Search Results (41,986)

Titanium alloy TC4 countersunk head bolts (CHB) are widely used in spacecraft structures, but the research on CHB does not receive enough attention at present. There are still some more opportunities worthy of in-depth research, such as insufficient research on CHB of high-strength fasteners for aerospace applications, an insufficient combination of CHB simulation tests with real working conditions, and inspection and testing methods. In this study, through the combination of finite element simulation and experiments, the working conditions of the CHB connection structure bearing tensile load and CHB screwing were analyzed, and the requirements of the CHB connection structure and installation of CHB were optimized. Based on the single-bolt tensile simulation, the working conditions of multi-bolt connection structures under eccentric load and single-bolt composite laminate connection structures under tensile load were analyzed. Meanwhile, the structure of CHB was further optimized, and the simulation analysis model of the CHB tightening process was established. The research shows that the larger fixing bolt countersunk angle θ₁ and the smaller countersunk fillet radius r, the better the ultimate bearing capacity of the connection structure will be. When the countersunk bevel angle of pressure plate θ₂ was greater than or less than 100°, the clamping force–angle slope will decrease, while when θ₂ was smaller, it will have a greater influence on the slope. The coaxiality Φ had little influence on the slope around the allowable tolerance range (0.3 mm), but the influence on the slope becomes greater when it exceeds the tolerance range. The research results provide a reference and basis for the layout of CHB and the use of composite materials in aerospace connection structures. Full article

Personalized face image generation is essential for Artificial Intelligence-Generated Content (AIGC) applications such as personalized digital avatars and user-customized media creation. However, existing diffusion-based approaches still suffer from insufficient identity consistency and limited text editability. In this work, we propose CoFaDiff, a diffusion-based face generation framework designed for coordinating identity consistency and text-driven editability. To enhance identity consistency, our method integrates a dual-encoder scheme that jointly leverages CLIP and ArcFace to capture both semantic and discriminative facial features, incorporates a progressive curriculum learning strategy to obtain more robust identity representations, and adopts a hybrid IdentityNet–IPAdapter architecture that explicitly models facial location, pose, and corresponding identity embeddings in a unified manner. To enhance text-driven editability, we introduce three complementary optimization strategies: First, long-prompt fine-tuning is employed to reduce the model’s dependency on identity conditions. Second, a semantic alignment loss is incorporated to regularize the influence of identity embeddings within the semantic space of the pretrained diffusion model. Third, during classifier-free guided sampling, we modulate the strength of the identity condition by stacking different numbers of zero-valued identity tokens, enabling users to flexibly balance identity consistency and text editability according to their needs. Experiments on FFHQ and IMDB-WIKI demonstrate that CoFaDiff achieves superior identity consistency and text editability compared to recent baselines. Full article

Fused filament fabrication (FFF, often called FDM) is widely used in polymer additive manufacturing; however, it suffers from mechanical anisotropy and weak bonding in the Z direction. This work examines how the infill pattern influences the tensile response of PLA parts at fixed printing conditions. Dog-bone specimens (PLA, four patterns: grid, honeycomb, rectilinear, adaptive cubic) were printed and tested in tension (n = 3 per pattern). Grid yielded the highest ultimate tensile strength, whereas honeycomb produced the largest Young’s modulus; rectilinear was intermediate and adaptive cubic was trailed in both metrics. X-ray diffraction of printed PLA showed a broad halo at 16–20° (2θ) with weak α-form reflections, consistent with largely amorphous microstructure after FFF. Together, the results indicate that, at constant material and nominal infill, pattern selection alone can shift the strength–stiffness balance, with grid favoring strength and honeycomb favoring stiffness. Full article

