Search Results (1,411)

This study examines the effect of oxygen concentration and sputtering power on the surface morphology of TiO₂ thin films deposited by DC reactive magnetron sputtering. Surface roughness parameters were obtained using MountainsMap^® software(10.2) from SEM images, while fractal dimensions and texture descriptors were extracted via Python-based image processing. Fractal dimension was calculated using the box-counting method applied to binarized images with multiple threshold levels, and texture analysis employed Gray-Level Co-occurrence Matrix (GLCM) statistics to capture local anisotropies and spatial heterogeneity. Four samples were analyzed, previously prepared with oxygen concentrations of 50% and 75%, and sputtering powers of 500 W and 1000 W. The results have shown that films deposited at higher oxygen levels and sputtering powers exhibited increased roughness, higher fractal dimensions, and stronger GLCM contrast, indicating more complex and heterogeneous surface structures. Conversely, films produced at lower oxygen and power settings showed smoother, more isotropic surfaces with lower complexity. This integrated analysis framework links deposition parameters with morphological characteristics, enhancing the understanding of surface evolution and enabling better control of TiO₂ thin film properties. Full article

The development of high-performance solid electrolytes is critical to advancing solid-state lithium-ion batteries (SSBs), with lithium lanthanum zirconium oxide (LLZO) emerging as a leading candidate due to its chemical stability and wide electrochemical window. In this study, we systematically investigated the effects of cation dopants, including aluminum (Al³⁺), tantalum (Ta⁵⁺), gallium (Ga³⁺), and rubidium (Rb⁺), on the structural, electronic, and ionic transport properties of LLZO using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. It appeared that, among all simulated results, Al-LLZO exhibits the highest ionic conductivity of 1.439 × 10⁻² S/cm with reduced activation energy of 0.138 eV, driven by enhanced lithium vacancy concentrations and preserved cubic-phase stability. Ta-LLZO follows, with a conductivity of 7.12 × 10⁻³ S/cm, while Ga-LLZO and Rb-LLZO provide moderate conductivity of 3.73 × 10⁻³ S/cm and 3.32 × 10⁻³ S/cm, respectively. Charge density analysis reveals that Al and Ta dopants facilitate smoother lithium-ion migration by minimizing electrostatic barriers. Furthermore, Al-LLZO demonstrates low electronic conductivity (1.72 × 10⁻⁸ S/cm) and favorable binding energy, mitigating dendrite formation risks. Comparative evaluations of radial distribution functions (RDFs) and XRD patterns confirm the structural integrity of doped systems. Overall, Al emerges as the most effective and economically viable dopant, optimizing LLZO for scalable, durable, and high-conductivity solid-state batteries. Full article

To study the mechanical properties and modification mechanism of thermosetting polyurethane (PU)-modified asphalt, the effects of polyurethane dosage on the workability of polyurethane-modified asphalt were analyzed by means of rotational viscosity tests. The mechanical properties of polyurethane-modified asphalt with different polyurethane dosages were explored using tensile tests and dynamic mechanical analysis (DMA). In addition, the thermodynamic behavior and micromorphology of polyurethane-modified asphalt were also thoroughly investigated using the test results of differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). The results showed that PU obtained the optimum workability when the polyurethane dose was 50%: at 120 min, its rotational viscosity was 1005 cp, which was lower than 2800 cp (40% PU) and 760 cp (60% PU). Additionally, the results of fracture elongation and fracture strength indicated that the PU-modified asphalt had good flexibility and strength. Compared with base asphalt, the tensile strength of 50% PU-modified asphalt increased by 509%, which was significantly higher than 157% (40% PU) and more balanced than 897% (60% PU) in terms of strength and flexibility. Added PU can significantly improve the elasticity of asphalt at high temperatures, while increasing the proportion of asphalt adhesive components, enhancing the deformation ability and temperature stability of asphalt. As the dose of PU increases, the interface between asphalt and PU blended more fully, and the surface became smoother. When the dose of PU was 50% or more, the interface between asphalt and PU was well integrated with a smooth and flat surface, forming a more uniform and stable cross-linked network structure. Full article

