Search Results (4,881)

Nearly all eukaryotic proteins are turned over by the ubiquitin (Ub)-26S proteasome system (UPS). Despite its broad cellular roles, only a handful of UPS members, particularly the Ub E3 ligases that specifically recognize a protein for ubiquitylation, have been characterized in plants to date. The challenge arises from the transient recognition and rapid degradation of ubiquitylation substrates by the UPS. To tackle this challenge, the emerging biotinylation-based proximity labeling (PL) offers an exciting tool for enriching transient interactors of Ub E3 ligases. In this study, we examined the efficacy of TurboID in identifying substrates of Arabidopsis Skp1-cullin1-F-box (SCF) ligases. We demonstrate that the Arabidopsis Skp1 Like (ASK)1-TurboID is not fully functioning in planta, which led us to discover a novel antagonism between biotinylation and ubiquitylation in regulating protein stability in vivo. This discovery lowers the effectiveness of PL in ubiquitylome studies. However, using one long-known SCF substrate, phytochrome A, we succeeded to apply its TurboID fusion for complementing the far-red-light response of the phyA-211 null mutant allele, suggesting an efficacy of PL in characterizing single ubiquitylation pathways. This study highlighted a limitation of PL in ubiquitylome studies, discovered a new antagonistic pathway of biotinylation, and developed a theoretical guidance for future PL-based characterization of ubiquitylation pathways. Full article

Background/Objectives: All-inside ACL reconstruction has emerged as a minimally invasive alternative to conventional techniques, with potential advantages in graft configuration and reduced surgical trauma. This study aimed to compare the clinical outcomes of all-inside and full tibial tunnel ACL reconstruction, focusing on graft diameter, postoperative stability, and functional recovery. We hypothesized that the all-inside technique would allow for thicker grafts and yield superior postoperative knee stability and functional outcomes, with postoperative anterior laxity as a major outcome of interest. Methods: This retrospective comparative study reviewed patients who underwent ACL reconstruction between January 2020 and February 2024. From January 2020 to September 2022, a four-strand hamstring autograft with full tibial tunnel technique (FT-4) was used, while from September 2022, a six-strand hamstring autograft with the all-inside technique (AI-6) was adopted to enable thicker grafts and optimize fixation. Among a total of 103 patients, 1:1 propensity score matching (PSM) was performed based on age, sex, BMI, laterality, ALL reconstruction, meniscal lesion, and preoperative anterior laxity (SSD). Graft diameter and clinical outcomes, including knee stability and functional scores, were compared between the matched groups. Results: After PSM, two comparable groups of 29 patients each were established. Graft diameter was significantly larger in the AI-6 group (9.5 ± 0.7 mm) compared to the FT-4 group (7.8 ± 0.8 mm, p < 0.001), while other baseline characteristics remained well balanced between the groups. At the final follow-up, both groups exhibited significant improvements in anterior laxity, functional scores, and pivot shift grades (all p < 0.001). The AI-6 group demonstrated superior outcomes with a significantly higher Lysholm score (82.2 ± 6.7 vs. 75.6 ± 8.9, p = 0.002), lower WOMAC score (8.0 ± 4.3 vs. 12.9 ± 10.5, p = 0.023), and reduced anterior laxity (1.6 ± 1.1 mm vs. 2.5 ± 1.4 mm, p = 0.005) compared to the FT-4 group, whereas no significant differences were observed in the IKDC, Tegner, Korean knee score, or pivot shift test results. A simple linear regression revealed a significant negative correlation between graft diameter and postoperative anterior laxity (B = −0.398, p = 0.048). Conclusions: The present study demonstrated that the use of a six-strand hamstring graft configuration in the AI-6 technique resulted in significantly thicker grafts and was associated with reduced postoperative anterior knee laxity compared to the FT-4 technique. While interpretation of these findings requires caution in light of MCID thresholds, the AI-6 group showed favorable outcomes in anterior laxity and selected functional scores, such as the Lysholm and WOMAC. This technique may offer practical clinical value, particularly in populations prone to smaller graft diameters, as it facilitates adequate graft thickness through multifold preparation, with the all-inside approach accommodating the inherent graft shortening. Full article

