Search Results (153)

Image inpainting, a pivotal technology for restoring damaged regions of images, has emerged as a significant research focus in computer vision. This review systematically surveys recent advances in deep learning-based image inpainting. We begin by categorizing prevailing methods into three groups based on their core architectures: Convolutional Neural Networks (CNNs), Generative Models, and Transformers. Through a comparative analysis of their symmetric versus asymmetric network architectures, applicable scenarios, and performance bottlenecks, we provide a critical discussion of the strengths and limitations inherent to each approach. The evolution of underlying design principles, such as symmetry, and the corresponding solutions to core challenges are also discussed. Furthermore, we introduce key benchmark datasets and commonly used image quality assessment metrics, offering a multidimensional framework for evaluation. We highlight that mainstream datasets collectively foster a greenhouse-like evaluation environment detached from real-world complexities and that existing metrics are critically misaligned with the fundamental objective of inpainting: generating plausible new content. Finally, we summarize the prevailing challenges in current deep learning-based inpainting research and outline promising future directions. We highlight critical issues, such as enhancing restoration quality, reducing computational costs, and broadening application scenarios, thereby providing valuable insights for subsequent research. Full article

Background/Objective: Pulmonary involvement in systemic sclerosis (SSc) is typically assessed using pulmonary function tests (PFTs), high-resolution CT (HRCT), and composite indices. Patient-reported outcomes (PRO), including ScleroID, provide insight into quality of life, but their relationship with clinical measures and role in overall disease assessment remain unclear. To assess the correlation between ScleroID scores and both lung involvement and disease activity/damage in a cohort of SSc-ILD patients from a large tertiary care center. Methods: Disease activity [European Scleroderma Study Group Activity Index (EScSG-AI), Scleroderma Clinical Trials Consortium Activity Index (SCTC-AI)], disease severity [Medsger severity scale (MSS)], and PRO measure ScleroID were assessed for associations with the extent and severity of SSc-ILD. Results: In 82 patients with SSc-ILD (mean age 56.0 ± 10.8 years; median disease duration 4.2 ± 4.7 years), higher fibrosis extent (>20%) was associated with worse lung function, greater exercise limitation, and higher ScleroID scores, particularly in fatigue, social life, and body mobility domains (all p ≤ 0.03). Patients with >20% fibrosis also had worse NYHA class and Borg scores during 6-MWD (p < 0.001). Cross-sectional correlations showed that ScleroID total and individual domains were negatively associated with FVC% and 6-MWD, and positively with ILD extent on HRCT. Fatigue, social impact, and mobility domains correlated most strongly with disease activity and severity scores, especially in patients with > 20% fibrosis (r = 0.384–0.635, all p ≤ 0.016), whereas breathlessness showed minimal associations (r < 0.2). Conclusions: In SSc-ILD, greater lung fibrosis and functional impairment are associated with worse patient-reported quality of life, particularly in fatigue, mobility, and social domains. ScleroID scores reflect both physiological severity and disease burden highlighting its value as a multidimensional outcome measure in patients with more advanced disease. Full article

To address the conflicting demands of lightweight materials and high load-bearing capacity in high-end fields such as aerospace and biomedical engineering, there is an urgent need to conduct research on the mechanical behavior and response mechanism of porous titanium alloy structures. In this paper, a combination of experimental testing, numerical simulation, and theoretical analysis was employed to conduct the research. A titanium alloy porous structure with different porosities was constructed based on classical three-period minimal surface optimization, and its preparation was completed using advanced selective laser melting technology. A multidimensional characterization experimental device was established to accurately obtain its mechanical performance data. It was found that the mechanical behavior of the structures is insensitive to loading rates, but more sensitive to their structural volume fraction. The quantitative characterization of microstructure damage and fracture morphology, as well as the identification of failure modes, indicates that the microstructure damage of the porous metal exhibits a ductile–brittle synergistic damage characteristic. By combining high-precision numerical simulation technology, the damage modes and damage evolution laws of porous metal structures in titanium alloys were comprehensively elucidated. By analyzing energy dissipation and constructing evaluation indicators for energy absorption efficiency, the energy absorption characteristics of the porous metal structure were elucidated, and the interaction behavior and correlation mode between the platform stress and the structural volume fraction of the porous metal structure were accurately described. Full article