The production of a stable and uniform spray is a primary concern in fuel atomization applications, such as in fluid catalytic cracking reactors, directly affecting the process quality and gas emissions. However, depending on nozzle geometry and operating conditions, undesired pulsed spray behavior may occur. This phenomenon originates from the internal multiphase flow interaction in Y-jet nozzles and leads to unstable sprays. Understanding the formation of spray pulsations is challenging due to limited internal flow visualization in the nozzle and the fast dynamics involved. Accordingly, this work elucidates the mechanisms of the pulsed spray formation through 3D transient numerical multiphase simulations inside a mixing chamber. The model is validated against internal pressure measurements and applied to investigate the internal mixing behavior across several operating conditions. Results show that the liquid-to-gas momentum flux ratio governs the internal flow regimes. A higher liquid momentum flux obstructs the gas flow, leading to periodic spray bursts when the gas overcomes the liquid back pressure. The simulations also reveal self-sustained oscillatory flow patterns and cyclic transitions between gas penetration and liquid accumulation, which produce periodic pressure fluctuations and nozzle discharge pulsations. The findings offer valuable guidance for optimizing nozzle operation and geometry to suppress pulsation and improve atomization performance. Full article

Underwater images often suffer from severe color distortion, low contrast, and reduced visibility, motivating the widespread use of image enhancement as a preprocessing step for downstream computer vision tasks. However, recent studies have questioned whether enhancement actually improves object detection performance. In this work, we conduct a comprehensive and rigorous evaluation of nine state-of-the-art enhancement methods and their interactions with modern object detectors. We propose a unified evaluation framework that integrates (1) a distribution-level quality assessment using a composite quality index (Q-index), (2) a fine-grained per-image detection protocol based on COCO-style mAP, and (3) a mixed-set upper-bound analysis that quantifies the theoretical performance achievable through ideal selective enhancement. Our findings reveal that traditional image quality metrics do not reliably predict detection performance, and that dataset-level conclusions often overlook substantial image-level variability. Through per-image evaluation, we identify numerous cases in which enhancement significantly improves detection accuracy—primarily for low-quality inputs—while also demonstrating conditions under which enhancement degrades performance. The mixed-set analysis shows that selective enhancement can yield substantial gains over both original and fully enhanced datasets, establishing a new direction for designing enhancement models optimized for downstream vision tasks. This study provides the most comprehensive evidence to date that underwater image enhancement can be beneficial for object detection when evaluated at the appropriate granularity and guided by informed selection strategies. The data generated and code developed are publicly available. Full article

Evacuated blood collection tubes are widely used in clinical and laboratory settings due to their simplicity and reliability. However, their performance is influenced by factors such as ambient pressure, temperature, tube design, and procedural conditions. This study systematically investigates and quantifies these effects on draw volume and filling dynamics, with a particular emphasis on high-altitude applications. A combination of theoretical modeling, experimental validation, and qualitative analysis was employed to identify critical parameters and assess their significance. The results demonstrate that standard tubes designed for sea-level conditions, particularly those with low fill ratios, may exhibit substantial deviations in draw volume at high altitudes. Factors such as blood temperature and venous pressure were found to have a considerable impact, while others, such as material creep, were negligible under typical conditions. By consolidating and analyzing these effects, this study provides a valuable resource for manufacturers and medical personnel, offering valuable insights to improve the design and use of evacuated blood collection tubes. The findings emphasize the importance of considering environmental conditions during production and clinical application, particularly for high-altitude scenarios. Future work should refine the models and expand testing under realistic conditions to enhance reliability and applicability. Full article

This study provides a comprehensive three-dimensional Computational Fluid Dynamics analysis of airflow distribution in a surgical operating room under realistic occupancy and equipment conditions. Using integrated modelling in SolidWorks and a subsequent analysis in ANSYS Fluent, a full-scale Operating Room geometry was simulated to assess the effectiveness of a laminar airflow system. The model includes surgical staff mannequins, thermal loads from surgical lights, and medical equipment that commonly disrupt unidirectional flow patterns. A polyhedral mesh with over 2.8 million nodes was employed, and a grid independence study confirmed solution reliability. The realisable k–ε turbulence model with enhanced wall treatment was used to simulate steady-state airflow, thermal stratification, and pressure variation due to door opening. Results highlight significant flow disturbances and recirculation zones caused by the shear zone created by supply air, overhead lights and heat plumes, particularly outside the core laminar air flow zone. The most important area, 10 cm above the surgical site, shows a maximum velocity gradient of 0.09 s⁻¹ while the temperature gradient shows 6.7 K.m⁻¹ and the pressure gradient, 0.0167 Pa.m⁻¹. Streamline analysis reveals potential re-entrainment of contaminated air into the sterile field. Full article

