Search Results (159)

This study focuses on the analysis of the simultaneous impact of inclined magnetohydrodynamic Carreau hybrid nanofluid flow over a stretching sheet, including microorganisms with the effects of chemical reactions in the presence and absence of slip conditions for dilatant $(n>1.0)$ and quasi-elastic hybrid nanofluid $(n<1.0)$ limitations. Meanwhile, the transfer of energy is strengthened through the employment of heat sources and bioconvection. The analysis incorporates nonlinear thermal radiation, chemical reactions, and Arrhenius activation energy effects on different profiles. Numerical simulations are conducted using the efficient Bvp5c solver. Motile concentration profiles decrease as the density slip parameter of the motile microbe and Lb increase. The Weissenberg number exhibits a distinct nature depending on the hybrid nanofluid; the velocity profile, skin friction, and Nusselt number fall when $(n>1.0)$ and increase when $(n<1.0)$. For small values of inclination, the 3D surface plot is far the surface, while it is close to the surface for higher values of inclination but has the opposite behavior for the 3D plot of the Nusselt number. A detailed numerical investigation on the effects of important parameters on the thermal, concentration, and motile profiles and the Nusselt number reveals a symmetric pattern of boundary layers at various angles $\left(\alpha \right)$. Results are presented through tables, graphs, contour plots, and streamline and surface plots, covering both shear-thinning cases $(n<1.0)$ and shear-thickening cases $(n>1.0)$. Full article

Background: Arterial switch operation (ASO) is the standard surgical treatment for dextro-transposition of great arteries (d-TGA). Long-term complications affecting pulmonary arteries, coronary arteries, and aortic root necessitate detailed surveillance, but the optimal imaging strategy remains undefined. Methods: We retrospectively analyzed 47 patients with d-TGA who underwent ASO between January 2023 and June 2025 with at least six months postoperative follow-up. All patients underwent both transthoracic echocardiography (TTE) and ECG-gated cardiac CT angiography (CTA). Anatomical measurements, functional parameters, and diagnostic completeness were compared between modalities. Results: Median age at follow-up was 37.2 months. CT detected pulmonary artery stenosis in 31 patients (65.9%) and aortic root dilatation in 31 patients (65.9%). TTE provided incomplete pulmonary artery assessment in 11 patients (23.4%) and incomplete coronary evaluation in 13 patients (27.6%), while CT successfully evaluated all patients (100%). Strong correlation was found between left pulmonary artery bending angle and aortic root dimensions (r = 0.65, p = 0.016), suggesting mechanical interdependence of post-surgical anatomical changes. Median radiation exposure was 2.684 mSv (IQR: 1.5–4.6). During follow-up, 10 patients (21.3%) required cardiovascular interventions, with CT providing complete pre-intervention assessment in all cases. Conclusions: TTE alone is insufficient for complete anatomical assessment following ASO. An integrated imaging approach utilizing TTE for functional assessment and CT for anatomical evaluation optimizes post-ASO surveillance. Full article

The fracture evolution of brittle rock under 3D stress states remains poorly understood, particularly the role of deviatoric stress symmetry as characterized by the Lode angle (θ_σ). To address this knowledge gap, we systematically investigated sandstone using a true triaxial loading apparatus under a constant mean stress (100 MPa) while varying θ_σ from −30° to +30°, integrated with real-time acoustic emission (AE) monitoring and post-failure X-ray computed tomography. Our results demonstrate a critical linear reduction in peak strength with increasing θ_σ. This strength reduction is accompanied by a corresponding transition in failure mechanism, from a progressive mode dominated by dilation to an abrupt mode characterized by shear localization. Innovatively, we introduce a novel AE-based parameter (C), derived from the coupled evolution of AE energy and hit rates, which quantifies fracturing intensity in real-time without pre-defined lithological and monitoring scale. Furthermore, digital reconstruction reveals that consistent X-shaped polymodal fault networks are governed by sequential tensile–shear interactions. This key mechanistic insight prompts us to propose a new “deflected shear–tensile hybrid kinked fracture” classification, which more accurately captures the topological complexity of fractures under 3D stresses than conventional monomodal schemes. This study provides fundamental insights into 3D rock fracture mechanics and practical tools for enhancing safety and efficiency in deep geo-engineering. Full article

