Search Results (522)

Background/Objectives: Trabecular bone exhibits brittle behaviour governed by microscale deformation and damage, yet quantifying crack progression is difficult because classical fracture-mechanics approaches do not apply to architecturally discontinuous porous tissue. This pilot study evaluates whether synchrotron X-ray computed tomography (XCT) combined with digital volume correlation (DVC) can provide a practical, geometry-normalised approach for quantifying crack-opening behaviour in human trabecular bone. Methods: Semicylindrical specimens from femoral heads of hip-fracture donors (n = 5) and non-fracture controls (n = 5) underwent stepwise three-point bending during XCT imaging. Full-field displacement maps were used to measure crack mouth opening displacement (CMOD), crack length (a), and their ratio CMOD/a, used here as a geometry-normalised comparative descriptor of brittle response rather than an intrinsic material property. Automated phase-congruency crack detection (PCCD) was compared with manual measurement. Results: XCT–DVC resolved three-dimensional displacement discontinuities during crack initiation and propagation in all specimens. Hip-fracture donors exhibited significantly lower critical crack-opening ratios (CMOD/a)* than Controls (median 0.31 vs. 0.47; p = 0.008) and reached instability at lower applied loads. Total crack extension (Δa*) was similar between groups. Automated crack tracking using phase-congruency-based segmentation showed excellent agreement with manual measurements (r² = 0.98), supporting reliable extraction of crack geometry from DVC displacement fields. Conclusions: In this small pilot sample, XCT–DVC provided a feasible, geometry-normalised approach for comparing crack-opening behaviour where classical fracture-mechanics parameters cannot be applied. The close agreement between automated and manual crack measurements supports the reproducibility of the displacement-based measurement pipeline. The lower critical CMOD/a in hip-fracture specimens may indicate a more brittle comparative response. However, given the small sample, differing sex distribution, and lower bone volume fraction in the hip-fracture group, these findings are preliminary and require confirmation in larger cohorts. Establishing whether the observed difference reflects intrinsic tissue brittleness, architectural factors, or both is an important objective for future work in microstructure-matched cohorts. Full article

To investigate the influence of propeller rotational speed on the flooding process, sailing trajectory, and motion responses of a damaged surface naval ship under various sea conditions, numerical simulations were conducted using STAR-CCM+. The study is based on the Finite Volume Method (FVM), the Volume of Fluid (VOF) approach, the body force method, overset grids, and a multi-degree-of-freedom motion system. The flooding behavior, trajectory evolution, and hydrodynamic responses of the damaged naval ship were analyzed under calm water, head sea, and beam sea conditions, each at four distinct propeller speeds. The research findings indicate that, regardless of the sea state, a damaged naval ship initially travels in a straight line for a certain distance before transitioning into a curved trajectory. The length of the straight-line travel remains largely unaffected by variations in propeller rotational speed but varies with different sea conditions. Notably, under beam sea conditions, this distance exhibits a significant reduction. The subsequent curved motion trajectory is significantly influenced by the propeller rotational speed and varying wave directions. In calm water, the motion exhibits repetitive circular trajectories toward the damaged side, with the diameter of the circular path increasing as the propeller speed rises. Under head and beam sea conditions, the vessel exhibits a helical motion, with the trajectory becoming more pronounced as the propeller rotational speed increases. In all three wave conditions, the maximum cumulative ingress of the damaged compartment is positively correlated with the propeller speed, whereas the ship’s roll, pitch, and heave motions exhibit distinct variation trends. Full article