To improve the accuracy of detecting external defects in seed potatoes and address the reliance of current hyperspectral imaging methods on single-dimensional data, this study proposes a multi-dimensional spectral–spatial information fusion approach via concatenation based on a one-dimensional convolutional neural network (1DCNN) within the framework of deep learning. Hyperspectral three-dimensional data were acquired for normal seed potatoes and for samples presenting six types of external defects—decay, mechanical damage, wormhole, common scab, black scurf, and frostbite—across a wavelength range of 935–1721 nm. From the hyperspectral images, one-dimensional spectral data and two-dimensional spatial data were extracted. The one-dimensional spectral data were preprocessed using six methods: Savitzky–Golay smoothing (SG), standard normal variate (SNV), multiplicative scatter correction (MSC), first derivative (FD), second derivative (SD), and orthogonal signal correction (OSC). Feature wavelengths were subsequently selected through the successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS), serving as inputs for traditional machine learning models. Two-dimensional spatial data were first subjected to dimensionality reduction via principal component analysis (PCA). Texture features were then extracted from each principal component using the gray-level co-occurrence matrix (GLCM). Following normalization, all spatial texture data were fused with the preprocessed spectral data to form the inputs for the deep learning models Basic1DCNN and Stacked1DCNN. The results demonstrate that the fusion data with the Stacked1DCNN model yielded the best performance in identifying normal seed potatoes and six types of external defects. The overall accuracy, precision, recall, F1 score, and mean average precision reached 98.77%, 98.77%, 98.93%, 98.73%, and 99.66%, respectively, outperforming traditional machine learning approaches. Compared with the Stacked1DCNN model trained using spectral data alone, these metrics improved by 2.81%, 2.78%, 3.20%, 3.01%, and 1.11%. This study offers theoretical and technical insights into the development of automated sorting and non-destructive detection systems for seed potatoes. Full article

Existing jealousy scales often conceptualize jealousy as an undesirable or maladaptive emotion. However, jealousy is a biologically rooted emotion inherent in humans and observable in certain animal species as well. The key lies not in the elimination of this emotion, but in its appropriate regulation. In contemporary society, where exposure to social media is pervasive, the experience and expression of jealousy can become more destructive. This study was designed in response to the growing need to understand and assess jealousy. The aim of the present research was to develop a multidimensional current jealousy scale and to present preliminary findings regarding the influence of social media. Employing a quantitative research design, data were collected online from a sample of 1053 adult volunteers (aged 18 and above) in Türkiye. The resulting instrument, named the Üsküdar Jealousy Scale, comprises 25 items and 4 dimensions: Relationship-Damaging Jealousy, Destructive Jealousy, Hostile Jealousy, and Controlled Jealousy. The total scale demonstrated high internal consistency (Cronbach’s Alpha = 0.93), with subscale reliabilities ranging from 0.75 to 0.89. The scale accounted for 57.20% of the total variance. Confirmatory factor analysis indicated that the model fit indices fell within acceptable limits, supporting the structural validity of the scale. Additionally, criterion validity was supported by moderate correlations (r > 0.30 and <0.70) with the Scale of Social Media Jealousy in Romantic Relationships (SSMJRR). Initial findings revealed generally low levels of jealousy among participants. The dimension concerning relationship-damaging jealousy showed moderate levels, while destructive and controlled jealousy dimensions indicated lower levels. Notably, patterns of social media usage significantly influenced jealousy scores. Individuals exhibiting continuous engagement in social media platforms reported higher levels of jealousy. In conclusion, the Üsküdar Jealousy Scale was found to be a psychometrically sound instrument, suitable for both research and self-assessment purposes in the multidimensional evaluation of jealousy. This validated and reliable tool has the potential to distinguish between adaptive and maladaptive expressions of jealousy, offering practical utility for clinicians and individuals seeking deeper self-understanding. Full article

