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Developing a facile strategy for the construction of vinylene-linked fully π -conjugated covalent organic frameworks (COFs) remains a huge challenge. Here, a versatile condition of Knoevenagel polycondensation for constructing vinylene-linked 2D COFs was explored. Three new examples of vinylene-linked 2D COFs ( BTH-1 , 2 , 3 ) containing benzobisthiazoles units as functional groups were successfully prepared under this versatile and mild condition. The electron-deficient benzobisthiazole units and cyano-vinylene linkages were both integrated into the π conjugated COFs skeleton and acted as acceptor moieties. Interestingly, we found the construction of a highly ordered and conjugated D-A system is favorable for photocatalytic activity. BTH-3 with benzotrithiophene as the donor with a strong D-A effect exhibited an attractive photocatalytic HER of 15.1 mmol h −1 g −1 under visible light irradiation. Synthesis of fully π -conjugated covalent organic frameworks (COFs) remains still challenging. Here, the authors propose a versatile synthesis method based on Knoevenagel polycondensation for the synthesis of vinylene-linked benzobisthiazole-based 2D COFs.

Applying reactive polymer materials sensitive to biological stimuli has recently attracted extensive research interest. The special physiological effects of reactive oxygen species (ROS) on tumors or inflammation and the application of ROS-responsive polymers as drug-delivery systems in organisms have attracted much attention. ROS is a vital disease signal molecule, and the unique accumulation of ROS-responsive polymers in pathological sites may enable ROS-responsive polymers to deliver payload (such as drugs, ROS-responsive prodrugs, and gene therapy fragments) in a targeted fashion. In this paper, the research progress of ROS-responsive polymers and their application in recent years were summarized and analyzed. The research progress of ROS-responsive polymers was reviewed from the perspective of nanoparticle drug delivery systems, multi-responsive delivery systems, and ROS-responsive hydrogels. It is expected that our work will help understand the future development trends in this field.

Traditional diagnostic methods for multifunction vehicle bus (MVB) faults often depend on feature extraction and classification, which typically require substantial expert experience and frequently yield low accuracy. To address this limitation, this paper introduces a MVB fault diagnosis method utilizing convolutional neural networks (CNNs). Initially, the method employs short-time Fourier transform (STFT) to convert the original vibration signals of MVB under various fault conditions into time-frequency images. Subsequently, a specific MVB fault diagnosis model, termed STCNN, is developed to conduct deep spatial feature learning on these two-dimensional signals. Fault classification is then achieved through a Softmax classifier. The model was tested on a MVB network dataset collected under diverse operating conditions on a test bench. The results demonstrated a fault detection accuracy of 99.68 , significantly surpassing other methods and highlighting its superior performance in fault diagnosis.

Background Tomato plant growth is frequently hampered by a high susceptibility to pests and diseases. Traditional chemical control causes a serious impact on both the environment and human health. Therefore, seeking environment-friendly and cost-effective green methods in agricultural production becomes crucial nowadays. Plant Growth Promoting Rhizobacteria (PGPR) can promote plant growth through biological activity. Their use is considered to be a promising sustainable approach for crop growth. Moreover, a vast number of biosynthetic gene clusters (BGCs) for secondary metabolite production are being revealed in PGPR, which helps to find potential anti-microbial activities for tomato disease control. Results We isolated 181 Bacillus -like strains from healthy tomato, rhizosphere soil, and tomato tissues. In vitro antagonistic assays revealed that 34 Bacillus strains have antimicrobial activity against Erwinia carotovora , Pseudomonas syringae; Rhizoctonia solani ; Botrytis cinerea ; Verticillium dahliae and Phytophthora infestans . The genomes of 10 Bacillus and Paenibacillus strains with good antagonistic activity were sequenced. Via genome mining approaches, we identified 120 BGCs encoding NRPs, PKs-NRPs, PKs, terpenes and bacteriocins, including known compounds such as fengycin, surfactin, bacillibactin, subtilin, etc. In addition, several novel BGCs were identified. We discovered that the NRPs and PKs-NRPs BGCs in Bacillus species are encoding highly conserved known compounds as well as various novel variants. Conclusions This study highlights the great number of varieties of BGCs in Bacillus strains. These findings pave the road for future usage of Bacillus strains as biocontrol agents for tomato disease control and are a resource arsenal for novel antimicrobial discovery.