Background: Breastfeeding enhances infant and maternal health, but global breastfeeding rates remain suboptimal. Virtual reality (VR) emerges as a promising tool for breastfeeding education. The objective of this review was to assess the effectiveness of VR-based interventions on breastfeeding outcomes in pregnant and postpartum women. Methods: PubMed, Embase, Web of Science, Scopus, and CENTRAL were searched until 10 January 2026, for randomized controlled trials (RCTs) and quasi-experimental studies comparing VR-based interventions (immersive simulations, 360° videos, or head-mounted displays) with standard care or non-VR comparators in pregnant or postpartum women. Primary outcomes included breastfeeding self-efficacy, motivation, and breastfeeding technique (LATCH score). Secondary outcomes included exclusive breastfeeding rates, milk production, and maternal anxiety. Risk of bias was assessed using the RoB 2.0 and ROBINS-I tools for RCTs and non-RCTs, respectively. A random-effects meta-analysis was conducted, with results reported as mean differences (MD) or risk ratios (RR), along with 95% confidence intervals (CIs). Certainty of the evidence was assessed using the GRADE approach. Results: Five studies (4 RCTs and 1 quasi-experimental; n = 344) were included. VR improved prenatal breastfeeding self-efficacy (2 studies, MD: 13.93; 95% CI: 10.96–16.90), motivation (1 study, MD: 2.88; 95% CI: 1.66–4.10), and LATCH score (1 study, MD: 1.72; 95% CI: 1.37–2.07), and reduced time to breastfeeding initiation (1 study, MD: −22.4 min; 95% CI: −29 to −15.9), the certainty of evidence was low to very low for these outcomes. No significant effects were observed for postnatal self-efficacy, exclusive breastfeeding, or maternal anxiety. Formal assessment of publication bias could not be done. The small sample sizes for most outcomes, heterogeneity, the open-label nature of the trials, and the subjective nature of the outcomes should be considered when interpreting these results. Conclusions: VR-based interventions may improve process outcomes, such as prenatal breastfeeding self-efficacy, motivation, breastfeeding technique, and early breastfeeding initiation; the certainty of evidence is low to very low. Evidence for clinically important outcomes, including exclusive breastfeeding and maternal anxiety, remains inconsistent. Larger, well-designed RCTs are warranted before these interventions can be considered in routine practice. Full article

Optical coherence tomography angiography (OCTA) is a depth-resolved, label-free optical imaging modality that uses motion contrast from repeated B-scans to reconstruct retinal microvasculature and provide co-registered en face views of the superficial and deep vascular plexuses (SVP and DVP). This capability is valuable for early diabetic retinopathy (DR) assessment, where deep-plexus perfusion deficits may precede clinically evident disease. However, microvascular differences among healthy controls, diabetic eyes without clinically apparent retinopathy, and mild DR are subtle and unevenly distributed across the two vascular slabs, while most deep learning methods prematurely fuse the plexuses and weaken depth-specific evidence provided by OCTA. To address this, we propose Class-Path Specific Representation Distillation and Reasoning (CPS-RDR), an interpretable framework that aligns model reasoning with the layered organization of OCTA. A frozen DINOv2-initialized dual-branch Vision Transformer preserves separate SVP and DVP representations, while class- and path-conditioned diagnostic queries instantiate four reasoning pathways for layer-specific evidence extraction and directional cross-plexus interaction. A lightweight EvidenceFusion head linearly integrates pathway-wise evidence, enabling final predictions to be decomposed into pathway-specific contributions. On 99 eyes from 55 participants, CPS-RDR achieved 97.29% accuracy, 0.9932 macro-AUC, and 0.9829 macro-F1 under five-fold patient-level cross-validation, outperforming seven representative baselines, while producing path-resolved maps that reveal how superficial- and deep-layer optical signals jointly support early DR stratification. Full article

This paper addresses the data-driven identification of open-chain robot morphology from finite windows of heterogeneous signals, including commanded joint references, measured joint states, and end-effector pose observations. Unlike conventional calibration procedures that assume a known kinematic topology, the proposed formulation estimates both discrete structural quantities and continuous kinematic coordinates: the number of active joints, the revolute/prismatic token sequence, Product-of-Exponentials (POE) screw axes, and the home pose of the end effector. A temporal transformer encoder is used as the main estimator and compared with a gated recurrent unit (GRU) baseline on the same dataset, with the same output heads and a multitask physics-aware objective. The continuous target is expressed in POE coordinates rather than as a Denavit–Hartenberg table because POE directly represents spatial joint axes and avoids several frame-assignment ambiguities. Simulated results on a noisy benchmark of 48 serial-robot families show that both sequence models recover the discrete structure on the tested in-library trajectories, while their continuous reconstruction errors reveal different trade-offs in screw-axis, home-pose, and trajectory reconstruction accuracy. The study also discusses inactive-slot masking, out-of-library behavior, synthetic-to-real limitations, persistent excitation, and the role of the learned model as an initialization for subsequent calibration refinement. Full article