Textile-reinforced concrete (TRC) is an alternative class of mechanical reinforcement for cement composites. The biaxial braided reinforcement structure in composite materials with diverse cross-sectional shapes offers high adaptability, torsional stability, and resistance to damage. In general, 3D textile reinforcements improve the mechanical properties of composites compared to 2D reinforcements. This study aimed to verify reinforcement behavior by comparing multidimensional braided textiles, 2D (one- and two-layer) reinforcements, and 3D reinforcement in composite cementitious boards. Experimental tests were performed to evaluate the effect of textile structures on cementitious composites using four-point bending tests, porosity measurements, and crack patterns. All textiles showed sufficient space between yarns, allowing the matrix (a commercial formulation) to infiltrate and influence the composite mechanical properties. All composites presented ductility behavior. The two layers of 2D textile composites displayed thicker cracks, influenced by shear forces. Three-dimensional textiles exhibited superior values in four-point bending tests for modulus of rupture (7.4 ± 0.5 MPa) and specific energy (5.7 ± 0.3 kJ/m²). No delamination or debonding failure was observed in the boards after the bending tests. The 3D textile structure offers a larger contact area with the cementitious matrix and creates a continuous network, enabling more uniform force distribution in all directions. Full article

To improve the seismic performance of prefabricated structures, this study suggested putting grouted sleeves at the half-height of the column (at the point of contraflexure). A quasi-static test under constant axial load was conducted on the full-scale cast-in-place column and the full-scale prefabricated column connected in half-height. The hysteresis loops, skeleton curves, ductility, stiffness degradation, and energy dissipation capacity were compared. The test results indicate that the prefabricated column connected in half-height exhibited reliable seismic performance. Compared with the cast-in-place specimen, the bearing capacity of the prefabricated column decreased by only 1.45%, the energy dissipation decreased by 5.61%, and the initial secant stiffness and ductility coefficient increased by 8.88% and 9.09%, respectively. ABAQUS finite element software was used to establish finite-element models based on the experimental results. The damage pattern and seismic performance indicators of the two types of columns were verified by resolving issues related to the bonding interface model of sleeve-connected columns and the convergence of the multidimensional constitutive model. The formula for calculating the shear bearing capacity was put forward to evaluate the failure pattern. The study provides a basis for further investigation of the seismic performance of sleeve-connected columns with different connection positions under extreme conditions. Full article

Silicon carbide (SiC) single crystals are extensively utilized in various fields due to their exceptional properties, such as a wide bandgap and a high breakdown threshold. Nevertheless, the intrinsic high hardness of SiC creates significant challenges for contact machining. This study investigates the surface damage characteristics and underlying mechanisms involved in processing both high-purity silicon carbide (HP-SiC) and nitrogen-doped silicon carbide (N-SiC) crystals using fundamental-frequency nanosecond pulsed lasers. This study establishes a laser-induced damage threshold (LIDT) testing platform and employs the internationally standardized 1-ON-1 test method to evaluate the damage characteristics of HP-SiC and N-SiC crystals under single-pulse laser irradiation. Experimental results indicate that N-SiC crystals exhibit superior absorption characteristics and a lower LIDT compared with HP-SiC crystals. Subsequently, a defect analysis model was established to conduct a theoretical examination of defect information across various types of SiC. Under fundamental-frequency nanosecond pulsed laser irradiation, N-SiC crystals demonstrate a lower average damage threshold and a broader defect damage threshold distribution than their HP-SiC counterparts. By integrating multi-dimensional analytical methods—including photothermal weak absorption mechanisms and damage morphology analysis—the underlying damage mechanisms of the distinct SiC forms were comprehensively elucidated. Moreover, although N-SiC crystals show weaker photothermal absorption properties, they exhibit more pronounced absorption and damage response processes. These factors collectively account for the different laser damage resistances observed in the two types of silicon carbide crystals, implying that distinct processing methodologies should be employed for nanosecond pulsed laser treatment of different SiC crystals. This paper elucidates the damage characteristics of various SiC materials induced by near-infrared nanosecond pulsed lasers and explores their underlying physical mechanisms. Additionally, it provides reliable data and a comprehensive mechanistic explanation for the efficient removal of these materials in practical applications. Full article