Autonomous navigation in dynamic, multi-vessel maritime environments presents a formidable challenge, demanding strict adherence to the International Regulations for Preventing Collisions at Sea (COLREGs). Conventional approaches often struggle with the dual imperatives of global path optimality and local reactive safety, and they frequently rely on simplistic state representations that fail to capture complex spatio-temporal interactions among vessels. We introduce a novel hybrid reinforcement learning framework, D* Lite + Transformer-Enhanced Soft Actor-Critic (TE-SAC), to overcome these limitations. This hierarchical framework synergizes the strengths of global and local planning. An enhanced D* Lite algorithm generates efficient, long-horizon reference paths at the global level. At the local level, the TE-SAC agent performs COLREGs-compliant tactical maneuvering. The core innovation resides in TE-SAC’s synergistic state encoder, which uniquely combines a Graph Neural Network (GNN) to model the instantaneous spatial topology of vessel encounters with a Transformer encoder to capture long-range temporal dependencies and infer vessel intent. Comprehensive simulations demonstrate the framework’s superior performance, validating the strengths of both planning layers. At the local level, our TE-SAC agent exhibits remarkable tactical intelligence, achieving an exceptional 98.7% COLREGs compliance rate and reducing energy consumption by 15–20% through smoother, more decisive maneuvers. This high-quality local control, guided by the efficient global paths from the enhanced D* Lite algorithm, culminates in a 10–32 percentage point improvement in overall task success rates compared to state-of-the-art baselines. This work presents a robust, verifiable, and efficient framework. By demonstrating superior performance and compliance with rules in high-fidelity simulations, it lays a crucial foundation for advancing the practical application of intelligent autonomous navigation systems. Full article

The utilization of Unmanned Aerial Vehicles (UAVs) in missions such as reconnaissance and surveillance has grown rapidly, underscoring the need for efficient path planning algorithms that ensure both optimality and collision avoidance. The A-star algorithm is widely used for global path planning due to its ability to generate optimal routes; however, its high computational cost makes it unsuitable for real-time applications, particularly in unknown or dynamic environments. For local path planning, the Artificial Potential Field (APF) algorithm enables real-time navigation by attracting the UAV toward the target while repelling it from obstacles. Despite its efficiency, APF suffers from local minima and limited performance in dynamic settings. To address these challenges, this paper proposes the A-star-Guided Potential Field (AGPF) algorithm, which integrates the strengths of A-star and APF to achieve robust performance in both global and local path planning. The AGPF algorithm was validated through simulations conducted in the Robot Operating System (ROS) environment. Simulation results demonstrate that AGPF produces smoother and more optimal paths than A-star, while avoiding the local minima issues inherent in APF. Furthermore, AGPF effectively handles moving and previously unknown obstacles by generating real-time avoidance trajectories, demonstrating strong adaptability in dynamic and uncertain environments. Full article

Shift organizations in automotive manufacturing often rely on manual task allocation, resulting in inefficiencies, human error, and increased workload for supervisors. This research introduces an automated solution using the Kuhn-Munkres algorithm, integrated with the Moodle learning management system, to optimize task assignments based on operator qualifications and task complexity. Simulations conducted with real industrial data demonstrate that the proposed method meets operational requirements, both logically and mathematically. The system improves the start of shifts by assigning simpler tasks initially, enhancing operator confidence and reducing the need for assistance. It also ensures that task assignments align with required training levels, improving quality and process reliability. For industrial practitioners, the approach provides a practical tool to reduce planning time, human error, and supervisory burden, while increasing shift productivity. From an academic perspective, the study contributes to applied operations research and workforce optimization, offering a replicable model grounded in real-world applications. The integration of algorithmic task allocation with training systems enables a more accurate matching of workforce capabilities to production demands. This study aims to support data-driven decision-making in shift management, with the potential to enhance operational efficiency and encourage timely start of work, thereby possibly contributing to smoother production flow and improved organizational performance. Full article