Retrieving non-optically active water quality variables, such as total hardness (TH) and permanganate index (CODMn), from hyperspectral data remains challenging because these parameters are not directly linked to spectral reflectance. To improve their estimation from UAV hyperspectral imagery, a GA-MHSA-BPNN framework was developed by combining a genetic algorithm (GA), multi-head self-attention (MHSA), and a backpropagation neural network (BPNN). In this framework, MHSA was introduced to strengthen the representation of informative spectral features, while GA was applied to optimize the initial network parameters and thus enhance convergence stability. The proposed framework was evaluated against BPNN, GA-BPNN, MHSA-BPNN, and 1D-CNN models. Among the tested approaches, GA-MHSA-BPNN produced the most favorable results for both TH and CODMn, with R² values of 0.878 and 0.843, respectively. Additional experiments using different proportions of training samples showed that the model remained relatively stable when the training data were reduced to 70% and 50% of the original dataset. These results indicate that integrating GA and MHSA into a UAV hyperspectral retrieval framework can improve the estimation of non-optically active water quality variables and provide useful methodological support for efficient and refined monitoring of drinking water source areas. Full article

This study examines how pre-service English teachers in Turkey experience the dimensions of proactive personality, job crafting, flow, and work engagement while making sense of their professional lives. In the phenomenological design research, semi-structured interviews were conducted with 13 teacher candidates selected through purposive sampling. Qualitative data were transcribed and subsequently analyzed using MAXQDA 2022 qualitative data analysis software and high inter-coder reliability was found. The findings were grouped under four themes. Under the heading of proactive personality, solution-focus, patience and communication, seeking support, and continuous development came to the fore. In the flow experience, open feedback from students, activities that made learning enjoyable, changes in the perception of time, and full participation in the natural flow of the lesson stood out. Professional craftsmanship manifested itself through strategies such as establishing trust-based relationships with students, colleagues, and parents, adapting methods, self-care, and time management. Dedication to work was defined through passion for the profession and the vitality provided by working with different student profiles. The results showed that teacher candidates demonstrated resilience-oriented professional strategies by combining individual initiative, social support, and continuous development tendencies. Furthermore, student-centered feedback and community-based relationships are understood to strengthen flow experiences and nurture dedication to work. The study points to the importance of supporting proactive tendencies in teacher training and designing learning environments conducive to flow. Full article

Arnica (Chiliadenus glutinosus (L.) Fourr.) is an endemic plant widely used in Spanish traditional medicine as infusions and alcoholic macerates for different ailments. Despite this use, information about the biological activity of these preparations in fish-related models is scarce. In the present study, the arnica extract bioactivity assay evaluated aqueous, ethanolic, and methanolic extracts at different doses (0, 0.001, 0.01, 0.125, 0.25, 0.5, and 1 mg mL⁻¹) to compare their antioxidant activity, effects on four marine fish pathogens (Vibrio harveyi, Vibrio anguillarum, Photobacterium damselae and Tenacibaculum maritimum), cytotoxicity on the PLHC1 tumour cell line, and their impact on immunological parameters in head-kidney leucocytes (HKLs) of gilthead seabream (Sparus aurata). All extracts showed dose-dependent antioxidant activity, while bactericidal effects depended on the solvent and were mainly observed at the highest concentrations. Ethanolic and methanolic extracts displayed clear cytotoxicity, whereas the aqueous extract showed lower toxicity and was selected for further evaluation. In the carrageenan stimulation assay, selected concentrations (0, 0.25, and 0.5 mg mL⁻¹) of the aqueous extract were tested in leucocytes stimulated with λ-carrageenan (0 and 1000 µg mL⁻¹), and respiratory burst and phagocytic activity, cell morphology, and gene expression were analysed. The aqueous extract reduced respiratory burst and phagocytic capacity in activated leucocytes and was associated with morphological signs of cell activation. It also downregulated crel and casp9 expression. These results provide a comparative view of the in vitro bioactivity of different traditional preparations of arnica and show that their biological effects strongly depend on the solvent used and the concentration tested, providing initial experimental information on their cellular effects in fish. Full article

