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Na3(VOPO4)2F (NVOPF) has emerged as a promising cathode candidate for commercial Na-ion batteries, ascribed to its elevated theoretical energy density and robust structure during the extraction/insertion of two Na+ ions. However, the intrinsic poor electronic conductivity and unscalable materials-preparation technologies make it unexpected to stand out in large-scale energy storage systems. In this study, a spray-drying process technology is implemented to synthesize Na3(VOPO4)2F@carbon nanotubes (NVOPF@CNTs) composite through the reduction of V5+ driven by methanol at room temperature, in which the shortened Na-ion transfer path and the rapid electron mobility are facilitated by the CNTs. The resulting NVOPF@CNTs electrode exhibits exceptional capabilities, including a high discharge capacity (122.1 mA h g−1 at 1 C= 120 mA h g−1), outstanding rate performance (103.1 mA h g−1 at 100 C), and an extended lifespan (71.8 % capacity retention after 6000 cycles at 20 C). Additionally, the Na3(VOPO4)2F//NaTi2(PO4)3 full battery system demonstrates impressive high-power output capabilities (93.3 mA h g−1, 20 C), versatile current switching adaptability, and robust cycling performance (75.3 % of 98.5 mA h g−1 for the initial capacity after 3000 cycles). The study underscores the potential of improving the preparation of vanadium-based phosphate materials to enhance the practical application of Na-ion batteries.

Abstract Application of aqueous zinc metal batteries (AZMBs) in large‐scale new energy systems (NESs) is challenging owing to the growth of dendrites and frequent side reactions. Here, this study proposes the use of Panthenol (PB) as an electrolyte additive in AZMBs to achieve highly reversible zinc plating/stripping processes and suppressed side reactions. The PB structure is rich in polar groups, which led to the formation of a strong hydrogen bonding network of PB−H2O, while the PB molecule also builds a multi‐coordination solvated structure, which inhibits water activity and reduces side reactions. Simultaneously, PB and OTF− decomposition, in situ formation of SEI layer with stable organic‐inorganic hybrid ZnF2‐ZnS interphase on Zn anode electrode, can inhibit water penetration into Zn and homogenize the Zn2+ plating. The effect of the thickness of the SEI layer on the deposition of Zn ions in the battery is also investigated. Hence, this comprehensive regulation strategy contributes to a long cycle life of 2300 h for Zn//Zn cells assembled with electrolytes containing PB additives. And the assembled Zn//NH4V4O10 pouch cells with homemade modules exhibit stable cycling performance and high capacity retention. Therefore, the proposed electrolyte modification strategy provides new ideas for AZMBs and other metal batteries.

The ice conditions in Arctic waters are complex and variable, requiring ships to dynamically adjust their routes to ensure safe and efficient navigation. Traditional dynamic path planning algorithms struggle to address the extensive variability of Arctic ice conditions. To tackle this issue, this paper improves the D* Lite algorithm by leveraging the gradual and convergent nature of Arctic ice condition changes. The original algorithm’s local update and path extraction rules are modified to prevent chain updates triggered by minor localized changes, thereby reducing the frequency of updates in non-critical areas. By simulating dynamic route planning for ships in Arctic waters during both the freezing and melting periods, the improved D* Lite algorithm was compared with the original D* Lite algorithm and a global update algorithm in terms of voyage distance, risk coefficient, planning time, and the number of node updates. The computational results demonstrate that the improved D* Lite algorithm achieves planning results very similar to those of the original D* Lite algorithm and the global update algorithm at the lowest update cost, significantly enhancing the safety and efficiency of dynamic route planning for ships in Arctic waters.

Ship fuel consumption plays a crucial role not only in understanding ships’ energy efficiency but also in gaining insights into their emissions. However, enhancing the accuracy of these predictions poses significant challenges due to data limitations and the methods employed. Due to these factors, such as data variability and equipment characteristics, ship fuel consumption exhibits certain fluctuations under specific conditions. Previous fuel consumption prediction methods primarily generate a single specific value, making it difficult to capture the volatility of and variability in fuel consumption. To overcome this limitation, this paper proposes a novel method that integrates Gaussian process prediction with quantile regression theory to perform interval predictions of ship fuel consumption, providing a range of possible outcomes. Through comparative analyses with traditional methods, the possibility of using the method is verified and its results are validated. The results indicate the following: (1) at a 95% confidence level, the proposed method achieves a prediction interval coverage probability of 0.98 and a prediction interval normalized average width of 0.123, which are significantly better than those of the existing backpropagation neural network (BPNN) and gradient boosting decision tree (GBDT) quantile regression models; (2) the prediction accuracy of the proposed method is 92% for point forecasts; and (3) the proposed method is applicable to main datasets, including both noon report and sensor datasets. These findings provide valuable insights into interval predictions of ship fuel consumption and highlight their potential applications in related fields, emphasizing the importance of accurate interval predictions in intelligent energy efficiency optimization.