(1) Background: Soccer action recognition (SAR) is essential in modern sports analytics, supporting automated performance evaluation, tactical strategy analysis, and detailed player behavior modeling. Although recent advances in deep learning and computer vision have enhanced SAR capabilities, many existing methods remain limited to coarse-grained classifications, grouping actions into broad categories such as attacking, defending, or goalkeeping. These models often fall short in capturing fine-grained distinctions, contextual nuances, and long-range temporal dependencies. Transformer-based approaches offer potential improvements but are typically constrained by the need for large-scale datasets and high computational demands, limiting their practical applicability. Moreover, current SAR systems frequently encounter difficulties in handling occlusions, background clutter, and variable camera angles, which contribute to misclassifications and reduced accuracy. (2) Methods: To overcome these challenges, we propose TAT-SARNet, a structured framework designed for accurate and fine-grained SAR. The model begins by applying Sparse Dilated Attention (SDA) to emphasize relevant spatial dependencies while mitigating background noise. Refined spatial features are then processed through the Split-Stream Feature Processing Module (SSFPM), which separately extracts appearance-based (RGB) and motion-based (optical flow) features using ResNet and 3D CNNs. These features are temporally refined by the Multi-Granular Temporal Processing (MGTP) module, which integrates ResIncept Patch Consolidation (RIPC) and Progressive Scale Construction Module (PSCM) to capture both short- and long-range temporal patterns. The output is then fused via the Context-Guided Dual Transformer (CGDT), which models spatiotemporal interactions through a Bi-Transformer Connector (BTC) and Channel–Spatial Attention Block (CSAB); (3) Results: Finally, the Cascaded Temporal Classification (CTC) module maps these features to fine-grained action categories, enabling robust recognition even under challenging conditions such as occlusions and rapid movements. (4) Conclusions: This end-to-end architecture ensures high precision in complex real-world soccer scenarios. Full article

The kinetic dependencies of the surface pressure, the dilational dynamic surface elasticity and ellipsometric angles of cupin-1.2 and vicilin solutions in 8M urea were measured at different concentrations. The analysis of these kinetics dependencies and the obtained master curves allowed us to determine a few adsorption steps in the investigated systems and showed that the master curves are individual characteristics of the protein for a given solvent. At the same time, the shape of these curves can be different for adsorbed and spread layers of plant proteins indicating different structures of these layers. The dependencies of the dynamic surface elasticity on surface pressure are non-monotonic, unlike the corresponding results for most of the solutions of the investigated plant proteins. The extremums of these dependencies can be connected to the formation of the distal region of the surface layer in agreement with the theory for the surface viscoelasticity of polymer solutions. Full article

This paper presents a comprehensive review of dilation angle models in rock mechanics. Dilation, a characteristic behavior of geomaterials, such as rocks and rock masses, involves volumetric changes during plastic deformation. This study focuses on the dilation angle, a key parameter for measuring dilation, and its dependence on the plastic strain history and confining stress. The review covers ten variable dilation angle models developed over the past two decades and analyzes their equations, parameters, and main features. These models range from simple approaches with few parameters to complex formulations that involve multiple coefficients. The strengths and limitations of each model, including their applicability to different rock types and testing conditions, are presented. Key findings include the importance of considering both plastic strain history and confining stress in dilatancy models, the variation in approaches for defining the onset of plastic strain, and the challenges in standardizing and comparing different models. This review also highlights the ongoing debate regarding the influence of rock type, specimen size, and structure on dilatant behavior. This review contributes to the field of rock mechanics by providing a comprehensive overview of the current dilatancy models, their applications, and limitations. It serves as a valuable resource for researchers and practitioners in geomechanical engineering, particularly in areas such as tunnel design, mining engineering, and petroleum extraction, where understanding the post-peak behavior of rocks may be crucial. Full article

This study concerns the evaluation of adhesive and wettability energetic signatures of a model orthodontic wire exposed to commercial mouthrinses. The surface wetting properties were evaluated from the contact angle hysteresis (CAH) approach applied to dynamic contact angle data derived from the original drop on a vertical filament method. Young, advancing, receding CA apart from adhesive film pressure, surface energy, work of adhesion, etc. were chosen as interfacial interaction indicators, allowing for the optimal concentration and placement of the key component(s) accumulation to be predicted for effective antibacterial activity to eliminate plaque formation on the prosthetic materials. Surfactant compounds when adsorb at interfaces confer rheological properties to the surfaces, leading to surface relaxation, which depends on the timescale of the deformation. The surface dilatational complex modulus E, with compression elasticity E_d and viscosity E_i parts, determined in the stress–relaxation Langmuir trough measurements, exhibited the viscoelastic surface film behavior with the relaxation times (0.41–3.13 s), pointing to the vertically segregated film structure as distinct, stratified layers with the most insoluble compound on the system top (as indicated with the 2D polymer film scaling theory exponent y = 12.9–15.5). Kinetic rheology parameters could affect the wettability, adhesion, and spreading characteristics of mouthrinse liquids. Full article

