Search Results (3,938)

Aircraft targets in SAR imagery often exhibit discrete scattering characteristics, significant variations in pose and scale, strong speckle noise in background clutter, and complex background interference, which jointly hinder stable structural feature extraction and accurate target localization. Existing detectors for SAR aircraft recognition primarily rely on bounding-box regression and classification; they do not completely exploit target structural cues, spatial attention, and frequency-domain information. To address these limitations, we propose a collaborative detection framework that integrates an uncertainty-aware keypoint-driven module (UAKM) with a fractional Fourier convolution backbone (S-FRConv). UAKM introduces a center-keypoint regression branch that jointly predicts keypoint coordinates and Laplacian scale parameters and employs a 2D Laplace negative log-likelihood loss to estimate uncertainty. The derived dense uncertainty heatmap is then used as spatial attention weights to guide distribution-based regression and multi-scale feature re-weighting, without requiring any additional annotations. S-FRConv embeds the Fractional Fourier Transform into shallow backbone layers and C2f modules, enabling joint spatial–spectral feature modeling that suppresses speckle noise and enhances edge and orientation representations. Experiments on the public SAR-AIRcraft-1.0 dataset demonstrate that the proposed method systematically improves the detection performance. For the Nano model, the overall mAP50 increases from 0.810 to 0.867, and the mAP 50:95 improves from 0.637 to 0.655 compared with the baseline, corresponding to gains of 5.7 and 1.8 percentage points, respectively. These results validate the effectiveness and generalization potential of combining uncertainty-driven spatial attention with fractional spectral feature enhancement for SAR aircraft target detection. Full article

Blue mold caused by Penicillium italicum triggers severe tissue decay and limits postharvest shelf life, representing the primary constraint to the commercial supply chain of Shatangju mandarins (Citrus reticulata cv. Shatangju). In this study, the biocontrol efficacy of an antagonistic yeast, Meyerozyma guilliermondii SR1, against postharvest blue mold in Shatangju mandarins was evaluated. The results showed that SR1 significantly inhibited the in vitro growth of P. italicum, delayed disease progression and restricted pathogen sporulation in inoculated fruits during storage. Furthermore, SR1 rapidly colonized fruit wounds to establish a population advantage and enhanced the antioxidant defense capacity of the host fruits. Meanwhile, SR1 treatment significantly reduced postharvest weight loss, with no significant differences in total soluble solids (TSS) and titratable acidity (TA) compared with the control. In conclusion, M. guilliermondii SR1 showed significant biocontrol efficacy against postharvest blue mold in Shatangju mandarins, which provides an experimental basis for the research and development of green citrus postharvest preservatives. Full article

Background/Objectives: Bariatric surgery is an effective intervention for severe obesity; however, long-term outcomes may be influenced by postoperative dietary behaviors, nutritional status, and complications. In Saudi Arabia, longitudinal evidence on weight trajectories and postoperative diet quality remains limited. The present study aimed at evaluating three-year weight status trends; assessing sociodemographic factors, baseline BMI, and postoperative diet quality; and examining nutrition-related complications following bariatric surgery. Methods: This retrospective longitudinal study included 189 adults who underwent sleeve gastrectomy at two tertiary hospitals in Jeddah, Saudi Arabia. Anthropometric data were obtained from medical records at six time points: preoperative, two weeks, six months, one year, two years, and three years postoperatively. Diet quality and postoperative complications were assessed via structured telephone interviews. Weight outcomes were expressed as percentage of total body weight loss (%TBWL), excess body weight loss (%EWL), excess body mass index loss (%EBMIL), and weight regain. Statistical analyses included Friedman’s test, Mann–Whitney U test, and multiple linear regression. Results: Significant improvements in all weight loss indicators were observed over three years (p < 0.001). Diet quality score was the only significant variable associated with weight loss at three years, with higher scores associated with greater %EWL and %EBMIL. Baseline BMI and DQS were significantly associated with %EWL (Beta = −0.17, 95% CI: −1.72 to −0.13 and Beta = 0.21, 95% CI: 1.37 to 7.12, respectively) and %EBMIL (Beta = −0.15, 95% CI: −1.68 to −0.07 and Beta = 0.24, 95% CI: 1.90 to 7.66, respectively). Age was significantly associated with weight regain (Beta = 0.20, 95% CI: 0.02 to 1.08). Conclusions: Bariatric surgery resulted in sustained weight reduction over three years. Postoperative baseline BMI and diet quality were significantly associated with %EWL and %EBMIL, underscoring the importance of structured nutritional follow-up and counseling. Full article