The increasing demand for fresh fruits and vegetables has been accompanied by a rise in foodborne illness outbreaks linked to fresh produce. Traditional antimicrobial washing treatments, such as chlorine and peroxyacetic acid, have limitations in efficacy and pose environmental and worker health concerns. This study evaluated the effectiveness of organic acids (citric, malic, and lactic acid) and power ultrasound, individually and in combination, for the reduction in Salmonella enterica and Listeria monocytogenes on four fresh produce types: romaine lettuce, cucumber, tomato, and strawberry. Produce samples were inoculated with bacterial cocktails at 8–9 log CFU/unit and treated with organic acids at 2 or 5% for 2 or 5 min, with or without power ultrasound (40 kHz). Results showed that pathogen reductions varied based on the produce matrix with smoother surfaces such as tomato, exhibiting greater reductions than rougher surfaces (e.g., romaine lettuce and strawberry). Lactic and malic acids were the most effective treatments, with 5% lactic acid achieving a reduction of >5 log CFU/unit for S. enterica and 4.53 ± 0.71 log CFU/unit for L. monocytogenes on tomatoes. The combination of organic acids and power ultrasound demonstrated synergistic effects, further enhancing pathogen reduction by <1.87 log CFU/unit. For example, S. enterica on cucumbers was reduced by an additional 1.87 log CFU/unit when treated with 2% malic acid and power ultrasound for 2 min compared to malic acid alone. Similarly, L. monocytogenes on strawberries was further reduced by 1.84 log CFU/unit when treated with 5% malic acid and power ultrasound for 2 min. These findings suggest that organic acids, particularly malic and lactic acids, combined with power ultrasound, may serve as an effective hurdle technology for enhancing the microbial safety of fresh produce. Future research can include validating these treatments in an industrial processing environment. Full article

Autonomous vehicles (AVs) have emerged as a promising sustainable urban mobility solution, expected to lead to enhanced road safety, smoother traffic flows, less traffic congestion, improved accessibility, better energy utilization and environmental performance, as well as more efficient passenger and freight transportation, in terms of time and cost, due to better fleet management and platooning. However, challenges also arise, mostly related to data privacy, security and cyber-security, high acquisition and infrastructure costs, accident liability, even possible increased traffic congestion and air pollution due to induced travel demand. This paper presents the results of a survey conducted among 654 residents who experienced an autonomous bus (AB) service in the city of Trikala, Greece, in order to assess their willingness to use (WTU) and willingness to pay (WTP) for ABs, through testing a range of factors based on a literature review. Results useful to policy-makers were extracted, such as that the intention to use ABs was mostly shaped by psychological factors (e.g., users’ perceptions of usefulness and safety, and trust in the service provider), while WTU seemed to be positively affected by previous experience in using ABs. In contrast, sociodemographic factors were found to have very little effect on the intention to use ABs, while apart from personal utility, users’ perceptions of how autonomous driving will improve the overall life standards in the study area also mattered. Full article

This study aimed to examine how downward load applied during instrumentation affects the stress generation and shaping properties in thermally treated and non-treated NiTi rotary instruments. ProTaper Universal (PTU; non-thermally treated) and ProTaper Gold (PTG; thermally treated) were used to prepare J-shaped canals in resin blocks. Load-controlled automated instrumentation and torque/force sensing devices were employed with preset downward loads of 1, 2, or 3 N (n = 10 each). The torque/force, instrumentation time, and canal-centering ratio were measured and analyzed using two-way or one-way analysis of variance with Tukey’s test (α = 0.05). In the PTU-1N group, instrumentation was not completed because a ledge was formed in all canals. The PTU-3N group showed significantly greater upward force (screw-in force) and clockwise torque, along with a significantly smaller canal-centering ratio (less deviation) at the apical 0 mm level, than the PTU-2N group (p < 0.05). The downward load did not influence the instrumentation time (p > 0.05). In the PTG groups, these effects of downward load on the force generation and canal-centering ratio were not significant (p > 0.05). In the non-thermally treated PTU instruments, greater downward loads enhanced screw-in force while decreasing apical canal deviation; however, these effects were abolished in the thermally treated PTG instruments. This study highlights the importance of adapting the instrumentation technique with instrument characteristics: thermally treated flexible instruments facilitate smoother use, while stiffer, non-thermally treated ones may require precise control of downward loads. Full article