With the development and application of artificial intelligence (AI) in the shipping industry, using AI to replace traditional draft survey methods in bulk carriers can significantly reduce manpower, lower the risks associated with visual observations, improve measurement accuracy, and minimize the impact of human subjective factors. Ultimately, the integration of software and hardware technologies will replace human visual observations with automated draft measurement calculations. A similar anti-fluctuation device described in this article has been used in ship draft observation based on AI-assisted proving, which can ease the fluctuation of the wave inside the pipe. Observers can directly read the water surface inside the pipe and compare it to the ship’s draft mark to obtain the final draft, effectively improving draft observation accuracy. However, some surveyors refuse to accept the readings obtained from this device, citing a lack of theoretical basis or the absence of accreditation from relevant technical authorities, leading to the rejection of results. To address these issues, this paper integrates wave energy attenuation theory with PaddlePaddle-OCR recognition to further validate the anti-fluctuation device for accurate ship draft observation. The experimental results are as follows: first, the pipe effectively suppresses the amplitude of external water surface fluctuations by 75%, explaining the fundamental theory that wave heights within the anti-fluctuation device are consistent with external swell heights. When taking a draft measurement, the system dynamically adjusts the position of the main tube in response to the ship’s movements, maintaining the stability of the measurement section and significantly reducing the difficulty of observations. Due to the reduction in fluctuation amplitude, there is a noticeable improvement in observation accuracy.

Abstract Objective This study aimed to explore the efficacy and safety of combining epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) with ZiLongJin Tablet (ZLJT) in delaying acquired resistance in advanced EGFR-mutant lung adenocarcinoma (LUAD) patients. Furthermore, we employed network pharmacology and molecular docking techniques to investigate the underlying mechanisms. Methods A retrospective comparative study was conducted on stage IIIc/IV LUAD patients treated with EGFR-TKIs alone or in combination with ZLJT at the Second Affiliated Hospital of the Air Force Medical University between January 1, 2017, and May 1, 2023. The study evaluated the onset of TKI resistance, adverse reaction rates, safety indicators (such as aspartate aminotransferase, alanine aminotransferase, and creatinine), and inflammatory markers (neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio) to investigate the impact of EGFR-TKI combined with ZLJT on acquired resistance and prognostic indicators. Additionally, we utilized the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine, PubChem, UniProt, and Swiss Target Prediction databases to identify the active ingredients and targets of ZLJT. We obtained differentially expressed genes related to EGFR-TKI sensitivity and resistance from the Gene Expression Omnibus database using the GSE34228 dataset, which included sensitive (n = 26) and resistant (n = 26) PC9 cell lines. The "limma" package in R software was employed to detect DEGs. Based on this, we constructed a protein‒protein interaction network, performed gene ontology and KEGG enrichment analyses, and conducted pathway network analysis to elucidate the correlation between the active ingredients in ZLJT and signaling pathways. Finally, molecular docking was performed using AutoDockVina, PYMOL 2.2.0, and Discovery Studio Client v19.1.0 software to simulate spatial and energy matching during the recognition process between predicted targets and their corresponding compounds. Results (1) A total of 89 patients were included, with 40 patients in the EGFR-TKI combined with ZLJT group (combination group) and 49 patients in the EGFR-TKI alone group (monotherapy group). The baseline characteristics of the two groups were comparable. There was a significant difference in the onset of resistance between the combination group and the monotherapy group (P 0.05). There were no statistically significant differences in serum AST, ALT, CREA, TBIL, ALB and BUN levels between the two groups after medication (P > 0.05). (3) Regarding inflammatory markers, there were no statistically significant differences in the changes in neutrophil-to-lymphocyte Ratio(NLR) and Platelet-to-lymphocyte Ratio(PLR) values before and after treatment between the two groups (P > 0.05). (4) Network pharmacology analysis identified 112 active ingredients and 290 target genes for ZLJT. From the GEO database, 2035 differentially expressed genes related to resistant LUAD were selected, and 39 target genes were obtained by taking the intersection. A "ZLJT-compound-target-disease" network was successfully constructed using Cytoscape 3.7.0. GO enrichment analysis revealed that ZLJT mainly affected biological processes such as adenylate cyclase-modulating G protein-coupled receptor. In terms of cellular components, ZLJT was associated with the cell projection membrane. The molecular function primarily focused on protein heterodimerization activity. KEGG enrichment analysis indicated that ZLJT exerted its antitumor and anti-drug resistance effects through pathways such as the PI3K-Akt pathway. Molecular docking showed that luteolin had good binding activity with FOS (-9.8 kJ/mol), as did tanshinone IIA with FOS (-9.8 kJ/mol) and quercetin with FOS (-8.7 kJ/mol). Conclusion ZLJT has potential antitumor progression effects. For patients with EGFR gene-mutated non-small cell LUAD, combining ZLJT with EGFR-TKI treatment can delay the occurrence of acquired resistance. The underlying mechanisms may involve altering signal transduction pathways, blocking the tumor cell cycle, inhibiting tumor activity, enhancing cellular vitality, and improving the bioavailability of combination therapy. The combination of EGFR-TKI and ZLJT represents an effective approach for the treatment of tumors using both Chinese and Western medicine.