The Standard Model (SM) fails to explain many problems (neutrino masses, dark matter, and matter–antimatter asymmetry, among others) that may be resolved with new particles beyond the SM. No observation of such new particles may be explained either by their exceptionally high mass or by considerably small coupling to SM particles. The latter case implies relatively long lifetimes. Such long-lived particles (LLPs) then to have signatures different from those of SM particles. Searches in the “central region” are covered by the LHC general purpose experiments. The forward small angle region far from the interaction point (IP) is unexplored. Such particles are expected to have the energy as large as E = $\mathcal{O}$(1 TeV) and Lorentz time dilation factor $\gamma =E/m\approx {10}^2$–${10}^3$ (with m the particle mass) hence long enough decay distances. A new class of specialized LHC detectors dedicated to LLP searches has been proposed for the forward regions. Among these experiments, FASER is already operational, and FACET is under consideration at a location 100 m from the LHC IP5 (the CMS detector intersection). However, some features of FACET require a specially enlarged beam pipe, which cannot be implemented for LHC Run 4. In this study, we explore a simplified version of the proposed detector PREFACE compatible with the standard LHC beam pipe in the HL-LHC Run 4. Realistic Geant4 simulations are performed and the background is evaluated. An initial analysis of the physics potential with the PREFACE geometry indicates that several significant channels could be accessible with sensitivities comparable to FACET and other LLP searches. Full article

During the automated picking of table grapes, the automatic recognition and segmentation of grape pedicels, along with the positioning of picking points, are vital components for all the following operations of the harvesting robot. In the actual scene of a grape plantation, however, it is extremely difficult to accurately and efficiently identify and segment grape pedicels and then reliably locate the picking points. This is attributable to the low distinguishability between grape pedicels and the surrounding environment such as branches, as well as the impacts of other conditions like weather, lighting, and occlusion, which are coupled with the requirements for model deployment on edge devices with limited computing resources. To address these issues, this study proposes a novel picking point localization method for table grapes based on an instance segmentation network called Progressive Global-Local Structure-Sensitive Segmentation (PGSS-YOLOv11s) and a simple combination strategy of morphological operators. More specifically, the network PGSS-YOLOv11s is composed of an original backbone of the YOLOv11s-seg, a spatial feature aggregation module (SFAM), an adaptive feature fusion module (AFFM), and a detail-enhanced convolutional shared detection head (DE-SCSH). And the PGSS-YOLOv11s have been trained with a new grape segmentation dataset called Grape-⊥, which includes 4455 grape pixel-level instances with the annotation of ⊥-shaped regions. After the PGSS-YOLOv11s segments the ⊥-shaped regions of grapes, some morphological operations such as erosion, dilation, and skeletonization are combined to effectively extract grape pedicels and locate picking points. Finally, several experiments have been conducted to confirm the validity, effectiveness, and superiority of the proposed method. Compared with the other state-of-the-art models, the main metrics $F1$ score and mask mAP@0.5 of the PGSS-YOLOv11s reached 94.6% and 95.2% on the Grape-⊥ dataset, as well as 85.4% and 90.0% on the Winegrape dataset. Multi-scenario tests indicated that the success rate of positioning the picking points reached up to 89.44%. In orchards, real-time tests on the edge device demonstrated the practical performance of our method. Nevertheless, for grapes with short pedicels or occluded pedicels, the designed morphological algorithm exhibited the loss of picking point calculations. In future work, we will enrich the grape dataset by collecting images under different lighting conditions, from various shooting angles, and including more grape varieties to improve the method’s generalization performance. Full article