This study analyzed the spatial patterns of species composition and biodiversity according to elevation on Mt. Gyebangsan, a representative protected ecosystem and the national park in Korea. Based on existing vegetation survey data, differences in species composition heterogeneity according to elevation were verified using non-metric multidimensional scaling and multi-response permutation procedure analyses. Significant differences were identified using the Sørensen distance measure. Zeta (ζ)-diversity was analyzed based on the number of shared species among habitats to quantitatively interpret the structural characteristics of biodiversity along the altitudinal gradient. The analysis revealed that the understory species composition became increasingly distinct and alpha-diversity increased with elevation. High-elevation areas (A3, A4) experienced frequent physical disturbances, including wind damage and limited moisture, resulting in active canopy openings. Consequently, rhizomatous species, including Sasa borealis rapidly covered the ground, influencing the understory vegetation structure. ζ-Diversity analysis showed that the ζ-ratio in high-elevation regions sharply declined with increasing ζ-order, indicating limited species overlap among habitats and the dominance of deterministic processes. Thus, altitudinal gradients represent a key factor in shaping biodiversity, indicating that climatic variables directly affect understory distribution and species turnover. This study quantitatively assessed biodiversity and ecological heterogeneity within the national park, providing a scientific foundation for biodiversity conservation and management. Full article

This study was conducted based on hybrid damping control theory, and an equivalent damping ratio calculation method was proposed. Additionally, a response calculation method for the elastoplastic stage of the hybrid control system was developed. Furthermore, a cooperative working mechanism between viscous dampers and metal composite dampers was introduced. A time–history analysis was employed to verify the system’s effectiveness in optimizing the multi-dimensional seismic performance of frame structures. Using actual engineering as the research background, an elastoplastic analysis of the hybrid control system was conducted. The analysis results show that the first three natural periods of vibration were shortened by 6.1% (in the X direction), 5.9% (in the Y direction), and 21.0% (torsion), effectively enhancing the overall stiffness of the structure. Under seismic action, the inter-story displacement decreased by 37.1% to 0.166 m in the X direction and by 48.3% to 0.080 m in the Y direction; the base shear forces were reduced by 58.8% (in the X direction) and 41.7% (in the Y direction). Regarding damage control, the number of plastic hinges was significantly reduced, and they appeared only on the most unfavorable floors; the axial compressive stress peaks in the frame columns were strictly controlled below 0.65 fc, and the inter-story displacement angles (<1/50) met the standards of GB50011-2010 for key protection structures. The hybrid system demonstrated multi-dimensional synergistic effects, whereby the viscous dampers primarily controlled the acceleration responses in the X direction, while the metal composite dampers dominated energy dissipation in Y displacement. The difference in seismic reduction efficiency between the two main axes was less than 11%, and a 21% improvement in the torsional period was achieved simultaneously. Full article

