Search Results (4,242)

Spun piles adjacent to the pile cap need sufficient confinement to ensure the formation of plastic hinges during severe earthquakes. However, the high confinement ratio required for precast piles according to ACI 318-19 results in tightly spaced spirals, which are difficult to implement. Since higher confinement is only needed at specific regions of the pile, external transverse reinforcement using steel jacketing has been proposed as an alternative solution. An experimental and numerical study was conducted to evaluate the effectiveness. The experimental results showed that the jacket enhanced both the strength and energy dissipation of the connection, but had only a minor effect on its ductility. A parametric study using finite element analysis was performed to investigate the parameters influencing connection behavior. The results indicated that variations in jacket thickness did not significantly impact the connection’s performance. A jacket height equal to 1.53 times the pile diameter was found to be the maximum effective height. It was also observed that higher axial loads led to a sudden loss of connection strength, thereby reducing ductility. Partial bonding between the jacket, grout, and pile was found to be acceptable within a certain range. The numerical analysis found that the steel jacket increases the ductility. Full article

Rice is one of the most important staple crops in China, and the rapid and accurate extraction of rice planting areas plays a crucial role in the agricultural management and food security assessment. However, the existing rice field identification methods faced the significant challenges in mountainous regions due to the severe cloud contamination, insufficient utilization of multi-dimensional features, and limited classification accuracy. This study presented a novel rice field identification method based on the Graph Convolutional Networks (GCN) that effectively integrated multi-source remote sensing data tailored for the complex mountainous terrain. A coarse-to-fine cloud removal strategy was developed by fusing the synthetic aperture radar (SAR) imagery with temporally adjacent optical remote sensing imagery, achieving high cloud removal accuracy, thereby providing reliable and clear optical data for the subsequent rice mapping. A comprehensive multi-feature library comprising spectral, texture, polarization, and terrain attributes was constructed and optimized via a stepwise selection process. Furthermore, the 19 key features were established to enhance the classification performance. The proposed method achieved an overall accuracy of 98.3% for the rice field identification in Huoshan County of the Dabie Mountains, and a 96.8% consistency compared to statistical yearbook data. The ablation experiments demonstrated that incorporating terrain features substantially improved the rice field identification accuracy under the complex topographic conditions. The comparative evaluations against support vector machine (SVM), random forest (RF), and U-Net models confirmed the superiority of the proposed method in terms of accuracy, local performance, terrain adaptability, training sample requirement, and computational cost, and demonstrated its effectiveness and applicability for the high-precision rice field distribution mapping in mountainous environments. Full article

Understanding the soil fungal community in vineyards sheds light on the interactions between plants and their associated microorganisms. For example, identifying arbuscular mycorrhizal fungi (AMF), which are beneficial to grapevine growth, is a good indicator of soil health. In contrast, other fungi, such as the pathogen group, can be detrimental to vine growth. The present study aimed to characterize the soil fungal community and the fungal diversity present at six Mediterranean vineyards located in Burgos (Spain), delving into fungal functional guilds and focusing on AMF and pathogenic fungal groups. The fungal structure was investigated using DNA metabarcoding in three soil samples taken from each vineyard, and differences in the abundance of functional guilds were assessed. Similar soil fungal community structures were observed among soil sample repetitions within vineyards. In contrast, adjacent vineyards presented differences in their microbial composition. Saprophytes followed by pathogens were the dominant fungal functional guilds across all vineyards. However, no differences in the relative abundance of the different fungal functional groups were observed among sites. The vineyard with the highest relative abundance of AMF (0.5%) also had the lowest pathogen relative abundance from all the sites (29.76%). Also, sites presenting a high relative abundance of pathogens in soil (>35%) had a low relative abundance of AMF (<0.05%). Our results suggest that the fungal community is affected by the intrinsic properties of the soil and the characteristics of each vineyard’s microsite over the effect of the geographical proximity. In addition, to improve our understanding of the soil microbial ecology, we highlight the necessity of prospecting soil fungal analyses into functional groups, interpreting diversity results within taxonomic groups alongside the total abundance of target groups/species. Full article