Early fault diagnosis in induction motors is important to maintain correct operation in terms of energy and efficiency, as well as to achieve a reduction in costs associated with maintenance or unexpected stoppages in production processes. These motors are widely used in industry due to their reliability, low cost, and great robustness; however, over time, they may be exposed to wear that can affect their performance, endanger the integrity of operators, or cause unexpected shutdowns that generate economic losses. Corrosion in the bearings is one of the most common failures, which is mainly triggered by high humidity in combination with high temperatures. However, despite its relevance, it has not been widely explored as a cause of failure in induction motors. Unlike failures that occur in specific or localized areas, corrosion in bearings does not manifest through specific frequencies associated with the phenomenon, since the corrosion occurs extensively on the surface of the raceway, making early diagnosis difficult with conventional techniques based on spectral analysis. Therefore, this work proposes an approach for the analysis of magnetic stray flux and vibration signals under different levels of corrosion using statistical and non-statistical parameters to capture variations in the dynamic behavior of the motors while employing genetic algorithms to select the most relevant parameters for each signal and optimize the configuration of an ensemble learning algorithm. The classification of the bearing condition is achieved using support vector machines in combination with the bagging method, which increases the robustness and accuracy of the model in the presence of signal variability. A classification accuracy between the healthy state and two gradualities greater than 99% was obtained, indicating that the proposed approach is reliable and efficient for corrosion diagnosis. Full article

The growing use of electric vehicles (EVs) creates challenges in designing charging systems that are smart, dependable, and efficient, especially when environmental conditions change. This research proposes a fuzzy-logic-based PID control strategy integrated into a photovoltaic (PV) powered EV charging system to address uncertainties such as fluctuating solar irradiance, grid instability, and dynamic load demands. A MATLAB-R2023a/Simulink-R2023a model was developed to simulate the charging process using real-time adaptive control. The fuzzy logic controller (FLC) automatically updates the PID gains by evaluating the error and how quickly the error is changing. This adaptive approach enables efficient voltage regulation and improved system stability. Simulation results demonstrate that the proposed fuzzy–PID controller effectively maintains a steady charging voltage and minimizes power losses by modulating switching frequency. Additionally, the system shows resilience to rapid changes in irradiance and load, improving energy efficiency and extending battery life. This hybrid approach outperforms conventional PID and static control methods, offering enhanced adaptability for renewable-integrated EV infrastructure. The study contributes to sustainable mobility solutions by optimizing the interaction between solar energy and EV charging, paving the way for smarter, grid-friendly, and environmentally responsible charging networks. These findings support the potential for the real-world deployment of intelligent controllers in EV charging systems powered by renewable energy sources This study is purely simulation-based; experimental validation via hardware-in-the-loop (HIL) or prototype development is reserved for future work. Full article

Cropland change detection (CD) in high-resolution remote sensing images is critical for cropland protection and food security. However, style differences caused by inconsistent imaging conditions (such as season and illumination) and ground object scale differences often lead to high numbers of false and missed detections. Existing approaches, predominantly relying on spatial domain features and a multiscale framework, struggle to address these issues effectively. Therefore, we propose FDFENet, incorporating a Frequency Domain Feature Exchange Module (FFEM) that unifies image styles by swapping the low-frequency components of bitemporal features. A Frequency Domain Aggregation Distribution Module (FDADM) is also introduced as a comparative alternative for handling style discrepancies. Subsequently, a Multiscale Feature Enhancement Module (MSFEM) strengthens feature representation, while a Multiscale Change Perception Module (MSCPM) suppresses non-change information, and the two modules work cooperatively to improve detection sensitivity to multiscale ground objects. Compared with the FDADM, the FFEM exhibits superior parameter efficiency and engineering stability, making it more suitable as the primary solution for long-term deployment. Evaluations on four CD datasets (CLCD, GFSWCLCD, LuojiaSETCLCD, and HRCUSCD) demonstrate that FDFENet outperformed 13 state-of-the-art methods, achieving F1 and IOU scores of 77.09% and 62.72%, 81.81% and 73.63%, 74.47% and 59.32%, and 75.95% and 61.23%, respectively. This demonstrates FDFENet’s effectiveness in addressing style differences and ground object scale differences, enabling high-precision cropland monitoring to support food security and sustainable cropland management. Full article