As global warming intensifies, extreme weather phenomena such as heatwaves, flash droughts, torrential floods, cold waves, and blizzards are becoming increasingly frequent. Against this backdrop, traditional static food security assessment methods fail to capture the dynamic transmission patterns of agricultural productivity risks and their regional heterogeneity. Therefore, it is imperative to reconstruct a resilience analysis paradigm for food production systems, dynamically investigate the mechanisms through which climate change affects China’s agricultural productivity and discern the interactive effects between technological evolution and climate constraints. This will provide theoretical foundations for building a climate-resilient food security system. Accordingly, this study establishes a multidimensional resilience measurement index system for China’s grain productivity by integrating agricultural factor elasticity analysis with disaster impact response modeling. Through production function decomposition and hybrid forecasting models, we reveal the evolutionary patterns of China’s grain productivity under climate risk shocks and trace the transmission pathways of risk fluctuations. Key findings indicate the following: (1) Extreme climate events exhibit significant negative correlations with grain production, with drought and flood impacts demonstrating pronounced regional heterogeneity. (2) A dynamic game relationship exists between agricultural technological progress and climate risk constraints, where the marginal contribution of resource efficiency improvements to productivity growth shows diminishing returns. (3) Climate-sensitive factors vary substantially across agricultural zones: Northeast China faces dominant cold damage, North China experiences drought stress, while South China contends with humid-heat disasters as primary regional risks. Consequently, strengthening foundational agricultural infrastructure and optimizing regionally differentiated risk mitigation strategies constitute critical pathways for enhancing food security resilience. (4) Future research should leverage higher-resolution, county-level data and incorporate a wider range of socio-economic variables to enhance granular understanding and predictive accuracy. Full article

Eaton Canyon in California serves as the focal point for a comprehensive post-wildfire ecological impact assessment. This study employs an approach integrating satellite imagery from the European Space Agency’s Sentinel constellation to study an area of 271.49 km². The data encompasses both radar and multispectral data, offering a multi-dimensional view of the affected landscape. The analysis leverages the power of the random forest algorithm. Firstly, three widely used indices—the difference normalized burn ratio (dNBR), relative burn ratio (RBR), and relative difference normalized burn ratio (RdNBR)—were calculated and compared based on their accuracy and Kappa index. Secondly, we developed a fusion approach by using all the fire indices to obtain a precise severity map by classifying the affected area into distinct severity classes. Thirdly, a separate fusion approach was developed utilizing the normalized difference vegetation index (NDVI), radar vegetation index (RVI), and modified normalized difference vegetation index (MNDVI) to analyze the distribution of vegetation before and after the wildfire. The merger proposals were developed using a combination of index values to obtain better information on the fire severity map and post-fire vegetation distribution. The results indicated an accuracy of 78% when employing the dNBR index. A higher accuracy of 81% was observed with the RBR index, while the RdNBR demonstrated an accuracy of 95%. Our approach, which combines all fire indicators, offers optimal accuracy of 99%. A percentage of 56.76% did not burn due to the topography of the canyon creating natural firebreaks. Areas classified as low severity (7.83%) showed minimal damage with minimal tree mortality. Moderate- to low-severity areas (5.83%) represented regions with partial crown burns and some tree mortality. Moderate- to high-severity areas (7.22%) showed significant tree mortality. Finally, high-severity areas (22.36%), characterized by complete tree mortality and significant loss of vegetation cover, were largely concentrated in specific sections of the canyon, likely influenced by factors such as slope and fuel type. These findings provide valuable information for post-fire ecological recovery efforts and future land management strategies in Eaton Canyon and similar fire-prone landscapes. Full article

Global soil salinization is accelerating. As the dominant fast-growing plantation genus, Populus spp. largely determines the success of coastal and inland saline-land restoration and the associated carbon-sequestration benefits. Yet most current studies rely on single indicators and lack a multidimensional physiological framework for ranking salt tolerance. Here, six elite poplar cultivars were exposed to 0% (CK), 0.2% (ST1), 0.3% (ST2) and 0.4% NaCl (ST3) for 30 d. We quantified membrane-lipid peroxidation, photosynthetic performance, osmotic adjustment and antioxidant enzymatics, then integrated the data with a principal-component–membership-function model. With increasing NaCl, MDA and REC either rose continuously or peaked slightly below ST3. ‘YX2’ reached the highest MDA (71.3 µmol g⁻¹ FW) and REC (80.3%) under ST2. Pn and SPAD declined overall, but ‘YX3’ retained the greatest photosynthetic stability (6.1 µmol m⁻² s⁻¹ at ST3). Osmolytes accumulated differentially: soluble sugar in ‘PZ2’ rose 52% above CK at ST3; soluble protein in ‘YX2’ peaked at 12.7 mg g⁻¹ FW; proline exceeded 110 µg g⁻¹ FW in ‘YX2’, ‘PZ1’ and ‘PZ2’. Antioxidant enzymes were up-regulated with stress; ‘YX3’ CAT peaked at 69.7 U g⁻¹ FW under ST2, while SOD and POD remained highly active. Correlation analysis revealed that photosynthetic decline is tightly linked to membrane oxidative damage, while the coordinated enhancement of antioxidant enzymes and concurrent accumulation of osmolytes form a synergistic protection mechanism. PCA showed that PC1 (57.1%) integrated photosynthetic capacity, membrane integrity and antioxidant synergy, whereas PC2 (14.3%) represented osmotic and enzymatic protection. The combined D-value ranked cultivars as ‘YX2’ > ‘YX3’ > ‘PZ2’ > ‘PZ1’ > ‘ZX1’ > ‘YX1’. This multi-trait platform provides both a theoretical reference and a germplasm basis for saline-site afforestation and salt-tolerant poplar breeding. Full article