Accurate prediction of lithium-ion battery state of health (SOH) is crucial for improving the safety, reliability, and operational efficiency of battery management systems (BMSs). However, many data-driven methods still struggle to maintain robust forecasting performance when degradation trajectories differ across cells, especially in later-stage aging. To address this issue, this study developed a robustness-oriented SOH prediction framework, termed Ada-TL, by integrating a Transformer encoder, an LSTM regressor, and adaptive hyperparameter tuning. Cycle-level health indicators were extracted from the publicly available CALCE dataset and transformed into a compact representation for supervised learning. The Transformer module captures non-local dependencies within each input window, whereas the LSTM summarizes sequential degradation dynamics. The number of attention heads, the initial learning rate, and the L2 regularization coefficient are adaptively optimized to reduce manual trial-and-error in model configuration. Experimental results on four CS2 cells show that Ada-TL consistently outperformed BP, CNN–LSTM, and the fixed-hyperparameter baseline in overall SOH prediction accuracy, achieving RMSE values of 0.0210–0.0310, MAE values of 0.0163–0.0262, and MAPE values of 4.17–9.30%. Additional late-stage and cumulative-drift analyses further indicate that Ada-TL provided more stable post-knee tracking and better control of long-horizon bias accumulation, with late-stage RMSE reduced to 0.0169–0.0217 across the four cells. An ablation study also showed that the KPCA-based three-dimensional representation improved the overall test-set accuracy on most cells while reducing input dimensionality. These results suggest that the main value of Ada-TL lies in robustness-oriented SOH forecasting under cell-to-cell variability. Full article

Background: Amnestic mild cognitive impairment (aMCI) is considered a transitional state between normal aging and dementia, often without visible abnormalities on standard brain magnetic resonance (MR) images. The aim of the study was to analyze both microstructural and functional brain abnormalities using advanced MR techniques. Methods: The study included 27 patients with aMCI and an age-matched control group (CG) of 25 healthy subjects. All MR studies were performed on a 3T MR scanner (Philips, Ingenia) with a 32-channel head and neck coil using volumetric 3D T1 sequences, followed by a resting-state functional MRI (rs-fMRI) sequence. Volumetric analysis was performed using the Destrieux atlas to assess potential structural differences between groups. Seed-to-voxel functional connectivity analyses were conducted using the bilateral hippocampi and both anterior and posterior divisions of the parahippocampal gyri as seed regions. Results: Compared to healthy controls, reduced cortical thickness was observed in aMCI subjects in the temporal regions, frontal and orbitofrontal areas, limbic areas, parietal and sensorimotor cortices, as well as occipito-temporal regions. Additionally, significantly increased functional connectivity was observed between bilateral medial temporal lobe (MTL) regions and the right thalamus. Conclusions: Cortical thinning in various brain regions along with the increased functional connectivity between the MTL regions and the right thalamus may reflect potential compensatory mechanisms in response to initial subtle degenerative changes, emphasizing the importance of using both functional and structural imaging to detect early changes in aMCI patients. Full article