Plant viruses have been traditionally considered pathogens restricted to plant hosts. However, recent studies have shown that some plant viruses can infect and replicate in filamentous fungi and oomycetes, suggesting that their host range is broader than previously thought, and that their ecological interactions are more complex. In this study, we investigated the ability of the well-characterized positive-sense RNA plant virus Tobacco mosaic virus (TMV) to replicate in four major phytopathogenic fungi from different taxonomic groups: Botrytis cinerea, Fusarium oxysporum f. sp. lycopersici, Verticillium dahliae, and Monilinia fructicola. Using a recombinant TMV-based vector expressing a green fluorescent protein (TMV-GFP-1056) as reporter, we demonstrated that TMV can enter, replicate, and persist within the mycelia of B. cinerea and V. dahliae—at least through the first subculture. However, it cannot replicate in F. oxysporum f. sp. lycopersici and M. fructicola. RNA interference (RNAi) is a conserved eukaryotic epigenetic mechanism that provides an efficient defence against viruses. We explored the role of RNAi in the interaction between TMV and the mycelia of V. dahliae and B. cinerea. Our results revealed a strong induction of the Dicer-like 1 and Argonaute 1 genes, which are key compounds of the RNA silencing pathway. This RNAi-based response impaired TMV-GFP replication in both fungi. Notably, despite viral replication and RNAi activation, the virulence of V. dahliae and B. cinerea on their respective host plants remained unaffected. These findings reinforce the emerging recognition of cross-kingdom virus transmission and interactions, which likely play a crucial role in pathogen ecology and viral evolution. Understanding these virus–fungus interactions not only sheds light on RNAi interference silencing mechanisms but also suggests that plant viruses like TMV could serve as simple and effective tools for functional genomic studies in fungi, such as in V. dahliae and B. cinerea. Full article

In recent years, solar energy has emerged as a pillar of sustainable development. However, maintaining panel efficiency under extreme environmental conditions remains a persistent hurdle. This study introduces an automated defect detection pipeline that leverages deep learning and computer vision to identify five standard anomaly classes: Non-Defective, Dust, Defective, Physical Damage, and Snow on photovoltaic surfaces. To build a robust foundation, a heterogeneous dataset of 8973 images was sourced from public repositories and standardized into a uniform labeling scheme. This dataset was then expanded through an aggressive augmentation strategy, including flips, rotations, zooms, and noise injections. A YOLOv11-based model was trained and fine-tuned using both fixed and adaptive learning rate schedules, achieving a mAP@0.5 of 85% and accuracy, recall, and F1-score above 95% when evaluated across diverse lighting and dust scenarios. The optimized model is integrated into an interactive dashboard that processes live camera streams, issues real-time alerts upon defect detection, and supports proactive maintenance scheduling. Comparative evaluations highlight the superiority of this approach over manual inspections and earlier YOLO versions in both precision and inference speed, making it well suited for deployment on edge devices. Automating visual inspection not only reduces labor costs and operational downtime but also enhances the longevity of solar installations. By offering a scalable solution for continuous monitoring, this work contributes to improving the reliability and cost-effectiveness of large-scale solar energy systems. Full article