Background: Preterm infants and their families face a challenging experience during their stay in the neonatal intensive care unit (NICU). Family-centered care emphasizes the importance of welcoming parents, involving them in their baby’s daily care, and supporting the development of parenting skills. NICU staff should support parents in understanding their baby’s needs and in strengthening the parent–infant bond. Although many tools outline what parents should learn, there is a limited structured framework to monitor their involvement in the infant’s care. Tracking parental participation in daily caregiving activities could support professionals in effectively guiding families, ensuring a smoother transition to discharge. Aims: The aim of this study was to evaluate the adherence to and effectiveness of a structured tool for parental involvement in the NICU. This tool serves several key purposes: to track the progression and timing of parents’ autonomy in caring for their baby, to support parents in building caregiving competencies before discharge, and to standardize the approach of NICU professionals in promoting both infant care and family engagement. Methods: A structured template form for documenting parental involvement (“together TO-CARE template”, TTCT) was integrated into the computerized chart adopted in the NICU of Modena. Nurses were asked to complete the TTCT at each shift. The template included the following assessment items: parental presence; type of contact with the baby (touch; voice; skin-to-skin); parental involvement in care activities (diaper changing; gavage feeding; bottle feeding; breast feeding); and level of autonomy in care (observer; supported by nurse; autonomous). We evaluated TTCT uploaded data for very low birth weight (VLBW) preterm infants admitted in the Modena NICU between 1 January 2023 and 31 December 2024. Staff compliance in filling out the TTCT was assessed. The timing at which parents achieved autonomy in different care tasks was also measured. Results: The TTCT was completed with an average of one entry per day, during the NICU stay. Parents reached full autonomy in diaper changing at a mean of 21.1 ± 15.3 days and in bottle feeding at a mean of 48.0 ± 22.4 days after admission. The mean length of hospitalization was 53 ± 38 days. Conclusions: The adoption of the TTCT in the NICU is feasible and should become a central component of care for preterm infants. It promotes family-centered care by addressing the needs of both the baby and the family. Encouraging early and progressive parental involvement enhances parenting skills, builds confidence, and may help reduce post-discharge complications and readmissions. Furthermore, the use of a standardized template aims to foster consistency among NICU staff, reduce disparities in care delivery, and strengthen the support provided to families of preterm infants. Full article

Benzoxazine resins are gaining attention for their impressive thermal stability, low water uptake, and strong mechanical properties. In this work, two new bio-based benzoxazine monomers were developed using renewable arbutin: one combined with 3-(2-aminoethylamino) propyltrimethoxysilane (AB), and the other with furfurylamine (AF). Both were synthesized using a simple Mannich-type reaction and verified through FT-IR and ¹H-NMR spectroscopy. By blending these monomers in different ratios, copolymers with adjustable thermal, dielectric, and surface characteristics were produced. Thermal analysis showed that the materials had broad processing windows and cured effectively, while thermogravimetric testing confirmed excellent heat resistance—especially in AF-rich blends, which left behind more char. The structural changes obtained during curing process were monitored using FT-IR, and XPS verified the presence of key elements like carbon, oxygen, nitrogen, and silicon. SEM imaging revealed that AB-based materials had smoother surfaces, while AF-based ones were rougher; the copolymers fell in between. Dielectric testing showed that increasing AF content raised both permittivity and loss, and contact angle measurements confirmed that surfaces ranged from water-repellent (AB) to water-attracting (AF). Overall, these biopolymers (AB/AF copolymers) synthesized from arbutin combine environmental sustainability with customizability, making them strong candidates for use in electronics, protective coatings, and flame-resistant composite materials. Full article

Accurate estimation of upper-limb joint angles is essential in biomechanics, rehabilitation, and wearable robotics. While inertial measurement units (IMUs) offer portability and flexibility, systems requiring multiple inertial sensors can be intrusive and complex to deploy. In contrast, optical motion capture (MoCap) systems provide precise tracking but are constrained to controlled laboratory environments. This study presents a deep learning-based approach for estimating shoulder and elbow joint angles using only three IMU sensors positioned on the chest and both wrists, validated against reference angles obtained from a MoCap system. The input data includes Euler angles, accelerometer, and gyroscope data, synchronized and segmented into sliding windows. Two recurrent neural network architectures, Convolutional Neural Network with Long-short Term Memory (CNN-LSTM) and Bidirectional LSTM (BLSTM), were trained and evaluated using identical conditions. The CNN component enabled the LSTM to extract spatial features that enhance sequential pattern learning, improving angle reconstruction. Both models achieved accurate estimation performance: CNN-LSTM yielded lower Mean Absolute Error (MAE) in smooth trajectories, while BLSTM provided smoother predictions but underestimated some peak movements, especially in the primary axes of rotation. These findings support the development of scalable, deep learning-based wearable systems and contribute to future applications in clinical assessment, sports performance analysis, and human motion research. Full article