Global warming is expected to have far‐reaching impacts on the frequency and intensity of extreme events, but the effects of anthropogenic warming on the emergence seasons of year‐maximum near‐surface wind speed (NSWS) remain poorly understood. We provide a comprehensive map of the changing emergence seasons of year‐maximum NSWS using Coupled Model Intercomparison Project Phase 6 projections. Our analysis reveals a rapid response of synoptic‐scale extreme NSWS to global warming, with consistent spatial patterns observed across various periods and warming scenarios. The most significant increase (∼16%) in the emergence season is projected to occur in December‐January‐February (DJF) over Mid‐high‐latitude Asia by the end of the 21st century. The study also anticipates changes in the emergence seasons of year‐maximum NSWS at a regional scale. These results deepen our understanding of the complex and interconnected nature of global climate change and underscore the need for concerted efforts in addressing this pressing challenge. Plain Language Summary Global warming is indisputably triggering changes in the world's weather systems, leading to more frequent and intense extreme weather events. However, it is unclear how anthropogenic warming affects the timing of the annual strongest near‐surface wind speed (NSWS). In this study, we used state‐of‐the‐art global climate models to create a comprehensive map illustrating these NSWS patterns of response to global warming. We discovered that these changes are consistent across various time periods (near to long term) and warming scenarios (low to high warming), revealing a robust relationship between extreme NSWS and global warming. The most significant change is observed during December‐January‐February in Mid‐high‐latitude Asia, with an increase of about 16% by the end of the 21st century. Our findings suggest that we can expect more year‐maximum NSWS occurs in different regions during specific seasons: December‐January‐February in North America and Asia, March‐April‐May in Africa, June‐July‐August in Asia and West Africa, and September‐October‐November in South America and Australia. These results offer valuable insights for guiding adaptation efforts even if ambitious climate actions manage to limit global warming at a lower level. Key Points Changing emergence seasons of the land year‐maximum near‐surface wind speed (NSWS) map is created There is a rapid response of emergence seasons of year‐maximum NSWS to anthropogenic warming The strongest increase (16%) in emergence season is projected to occur in December‐January‐February over Mid‐high‐latitude Asia

Hypertriglyceridemic pancreatitis (HTGP) is featured by higher incidence of complications and poor clinical outcomes. Gut microbiota dysbiosis is associated with pancreatic injury in HTGP and the mechanism remains unclear. Here, we observe lower diversity of gut microbiota and absence of beneficial bacteria in HTGP patients. In a fecal microbiota transplantation mouse model, the colonization of gut microbiota from HTGP patients recruits neutrophils and increases neutrophil extracellular traps (NETs) formation that exacerbates pancreatic injury and systemic inflammation. We find that decreased abundance of Bacteroides uniformis in gut microbiota impairs taurine production and increases IL-17 release in colon that triggers NETs formation. Moreover, Bacteroides uniformis or taurine inhibits the activation of NF-κB and IL-17 signaling pathways in neutrophils which harness NETs and alleviate pancreatic injury. Our findings establish roles of endogenous Bacteroides uniformis -derived metabolic and inflammatory products on suppressing NETs release, which provides potential insights of ameliorating HTGP through gut microbiota modulation. Given the association of gut microbiota dysbiosis with hypertriglyceridemic pancreatitis (HTGP), authors assess the gut microbial diversity of patients with HTGP, and provide immunological insight utilising a murine model.

Low temperature and cold damage seriously hinder the growth, development, and morphogenesis of cotton seedlings. However, the response mechanism of cotton seedlings under cold stress still lacks research. In this study, transcriptome sequencing, gas exchange parameters, and rapid chlorophyll fluorescence parameters were analyzed in leaves of cold-tolerant upland cotton variety “ZM36” under different temperature stress [25°C (T25, CK), 15°C (T15), 10°C (T10), and 4°C (T4)]. The results showed that the net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), PSII potential maximum photochemical efficiency (Fv/Fm), and performance index (PIabs) of cotton leaves significantly decreased, and the intercellular CO 2 concentration (Ci) and Fo/Fm significantly increased under cold stress. The transcriptome sequencing analysis showed that a total of 13,183 DEGs were involved in the response of cotton seedlings at each temperature point (T25, T15, T10, and T4), mainly involving five metabolic pathways—the phosphatidylinositol signaling system, photosynthesis, photosynthesis antenna protein, carbon fixation in photosynthetic organisms, and carotenoid synthesis. The 1,119 transcription factors were discovered among all the DEGs. These transcription factors involve 59 families, of which 15.8% of genes in the NAC family are upregulated. Through network regulatory analysis, the five candidate genes GhUVR8 ( GH_A05G3668 ), GhPLATZ ( GH_A09G2161 ), GhFAD4-1 ( GH_A01G0758 ), GhNFYA1 ( GH_A02G1336 ), and GhFAD4-2 ( GH_D01G0766 ) were identified in response to cold stress. Furthermore, suppressing the expression level of GhPLATZ by virus-induced gene silencing led to the reduction of low temperature resistance, implying GhPLATZ as a positive regulator of low temperature tolerance. The findings of the study revealed a piece of the complex response mechanism of the cold-tolerant variety “ZM36” to different cold stresses and excavated key candidate genes for low temperature response, which provided support for accelerating the selection and breeding of cotton varieties with low temperature tolerance.