This study explores the enhancement of mechanical properties in cotton yarn-reinforced poly(lactic acid) (PLA) biocomposites, aimed at providing a sustainable alternative to petroleum-based plastics. The primary challenge addressed is the low interfacial shear strength (ISFF) between the hydrophilic cotton yarn and the hydrophobic PLA matrix. To overcome this, cotton yarn surface was chemically modified using silane treatment. Cotton yarns were aligned on a metal frame and treated with hydrolyzed silane solutions at concentrations of 1%, 2%, 3%, and 4% (w/v) for 3 h. Although the tensile stress of the cotton yarn decreased significantly (p < 0.05) with higher silane concentrations, from 520.46 MPa (untreated) to 340.88 MPa (4% silane-treated), the IFSS improved significantly (p < 0.05) from 5.63 MPa to 12.12 MPa. Consequently, the tensile stress of the cotton yarn/PLA biocomposites increased significantly (p < 0.05), from 20.74 MPa (untreated) to 41.58 MPa (4% silane-treated). This is because the increased IFSS achieved through silane treatment allowed the PLA polymer to more firmly connect adjacent cotton fibers, resulting in maximum strength. FTIR and SEM analyses confirmed successful surface modification of the cotton yarn. These findings demonstrate that silane treatment effectively enhances interfacial bonding between cotton yarn and PLA resin, leading to improved mechanical performance of the biocomposites. Full article

This pilot study uses Raman spectroscopy and SERS to monitor monthly water composition changes in two adjacent hypersaline lakes (L1 and L2) at a balneary resort, during the peak tourist season (May–October 2023). In situ pH and electrical conductivity (EC) measurements, along with evaporite analyses, complemented the spectroscopic data. Although traditionally considered similar, the lakes frequently raise public questions about their relative bathing benefits. While not directly addressing the therapeutic effects, the study reveals distinct physicochemical profiles between the lakes. Raman data showed consistently higher sulfate levels in L2, a trend also observed in winter monitoring. pH levels were higher in L1 (8–9.8) than in L2 (7.2–8), except for one October depth reading. This trend held during winter, except in April. Surface waters showed more variability and slightly higher values than those at 1 m depth. SERS spectra featured β-carotene peaks, linked to cyanobacteria, and Ag–Cl bands, indicating nanoparticle aggregation from inorganic ions. SERS intensity strongly correlated with pH and EC, especially in L2 (r = 0.96), suggesting stable surface–depth chemistry. L1 exhibited more monthly variability, likely due to differing biological activity. Although salinity and EC were not linearly correlated at high salt levels, both reflected seasonal trends. The integration of Raman, SERS, and physicochemical data proves effective for monitoring hypersaline lake dynamics, offering a valuable tool for environmental surveillance and therapeutic water quality assessment, in support of evidence-based water management and therapeutic use of salt lakes, aligning with goals for sustainable medical tourism and environmental stewardship. Full article

Background: Multilevel posterior spinal fusion to T10 often encounters complications such as screw loosening and proximal junctional kyphosis. Cement augmentation or prophylactic vertebroplasty is used to prevent these, but their biomechanical effects remain unclear. Methods: A validated finite element model (T8–pelvis) from CT data of a 57-year-old male was tested in five configurations: fusion only, fusion with cement augmentation at T10, T10–T11, T10–T11 plus T9 vertebroplasty, and T10–T11 plus T8–T9 vertebroplasty. Range of motion (ROM), intradiscal pressure (IDP), posterior ligament/facet stress, and cement–bone interface stresses were analyzed under a 400 N follower load and 10 N·m moments. Results: Cement augmentation at the upper instrumented vertebra produced <5% changes in ROM, IDP, and posterior ligament/facet stresses compared with fusion only, indicating preserved stability. Prophylactic vertebroplasty redistributed stress proximally, with elevated cement–bone interface stresses localized at T9 when vertebroplasty was performed at a single adjacent level (T9) and distributed to both T8 and T9 when performed at two adjacent levels (T8–9)—with T9 stressed mainly during lateral bending and extension, and T8 during flexion and lateral bending. Conclusion: Cement augmentation alone did not compromise adjacent-level biomechanics, but prophylactic vertebroplasty created abnormal stress concentrations at adjacent interfaces, potentially increasing fracture risk. These findings highlight the need for careful patient selection and further studies in osteoporotic populations. Full article