Floods are among the most frequent and damaging hazards worldwide, with impacts intensified by climate change and rapid urban growth. This review analyzes how satellite-based Earth Observation (EO) technologies are evolving to meet operational needs in flood detection and water depth estimation, with a focus on the Copernicus Emergency Management Service (CEMS) as a mature and widely adopted European framework. We compare the capabilities of conventional EO datasets—optical and Synthetic Aperture Radar (SAR)—with 3D geospatial datasets such as high-resolution Digital Elevation Models (DEMs) and Light Detection and Ranging (LiDAR). While 2D EO imagery is essential for rapid surface water mapping, 3D datasets add volumetric context, enabling improved flood depth estimation and urban impact assessment. LiDAR, in particular, can capture microtopography between high-rise structures, but its operational use is constrained by cost, data availability, and update frequency. We also review how artificial intelligence (AI), including machine learning and deep learning, is enhancing automation, generalization, and near-real-time processing in flood mapping. Persistent gaps remain in model transferability, uncertainty quantification, and the integration of scarce high-resolution topographic data. We conclude by outlining a roadmap towards hybrid frameworks that combine EO observations, 3D datasets, and physics-informed AI, bridging the gap between current technological capabilities and the demands of real-world emergency management. Full article

This study evaluates the feasibility and benefits of adopting the IEC 62034:2012 standard for Automatic Testing Systems (ATS) for emergency and escape lighting on the BorWin5 High Voltage Direct Current (HVDC) offshore converter platform. The system comprises approximately 1800 luminaires from multiple manufacturers that are integrated into an open-architecture 220 VDC emergency network. Life-cycle cost analysis (LCCA) and multi-criteria decision-making (MCDM) approaches were employed to evaluate four configurations, ranging from manual testing to fully automated, centrally powered systems, based on technical, economic, operational, and environmental criteria. The chosen solution, which combines centralized power with automated testing and real-time monitoring, represents a significant advancement in offshore safety infrastructure. Implementing this solution on BorWin5 enhances reliability and maintainability while ensuring compliance with international standards, supporting a projected service life of over 30 years for an emergency and escape lighting system in an extreme marine environment. The findings offer a scalable model for future offshore platforms operating in similarly challenging conditions. Full article

Natural resource assets inherently integrate tripartite synthesis of legal, economic, and ecological attributes. They serve dual critical functions as foundational elements supporting the evolution of new-quality productive forces and pivotal mechanisms safeguarding ecosystemic integrity. It has become a global consensus and direction of action to advance comprehensive supervision of natural resource assets and practice the concept of “Community of Life for Human and Nature”. Under the background of the super-ministry system restructuring in China, comprehensive supervision of natural resource assets remains challenged by system fragmentation in supervision objectives and multifaceted interest conflicts among stakeholders. In light of this, this research focuses on the theoretical justification and system optimization of the comprehensive supervision of natural resource assets in China. Using comparative analysis and normative analysis methods, we validate the system’s function on the comprehensive supervision of natural resource assets, summarize foreign experiences, and ultimately aim to explore the optimization pathway of the legal system for the comprehensive supervision of natural resource assets. The results show the following: (1) The choice of the legal system for the comprehensive supervision of natural resource assets emerges as the functional product aligning societal objectives, the rational paradigm for achieving efficient resource allocation, and the adaptive response to the external effects of common property. (2) The system supply of comprehensive supervision of natural resource assets in foreign countries is characterized by normative convergence in conceptual elements and typological categorization in objectives and objects. Therefore, this research recommends that, in order to optimize the system of the comprehensive supervision of natural resource assets in China, (1) in terms of protection of source, natural resource assets should be categorized, with operational natural resource assets focusing on management and public welfare natural resource assets focusing on conservation. (2) In terms of valuation, the economic valuation of natural resource assets should be integrated with ecosystem service assessments to enhance fair market equity. (3) In terms of method, the big data center should be established to enable the synergistic integration of technological innovation and system reforms. (4) In terms of subject, requiring the participation of various government departments, non-governmental organizations, the general public, and other parties could realize the connection of different legal bases for the comprehensive supervision of natural resource assets and the balance of multiple rights and interests, which should help to achieve balanced resource efficiency and biodiversity conservation and safeguard national ecological security. Full article