Background: The role of immune checkpoint inhibition in treating head and neck squamous cell carcinoma (HNSCC) is expanding, yet response rates to PD-L1 therapy remain inconsistent and generally poor. Although several studies have examined heterogeneous intratumoral PD-L1 expression, the disparity in response to PD-L1 therapy between primary tumors and their associated lymph node metastases remains unclear. Methods: Primary tumor samples and two matching lymph node metastases were obtained from a cohort of 50 patients and immunohistochemically stained with a PD-L1 antibody. PD-L1 expression, assessed using the combined positive score (CPS) and tumor proportion score (TPS), and immune infiltration, measured with an immunoreactive score (IRS), were compared between the primary tumor and lymph node metastases. These measures were then correlated with other histopathological and clinical features. Results: PD-L1 expression, evaluated by CPS and TPS, showed no significant differences between the primary tumor and matched lymph node metastases. Discordance relative to established regulatory cut-offs was observed in a subset of patients, affecting 18% (CPS; 95% CI, 8.0–30.0%) and 4% (TPS; 95% CI, 0.0–10.0%) of cases. CPS and TPS values were not influenced by primary tumor subsite or HPV status. Conversely, immune infiltration measured by IRS was significantly affected by primary tumor subsite location. Both HPV tumor status and primary tumor subsite were statistically significantly associated with overall survival. Conclusions: Our findings highlight variability in PD-L1 expression in HNSCC and may offer context for differential responses of primary tumors and lymph node metastases to immune checkpoint therapy reported in recent clinical studies. These observations support the need for a more comprehensive characterization of PD-L1 expression across tumor sites in head and neck cancer. Further investigation is required to determine whether, and in which settings, reassessment of PD-L1 status in metastatic lesions—including lymph node metastases—may provide additional clinically relevant information when initial testing does not meet established therapeutic cut-offs. Full article

Traditional pedestrian inertial navigation (PDR) algorithms usually assume that the carrying mode of a smartphone is fixed and remains horizontal, while ignoring the significant impact of dynamic changes in the carrying mode on heading estimation, which is the core element of PDR algorithms. In practical application scenarios, pedestrians often change their way of carrying smart terminals (e.g., calling) according to their needs, corresponding to the difference in the heading estimation method; especially when the mode is switched, it will cause a sudden change in heading, which will lead to a significant increase in the localization error if it cannot be corrected in time. Existing smart terminal carrying mode recognition methods that rely on traditional machine learning or set thresholds have poor robustness; lack of universality, especially weak diagnostic ability for mutation; and can not effectively reduce the heading error. Based on these practical problems, this paper innovatively proposes a PDR framework that tries to overcome these limitations. Based on this research purpose, firstly, this paper classifies four types of common carrying modes based on practical applications and designs a CNN-LSTM hybrid model, which can classify the four common carrying modes in near real-time, with a recognition accuracy as high as 99.68%. Secondly, based on the mode recognition results, a multi-layer heading correction strategy is introduced: (1) introducing a quaternion-based universal filter (VQF) algorithm to realize the accurate estimation of initial heading; (2) designing an algorithm to accurately detect the mode switching point and developing an adaptive offset correction algorithm to realize the dynamic compensation of heading in the process of mode switching to reduce the impact of sudden changes; and (3) considering the motion characteristics of pedestrians walking in a straight line segment where lateral displacement tends to be close to zero. This study designs a heading optimization method with lateral displacement constraints to further inhibit the drifting of the heading caused by the slight swaying of the smart terminal. In this study, two validation experiments are carried out in two different environment—an indoor corridor and a tree shelter—and the results show that based on the proposed multi-layer heading optimization strategy, the average heading error of the system is lower than 1.5°, the cumulative positioning error is lower than 1% of the walking distance, and the root mean square error of the checkpoints is lower than 2 m, which significantly reduces the positioning error and shows the effectiveness of the framework in complex environments. Full article

