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Unmanned underwater vehicles are typically deployed in deep sea environments, which present unique working conditions. Lithium-ion power batteries are crucial for powering underwater vehicles, and it is vital to accurately predict their remaining useful life (RUL) to maintain system reliability and safety. We propose a residual life prediction model framework based on complete ensemble empirical mode decomposition with an adaptive noise-temporal convolutional net (CEEMDAN-TCN), which utilizes dilated causal convolutions to improve the model’s ability to capture local capacity regeneration and enhance the overall prediction accuracy. CEEMDAN is employed to denoise the data and prevent RUL prediction errors caused by local regeneration, and feature expansion is utilized to extend the temporal dimension of the original data. The NASA and CALCE battery capacity datasets are used as input to train the network framework. The output is the current predicted residual capacity, which is compared with the real residual battery capacity. The MAE, RMSE and RE are used as the evaluation indexes of the RUL prediction performance. The proposed network model is verified on the NASA and CACLE datasets. The evaluation results show that our method has better life prediction performance. At the same time, it is proved that both feature expansion and modal decomposition can improve the generalization ability of the model, which is very useful in industrial scenarios.

Polymetallic enrichment layers are commonly found at the base of the Lower Cambrian and extensively distributed across the Upper Yangtze Platform, yet their genetic models remain controversial. This study systematically collected samples from a typical section in the southeastern Chongqing region for mineral, organic, and inorganic analyses. It investigates the relationship between the abundance of various trace metal elements and organic matter at the base of the Niutitang Formation, as well as the vertical distribution characteristics of organic carbon isotopes and organic matter features. The results indicate that the Niutitang Formation shale exhibits a distinct three-part structure from bottom to top. Various metal elements are enriched in the lower interval, showing a close correlation between the abundance of polymetallic elements and the carbon isotopes of shale organic matter. The middle interval contains the highest TOC value and the lowest Ti/Al ratio, while the upper interval shows a significant decrease in organic matter abundance, with a clear positive correlation between the excess silicon content and Ti/Al ratio. Additionally, the mixing effect of deep-sea upwelling is the primary control on the formation of polymetallic enrichment layers in the lower interval, followed by the adsorption of organic matter under anoxic conditions. The sedimentary environment of the upper interval of the Niutitang Formation trends toward oxidation, with paleoclimate shifting toward colder and drier conditions, exhibiting aeolian sedimentary features that are unfavorable for the enrichment of trace metal elements. Consequently, upwelling is a key factor in the enrichment and mineralization of trace metal elements at the base of the Lower Cambrian in the Upper Yangtze region. [ABSTRACT FROM AUTHOR]

Standard-essential patents (SEPs) are an important technological resource for firms in the telecommunication industry. The utilisation of technological topic analysis to reveal the global development dynamics of SEPs has significant theoretical and practical implications. First, this study defines the phrase extraction rules and constructs a phrase importance evaluation model to extract key technical phrases in the patent text. Second, the extracted key phrases are used as input for the Latent Dirichlet Allocation (LDA) model, and the relative independence (RI) model is proposed to determine the optimal number of topics based on two dimensions of coherence and similarity. Finally, the technological topic analysis based on the improved LDA model is performed on 30,154 texts of declared 5G SEPs. The results show that (1) the RI model can better identify the optimal number of topics for the LDA model; (2) 23 key technologies and four hot spots in 5G are identified based on the improved LDA model; (3) different firms have different technological layouts, and the diversification trend of technology development appears; and (4) the forecasting results also reveal the dynamics of emerging and declining technical areas in the 5G industry. [ABSTRACT FROM AUTHOR]

Neurological diseases are expected to become the leading cause of death in the next decade. Although little is known about it, the interaction between oxidative stress and inflammation is harmful to the nervous system. To find an advanced tool for neural genetics, mouse haploid neural stem cells (haNSCs) from the somite of chimeric mouse embryos at E8.5 is established. The haNSCs present a haploid neural progenitor identity for long‐term culture, promising to robustly differentiate into neural subtypes and being able to form cerebral organoids efficiently. Thereafter, haNSC mutants via a high‐throughput approach and screened targets of oxidative stress is generated using the specific mutant library. Deletion of Nfkbia (the top hit among the insertion mutants) reduces damage from reactive oxygen species (ROS) in NSCs exposed to H2O2. Transcriptome analysis revealed that Atp2b4 is upregulated significantly in Nfkbia‐null NSCs and is probably responsible for the observed resistance. Additionally, overexpression of Atp2b4 itself can increase the survival of NSCs in the presence of H2O2, suggesting that Atp2b4 is closely involved in this resistance. Herein, a powerful haploid system is presented to study functional genetics in neural lineages, shedding light on the screening of critical genes and drugs for neurological diseases. [ABSTRACT FROM AUTHOR]

Aiming at the trend of denim yarn and the deficiencies of the current dyeing, characteristics of denim colored yarn were simulated and a multi-colored yarn by vortex spinning was developed. Traditional ring spinning and air-jet vortex core-spun technology were combined. Short staple fibers were taken as core yarn instead of filament to achieve the color of core yarn, the thickness and twist direction could be adjusted. The twisting stress of the fibers was counteracted by combining the core yarn with the opposite twist direction of the outer layer fibers and selecting the corresponding twist coefficients during the spinning process. The use of uneven wrapping effect of the air-jet vortex spinning could highlight the unique exposed core effect, inner and outer layers could be used in different colors and ratios. The multi-colored yarn by vortex spinning coud be used for knitting and weaving, the rich color variation of multi-colored yarn by vortex spinning was suitable for the production of dye-free denim production. [ABSTRACT FROM AUTHOR]