Background: Prognostic stratification remains challenging in patients with stage IIIC non-small cell lung cancer (NSCLC) treated with definitive chemoradiotherapy (CCRT), and the relative performance of host-related prognostic indices in this setting is unclear. The CARWL (C-reactive Protein, Albumin, and Recent Weight Loss) score and the Naples prognostic score (NPS) have each been proposed as prognostic tools, but direct comparisons are lacking. This study compared their prognostic performance. Methods: We retrospectively analyzed 795 patients with stage IIIC NSCLC treated with CCRT between 2010 and 2020. Patients were stratified into three prognostic groups according to CARWL and NPS. Overall survival (OS) was the primary endpoint; progression-free survival (PFS) and locoregional PFS (LRPFS) were secondary endpoints. Survival was assessed using Kaplan–Meier analysis and Cox regression. Results: Both CARWL and NPS significantly stratified OS, PFS, and LRPFS (all p < 0.001). CARWL demonstrated modestly higher discriminatory performance across endpoints. The OS difference between unfavorable and favorable groups was larger with CARWL than with NPS (19.3 vs. 12.3 months). CARWL also provided greater separation for PFS (5.3 vs. 3.2 months) and LRPFS (4.9 vs. 3.4 months). In multivariable analyses, both indices retained independent prognostic significance; however, CARWL consistently exhibited stronger hazard gradients and maintained prognostic value when modeled alongside NPS. Conclusions: Both CARWL and NPS offered meaningful prognostic stratification in stage IIIC NSCLC treated with CCRT, but CARWL demonstrated a modest but more consistent prognostic discrimination than NPS. Pending external validation, CARWL represents a practical and biologically grounded tool for risk stratification in this population. Full article

In this study, the rapidly setting and hardening high-belite sulfoaluminate cement (HBSAC) is used as the cementitious material, with natural river sand as the fine aggregate, and a high-performance repair mortar is prepared through the synergistic use of different polymers and admixtures. The influences of two polymers (VAE and HPMC) on the working performance, mechanical properties, and hydration characteristics of HBSAC mortars are systematically studied. The results showed that the two polymers had a significant improvement effect on the setting time, mortar flowability, and water retention rate of HBSAC mortar. Among them, VAE had a significant effect on the mortar flowability, and a 5% content could increase the flowability of HBSAC mortar by 29.8%. HPMC has a significant improvement effect on setting time and water retention rate; at 0.1% content, it can delay the initial setting time by 6.5 min and achieve a water retention rate of over 90%. As the polymer to binder ratio increases, both polymers, except for 2.5% VAE, which can slightly improve the flexural strength of mortar, will reduce the flexural and compressive strength of mortar, with VAE causing greater damage to strength. On the contrary, the polymer significantly enhanced the bond strength of the mortar. Compared with the cement control group, the 28 d bond strength of 5% VAE and 0.1% HPMC groups increased by 56.7% and 15.1%, respectively. Moreover, the addition of polymers delayed the occurrence of the exothermic peaks of HBSAC dissolution and ettringite formation, but the total amount of hydration heat released within 48 h was higher than that of pure cement. The diffraction peaks of AFt in the hydration products of VAE-HBSAC paste at 3d and 28d showed significant enhancement, and the peak intensity increased with higher doping levels, while the diffraction peak intensity of C₂S showed a certain decrease. The polymer significantly increased the weight loss peak intensity and mass loss after heating of AFt, AH₃, AFm, and C-S-H gel. The SEM images indicate that VAE can form a mesh on the surface of hydration products and refine the crystal size of AFt; HPMC wraps more flocculent substances around the hydration products, thereby improving the compactness of paste. This study can provide scientific reference for improving the performance and promoting the practical application of high-performance rapid repair mortar for concrete structure damage. Full article