Laser sensing and vision sensing smart canes can improve the convenience of travel for the visually impaired, but for the present, most of the system functions of laser sensing and vision sensing smart canes are still defective. Guide equipment and smart blind canes are introduced and classified first, and the smart blind canes based on vision sensing, laser sensing and laser vision sensing are investigated, respectively, and the research status of laser vision sensing smart blind canes is sorted out. The advantages and disadvantages of various laser vision sensing smart blind canes are summarized, especially the research development of laser vision fusion as the core of new smart canes. The future development prospects of laser vision sensing smart blind cane are overviewed, to boost the development of laser vision sensing smart blind cane, to provide safe and efficient travel guarantee for the visually impaired.

An effective fault diagnosis method of bearing is the key to predictive maintenance of modern industrial equipment. With the single use of equipment failure mechanism or operation of data, it is hard to resolve multiple complex variable working conditions, multiple types of fault and equipment malfunctions and failures related to knowledge and data. In order to solve these problems, a fault diagnosis method based on the fusion of deep learning with a knowledge graph is proposed in this paper. Firstly, the knowledge rules of bearing data is used for entity extraction. Next, the multiscale optimized convolutional neural network (MOCNN) proposed in this paper is used for fault classification to achieve relationship extraction. Finally, the fault diagnosis graph of the bearing is constructed for fault-assisted decision-making as well as the detailed display of fault information. According to experiment analysis, the fault diagnosis model based on MOCNN proposed in this paper, which integrates the end-to-end convolutional neural network and the attention mechanism, still achieves an accuracy of 97.86% under the data set of 160 types of faults. Compared with the deep learning models such as Resnet and Inception in the noise environment of multiple working conditions and variable working conditions, the model proposed in this paper not only shows a faster convergence speed and stable performance, but also a higher accuracy in evaluation indicators, which is beneficial to practical use.

Understanding the link between future changes in East Asian summer monsoon (EASM) and global warming levels is of great importance for regional climate change adaptation and mitigation in East Asia. Here, we analyze the projected changes in EASM circulation and precipitation under different warming levels from 1.5 to 5 °C above the preindustrial global mean temperature, using large‐ensemble simulations conducted with Canadian Earth System Model version 2. We find that the model projects enhanced monsoon circulation and precipitation with global warming. The 850‐hPa meridional winds, precipitation, and 500‐hPa vertical ascending motion will be enhanced nonlinearly, while the total column precipitable water will increase quasi‐linearly. The increase in precipitable water in the wet EASM region is only slightly greater than global average but the increase in precipitation is much greater than global one, with enhanced 500‐hPa vertical ascending motion contrary to global mean. The increased low‐level land‐sea thermal contrast leads to the enhanced EASM meridional circulation and thus bring a large amount of moisture into Eastern China, providing favorable conditions for additional increase in precipitation. A simplified moisture budget analysis  shows that the dynamic component related to strengthening monsoon circulation plays dominant role in the increase in EASM precipitation when the global temperature increases by more than approximately 2 °C, while the thermodynamic component caused by increased water vapor is important when the warming is smaller. Plain Language Summary Changes in East Asian summer monsoon (EASM) circulation and precipitation have great impacts on human society, agriculture and energy in East Asia. Previous studies rarely investigated EASM circulation and precipitation changes under specific global mean temperature increases, such as 1.5 to 5 °C of warming. Here, we focus on EASM circulation and precipitation changes linked with different global warming levels. Four EASM metrics (850‐hPa meridional wind, precipitation, precipitable water, and 500‐hPa vertical velocity) are examined to reflect EASM system changes based on Canadian Earth System Model version 2 large‐ensemble runs. We find that EASM low‐level meridional wind, precipitation, and midlevel vertical ascending motion will be enhanced nonlinearly with warming, while precipitable water will increase quasi‐linearly with warming. The increase in EASM precipitation is greater than global average, accompanied by increasing vertical ascending motion and strengthened southerly winds. When global mean near‐surface air temperature increases by more than 2 °C, the dynamic component plays dominant role in the increased EASM precipitation, while the thermodynamic factor plays a secondary role. These results provide useful information for developing strategies for climate change policy in East Asia. Key Points East Asian summer monsoon (EASM) circulation and precipitation are projected to  increase nonlinearly with warming The EASM circulation is projected to enhance mainly driven by increased thermal contrasts in the lower troposphere rather than in upper layer Both dynamic and thermodynamic components contribute to precipitation increase but dynamic change is more important at high warming level