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The maritime industry is one of the most crucial sectors in the global economy, facilitating the transportation of goods and commodities across vast distances. However, maritime network congestion has become an increasingly critical challenge that significantly affects shipping efficiency and the overall operational performance of the industry. This study proposes an innovative congestion prediction approach using dynamic big data analysis of vessel trajectories and multiscale feature analysis. First, the dynamic analysis of vessel trajectories aims to extract valuable information from ships’ data as they navigate the oceans, enabling proactive traffic management and optimized routing. Second, the multiscale feature analysis provides a comprehensive understanding of maritime network congestion by examining it from different perspectives and scales, leading to more accurate predictions and effective congestion management strategies. Furthermore, this study introduces an enhanced Faster R‐CNN vessel detection model for real‐time tracking, integrating convolutional and SKNet networks. To improve short‐term traffic flow prediction accuracy, this study employs multiscale feature analysis through wavelet transformation. The foundational traffic data undergo wavelet decomposition for a detailed representation across frequencies. Gated recurrent unit (GRU) neural network and autoregressive moving average (ARMA) models are utilized to predict trend and noise components, respectively. Fusion of predictions demonstrates superior accuracy and is validated against real data. Empirical results showcase minimal errors and heightened prediction accuracy compared to actual data.

Growth traits, such as fresh weight, diameter, and leaf area, are pivotal indicators of growth status and the basis for the quality evaluation of lettuce. The time-consuming, laborious and inefficient method of manually measuring the traits of lettuce is still the mainstream. In this study, a three-stage multi-branch self-correcting trait estimation network (TMSCNet) for RGB and depth images of lettuce was proposed. The TMSCNet consisted of five models, of which two master models were used to preliminarily estimate the fresh weight (FW), dry weight (DW), height (H), diameter (D), and leaf area (LA) of lettuce, and three auxiliary models realized the automatic correction of the preliminary estimation results. To compare the performance, typical convolutional neural networks (CNNs) widely adopted in botany research were used. The results showed that the estimated values of the TMSCNet fitted the measurements well, with coefficient of determination ( R 2 ) values of 0.9514, 0.9696, 0.9129, 0.8481, and 0.9495, normalized root mean square error (NRMSE) values of 15.63, 11.80, 11.40, 10.18, and 14.65% and normalized mean squared error (NMSE) value of 0.0826, which was superior to compared methods. Compared with previous studies on the estimation of lettuce traits, the performance of the TMSCNet was still better. The proposed method not only fully considered the correlation between different traits and designed a novel self-correcting structure based on this but also studied more lettuce traits than previous studies. The results indicated that the TMSCNet is an effective method to estimate the lettuce traits and will be extended to the high-throughput situation. Code is available at https://github.com/lxsfight/TMSCNet.git .

Aquatic ecosystems worldwide are increasingly affected by human activities, with urbanization representing a major source of environmental stress. Channelization and flow depletion are key stressors in urban aquatic ecosystems. However, the combined effects of these factors on benthic macroinvertebrate and fish communities in urban rivers remain poorly understood. We examined the ecological impacts of channelization and flow depletion on benthic macroinvertebrates and fish in four urban rivers in Beijing, China: the natural high-flow Yongding River, the natural low-flow Gaojinggou River, the artificial high-flow Yongding River Diversion Channel, and the artificial low-flow Renmin Channel. By analyzing community composition, diversity, biomass, and water quality parameters, we assessed how river type (natural vs. artificial) and flow conditions (high vs. low) shape macroinvertebrate and fish communities across these urban rivers. Results showed that artificial channels had higher water temperatures, lower pH and DO, and higher concentrations of COD, NH 4 + , TP, fluorides, and sulfides compared to natural rivers, with flow depletion intensifying these effects. Both macroinvertebrate and fish community compositions varied significantly between river types and flow conditions. Channelization and flow depletion significantly reduced species richness, Shannon-Wiener diversity, and biomass in both macroinvertebrates and fish. Furthermore, we found a significant interaction between river type and flow depletion, as revealed by two-way ANOVA, with macroinvertebrate and fish communities in natural rivers being more sensitive to flow reductions than artificial channels. Redundancy analyses (RDAs) revealed that total phosphorus (TP) was the primary driver of macroinvertebrate community variation (contributing 23.6%), while DO played a crucial role in fish assemblages (contributing 20.6%). These findings underscore the significant impacts of channelization and flow depletion on urban river ecosystems, highlighting the vulnerability of natural rivers to flow depletion. Our study calls for urgent implementation of integrated management strategies to mitigate hydrological alterations, restore natural flow regimes, and reduce nutrient inputs, thereby enhancing the ecological resilience of urban aquatic ecosystems.