The present work develops an explicit dynamic finite element model of soil–disc interaction for a notched harrow disc, aiming to quantify how APS coatings, soil type and disc–soil friction influence stresses in the disc and surrounding soil. The model reproduces a four-gang offset harrow operating at 7 km/h, 0.15 m working depth, with 18°disc angle and 15° tilt angle, and compares an uncoated steel disc with three APS-coated variants (P1 Metco 71NS, P2 Metco 136F, P3 Metco 45C-NS). Mechanical properties of the substrate and coatings are obtained from micro-indentation tests and introduced via a bilinear steel model and Johnson–Cook plasticity for the coatings, while disc–soil friction coefficients are calibrated from microscratch measurements. Soil behaviour is described using the AUTODYN Granular model for four representative agricultural soils, spanning sandy loam to saturated heavy clay. Results show that the uncoated disc develops von Mises stresses in the disc–soil contact region of ≈150–220 MPa, with intermediate-stiffness soils being most critical. APS coatings significantly alter both the level and distribution of stresses: P2, the stiffest ceramic, yields the highest stresses (≈421–448 MPa), P1 keeps stresses near the baseline while shielding the substrate through extended plastic zones, and P3 provides an intermediate, more uniformly distributed stress regime. Increasing disc–soil friction systematically amplifies von Mises stresses in the contact region, especially for P2. Overall, the calibrated explicit model captures the coupled influence of soil properties, coating stiffness and friction, and indicates that P1 is better suited for light-to-medium soils, P3 offers the most balanced response in medium-to-stiff soils, whereas P2 should be reserved for highly abrasive conditions and used with caution in cohesive soils. Full article

The research elaborates on and empirically verifies an integrative model that describes how the combination of various workplace resources results in the improvement of employee and organizational outcomes. It is based on the Job Demands–Resources model and the Resource-Based View to conceptualize Employee Experience Capital (EEC) as a higher-order construct, consisting of seven interrelation drivers, including digital autonomy, inclusive cognition, sustainability alignment, AI synergy, mindful design, learning agility, and wellness technology. This study examines the effect of these resources in developing two psychological processes, work resonance and employee vitality, which subsequently improves organizational performance. It also examines how the well-being of employees can be a contextual moderator that determines such relationships. The study, based on a cross-sectional design and the diversified sample of the employees who work in various digitally transformed industries, proves that EEC is a great way to improve resonance and vitality, which are mutually complementary mediators between resource bundles and performance outcomes. Employee well-being turns out to be a factor of performance, as opposed to a circumscribed condition. The results put EEC as one of the strategic types of human capital that values digital, sustainable, and wellness-oriented practices to employee well-being and sustainable organizational performance and provides new theoretical contributions and practical guidance to leaders striving to create resource-rich, high-performing workplaces. Full article

The current study assessed organizational and psychosocial factors related to intentions to quit in American working college undergraduates (N = 382; mean age = 19 years; ~80% female). Students were surveyed on organizational scales (e.g., organizational identification, perceived support, work–life conflict, and intentions to quit) and psychosocial scales (e.g., perceived stress, social support, burnout, and mental health conditions). Variables significantly correlated with intent to quit at the bivariate level were included in an exploratory multiple regression model. The results indicated that burnout, engagement, organizational identification, perceived social support, and life–work conflict were uniquely predictive of intention to quit. A subsequent path analysis based on the Job Demands–Resources model revealed a good fit to the student data: demands (i.e., work–life conflict, perceived stress) and resources (organizational support and identification) predicted burnout and engagement, which in turn predicted intent to quit (along with a direct path from organizational support). This model can therefore explain behavior in both traditional and college undergraduate employees. In order to retain these employees, organizations should invest in practices that increase organizational identification and perceived support, as well as initiatives that help students mitigate the increased risks of stress and burnout associated with working while in college. Full article