This paper proposes a dynamic obstacle-avoidance algorithm for unmanned surface vehicles (USVs) that combines a Fuzzy-enhanced Dynamic Window Approach (FDWA) with an Improved Bidirectional A*–Improved Grey Wolf Optimizer (IBA*–IGWO) framework. Firstly, the traditional dynamic window method (DWA) is improved by adopting an initial heading angle optimization strategy to reduce the heading deviation of unmanned vessels during cruising. Secondly, a fuzzy controller is introduced, which can adaptively adjust the weight coefficients in the cost function of the DWA algorithm based on the current position of the unmanned vessel, surrounding environmental information, etc., to improve obstacle avoidance ability and adaptability in different environments. Finally, using the global static cruise route provided by the IBA*–IGWO algorithm, key nodes are selected as local endpoints for the FDWA algorithm to ensure that the unmanned vessel can perform cruise tasks according to the optimal plan during navigation and make dynamic adjustments in case of emergencies. The simulation results demonstrate the feasibility of the proposed method in handling unknown and dynamic obstacles under the current grid-based experimental settings, while enabling the USV to return to the pre-planned global route after local obstacle avoidance. These results provide a basis for further development toward more robust and rule-aware autonomous navigation in realistic maritime environments. Full article

A rock-socketed pile model load test was conducted for the renovation project of the dangerous old bridge at Shaoping Bridge. The experiment focused on the core parameter of the roughness factor (RF) of the pile body, revealing its influence on the bearing characteristics. The study delved into the load–displacement relationship, ultimate bearing capacity evolution, axial force transmission mechanism, average lateral resistance performance characteristics, and pile–soil relative displacement law of test piles in complex rock formations under different RF values. The research results indicated the following: The test pile exhibited typical brittle failure. At the moment of failure, the load at the pile head dropped abruptly, resulting in a steep drop in its load–displacement curve. Under ultimate load conditions, the average attenuation amplitudes of axial force in the four test piles decreased progressively in Rock Layer I, II, and III, measuring 26.96%, 14.86%, and 10.84%, respectively. The average side resistance distribution along the pile shaft showed a single-peak pattern, peaking in Rock Layer I. Increasing RF effectively enhanced the bearing capacity of test piles. However, a higher RF value does not necessarily yield better results, as it exhibits an inverted U-shaped relationship with bearing capacity. Under the specific conditions of this study, the highest bearing capacity among the tested RF values was observed at RF = 0.168; beyond this threshold, performance actually declined. The pile-top load was primarily shared by side resistance and end bearing resistance. Both components initially increased and then decreased with increasing RF, where the end bearing resistance accounted for 43.64~49.47% of the upper load. Full article

Atlantic salmon (Salmo salar) is an important dietary source of health-promoting long-chain polyunsaturated fatty acids (PUFAs). As rearing conditions significantly influence fillet quality, this study evaluated the effects of warm and cool rearing temperature and photoperiod regimes on salmon growth, lipid profiles, and antioxidant capacity. Atlantic salmon (210 days old) were reared for 92 days under low temperature (14 °C, 12 h light) or high temperature (21 °C, 24 h light) conditions to simulate relevant seasonal conditions, winter and summer respectively. At day 302, conditions were reversed to create low-to-high (L→H) and high-to-low (H→L) treatments, continuing until day 362. Growth parameters, muscle lipid content, fatty acid profile, and antioxidant activity were measured at 302 and 362 days. Lipid content and fatty acid profile were also measured based on fillet location and fish sex. High rearing temperatures accelerated weight gain and increased total and neutral lipid contents, but elevated saturated fatty acids (SFA) and decreased PUFAs in structural polar lipids. High temperatures also significantly increased antioxidant activity, indicating elevated oxidative stress. Conversely, low temperatures suppressed growth but preserved essential PUFAs and maintained oxidative stability. Following the temperature shift, the H→L group had enriched polar lipids with PUFAs and maintained oxidative stability. On the other hand, L→H group showed lower PUFAs accumulation in polar lipid and enhanced oxidative stress. Total lipid content was higher in the head region, followed by the middle and tail sections of the fillet. However, fatty acid composition remained largely uniform across all three sections of the fillet. There were no significant differences in total lipid content between fish sexes. In conclusion, production efficiency and nutritional quality can be optimized by initially rearing salmon at high temperatures to promote rapid growth, followed by low temperature finishing phase to increase essential PUFA content and maintain oxidative stability. Full article