Background Age-dependent accumulation of lipofuscin in the retinal pigment epithelium (RPE) is closely related to the etiology of autosomal recessive Stargardt’s disease (STGD1) and dry age-related macular degeneration (AMD). N -retinylidene- N -retinylethanolamine (A2E) is a leading component of RPE lipofuscin that is highly susceptible to blue light. Ferroptosis is an iron-dependent form of non-apoptotic cell death characterized by the accumulation of lipid peroxides to a lethal level, which plays an important role in retinal diseases. However, it remains unknown whether A2E functions as a physiological trigger for eliciting blue light-induced ferroptosis of RPE cells. Methods A2E-loaded RPE cells and Abca4 −/− Rdh8 −/− mice were exposed to blue light, respectively. Western blotting, immunofluorescence staining, reactive oxygen species (ROS) staining, intracellular iron staining, lipid peroxidation staining, fundus imaging, optical coherence tomography (OCT), hematoxylin–eosin (HE) staining, and electroretinography (ERG) were utilized to elucidate the role of blue light in A2E induced ferroptosis in the RPE and its potential mechanisms. Results Exposure of A2E to blue light promoted ferroptotic cell death in RPE cells by elevating ferrous ion (Fe 2+ ) levels and inhibiting the solute carrier family 7 membrane 11 (SLC7A11)-glutathione (GSH)-glutathione peroxidase 4 (GPX4) axis. GPX4 inactivation and ROS generated by Fe 2+  overload and GSH depletion precipitated lipid peroxidation and subsequent ferroptosis in A2E-containing RPE cells upon exposure to blue light. In addition to GSH supplement, repressing either Fe 2+  by deferiprone (DFP) or lipid peroxidation with ferrostatin-1 (Fer-1) significantly protected RPE cells against ferroptosis caused by blue light illumination of A2E.  Abca4 −/− Rdh8 −/−  mice featured by an accelerated deposition of A2E in the RPE is an animal model for STGD1 and dry AMD. It was observed that ferroptosis was indeed present in the RPE of  Abca4 −/− Rdh8 −/−  mice following exposure to blue light. Notably, alleviating ferroptosis by intraperitoneally injected Fer-1 effectively rescued retinal function and ameliorated RPE/photoreceptor degeneration in blue light-exposed  Abca4 −/− Rdh8 −/−  mice. Conclusions Our results suggest the importance of blue light in A2E-mediated ferroptosis in the RPE, and deeply broaden the understanding of mechanisms underlying RPE atrophy arising from lipofuscin accumulation in STGD1 and dry AMD.

Background Disruption of the retinoid (visual) cycle causes all- trans -retinal (atRAL) to accumulate in photoreceptors and retinal pigment epithelium (RPE), contributing to Stargardt disease type 1 (STGD1) and dry age-related macular degeneration (dAMD). Yet, the mechanisms underlying atRAL-induced RPE degeneration are not well understood. Here, we explored whether ferroptosis, a form of regulated cell death marked by iron-dependent lipid peroxidation, mediated RPE damage by atRAL. Methods Cell and animal models of STGD1 and dAMD were established using ARPE-19 cells loaded with atRAL and Abca4 −/− Rdh8 −/− mice subjected to light exposure. Cell viability and morphology, mitochondrial morphology, ferrous iron (Fe 2+ ) levels, reactive oxygen species (ROS) production, lipid peroxidation, and ferroptosis-related gene and protein expression were assessed using MTS assay, inverted and confocal microscopy, fluorescence staining, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blotting, respectively. The conditions of mouse retina were evaluated by electroretinography (ERG), optical coherence tomography (OCT), fundus imaging, and immunofluorescence labeling. Results atRAL triggered ferroptosis of ARPE-19 cells through Fe 2+ accumulation, ROS generation, lipid peroxidation, mitochondrial damage, and abnormal expression of typical ferroptosis-related genes and proteins. These effects were capable of being alleviated by treatment with ferrostatin-1 (Fer-1), a potent ferroptosis inhibitor. Moreover, ferroptosis was clearly observed in the RPE of light-exposed Abca4 −/− Rdh8 −/− mice that showed rapid and excessive accumulation of atRAL in the retina. Notably, intraperitoneal administration of Fer-1 effectively mitigated the degeneration of the RPE and photoreceptors and significantly ameliorated retinal function in Abca4 −/− Rdh8 −/− mice following light exposure. Conclusions Ferroptosis plays a critical role in RPE damage by atRAL. Inhibition of ferroptosis by Fer-1 may enhance RPE cell survival and prevent subsequent photoreceptor degeneration in STGD1 and dAMD.