Accurate Unmanned Aerial Vehicle (UAV) position estimation is the cornerstone of urban low-altitude safety management systems. Time Difference of Arrival (TDOA) and Remote Identification (Remote ID) are widely used surveillance technologies with complementary characteristics. TDOA provides high-rate updates but suffers from geometry-induced horizontal–vertical anisotropy and multipath effects, while Remote ID supplies absolute state information yet struggles with intermittent sampling and packet loss. Existing fusion schemes typically address these issues in isolation: sequential filtering manages asynchrony but assumes Gaussian noise, robust estimators suppress outliers at the cost of discarding valid data, and coupled-filter architectures allow vertical anomalies to contaminate horizontal estimates through the Kalman gain cross-coupling. No prior framework jointly handles structural TDOA altitude jumps, stochastic Remote ID timing jitter, and the geometric anisotropy between estimation subspaces within a single coherent pipeline. To bridge this gap, we propose a Hybrid Conditional Kalman Filter (HCKF) framework comprising three integrated modules. First, a kinematics-based temporal alignment module maps asynchronous measurements onto a uniform timeline and predicts missing samples, resolving cross-modal time mismatches. Second, a measurement quality evaluation mechanism detects TDOA altitude steps via robust two-layer stratification and scores Remote ID timing irregularity through a confidence mapping, converting these anomalies into dynamic covariance adjustments and weight caps without discarding observations. Third, a Subspace-Decoupled Fusion strategy exploits the physical insight that TDOA horizontal precision derives from hyperbolic intersection geometry, whereas its vertical estimates suffer from weak observability due to near-coplanar ground-station deployment . By applying entropy-guided weighting in the horizontal plane and a conditional Remote ID-dominant rule in the vertical axis, this design prevents cross-dimensional error propagation. The framework was validated using three real-world flight missions at distinct altitudes (255 m, 345 m, and 440 m) totaling 13.51 km of flight distance, with RTK serving as ground truth. HCKF reduces the Root Mean Square Error by over 40% relative to single-source baselines (95% bootstrap confidence interval: [35.2%, 48.7%]), and paired Wilcoxon signed-rank tests confirm statistically significant improvement ($p<0.01$) over standard EKF, Covariance Intersection, and Iterative CI across all three tracks. Full article

Among the ten local breeds of the Veneto region in Italy, Pepoi (PP) and Ermellinata di Rovigo (ER) hens start laying eggs earlier than the others. The egg laying rate (27–34 weeks of age) is higher (p < 0.01) in PP than in ER hens. Egg quality (at 33 weeks of age, 120 eggs/breed) was studied in fresh 1 day-old eggs and in preserved 21 day-old eggs according to breed and storage temperature (12 and 21 °C). Fresh ER eggs showed higher (p < 0.01) egg weights, yolk pH, Haugh units and yolk indices and lower (p < 0.01) eggshell lightness and thickness, surface area-to-volume ratios, and albumen pH than PP eggs, but the yolk-to-albumen ratio was similar between the breeds. After 21 days of storage, the egg traits showed the same trend for significant differences between breeds, with the exception of albumen pH and Haugh units, which were similar. Eggs stored at 21 °C showed lower (p < 0.01) Haugh units and yolk index values and higher (p < 0.01) albumen and yolk pH, albumen yellowness, and weight loss than eggs stored at 12 °C. Stored PP and ER eggs also differed in terms of observed changes in Haugh units, yolk pH and yolk index values with storage temperature: ER eggs showed higher (p < 0.01) yolk index values than PP eggs at both storage temperatures. Eleven weeks after the onset of laying, significant differences were observed in several traits of fresh and stored eggs from the studied breeds, particularly regarding the strength of the vitelline membrane. These preliminary results contribute to the characterization of the storage suitability of eggs from local breeds and to future crossbreeding programmes for enhancing chicken biodiversity. Full article

Starvation is one of the common survival stresses frequently encountered by wildlife, and the adaptive strategies of animals to starvation stress exhibit significant interspecific differences. This study investigated the effects of different starvation periods (1–4 weeks) on the growth characteristics, locomotor performance, foraging behavior, and hypoxia tolerance of Chinese giant salamander (Andrias davidianus) larvae (5.41 ± 0.06 g; 9.78 ± 0.03 cm). Our results showed that the final body weight of A. davidianus larvae decreased significantly with prolonged starvation time, with a more pronounced rate of decrease during the early starvation period. However, the final body length of A. davidianus larvae was less significantly affected by starvation stress. Starvation had no significant effects on the relative induction flow speed, relative burst swimming speed, total foraging distance, relative foraging speed, and foraging time of A. davidianus larvae. The resting metabolic rate of A. davidianus larvae decreased significantly as the starvation period lengthened. Starvation lasting 2–4 weeks significantly increased the dissolved oxygen level at which A. davidianus larvae exhibited the loss of equilibrium (ventral side facing upward). These results indicate that (1) starvation has a more significant negative impact on body mass than on body length in A. davidianus larvae; (2) starvation stress does not significantly affect the locomotor performance or foraging behavior of A. davidianus larvae, but it does lead to a significant reduction in their extreme hypoxia tolerance. Full article