Background and Objectives: Chronic knee pain (cKP) affects approximately 25% of adults worldwide, with prevalence increasing over recent decades. While conventional treatments have clinical limitations, several types of electrical stimulation have been suggested to improve patients’ quality of life. The electrical stimulation literature contains inadequate patient-reported outcome measures (PROMs) data. Encouraging preliminary H-Wave^® device PROMs results for chronic neck, shoulder, and low back pain have previously been published. This PROMs study’s goal is to similarly assess the efficacy of H-Wave^® device stimulation (HWDS) in patients with differing knee disorders. Materials and Methods: This is an independent, retrospective, observational cohort study analyzing H-Wave^® PROMs data, prospectively and sequentially collected over 4 years. In total, 34,192 pain management patient final surveys were screened for participants who were at least 18 years old, used H-Wave^® for any knee-related disorder, reporting chronic pain from 90 to 730 days, with device treatment duration from 22 to 365 days. PROMs included effects on function, pain, sleep quality, need for medications, ability to work, and patient satisfaction; additional data includes gender, age (when injured), chronicity of pain, prior treatments, and frequency and length of device use. Results: PROMs surveys from 34,192 HWDS patients included 1143 with “all knee”, 985 “knee injury”, and 124 “knee degeneration” diagnoses. Reported improvements in function/ADL (96.51%) and work performance (84.63%) were significant (p < 0.0001), with ≥20% pain relief in 86.76% (p < 0.0001), improving 2.96 points (average 0–10 NRS). Medication use decreased (69.85%, p = 0.0008), while sleep improved (55.33%) in knee injury patients. Patient satisfaction measures exceeded 96% (p < 0.0001). Subgroup analysis suggests that longer device use and shorter pain chronicity resulted in increased (p < 0.0001) HWDS benefits. Conclusions: HWDS PROMs data analysis demonstrated similarly encouraging outcomes for cKP patients, as previously reported for several other body regions. Knee injury and degeneration subgroups had near-equivalent benefits, as observed for all knee conditions. Despite many reported methodological limitations, which limit causal inference and preclude broader recommendations, HWDS appears to potentially offer several benefits for refractory cKP patients, requiring further studies. Full article

With the rapid development of the automotive industry, particularly the year-on-year growth in sales of new energy vehicles, automobile outer panel materials have shown a trend toward high-strength lightweight solutions. Regarding steel for outer panels, existing research has paid less attention to the UF steel that has entered the market in recent years. Moreover, studies on the similarities and differences in deformation behavior among various outer panel steels are lacking. In this study, room-temperature tensile tests at 5% and 8% strain were conducted in accordance with the stamping deformation range on commonly used ultra-low carbon automotive outer panel steels of comparable strength grades, namely, UF340, HC180BD, and DX53D+Z. Prior to deformation, the three materials exhibited similar texture components, predominantly characterized by the γ-fiber texture beneficial for deep drawing, and their room-temperature tensile deformation behaviors were fundamentally identical. After transverse tensile deformation, the textures concentrated towards {111}<112> texture. After 8% deformation, UF340 demonstrated a more rapid stress increase and a higher degree of work hardening. This phenomenon is attributed to the presence of the precipitate free zone (PFZ) near grain boundaries in the UF340, which facilitates the continuous generation of dislocations at grain boundaries during deformation, leading to a rapid increase in dislocation density within the grains. Consequently, this induces accelerated work hardening under small-strain conditions. This mechanism enables UF steels to achieve a strength level comparable to that of bake-hardened (BH) steels, exhibiting a significant performance advantage. Full article