Fusarium head blight (FHB) is a critical fungal disease causes serious grain yield losses and mycotoxin contaminations. Currently, utilization of chemical fungicides is the main control method which has led to serious resistance. Development of novel synergist is an important strategy to reduce the usage of chemical fungicides and postpone the development of resistance, while natural components are interesting resources. In this study, the synergistic effect of Taxodium 'zhongshansha' essential oil (TZEO) was determined and the best synergistic ratio (SR) of 3.96 in laboratory which was observed when the weight ratio of TZEO and prothioconazole was 1 : 1 with the corresponding EC 50 (half maximal effective concentration) value of Fusarium graminearum was 0.280 mg L −1 . Subsequently, an increase of 6.31% on the control effect to FHB index in field test was observed when compared to the treatment with prothioconazole alone, though there was no significant difference between these treatments. Furthermore, we established an effective method to detect the mycotoxin contaminations in wheat grain with the limits of quantifications (LOQs) value of 5 µg kg −1 (DON, ZEN, 3-DON, and 15-DON) and 1 µg kg −1 (OTA) and the contents were less to the maximum residue limit (MRL) values. It was also shown that the application of 20% TZEO EW led to a 20% reduction in the use of prothioconazole, which was calculated based on the control effect values of 86.41% and 90.20% between the treatments of 30% prothioconazole OD (225 g a.i ha −1 , recommend dosage) and 30% prothioconazole OD (180 g a.i ha −1 ) + 20% TZEO EW (225 mL ha −1 ), significantly. The initial residue of prothioconazole and prothioconazole-desthio was increased in the treatment with TZEO, which may play an important role in the synergistic effect on FHB. Moreover, none of the treatments posed a prothioconazole residue risk in the wheat grain and the environment. In addition, the essential oil has no any negative influence on wheat growth, which was revealed by a study of the chlorophyll content. These results provide an important botanical synergist for use with prothioconazole to control Fusarium head blight, and in-depth study to the synergistic mechanism of this oil is necessary in our future research.

Asian soybean rust is a highly aggressive leaf-based disease triggered by the obligate biotrophic fungus which can cause up to 80% yield loss in soybean. The precise image segmentation of fungus can characterize fungal phenotype transitions during growth and help to discover new medicines and agricultural biocides using large-scale phenotypic screens. The improved Mask R-CNN method is proposed to accomplish the segmentation of densely distributed, overlapping and intersecting microimages. First, Res2net is utilized to layer the residual connections in a single residual block to replace the backbone of the original Mask R-CNN, which is then combined with FPG to enhance the feature extraction capability of the network model. Secondly, the loss function is optimized and the CIoU loss function is adopted as the loss function for boundary box regression prediction, which accelerates the convergence speed of the model and meets the accurate classification of high-density spore images. The experimental results show that the mAP for detection and segmentation, accuracy of the improved algorithm is improved by 6.4%, 12.3% and 2.2% respectively over the original Mask R-CNN algorithm. This method is more suitable for the segmentation of fungi images and provide an effective tool for large-scale phenotypic screens of plant fungal pathogens.

Virtual reality (VR) is a widely used tool in anesthesia education. By integrating multimedia and simulation technologies, it generates immersive environments that can serve as a controlled alternative to real-world training, thereby enhancing both theoretical knowledge and practical skills among anesthesia students. As a valuable, scientifically grounded, and feasible educational approach, VR helps foster student engagement and self-directed learning in anesthesiology. Additionally, it supports the development of more harmonious doctor–patient relationships and promotes standardized training and ethical practices in anesthesia. Given these advantages, the innovative application of VR in anesthesia teaching merits further exploration. In this article, an in-house VR system with independent intellectual property was developed at the author’s institution. This system is equipped with dedicated training modules designed for medical interns and graduate students.

The adult mammalian heart lacks the ability to regenerate after injury, contributing to heart failure. No current treatment reactivates heart muscle cell division to prevent this decline. We used a targeted, non-viral modified mRNA system to transiently boost expression of a regenerative enzyme, pyruvate kinase muscle isozyme M2, in heart muscle cells of juvenile and adult pig models after ischemic injury. In juvenile pigs treated one-week post-injury, we observed increased markers of cell division, secretion of protective factors, improved heart function, and reduced scarring two months later. In adult pigs treated immediately after injury, we saw improved heart contractility and less fibrosis one month later. These results show that targeted pyruvate kinase muscle isozyme M2 modified mRNA delivery can stimulate muscle regeneration and functional recovery in both young and adult pig hearts. This approach offers a promising strategy for repairing ischemic injury and preventing heart failure in humans. Ischemic heart disease causes irreversible damage due to poor cardiomyocyte renewal. Here, the authors show that PKM2 modRNA therapy in pigs drives cardiomyocyte proliferation, minimizes fibrosis, restores cardiac function and prevents heart failure after injury.