Background/Objectives: Recent changes in obstetric practices and population demographics have prompted a re-evaluation of labor patterns. This study aimed to characterize labor patterns in a Greek pregnant population using ultrasound and compare them with established labor curves. Methods: A prospective cohort study was conducted at the Third Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, over a two-year period (December 2022 to June 2024). Transabdominal ultrasound was used to determine the fetal head position and transperineal ultrasound was used to measure angle of progression (AoP) and head–perineum distance (HPD) during labor. Maternal and labor characteristics, including body mass index (BMI), parity, labor duration, and mode of delivery, were recorded. Statistical analysis included mixed linear models to assess the relationship between AoP, HPD, and cervical dilatation. Results: In total, 500 parturients were included in this study. Women entered the active phase of labor approximately 5 h before delivery, with AoP increasing sharply and HPD decreasing rapidly at this point. Cesarean section (CS) cases showed a slower increase in AoP compared to vaginal deliveries (VDs), with CS cases having a mean AoP of 117.9° (95% CI: 111.6–124.2°) at full dilation, compared to 133.4° (95% CI: 130.6–136.2°) in VD. HPD values declined more slowly in CS cases, with a mean HPD of 45.1 mm (95% CI: 40.6–49.6 mm) at full dilation, compared to 36.4 mm (95% CI: 34.3–38.5 mm) in VD. Epidural analgesia was associated with steeper increases in AoP and decreases in HPD in the final 2.5 h before delivery, while oxytocin administration accelerated these changes in the last 3–4 h. The mean time to delivery was 3.19 h (95% CI: 2.80–3.59 h) when AoP reached 125° and 3.92 h when HPD was 40 mm (95% CI: 3.53–4.30 h). BMI in women who gave birth via CS was significantly higher compared to VD (32.03 vs. 29.94 kg/m², p-value: 0.008), and the total duration of labor was shorter in VD compared to CS and operative vaginal delivery (OVD) (8 h vs. 15 h, p-value < 0.001 and 8 h vs. 12 h, p-value < 0.001, respectively). Birthweight was also lower in VD compared to CS (3103.09 g vs. 3267.88 g, p-value: 0.05). Conclusions: This study provides the first ultrasonographic characterization of labor patterns in a Greek population, highlighting the utility of ultrasound in objectively assessing labor progression. Full article

Atmospheric climate science lacks the capacity to integrate thermodynamics with the gravitational potential of air in a classical quantum theory. To what extent can we identify Carnot’s ideal heat engine cycle in reversible isothermal and isentropic phases between dual temperatures partitioning heat flow with coupled work processes in the atmosphere? Using statistical action mechanics to describe Carnot’s cycle, the maximum rate of work possible can be integrated for the working gases as equal to variations in the absolute Gibbs energy, estimated as sustaining field quanta consistent with Carnot’s definition of heat as caloric. His treatise of 1824 even gave equations expressing work potential as a function of differences in temperature and the logarithm of the change in density and volume. Second, Carnot’s mechanical principle of cooling caused by gas dilation or warming by compression can be applied to tropospheric heat–work cycles in anticyclones and cyclones. Third, the virial theorem of Lagrange and Clausius based on least action predicts a more accurate temperature gradient with altitude near 6.5–6.9 °C per km, requiring that the Gibbs rotational quantum energies of gas molecules exchange reversibly with gravitational potential. This predicts a diminished role for the radiative transfer of energy from the atmosphere to the surface, in contrast to the Trenberth global radiative budget of ≈330 watts per square metre as downwelling radiation. The spectral absorptivity of greenhouse gas for surface radiation into the troposphere enables thermal recycling, sustaining air masses in Lagrangian action. This obviates the current paradigm of cooling with altitude by adiabatic expansion. The virial-action theorem must also control non-reversible heat–work Carnot cycles, with turbulent friction raising the surface temperature. Dissipative surface warming raises the surface pressure by heating, sustaining the weight of the atmosphere to varying altitudes according to latitude and seasonal angles of insolation. New predictions for experimental testing are now emerging from this virial-action hypothesis for climate, linking vortical energy potential with convective and turbulent exchanges of work and heat, proposed as the efficient cause setting the thermal temperature of surface materials. Full article

Background/Objectives: Anatomical and functional damage of the mitral valve (MV) apparatus in patients with dilated cardiomyopathy (DCM) is secondary to left ventricular (LV) injury, leading to functional mitral regurgitation (FMR). Real-time four-dimensional echocardiography (RT 4DE) is a useful imaging technique in different pathologies, including DCM. Left atrial (LA) strain, as measured by left atrium quantification software, is an accurate technique for evaluating increased filling pressure. The MV has a complex three-dimensional morphology and motion. Four-dimensional echocardiography (4DE) has revolutionized clinical imaging of the mitral valve apparatus. This study aims (1) to characterize the mitral annulus (MA) parameters in patients with DCM and advanced-stage heart failure (HF) according to etiology and (2) to find correlations between left atrial function and MA remodeling in this group of patients, using 4DE quantification software. Methods: A total of 82 patients with DCM and an LV ejection fraction ≤ 40% were recruited. Conventional 2DE and RT 4DE were conducted in DCM patients with a compensated phase of HF before discharge. The measured parameters were left atrial reservoir strain (LASr), annular area (AA), annular perimeter (AP), anteroposterior diameter (A-Pd), posteromedial to anterolateral diameter (PM-ALd), commissural distance (CD), interregional distance (ITD), annular height (AH), nonplanar angle (NPA), tenting height (TH), tenting area (TA), and tenting volume (TV). Results: Measured parameters revealed more advanced damage of LA and MA parameters in ischemic compared to nonischemic etiology. Univariate analysis identified AA, AP, A-Pd, PM-ALd, CD, ITD, TH, TA, and TV (p < 0.0001) as determinants of LASr. Including these parameters in a stepwise multivariate logistic regression, PM-ALd (p = 0.03), TH (p = 0.043), and TV (p = 0.0001) were the best predictors of LAsr in these patients. Conclusions: The results of this study revealed the correlation between LA function depression and MA remodeling in patients with DCM. Full article

