during challenging scenarios. This work presents an advanced Incremental Conductance (AIC) MPPT control technique specifically suggested to enhance the tracking efficiency and performance under Partial Shading Conditions (PSCs). The suggested method presents a modified step size that adaptively adjusts the control action according to operating conditions, allowing fast convergence with negligible oscillations. This technique is applied in off-grid mode, which consists of a PV array and a DC-DC step-up converter linked to a resistive DC load, using MATLAB/Simulink software, version 2020b. Simulation results are performed under complex PSC test, confirming the robustness and resilience of the proposed control strategy that rapidly attains the maximum power point (MPP) in less than 0.2 seconds and significantly enhances tracking efficiency and reduces steady-state fluctuations compared to the benchmarked traditional IC method, thereby contributing to optimized reliability in off-grid PV systems.

The global demand for clean, renewable energy sources has significantly increased, particularly for photovoltaic (PV) systems, which require less maintenance and operational costs. They are known for their flexibility to support both off-grid and grid-connected applications, making them a key technology for modern sustainable energy systems. Grid-Tied PV Systems (GTPVSs) have attained attention due to their capability of injecting power directly into the electrical grid without the need for batteries, unlike the grid-off PV systems that require energy storage. The use of GTPVS minimizes battery maintenance and ensures the direct synchronization of the extracted PV power with the utility grid. Nevertheless, abrupt variations and partial shading in environmental conditions and grid disturbances may reduce the robustness and efficiency of these systems. For this purpose, improved and advanced control techniques are required for establishing high performance and superior power quality injection. The utility of these methods is crucial for establishing a fast tracking of the Maximum Power Point (MPP) and enabling a stable grid injection with international standard compatibility. Thus, a Robust Intelligent-Fuzzy Backstepping (RI-FB) control technique is introduced for improving the performance of GTPVS, by providing a fast tracking under Partial Shading Conditions (PSCs) and delivering a rapid power injection into the grid, even under grid disturbances, such as AC loads. The integration of robust backstepping and fuzzy logic ensures an optimal power tracking that exceeds 98 % in only 18 ms while maintaining the grid synchronization, and offering a minimized Total Harmonic Distortion (THD) below 0.90 %, surpassing other benchmarked strategies. The proposed RI-FB technique confirms its real-time feasibility through Processor-In-the-Loop (PIL) implementation using the TMS320F28335 platform, which presents a robust key for the GTPVS.

Fused deposition modeling is a widely used additive manufacturing technique across the globe. The method has been rapidly adopted by academia and industry for making polymeric material components for various applications. The quality of the produced parts depends on process parameters and the fabrication environment. Key process parameters, such as nozzle temperature, print speed, layer thickness, and build orientation, influence the quality of the manufactured parts. However, waste materials are generated from failed prints, support structures, and end-of-life components. Such material waste production raises concerns regarding resource efficiency as well as environmental sustainability. In this investigation, we use process parameters to find the critical factors involved in the effective management of waste materials for FDM (fused deposition modeling) additive manufacturing (3D printing) applications. We use the most common biodegradable thermoplastic polymer materials, such as polylactic acid (PLA). We also employ acrylonitrile butadiene styrene (ABS) and reinforcement-based polymer composite materials. We emphasize the collection, segregation, cleaning, shredding, and re-extrusion of wastes, giving particular attention to their influence on filament quality and printability. The fabrication step is also monitored by an in-built camera to identify any anomalies occurring during the part-making process. The findings demonstrate that tailored parameter sets are essential to mitigate common challenges like poor layer adhesion, warping, and inconsistent extrusion inherent to reprocessed materials. The research shows whether process parameters influence waste material production for a specifically designed material.