Objective: This study aimed to elucidate the regulatory mechanisms of the long intergenic non-protein coding RNA 02381 (LINC02381)/microRNA-let-7g-5p (let-7g-5p)/thrombospondin 1 (THBS1) signaling axis in osteosarcoma (OS). Methods: The expression levels of LINC02381, let-7g-5p, and THBS1 were quantified in OS and adjacent normal tissues via reverse transcription quantitative polymerase chain reaction. Their correlations with clinicopathological features were analyzed. Expression patterns were further validated in OS cell lines (143B, U-2OS, Saos-2, MNNG-HOS, MG-63) and normal osteoblast cell line hFOB1.19. The molecular interaction between LINC02381 and let-7g-5p and the targeting relationship of let-7g-5p with THBS1 were verified via dual-luciferase reporter and RNA pull-down assays. Functional effects were assessed using cell counting kit-8, colony formation, Transwell migration, and xenograft tumor models. Results: Compared to adjacent normal tissues, LINC02381 and THBS1 were upregulated in OS tissues (fold change > 3.0, p < 0.001), while let-7g-5p was downregulated (fold change ≈ 0.038, p < 0.001). Similar expression trends were observed in U-2OS cells. Knockdown of LINC02381 or overexpression of let-7g-5p reduced cell proliferation, colony formation, migration, THBS1 expression, and tumor volume (p < 0.001). These inhibitory effects were partially reversed by let-7g-5p inhibitors, restoring cell viability and migration by approximately 70%. Mechanistically, LINC02381 functioned as a competing endogenous RNA (ceRNA), directly binding to let-7g-5p and mitigating its suppression of THBS1. Conclusions:LINC02381 promotes OA progression by acting as a ceRNA for let-7g-5p, thereby upregulating THBS1 expression. This signaling axis represents a potential therapeutic target for OS. Full article

This study examines the spatial crime perception gap (SCPG), the mismatch between perceived and actual crime, which can lead to unnecessary avoidance behaviors, anxiety, or lack of vigilance. While few studies have explored this phenomenon from a spatial perspective, this research analyses the collective spatial perception of safety and unsafety in Vienna and Budapest and compares them with recorded crime patterns. Using a digital sketch map survey tool, 656 participants identified safe and unsafe areas as well as their daily routes. The responses were analyzed using spatial analytical and statistical methods to delineate the perception gaps in space, which were also diversified by crime type aggregations, including all crimes, violent crimes, property crimes, and visible crimes. Distance-based analyses were also conducted to examine the “spatial diffusion” and “spatial endowment” effects. The results show that many areas that are perceived as unsafe are not statistical crime hotspots. Perception aligns more closely with violent crime patterns than with property or visible crimes. The spatial diffusion effect illustrates that crime hotspots may influence and expand the perception of unsafety in adjacent and nearby areas. The spatial endowment effect suggests that people are more likely to perceive an area as unsafe if it is further away from their activity spaces, while overlooking crime hotspots that may intersect with it. These patterns were consistent across both cities, although the perception gap was larger in Budapest, while the endowment effect was more pronounced in Vienna. By highlighting where and how perception diverges from reality, this study provides insights that can inform strategies to reduce unfounded fear and strengthen the perceived safety and psychological resilience of urban populations. Full article

Background/Objectives: Integrating 3D visualization technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), into dental education may enhance students’ understanding of facial anatomy and clinical procedures. This study aimed to assess dental students’ perceptions of using MR for three-dimensional visualizations of impacted teeth. Methods: Cone-beam computed tomography (CBCT) scans of patients with impacted teeth were retrospectively selected from a university clinic database. The CBCT images were processed to adjust contrast for optimal visualization before being uploaded to MR goggles (HoloLens 2). A total of 114 final-year dental students participated, each manipulating the 3D images in space using the goggles. Following this, they completed a seven-question survey on a five-point Likert scale (1 = strongly agree, 5 = strongly disagree), evaluating image quality and the usefulness of 3D visualization. Results: The study group consisted of 29 males and 85 females (mean age = 24.11 years, SD = 1.48). The most favorable responses were for enhanced visualization of the impacted tooth’s position relative to adjacent structures and the inclusion of 3D image visualization as a teaching aid, which benefited students while learning and allowed them to better understand the course of the procedure for exposure/extraction of the impacted tooth, with median scores of 1, indicating a highly favorable opinion. A statistically significant relationship was found between the responses of females and males regarding the quality of the presented image using HoloLens 2 goggles. No significant correlation was found between participants with and without prior experience using VR/MR/AR. No significant correlation was found between age and responses. Conclusions: Students reported an improved understanding of the relationships between impacted teeth and adjacent structures, as well as potential benefits for clinical training. These findings demonstrate a high level of acceptance of MR technology among students; however, further research is required to objectively assess its effectiveness in enhancing learning outcomes. Full article

