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● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality. ● Improved model quickly converges to the global optimal fitness and remains stable. ● The prediction accuracy of water quality parameters is significantly improved. Water quality prediction is vital for solving water pollution and protecting the water environment. In terms of the characteristics of nonlinearity, instability, and randomness of water quality parameters, a short-term water quality prediction model was proposed based on variational mode decomposition (VMD) and improved grasshopper optimization algorithm (IGOA), so as to optimize long short-term memory neural network (LSTM). First, VMD was adopted to decompose the water quality data into a series of relatively stable components, with the aim to reduce the instability of the original data and increase the predictability, then each component was input into the IGOA-LSTM model for prediction. Finally, each component was added to obtain the predicted values. In this study, the monitoring data from Dayangzhou Station and Shengmi Station of the Ganjiang River was used for training and prediction. The experimental results showed that the prediction accuracy of the VMD-IGOA-LSTM model proposed was higher than that of the integrated model of Ensemble Empirical Mode Decomposition (EEMD), the integrated model of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Autoregressive Network with Exogenous Inputs (NARX), Recurrent Neural Network (RNN), as well as other models, showing better performance in short-term prediction. The current study will provide a reliable solution for water quality prediction studies in other areas.

With the low redox potential of −3.04 V (vs SHE) and ultrahigh theoretical capacity of 3862 mAh g−1, lithium metal has been considered as promising anode material. However, lithium metal battery has ever suffered a trough in the past few decades due to its safety issues. Over the years, the limited energy density of the lithium‐ion battery cannot meet the growing demands of the advanced energy storage devices. Therefore, lithium metal anodes receive renewed attention, which have the potential to achieve high‐energy batteries. In this review, the history of the lithium anode is reviewed first. Then the failure mechanism of the lithium anode is analyzed, including dendrite, dead lithium, corrosion, and volume expansion of the lithium anode. Further, the strategies to alleviate the lithium anode issues in recent years are discussed emphatically. Eventually, remaining challenges of these strategies and possible research directions of lithium‐anode modification are presented to inspire innovation of lithium anode. The improvement of lithium anodes plays a great role in developing lithium metal batteries with high energy density. With the aim of enlighting the future directions of the researches on lithium anodes, the challenges and progress in the field of lithium anodes in recent years are presented.

Reducing the silver film to 10 nm theoretically allows higher transparency but in practice leads to degraded transparency and electrical conductivity because the ultrathin film tends to be discontinuous. Herein, we developed a thinning-back process to address this dilemma, in which silver film is first deposited to a larger thickness with high continuity and then thinned back to a reduced thickness with an ultrasmooth surface, both implemented by a flood ion beam. Contributed by the shallow implantation of silver atoms into the substrate during deposition, the thinness of silver films down to 4.5 nm can be obtained, thinner than ever before. The atomic-level surface smooth permits excellent visible transparency, electrical conductivity, and the lowest haze among all existing transparent conductors. Moreover, the ultrathin silver film exhibits the unique robustness of mechanical flexibility. Therefore, the ion-beam thinning-back process presents a promising solution towards the excellent transparent conductor for flexible optoelectronic devices. The use of thin silver films with nanometric thickness for optoelectronic devices is essential for high transparency, flexibility, and electrical properties. Ma et al. report a thinning-back process with a flood ion beam, to further reduce film thickness down to 4.5 nm.

The process of plug tray seedling transplanting is a crucial step in protected agriculture production. Due to issues such as high labor intensity, poor consistency of work quality, and low efficiency, the application of automated transplanting machines has provided a solution to these issues. For the diversity of transplanting operations, various mechanical structures and technological applications have been developed for automated transplanting equipment. Therefore, this paper provides systematic research of current studies on the key transplanter technologies. Firstly, through an analysis of the types of transplanting operations, the technical requirements of automated transplanting equipment for different operation types are elucidated. Subsequently, the key technologies applied in transplanting machines are discussed from the perspectives of substrate physical characteristics, end effectors, integration of multiple end effectors, vision systems, and transplanting path planning. Moreover, an analysis is conducted on the advantages, disadvantages, and application scenarios of different research methods for each key technology. Lastly, the existing problems and technical difficulties of the transplanting machine are summarized, and future research directions are discussed. This analysis provides a valuable reference for further research and development in the field of transplanting machines for plug tray seedlings.

Background Salinity, alkalinity, and drought stress are the main abiotic stress factors affecting plant growth and development. Sophora alopecuroides L., a perennial leguminous herb in the genus Sophora , is a highly salt-tolerant sand-fixing pioneer species distributed mostly in Western Asia and northwestern China. Few studies have assessed responses to abiotic stress in S. alopecuroides . The transcriptome of the genes that confer stress-tolerance in this species has not previously been sequenced. Our objective was to sequence and analyze this transcriptome. Results Twelve cDNA libraries were constructed in triplicate from mRNA obtained from Sophora alopecuroides for the control and salt, alkali, and drought treatments. Using de novo assembly, 902,812 assembled unigenes were generated, with an average length of 294 bp. Based on similarity searches, 545,615 (60.43%) had at least one significant match in the Nr, Nt, Pfam, KOG/COG, Swiss-Prot, and GO databases. In addition, 1673 differentially expressed genes (DEGs) were obtained from the salt treatment, 8142 from the alkali treatment, and 17,479 from the drought treatment. A total of 11,936 transcription factor genes from 82 transcription factor families were functionally annotated under salt, alkali, and drought stress, these include MYB , bZIP , NAC and WRKY family members. DEGs were involved in the hormone signal transduction pathway, biosynthesis of secondary metabolites and antioxidant enzymes; this suggests that these pathways or processes may be involved in tolerance towards salt, alkali, and drought stress in S. alopecuroides . Conclusion Our study first reported transcriptome reference sequence data in Sophora alopecuroides, a non-model plant without a reference genome. We determined digital expression profile and discovered a broad survey of unigenes associated with salt, alkali, and drought stress which provide genomic resources available for Sophora alopecuroides .