To address the operational demands of irregular farmland with fixed obstacles, this study proposes a full-coverage path planning framework that integrates UAV-based 3D perception and angle-adaptive optimization. First, digital orthophoto maps (DOMs) and digital elevation models (DEMs) were reconstructed from low-altitude aerial imagery. The feasible working region was constructed by shrinking field boundaries inward and dilating obstacle boundaries outward. This ensured sufficient safety margins for machinery operation. Next, segmentation angles were scanned from 0° to 180° to minimize the number and irregularity of sub-regions; then a two-level simulation search was performed over 0° to 360° to optimize the working direction for each sub-region. For each sub-region, the optimal working direction was selected based on four criteria: the number of turns, travel distance, coverage redundancy, and planning time. Between sub-regions, a closed-loop interconnection path was generated using eight-directional A* search combined with polyline simplification, arc fitting, Chaikin subdivision, and B-spline smoothing. Simulation results showed that a 78° segmentation yielded four regular sub-regions, achieving 99.97% coverage while reducing the number of turns, travel distance, and planning time by up to 70.42%, 23.17%, and 85.6%. This framework accounts for field heterogeneity and turning radius constraints, effectively mitigating path redundancy in conventional fixed-angle methods. This framework enables general deployment in agricultural field operations and facilitates extensions toward collaborative and energy-optimized task planning. Full article

Understanding the mechanical behavior of frozen clay subgrade soils was essential for ensuring the safe and stable operation of transportation lines. However, the influence of remolding water content w on this behavior remained unclear. To address this gap, this study examined the effect of w through monotonic triaxial testing. Three typical remolding water contents (w = 19%, 27.5% and 35%) and three confining pressures (σ₃ = 200 kPa, 700 kPa and 1200 kPa) were considered. Results showed that the mechanical behavior of frozen clay soils displayed a clear dependence on w, which was controlled by microstructural evolution. As w increased, the shear strength q_max, resilient modulus E₀ and cohesion c increased, which resulted from the progressive development of ice bonding within the shear plane. A threshold w value was found at w_opt = 27.5%, marking a structural transition and separating the variations of q_max, E₀ and c into two regimes. When w ≤ 27.5%, the soil fabric was controlled by clay aggregates. As w increased, the growth in ice cementation was confined within these aggregates, leading to limited increase in q_max, E₀ and c. However, as w exceeded 27.5%, the soil fabric transitioned into a homogeneous matrix of dispersed clay particles. In this case, increasing w greatly promoted the development of an interconnected ice cementation network, thus significantly facilitating the increase in q_max, E₀ and c. The friction angle φ decreased with w increasing, primarily due to the lubrication effect caused by the growing ice. In addition, the enhanced lubrication effect in the clay particle-dominated fabric (w > 27.5%) resulted in a larger reduction rate of φ. Regarding Poisson’s ratio v and dilation angle ψ, the w increase led to growth in both parameters. This phenomenon could be explained by the increased involvement of solid ice into the soil structure. Full article

Access to significant amounts of data is typically required to develop structural health monitoring (SHM) systems. In this study, a novel SHM approach was evaluated, with all training data collected solely from a validated finite element analysis (FEA) of a reinforced concrete (RC) beam and the structural health based on the tension side of a rebar under flexural loading. The developed SHM system was verified by four-point bending experiments on three RC beams cast in the dimensions of 4000 mm × 200 mm × 400 mm. Distributed optical fibre sensors (DOFS) were mounted on the concrete surface and on the bottom rebar to maximise sample points and investigate the reliability of the strain data. The FEA model was validated using a single beam and subsequently used to generate labelled SHM strain data by altering the dilation angle and rebar sizes. The generated strain data were then used to train an artificial neural network (ANN) classifier using deep learning (DL). Training and validation accuracy greater than 98.75% were recorded, and the model was trained to predict the tension state up to 90% of the steel yield limit. The developed model predicts the health condition with the input of strain data acquired from the concrete surface of reinforced concrete beams under various loading regimes. The model predictions were accurate for the experimental DOFS data acquired from the tested beams. Full article