Background: Necrotizing enterocolitis (NEC) is a life-threatening condition characterized by necrosis of the gastrointestinal tract caused by hypoperfusion and hypoxia-induced inflammation. Surgical treatment often requires resection, with high morbidity and mortality. Intestinal tissue engineering using absorbable biomaterials represents a potential alternative. Small intestinal submucosa (SIS) is a biodegradable extracellular matrix (ECM) scaffold that may facilitate regeneration of the native tissue. Objectives: The aim of our study is to investigate the regenerative potential of SIS in a rat model with multiple gastrointestinal defects. Methods: In rats, after a midline laparotomy, an approximately 1 cm full-thickness incision was performed on the anterior gastric wall, on the antimesenteric side of the small and large intestine, each covered with an SIS patch. After three weeks, the graft sites and adjacent fragments were harvested and fixed in 10% neutral buffered formalin. Cross-sections of the grafted area were processed and stained with hematoxylin and eosin for histologic analysis. Results: Among the fifteen Wistar rats used in the study, the survival rate was 80% (12/15). Macroscopic examination of the abdominal cavity after the second surgery showed no complications. Adhesions were present in 92% (11/12). Histological examination demonstrated complete mucosal coverage in all stomach samples, nine of the small intestine, and ten of the large intestine. Mild fibrosis with minimal inflammatory infiltrates predominated. Ulceration with granulation tissue replacement was observed in three small intestine samples. Foreign body reactions were restricted to suture sites. Conclusions: In this multifocal injury model, SIS integrated effectively and supported early regenerative healing across gastric, small-intestinal, and colonic sites at 3 weeks. These data support further studies with longer follow-up, quantitative histology and functional assessment, and evaluation in neonatal-relevant large animal models to determine translational potential for NEC surgery. Full article

In some projects, a lack of data causes problems for presenting an accurate prediction model for surface settlement caused by shield tunneling. Existing models often rely on large volumes of data and struggle to maintain accuracy and reliability in shield tunneling. In particular, the spatial dependency between adjacent rings is overlooked. To address these limitations, this study presents a small-sample prediction framework for settlement induced by shield tunneling, using an adjacent-ring graph convolutional network (GCN-SSPM). Gaussian smoothing, empirical mode decomposition (EMD), and principal component analysis (PCA) are integrated into the model, which incorporates spatial topological priors by constructing a ring-based adjacency graph to extract essential features. A dynamic ensemble strategy is further employed to enhance robustness across layered geological conditions. Monitoring data from the Wuhan Metro project is used to demonstrate that GCN-SSPM yields accurate and stable predictions, particularly in zones facing abrupt settlement shifts. Compared to LSTM+GRU+Attention and XGBoost, the proposed model reduces RMSE by over 90% (LSTM) and 75% (XGBoost), respectively, while achieving an R² of about 0.71. Notably, the ensemble assigns over 70% of predictive weight to GCN-SSPM in disturbance-sensitive zones, emphasizing its effectiveness in capturing spatially coupled and nonlinear settlement behavior. The prediction error remains within ±1.2 mm, indicating strong potential for practical applications in intelligent construction and early risk mitigation in complex geological conditions. Full article

Previous studies on tunnel fires have primarily focused on tunnels with flat ceilings and lacked studies on tunnels with beams. The present study is predicated on a reduced-scale tunnel model with a beam structure. Through meticulous analysis of the effects of factors such as longitudinal ventilation velocity and beam dimensions, the study unveils the distribution pattern of ceiling temperatures under the longitudinal smoke exhaust mode. The findings suggest that the presence of beams can induce turbulence in the longitudinal ventilation airflow. It has been demonstrated that the magnitude of this phenomenon is directly proportional to the spacing of the beams. This results in fluctuations in the ceiling temperature rise close to the combustion zone. The smoke storage capacity of the open cavities formed between adjacent beams is significantly affected by the beam height, thereby influencing the overall temperature rise beneath the ceiling. The greater the beam height, the higher the overall ceiling temperature rise near the combustion zone, but the lower the ceiling temperature rise downstream of the fire source. A prediction model for the longitudinal decay of ceiling temperature downstream of the fire source in tunnels with beams has been obtained. This model is related to the dimensionless beam dimension. Full article