As global food demand continues to rise, conventional agricultural practices face increasing difficulty in sustainably meeting production requirements. In response, deep learning-driven automated systems have emerged as promising solutions for enhancing precision farming. Nevertheless, accurate fruit segmentation remains a significant challenge in orchard environments due to factors such as occlusion, background clutter, and varying lighting conditions. This study proposes the Depthwise Asymmetric Bottleneck with Attention Mechanism Network (DABAMNet), an advanced convolutional neural network (CNN) architecture composed of multiple Depthwise Asymmetric Bottleneck Units (DABou), specifically designed to improve apple segmentation in RGB imagery. The model incorporates the Convolutional Block Attention Module (CBAM), a dual attention mechanism that enhances channel and spatial feature discrimination by adaptively emphasizing salient information while suppressing irrelevant content. Furthermore, the CBAM attention module employs multiple global pooling strategies to enrich feature representation across varying spatial resolutions. Through comprehensive ablation studies, the optimal configuration was identified as early CBAM placement after DABou unit 5, using a reduction ratio of 2 and combined global max-min pooling, which significantly improved segmentation accuracy. DABAMNet achieved an accuracy of 0.9813 and an Intersection over Union (IoU) of 0.7291, outperforming four state-of-the-art CNN benchmarks. These results demonstrate the model’s robustness in complex agricultural scenes and its potential for real-time deployment in fruit detection and harvesting systems. Overall, these findings underscore the value of attention-based architectures for agricultural image segmentation and pave the way for broader applications in sustainable crop monitoring systems. Full article

To systematically elucidate the chronological patterns of embryonic development and morphological changes in the larval and juvenile stages of Silurus glanis, and provide fundamental biological insights into this species, in this study, fertilized eggs were obtained through artificial spawning induction technology. After removing adhesiveness from fertilized eggs using trypsin, a detailed developmental study was conducted. The study systematically analyzed the chronological sequence of embryonic development and the morphological change patterns of larval and juvenile fish. The results showed the following: The fertilized eggs of S. glanis are yellow, spherical, and sticky, and the stickiness allows eggs to attach to spawning substrates, enhancing hatching success. The egg diameter after water absorption was (2.88 ± 0.13) mm. The embryonic development took 47 h and 55 min, with a total accumulated temperature of 1245.56 h degrees Celsius, the developmental process includes seven stages and twenty-six periods, namely the zygophase stage, cleavage stage, blastula stage, gastrula stage, neurula stage, organogenesis stage, and hatching stage. At a temperature of (26.0 ± 0.9) °C, the hatched individuals went through the pre-yolk sac larval stage, late larval stage, juvenile fry stage, and juvenile stage. In the pre-yolk sac larval stage, otoliths appeared in the bilateral otic vesicles, a pair of barbel primordia emerged under the mandible, a short and thin straight intestine formed in the abdominal cavity, and the oral fissure first appeared. In the late larval stage, the fin rays were initially formed, the intestine became thicker and longer, the oral fissure, anus, and cloaca were formed, and the larvae could float and start feeding on exogenous food. In the juvenile fry stage, the differentiation of various organs was basically complete, the nostrils became larger, and both the anal fin and caudal fin had dark black markings. In the juvenile stage, the maxillary barbels elongated, the mucus layer thickened on the body and back, the abdomen is light white, and it had the external morphological characteristics of an adult fish. By measuring and calculating the total length, body length, body height, and head length of S. glanis larvae and juveniles (0–40 days), the results showed that the growth characteristics conformed to the following fish growth formula: TL = 0.0141x² + 0.8096x + 8.2421 (R² = 0.9916), where x denotes days after hatching. This study has preliminarily mastered the chronological patterns of the embryonic development, growth, and formation of the morphological characteristics in larval and juvenile S. glanis, providing scientific data and laying a theoretical foundation for the division of early developmental stages, reproduction, hatching, and fry cultivation. Full article