Fe-Mn-Al-C lightweight steel is an alternative to traditional low-alloy structural steels. It is lightweight and can be used to reduce the weight of structures without increasing their density. However, in the marine environment, traditional low-alloy structural steels can be damaged by chloride ions, which shortens their service life. We do not yet understand how aluminum, an important alloying element in lightweight steel, affects the process of corrosion. In this study, we examined Fe-Mn-Al-C lightweight steels with different amounts of aluminum. We used full-immersion simulated marine corrosion tests and multi-dimensional characterization techniques, such as microstructure observation and electrochemical measurements, to explore the relationship between aluminum content and the steel’s corrosion rate, corrosion product structure, and corrosion resistance. The results showed that, compared with CS, the weight loss and rate of corrosion of steels that contain aluminum were a lot lower. While the corrosion rate of CS is approximately 0.068 g·h⁻¹·m⁻², that of 7Al steel is reduced to 0.050 g·h⁻¹·m⁻². The stable phases α-FeOOH and FeAl₂O₄ are formed in the corrosion products when Al is added. As the Al content increases, so does the relative content of these phases. Furthermore, FeAl₂O₄ acts as a nucleation site that refines corrosion product grains, reduces pores and cracks, and significantly improves the compactness of corrosion products. It also forms a dense inner rust layer that blocks the penetration of corrosive ions such as Cl⁻. This study confirmed that aluminum improves the corrosion resistance of steel synergistically by regulating the structure of the corrosion products, optimizing the phase composition, and improving the electrochemical properties. The optimal aluminum content for lightweight steel in marine environments is 7%, within a range of 5–9%. Full article

Roof instability in coal mines is one of the primary causes of mining disasters, casualties, and environmental damage. Accurately assessing its reliability is crucial for achieving safe production and sustainable development in coal mining. Based on 192 small measured samples from multiple domestic coal mines (including Anhui, Shanxi, Shaanxi, and Inner Mongolia), this study constructs multidimensional Gaussian Copula and t Copula models to characterize the complex correlation structure of mechanical parameters. The hybrid adaptive multi-method data augmentation (HAMDA) method with three distinct weighting strategies is proposed. Through Monte Carlo Simulation (MCS), systematic reliability assessments are conducted for different roof locations. The results indicate that multidimensional elliptical Copulas effectively simulate the correlation structure of highly variable multidimensional coal mine roof mechanical parameters. Roof system instability is primarily triggered by failure in the bottom zone, accompanied by sidewall instability in approximately 60% of cases, while the top zone remains relatively secure. This provides crucial insights for optimizing support design. The HAMDA method significantly overcomes the limitations of small sample data, with its expanded statistical characteristics closely matching measured data. Failure probability estimates vary across different HAMDA schemes: conservative programs may underestimate risks, while diverse programs tend toward conservatism in lateral zones. These results provide theoretical support for refined roof support design in coal mines, holding significant theoretical and practical value for advancing safety, environmental sustainability, and sustainable development in the coal industry. Full article