Bismuth has garnered significant interest as an anode material for magnesium batteries (MBs) because of its high volumetric specific capacity and low working potential. Nonetheless, the limited cycling performance (≤100 cycles) limits the practical application of Bi as anode for MBs. Therefore, the improvement of Bi cycling performance is of great significance to the development of MBs and is also full of challenges. Here, Bi nanoparticles encapsulated in nitrogen-doped carbon with single-atom Bi embedded (Bi@NC) are prepared and reported as an anode material for MBs. Bi@NC demonstrates impressive performance, with a high discharge capacity of 347.5 mAh g−1 and good rate capability (206.4 mAh g−1@500 mA g−1) in a fluoride alkyl magnesium salt electrolyte. In addition, Bi@NC exhibits exceptional long-term stability, enduring 400 cycles at 500 mA g−1. To the best of our knowledge, among reported Bi and Bi-based compounds for MBs, Bi@NC exhibits the longest cycle life in this work. The magnesium storage mechanism of Bi@NC is deeply studied through X-ray diffraction, transmission electron microscopy and X-ray photoelectron spectroscopy. This work provides some guidance for further improving the cycling performance of other alloy anodes in MBs.

Efficient and rapid deployment of maritime search and rescue(MSAR) resources is a prerequisite for maritime emergency search and rescue, in order to improve the efficiency and accuracy of MSAR. This paper proposes an integrated approach for emergency resource allocation. The approach encompasses three main steps: identifying accident black spots, assessing high-risk areas, and optimizing the outcomes through a synergistic combination of an optimization algorithm and reinforcement learning. In the initial step, the paper introduces the iterative self-organizing data analysis technology (ISODATA) for identifying accident spots at sea. A comparative analysis is conducted with other clustering algorithms, highlighting the superiority of ISODATA in effectively conducting dense clustering. This can effectively carry out dense clustering, instead of the situation where the data spots are too dispersed or obvious anomalies that affect the clustering. Furthermore, this approach incorporates entropy weighting to reassess the significance of accident spots by considering both the distance and the frequency of accidents. This integrated approach enhances the allocation of search and rescue forces, ensuring more efficient resource utilization. To address the MSAR vessel scheduling problem at sea, the paper employs the non-dominated sorting genetic algorithm II combined with reinforcement learning (NSGAII-RL). Comparative evaluations against other optimization algorithms reveal that the proposed approach can save a minimum of 7% in search and rescue time, leading to enhanced stability and improved efficiency in large-scale MSAR operations. Overall, the integrated approach presented in this paper offers a robust solution to the ship scheduling problem in maritime search and rescue operations. Its effectiveness is demonstrated through improved resource allocation, enhanced timeliness, and higher efficiency in responding to maritime accidents.

Rechargeable aqueous zinc metal battery has been one of the next‐generation energy storage systems with a promising future due to the advantages of aqueous electrolyte and metallic zinc anode. Among many cathode materials, vanadium‐based materials with considerable specific capacity, adjustable crystal structure, and multiple valence states are very promising cathodes, but the electrochemical performance of vanadium‐based zinc metal batteries faces severe challenges such as the limited and declining capacity and sluggish ion/e− transport kinetics process. Herein, taking VO2 as an example, the crystal structure and energy storage mechanism of VO2 cathode are briefly introduced. The challenges of aqueous Zn/VO2 battery are analyzed in depth. Significantly, the current advanced modification strategies for aqueous Zn/VO2 battery are summarized and discussed in detail, and the future development is also prospected. This article can provide some significant references for the development of aqueous Zn/VO2 battery and the guiding significance for other metal ion battery.