The objective of this study is to explore the use of emerging technologies such as the Metaverse and Digital Twin to highlight how these can be used to analyse and improve the perception of security in urban parks. Through the proposed methodological approach, which combines real data collection, 3D modelling, immersive simulations, and user feedback, a virtual environment representative of the Quartieri Spagnoli Park in Naples, chosen as a case study, was developed and tested. The experimentation involved a heterogeneous group of users and consisted of two phases of questionnaire administration, one in person and one in a virtual environment, to compare the individual and collective perceptions of users in relation to issues such as disorientation, lighting, and maintenance. The results obtained made it possible to identify a correspondence between the data collected in the two environments, and to highlight any critical issues that emerged. Undoubtedly, the virtual experience proved to be useful, accessible, and immersive, demonstrating the potential of these tools not only in identifying issues but especially in supporting participatory design and urban planning with a view to a smart city. In urban design, as in many other fields, being able to intervene and test changes in a virtual environment before actually implementing them is a valuable opportunity, as it allows the feasibility to be assessed without compromising the real space. It is precisely this aspect that makes this type of approach extremely interesting and important. The distinctive feature of the proposed approach lies in the implementation of digital twins in the metaverse, which can perform a dual function: simulation and verification. In the first case, simulations within the virtual environment allow project planning to be tested in order to predict the outcome; in the second case, it is possible to investigate the state of affairs, thus assessing whether the planning put in place has achieved the desired results. Full article

The tension in the relationship between water and energy seriously restricts the harmonious coexistence between man and the ecological environment. The solar-powered interface evaporation technology emerging in recent years has shown good application prospects in high-salt wastewater treatment for achieving the zero-discharge treatment of wastewater. In this review, advanced solar-driven interfacial evaporation is primarily focused on its mechanisms, photothermal materials optimization, and the structure of solar evaporators for salt removal. The high wide-spectrum solar absorption rate of photothermal materials determines the total energy that can be utilized in the evaporation system. The light-to-heat conversion capacity of photothermal materials directly affects the efficiency and performance of solar interface evaporators. We highlight the microstructures enabled by the nanophotonic designs of photothermal material-based solar absorbers, which can achieve highly efficient light harvesting across the entire solar irradiance spectral range with weighted solar absorptivity. Finally, based on current research, existing problems, and future development directions for high-salt wastewater evaporation research are proposed. The review provides insights into the effective treatment of high-salt wastewater. Full article

This study examines the strategic deployment of religion as a political tool in contemporary Turkey through a comparative analysis of two ideologically distinct Islamic movements: the Gülen movement (Hizmet) and the movement of Adnan Oktar. Despite their divergent theological premises and organizational structures, both movements articulate religious worldviews that diverge significantly from dominant Islamist narratives—particularly in their surprisingly affirmative positions toward Israel. Rather than treating religion as a fixed doctrinal corpus, this article conceptualizes it as a flexible repertoire shaped by political context and rhetorical need. In this light, Israel emerges not as a diplomatic partner but as a symbolic site through which broader ideological positions are negotiated. The contrast between the two movements sheds light on how religious language can serve as both a boundary marker and a strategic resource in the articulation of identity, authority, and ideological distinctiveness. This article contributes to a deeper understanding of how Islamic movements in Turkey—often perceived as monolithic in their opposition to Zionism—can, under certain conditions, reframe religion to support non-hostile, and even sympathetic, positions. It offers a framework for analyzing the political uses of religion without overlooking theological nuance or disregarding intra-Islamic plurality. Full article

Photocatalysis is an emerging technology that harnesses light energy to facilitate chemical reactions. It has garnered considerable attention in the field of catalysis due to its promising applications in environmental remediation and sustainable energy generation. Recently, researchers have been exploring innovative techniques to improve the surface reactivity of ferroelectric materials for catalytic purposes, leveraging their distinct properties to enhance photocatalytic efficiency. With their switchable polarization and improved charge transport capabilities, ferroelectric materials show promise as effective photocatalysts for various reactions, including carbon dioxide (CO₂) reduction. Through a blend of experimental studies and theoretical modeling, researchers have shown that these materials can effectively convert CO₂ into valuable products, contributing to efforts to reduce greenhouse gas emissions and promote a cleaner environment. An artificial neural network (ANN) was employed to analyze parameter relationships and their impacts in this study, demonstrating its ability to manage training data errors and its applications in fields like speech and image recognition. This research also examined changes in charge separation, light absorption, and surface area related to variations in band gap and polarization, confirming prediction accuracy through linear regression analysis. Full article