In sparse representation learning-based linear k-nearest neighbors methods, the linear representation assumption frequently fails when applied to nonlinear distributed data, leading to degraded generalization and a loss of physical interpretability. To address this, we propose the Kernelized Manifold-Optimized Linear Nearest Neighbor (KMOLNN) method. Methodologically, KMOLNN projects the data into a high-dimensional kernel space to capture the nonlinear relationships, while introducing an adaptive manifold-preserving regularization term—via an adaptive Laplacian matrix—to dynamically preserve the local geometric structures. Theoretically, this study provides a mathematical proof of the nearest neighbor group effect for the kernel framework and reveals that its weight optimization behavior implicitly implements the Bayesian decision rule. Furthermore, we derive a rigorous generalization error bound using Rademacher complexity to validate its theoretical robustness. Empirically, we evaluate KMOLNN on 15 small-to-medium-scale benchmark datasets against eight comparative methods, including recent variants. The results demonstrate significant numeric superiority, with KMOLNN achieving an average accuracy of 90.76% and a Macro F1-score of 88.62% across the evaluated datasets. Finally, we present a comprehensive runtime analysis, explicitly acknowledging that these gains in generalization capability and theoretical interpretability present a practical trade-off, requiring increased computational runtime due to the iterative alternating optimization process. Full article

This study proposes a rigorous methodology for the optimal placement of voltage regulators in the Guayacanes feeder of the Buena Fe substation, Ecuador, by integrating electrical feeder modeling, exhaustive search, and multi-criteria decision-making. The feeder was modeled in detail by incorporating its radial topology, nodal electrical parameters, and representative operating conditions under minimum- and maximum-load scenarios. Based on this model, a set of technical evaluation criteria was established to quantify the impact of regulator installation, including active power losses, reactive power losses, global voltage deviation, average voltage variation, and voltage imbalance. An exhaustive search strategy was then implemented to evaluate all feasible regulator-location alternatives over the candidate nodes, thereby ensuring a complete exploration of the solution space. The resulting alternatives were ranked using the Weighted Sum Method (WSM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), allowing the comparison of candidate locations from a multi-criteria perspective. The results indicate that node MTS 108932 provides the most technically favorable overall solution, achieving the greatest improvement in voltage profile quality and the most significant reduction in electrical losses. In addition, a sensitivity analysis was conducted by varying the weighting structure of the decision criteria, confirming the robustness of the selected alternative under different decision-maker preference scenarios. The proposed framework provides a technically sound decision-support methodology for voltage regulation planning in real radial distribution systems. Full article

Global avocado production exceeds 10 million tons annually. Among the diseases affecting avocado fruit, anthracnose is one of the most significant, causing black lesions and fruit decay that can result in yield losses of 20–30%. To facilitate the early detection of anthracnose, this study proposes a computer vision-based approach. A dataset containing 2218 images of Fuerte avocados was first developed, comprising 1730 healthy samples and 488 anthracnose-infected samples after the labeling process. In the experimental phase, several convolutional neural network (CNN) models with varying depths (3, 4, 5, and 6 layers) were designed and evaluated. These models were subsequently integrated into different weighted ensemble configurations, where the best performance was achieved by the ensemble combining all four individual CNNs. The proposed weighted ensemble was compared against widely used state-of-the-art architectures, including VGG-16, ResNet-18, and MobileNetV2. Experimental results demonstrated the effectiveness of the proposed approach, achieving an F1-score of 0.9052, outperforming VGG-16 (0.8283), ResNet-18 (0.7328), and MobileNetV2 (0.7320). Full article

This investigation primarily focuses on addressing the challenges posed by the traditional use of carbon steel, which, despite its strength and cost-effectiveness, is prone to rapid corrosion in harsh chemical environments within the petrochemical industry. This issue constitutes a chronic operational vulnerability, exacerbated by extreme environmental stressors. The combined effect of corrosive atmospheres and rigorous EHSS (Environment, Health, Safety, and Security) mandates creates a significant fiscal burden, primarily driven by escalated lifecycle maintenance and the necessity for specialized regulatory compliance. Integrating Inconel, known for its exceptional corrosion resistance and durability, particularly at high temperatures, will significantly enhance the lifespan, safety, and operational efficiency of these vessels. This investigation aims to study the corrosion resistance of carbon steel specimens and carbon steel specimens clad with Inconel at thicknesses of 2 mm and 4 mm in different environments: acidic pH = 2 (HCl), neutral pH = 7 (distilled water), and alkaline pH = 12 (NaClO). All specimens were tested at the same immersion intervals of 5 and 10 days. Corrosion resistance was measured for the immersion corrosion tests. Weight loss in the specimens was measured before and after immersion to calculate the corrosion rate, and surface analysis was conducted using a scanning electron microscope (SEM). It was observed that at pH = 12 (NaClO), carbon steel corrosion reached a rate of 6.96 mm/year, while Inconel showed very low corrosion, 0.05 mm/year, indicating a resistance 139 times greater than that of carbon steel. At pH = 2 (HCl), carbon steel corrosion reached a rate of 1.29 mm/year, while Inconel showed a very low corrosion rate of 0.015 mm/year, indicating a resistance 86 times greater than that of carbon steel. In a neutral environment, all materials exhibited approximately the same corrosion rate between 0.0017 and 0.12 mm/year. This indicates that Inconel is highly resistant to corrosion in both acidic and alkaline environments, making it suitable for petrochemical plants. Full article