Cracks in concrete structures, caused by aging, adjacent construction, and seismic activity, pose critical risks to structural integrity, durability, and serviceability. Traditional monitoring methods based solely on absolute thresholds are inadequate for detecting progressive crack growth at early stages. This study proposes a big data-driven anomaly detection model that combines absolute threshold evaluation with periodic trend analysis to enable both real-time monitoring and early anomaly identification. By incorporating relative comparisons, the model captures subtle variations within allowable limits, thereby enhancing sensitivity to incipient defects. Validation was conducted using approximately 2700 simulated datasets with an increase–hold–increase pattern and 470,000 real-world crack measurements. The model successfully detected four major anomalies, including abrupt shifts and cumulative deviations, and time series visualizations identified the exact onset of abnormal behavior. Through periodic fluctuation analysis and the Isolation Forest algorithm, the model effectively classified risk trends and supported proactive crack management. Rather than defining fixed labels or thresholds for the detected results, this study focused on verifying whether the analysis of detected crack data accurately reflected actual trends. To support interpretability and potential applicability, the detection outcomes were presented using quantitative descriptors such as anomaly count, anomaly score, and persistence. The proposed framework addresses the limitations of conventional digital monitoring by enabling early intervention below predefined thresholds. This data-driven approach contributes to structural health management by facilitating timely detection of potential risks and strengthening preventive maintenance strategies. Full article

To address the challenges of radar multi-target detection in marine environments, this paper proposes an information geometry (IG)-based, two-stage track-before-detect (TBD) framework. Specifically, multi-target measurements are first modeled on the manifold, leveraging its geometric properties for enhanced detection. The designed scoring function incorporates both the feature dissimilarity between targets and clutter, as well as the precise inter-target path associations. Consequently, a novel merit function combining feature dissimilarity and transition cost is derived to mitigate the mutual interference between adjacent targets. Subsequently, to overcome the integrated merit function expansion phenomenon, a two-stage integration strategy combining dynamic programming (DP) and greedy integration (GI) algorithms was adopted. To tackle the challenges of unknown target numbers and computationally infeasible multi-hypothesis testing, a target cancellation detection scheme is proposed. Furthermore, by exploiting the independence of multi-target motions, an efficient implementation method for the detector is developed. Experimental results demonstrate that the proposed algorithm inherits the superior clutter discrimination capability of IG detectors in sea clutter environments while effectively resolving track mismatches between neighboring targets. Finally, the effectiveness of the proposed method was validated using real-recorded sea clutter data, showing significant improvements over conventional approaches, and the signal-to-clutter ratio was improved by at least 2 dB. Full article

The global forestry discourse frequently highlights the issue of ungulate browsing, which can significantly impact tree regeneration and tree species composition by inhibition of growth and elimination of certain, particularly ecologically valuable, tree species. The forestry field often utilizes the percentage of browsed trees within a specific area, ranging from single hunting grounds to broader provincial scales, as a metric of browsing intensity. This measure correlates with ungulate density, which is known to vary across landscapes, rendering spatially averaged browsing percentages less useful for silvicultural decisions even with accurate results. Addressing this gap, we utilized a GLMM with random effects to assess tree specific browsing pressure more appropriately. We incorporated data from two adjacent areas in the northeastern limestone Alps, focussing on the four important tree species in the region (Abies alba, Acer pseudoplatanus, Fagus sylvatica, and Picea abies). We analyzed data collected with distinct methodologies for the two regions, respectively, Austrian Federal Game Impact Monitoring and Austrian Regeneration and Browsing Monitoring of Federal Forests. Overall, the data documented browsing occurrence on 8933 trees over 632 sampling plots totalling 55,000 hectares. By comparing various models, including those with spatial considerations, we found that treating sampling plot location as a latent state variable improved the model fit and allowed prediction of browsing probability on a landscape scale. This study underlines the value of incorporating spatial elements into models for assessing browsing pressure and its spatial variations, thereby facilitating more informed silvicultural decisions. Full article