Postharvest losses due to fungal decay pose a significant challenge to global fruit and vegetable production, especially in regions where rot pathogens are prevalent. Traditional control methods rely heavily on synthetic fungicides, which are increasingly criticized for their environmental risks, human health concerns, and their role in fostering pathogen resistance. These issues underscore the urgent need for sustainable, residue-free alternatives that not only manage postharvest diseases but also enhance produce quality. Light-emitting diode [LED] technology has emerged as a promising, eco-friendly solution capable of modulating plant physiological responses through specific light wavelengths. However, the exact defense mechanisms activated by LED exposure in postharvest decay control and nutritional enhancement remain underexplored. This review provides a comprehensive synthesis of recent findings on LED-induced control of fungal decay, focusing on how LED treatments modulate pathogen–fruit interactions, activate innate defense pathways, regulate gene networks linked to defense and nutritional traits, and contribute to improved fruit and vegetable quality and health benefits. Full article

Background: Dopamine (DA) is a critical neurotransmitter that regulates many physiological and behavioral processes. The central dopaminergic system plays a pivotal role in modulating general anesthesia (GA). DA release in the brain is mainly concentrated in the nucleus accumbens (NAc), prefrontal cortex, hypothalamus, and dorsal striatum. Several NAc neuron subtypes are essential for modulating states of consciousness during GA. However, whether NAc DA signal dynamics correlate with different states of consciousness under sevoflurane anesthesia remains to be elucidated. In this study, we measured the dynamic fluctuations of NAc DA levels throughout sevoflurane anesthesia to verify its role. Methods: An intensity-based genetically encoded DA indicator, dLight1.1, was employed to track DA release in the NAc. Fiber photometry combined with electroencephalogram/electromyogram recordings was employed to synchronously track NAc DA signal dynamics across different states of consciousness under sevoflurane anesthesia. Results: Under 2.5% sevoflurane exposure, DA release in the NAc significantly increased during the initial 100 s of sevoflurane induction, which was designated as sevo on-1 (mean ± standard error of the mean [SEM]; baseline vs. sevo on-1, p = 0.0261), and continued to decrease in the subsequent anesthesia maintenance phases (sevo on-1 vs. sevo on-4, p = 0.0070). Following the cessation of sevoflurane administration (with intervals denoted as sevooff), NAc DA gradually returned to baseline levels (sevo on-1 vs. sevo off-1, p = 0.0096; sevo on-1 vs. sevo off-3, p = 0.0490; sevo on-1 vs. sevo off-4, p = 0.0059; sevo on-4 vs. sevo off-4, p = 0.0340; sevo off-1 vs. sevo off-4, p = 0.0451). During the induction phase, NAc DA signal dynamics markedly increased during the pre-loss of consciousness (LOC) period (pre-anesthesia baseline vs. pre-LOC, p = 0.0329) and significantly declined after LOC (pre-LOC vs. post-LOC, p = 0.0094). For the emergence period, NAc DA release exhibited a noticeable increase during the initial period after recovery of consciousness (ROC) (anesthesia baseline vs. post-ROC, p = 0.0103; pre-ROC vs. post-ROC, p = 0.0086). Furthermore, the DA signals peaked rapidly upon the initiation of the burst wave and then gradually attenuated, indicating a positive correlation with the burst wave onset during burst suppression events. Conclusions: Our findings revealed that NAc DA neurotransmitter signal dynamics correlate with different states of consciousness throughout sevoflurane anesthesia. Full article