Irregular text recognition of natural scene is a challenging task due to large span of character angles and morphological diversity of a word. Recent work first rectifies curved word region, and then employ sequence algorithm to complete the recognition task. However, this strategy largely depends on rectification quality of the text region, and cannot be applied to large difference between tilt angles of character. In this work, a novel anchor-free network structure of rotating character detection is proposed, which includes multiple sub-angle domain branch networks, and the corresponding branch network can be selected adaptively according to character tilt angle. Meanwhile, a curvature Adaptive Text linking method is proposed to connect the discrete strings detected on the two-dimensional plane into words according to people’s habits. We achieved state-of-the-art performance on two irregular texts (TotalText, CTW1500), outperforming state-of-the-art by 2.4% and 2.7%, respectively. The experimental results demonstrate the effectiveness of the proposed algorithm.

Irregular text recognition of natural scene is a challenging task due to large span of character angles and morphological diversity of a word. Recent work first rectifies curved word region, and then employ sequence algorithm to complete the recognition task. However, this strategy largely depends on rectification quality of the text region, and cannot be applied to large difference between tilt angles of character. In this work, a novel anchor-free network structure of rotating character detection is proposed, which includes multiple sub-angle domain branch networks, and the corresponding branch network can be selected adaptively according to character tilt angle. Meanwhile, a curvature Adaptive Text linking method is proposed to connect the discrete strings detected on the two-dimensional plane into words according to people’s habits. We achieved state-of-the-art performance on two irregular texts (TotalText, CTW1500), outperforming state-of-the-art by 2.4% and 2.7%, respectively. The experimental results demonstrate the effectiveness of the proposed algorithm.

The field of radiation-induced cardiac damage (RIHD) is garnering increasing attention. The application of advanced radiotherapy reduces the cardiac radiation dose. Still, challenges remain in the uneven dose distribution, the different sensitivity among cardiac substructures (CSs), and the delineation of target areas within these substructures. This article encompasses cardiac substructures, including atria and ventricles, coronary arteries, pulmonary vasculars and superior vena cava (SVC), cardiac conduction system, heart valves and heart base. This review will provide better understanding of RIHD as it firstly summarizes dose limitation of CSs, as well as the risk of cardiac toxicities and its impact on survival following the comprehensive search.

Objective This study aims to conduct an in-depth genomic analysis of a carbapenem-resistant Proteus mirabilis strain to uncover the distribution and mechanisms of its resistance genes. Methods The research primarily utilized whole-genome sequencing to analyze the genome of the Proteus mirabilis strain. Additionally, antibiotic susceptibility tests were conducted to evaluate the strain’s sensitivity to various antibiotics, and related case information was collected to analyze the clinical distribution characteristics of the resistant strain. Results Study on bacterial strain WF3430 from a tetanus and pneumonia patient reveals resistance to multiple antibiotics due to extensive use. Whole-genome sequencing exposes a 4,045,480 bp chromosome carrying 29 antibiotic resistance genes. Two multidrug-resistant (MDR) gene regions, resembling Tn 6577 and Tn 6589 , were identified (MDR Region 1: 64.83 Kb, MDR Region 2: 85.64 Kbp). These regions, consist of integrative and conjugative elements (ICE) structures, highlight the intricate multidrug resistance in clinical settings. Conclusion This study found that a CR-PMI strain exhibits a unique mechanism for acquiring antimicrobial resistance genes, such as bla NDM−1 , located on the chromosome instead of plasmids. According to the results, there is increasing complexity in the mechanisms of horizontal transmission of resistance, necessitating a comprehensive understanding and implementation of targeted control measures in both hospital and community settings.

Given the potential risks of unknown and emerging infectious respiratory diseases, prioritizing an appropriate ventilation strategy is crucial for controlling aerosol droplet dispersion and mitigating cross-infection in hospital wards during post-epidemic periods. This study optimizes the layout of supply diffusers and exhaust outlets in a typical two-bed ward, employing a downward-supply and bottom-exhaust airflow pattern. Beyond ventilation, implementing strict infection control protocols is crucial, including regular disinfection of high-touch surfaces. CO2 serves as a surrogate for exhaled gaseous pollutants, and a species transport model is utilized to investigate the airflow field under various configurations of vents. Comparisons of CO2 concentrations at the respiratory planes of patients, accompanying staff (AS), and healthcare workers (HCWs) across nine cases are reported. A discrete phase model (DPM) is employed to simulate the spatial-temporal dispersion characteristics of four different particle sizes (3 μm, 12 μm, 20 μm, and 45 μm) exhaled by the infected patient (Patient 1) over 300 s. Ventilation effectiveness is evaluated using indicators like contaminant removal efficiency (CRE), suspension rate (SR), deposition rate (DER), and removal rate (RR) of aerosol droplets. The results indicate that Case 9 exhibits the highest CRE across all respiratory planes, indicating the most effective removal of gaseous pollutants. Case 2 shows the highest RR at 50.3%, followed by Case 1 with 40.4%. However, in Case 2, a significant portion of aerosol droplets diffuse towards Patient 2, potentially increasing the cross-infection risk. Balancing patient safety with pollutant removal efficacy, Case 1 performs best in the removal of aerosol droplets. The findings offer novel insights for the practical implementation of ventilation strategies in hospital wards, ensuring personnel health and safety during the post-epidemic period.