Reliable wave prediction plays a significant role in wave energy converter (WEC) research, but there are still prediction errors that would increase the uncertainty for the power grid and reduce the power quality. The efficiency and stability of the power take-off (PTO) system are also important research topics in WEC applications. In order to solve the above-mentioned problems, this paper presents a model predictive control (MPC) method composed of a prediction error compensation controller and a PTO optimization controller. This work aims to address the limitations of existing wave prediction methods and improve the efficiency and stability of hydraulic PTO systems in WECs. By controlling the charging and discharging of the accumulator, the power quality is enhanced by reducing grid frequency fluctuations and voltage flicker through prediction error compensation. In addition, an efficient and stable hydraulic PTO system can be obtained by keeping the operation pressure of the hydraulic motor at the optimal range. Thus, smoother power output minimizes grid-balancing penalties and storage wear, and stable hydraulic pressure extends PTO component lifespan. Finally, comparative numerical simulation studies are provided to show the efficacy of the proposed method. The results validate that the dual-controller MPC framework reduces power deviations by 74.3% and increases average power generation by 31% compared to the traditional method. Full article

The development of Global Positioning System (GPS) technology has contributed in various ways to improving the physical condition of modern football players by enabling the quantification of physical load. Previous studies have reported that the running demands of matches vary depending on playing position and formation. Over the past decade, despite the widespread use of GPS technology, studies that have investigated the running performance of young football players within the 1-4-3-3 formation are particularly limited. Therefore, the aim of the present study was to create the match running profile of playing positions in the 1-4-3-3 formation among high-level youth football players. An additional objective of the study was to compare the running performance of players between the two halves of a match. This study involved 25 football players (Under-19, U19) from the academy of a professional football club. Data were collected from 18 league matches in which the team used the 1-4-3-3 formation. Positions were categorized as Central Defenders (CDs), Side Defenders (SDs), Central Midfielders (CMs), Side Midfielders (SMs), and Forwards (Fs). The players’ movement patterns were monitored using GPS devices and categorized into six speed zones: Zone 1 (0.1–6 km/h), Zone 2 (6.1–12 km/h), Zone 3 (12.1–18 km/h), Zone 4 (18.1–21 km/h), Zone 5 (21.1–24 km/h), and Zone 6 (above 24.1 km/h). The results showed that midfielders covered the greatest total distance (p = 0.001), while SDs covered the most meters at high and maximal speeds (Zones 5 and 6) (p = 0.001). In contrast, CDs covered the least distance at high speeds (p = 0.001), which is attributed to the specific tactical role of their position. A comparison of the two halves revealed a progressive decrease in the distance covered by the players at high speed: distance in Zone 3 decreased from 1139 m to 944 m (p = 0.001), Zone 4 from 251 m to 193 m (p = 0.001), Zone 5 from 144 m to 110 m (p = 0.001), and maximal sprinting (Zone 6) dropped from 104 m to 78 m (p = 0.01). Despite this reduction, the total distance remained relatively stable (first half: 5237 m; second half: 5046 m, p = 0.16), indicating a consistent overall workload but a reduced number of high-speed efforts in the latter stages. The results clearly show that the tactical role of each playing position in the 1-4-3-3 formation, as well as the area of the pitch in which each position operates, significantly affects the running performance profile. This information should be utilized by fitness coaches to tailor physical loads based on playing position. More specifically, players who cover greater distances at high speeds during matches should be prepared for this scenario within the microcycle by performing similar distances during training. It can also be used for better preparing younger players (U17) before transitioning to the U19 level. Knowing the running profile of the next age category, the fitness coach can prepare the players so that by the end of the season, they are approaching the running performance levels of the next group, with the goal of ensuring a smoother transition. Finally, regarding the two halves of the game, it is evident that fitness coaches should train players during the microcycle to maintain high movement intensities even under fatigue. Full article

Addressing lateral-directional control challenges during unmanned aerial vehicle (UAV) landing in complex wind fields, this study proposes a drift angle control strategy that integrates coordinated heading and trajectory regulation. An adaptive radius optimization method for the Dubins approach path is designed using wind speed estimation. By developing a wind-coupled flight dynamics model, we establish a roll angle control loop combining the $L_1$ nonlinear guidance law with Linear Active Disturbance Rejection Control (LADRC). Simulation tests against conventional sideslip approach and crab approach, along with flight tests, confirm that the proposed autonomous landing system achieves smoother attitude transitions during landing while meeting all touchdown performance requirements. This solution provides a theoretically rigorous and practically viable approach for safe UAV landings in challenging wind conditions. Full article