Obesity prevalence has increased globally, and metabolic bariatric surgery (MBS) is the most effective treatment for severe obesity. However, the impact of postoperative dietary counselling (DC) on clinical outcomes including weight is unclear. This review aims to assess the nature and impact of postoperative DC delivered by dietitians on clinical outcomes in adults undergoing post-MBS, focusing on weight change as the primary outcome, and body composition, nutritional status, biochemical parameters, and complications as secondary outcomes. Five databases (Medline, Embase, Web of Science, CINAHL, and Cochrane Library) were searched for observational studies and randomised controlled trials (RCTs) assessing DC related to weight change. Thirteen studies met the inclusion criteria (five RCTs and eight observational studies), involving 4173 individuals. Eight studies reported no significant difference in weight outcomes between the groups receiving DC and comparison groups. However, secondary outcomes such as nutritional status, complications, and levels of transferrin saturation, vitamin B12, and vitamin D showed improvements with more frequent DC. The components of DC delivered by dietitians varied, including advice on micronutrient supplements, protein intake, physical activity, transition diets, healthy eating, and mindful eating. Evidence supporting the efficacy of postoperative DC in promoting weight loss is limited by short-term assessment and inconsistencies in reporting weight outcomes, highlighting the need for long-term RCTs to ascertain its effectiveness. Full article

Brain tumor segmentation from 3D MRI presents significant challenges due to small lesion sizes, ambiguous boundaries, arbitrary spatial distributions, and heterogeneous morphological properties. To tackle these issues, this paper presents a fully automatic 3D brain tumor segmentation network that integrates morphological and anatomical information under a multi-task learning framework for whole tumor, tumor core, and enhanced tumor segmentation. We propose a multimodal feature fusion module to adaptively weight features from four MRI modalities (T1, T1ce, T2, FLAIR), enabling discriminative information integration and helping reduce modality intensity discrepancy and data imbalance. Furthermore, a ConvReXt downsampling module is introduced to preserve fine-grained semantic details by reducing information loss caused by conventional pooling. A dense parallel global attention module is also developed to capture both local details and long-range dependencies, addressing the limited receptive field of standard convolutions. Extensive experiments on the BraTS2020 dataset show that the proposed model obtains average Dice coefficients of 92.54%, 89.21%, and 86.54% for whole tumors, tumor cores, and enhanced tumors. The proposed model achieves competitive performance compared with state-of-the-art methods including nnFormer, validating that it can effectively fuse multimodal and multi-scale features and improve brain tumor segmentation accuracy. Full article

Cementitious materials are naturally brittle, which makes them prone to cracking. This study effectively employs autogenous healing techniques using microcapsules to solve this issue. The goals were twofold: first, to microencapsulate isophorone diisocyanate (IPDI) as a catalyst-free healing agent; and second, to evaluate how these microcapsules improve the healing abilities of cementitious materials. Polyurethane (PU) prepolymer with an NCO content of 19.8% was successfully created. Using interfacial polymerization, smooth, spherical microcapsules of IPDI with an average diameter of 38 to 62 micrometers were produced. The elastic modulus of the microcapsules ranged from 0.23 to 0.18 GPa, while their hardness varied between 5.29 and 4.15 MPa. Over six months, the microcapsules showed a weight loss of 9.72% to 12.47%, depending on their size, under ambient conditions. Specimens containing 3% of fabricated microcapsules demonstrated the ability to seal cracks less than 100 µm wide by up to 70%. Specimens that incorporated 3% of their cement weight in IPDI microcapsules achieved an impressive 74% recovery rate in compressive strength. In contrast, control mortars without microcapsules showed a recovery rate of less than 50%. Analysis using Energy Dispersive Spectroscopy (EDS) revealed a significant presence of carbon in areas where the microcapsules had ruptured and the cracks had healed. This confirms the effectiveness of the healing process, consistent with established self-healing theories. The water tightness recovery trace showed a recovery rate of up to 61%. Additionally, the specimens containing microcapsules exhibited higher initial compressive strength than the control specimens. However, this also indicates that some microcapsules may have ruptured unintentionally during preparation and molding. Therefore, further research on the mechanical properties of microcapsules, especially their stiffness in cementitious composites, is necessary. Full article