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The aluminum alloy performance gradient plate was prepared by friction stir joining. Analysis results of the macro morphology, microstructure, and hardness of the aluminum alloy performance gradient plate prepared under various parameters show that when the feed speed of the stirring tool is 250 mm/min, the downward pressure of the stirring tool is 6.6 mm, and the rotation speed of the stirring tool changes from 200 rpm to 800 rpm. The macroscopic morphology of the aluminum alloy gradient plates prepared by the method first changed from burr to smooth, and vice versa. There is a different cross-section morphology of the prepared aluminum alloy gradient plates, however, the aluminum alloy plates are stirred and involved with each other, and the grains of the prepared plates are refined. The hardness of the upper and lower surfaces of the aluminum alloy gradient sheet decreases, whereas that of the upper surface of the side increases, and that of the middle and bottom sides also decreases. However, the hardness of the middle side of the sheet prepared with the rotation speed of the stirring tool at 800 rpm increases, but that of the bottom side still decreases. Obtained through analysis that the performance of the aluminum alloy gradient sheet prepared at the stirring tool rotation speed of 500 rpm increases in equal proportion to achieve a good performance gradient change.

Acupuncture and moxibustion are increasingly recognized as effective and safe modalities for the management of neurological disorders, garnering substantial interest from both neurologists and patients. This study systematically reviews literature from major databases spanning the years 2012 to 2024 to construct a comprehensive dataset on the acupuncture treatment of neurological diseases. The data were meticulously compiled through a detailed search and screening process, adhering to established principles for data extraction and segmentation. The resultant acupuncture treatment database served as the foundation for subsequent analyses utilizing the association rule algorithm. This advanced computational approach facilitated a deep investigation into the relationships among acupuncture points used in neurological treatments. By employing a complex network analysis, the study identified the optimal distribution of acupuncture points, and cluster analysis further categorized these points for diverse neurological conditions. Our findings indicate that a total of 206 acupuncture points are prevalently used in neurological therapies. The regions of the head, face, and neck are most frequently targeted, with these areas collectively accounting for 1,048 instances of point utilization. Specifically, 124 unique acupuncture points have been identified as particularly effective for neurological applications. The association pairs “Yangbai-Zusanli” and “Sanyinjiao-Zusanli” demonstrated the highest levels of support and confidence, at 96.29% and 48.59% respectively. The core constellation of acupuncture points, comprising “Zhuzhu,” “Yangbai,” “Sizhukong,” “Yuyin,” “Sibai,” “Zusanli,” and “Baihui,” encapsulates the strategic focal areas for enhancing therapeutic outcomes in neurology. The integration of data mining techniques in this research not only underscores the specific patterns in the distribution of acupuncture points but also suggests a potential framework for augmenting the efficacy of treatments for neurological conditions. Through such analytical methodologies, the study contributes to a nuanced understanding of acupuncture’s role in neurology, paving the way for targeted and optimized therapeutic strategies.

Specimen data play a crucial role in geographical distribution research. In this study, the collection information of liverwort specimens in China was compiled and analyzed to investigate the history, current status, and limitations of liverwort research in China. By utilizing the latest systematic research findings and corresponding environmental data, a niche model was developed to offer theoretical support for exploring the potential geographical distribution and diversity of liverwort resources. A total of 55,427 liverwort specimens were collected in China, resulting in the recording of 1212 species belonging to 169 genera and 63 families. However, there are imbalances in the distributions of liverwort data among different groups, collection units, and geographical areas, with families such as Lejeuneaceae, Porellaceae, and Plagiochilaceae having the highest number of specimens. Similarly, genera such as Porella, Frullania, and Horikawaella were well represented. Remarkably, 125 species had specimen counts exceeding 100. Unfortunately, approximately 51.77% of the species had fewer than 10 recorded specimens. There were four obvious peaks in the collection years of the bryophyte specimens in China, among which the largest collection occurred from 2010 to 2023. Notably, the number of specimens collected at different stages closely aligned with the history of taxonomic research on liverworts in China. The results of the integrity of the liverwort collection indicate that there is insufficient representation of some families and genera, with a concentration of common and widely distributed large families and genera. Tropical and subtropical humid areas are key regions for liverwort diversity, with water and temperature being the primary environmental factors influencing their geographical distribution. The specific temporal and spatial data of species recorded from plant specimens will enhance the study of species diversity, comprehensive protection, and sustainable utilization. Additionally, these data will contribute to the investigation of large-scale biodiversity distribution patterns and the impact of global change on diversity. [ABSTRACT FROM AUTHOR]

SUMMARY: Proanthocyanidins (PAs), a group of flavonoids, are found in leaves, flowers, fruits, and seed coats of many plant species. PAs are primarily composed of epicatechin units in the seed coats of the model legume species, Medicago truncatula. It can be synthesized from two separate pathways, the leucoanthocyanidin reductase (MtLAR) pathway and the anthocyanidin synthase (MtANS) pathway, which produce epicatechin through anthocyanidin reductase (MtANR). These pathways are mainly controlled by the MYB–bHLH–WD40 (MBW) ternary complex. Here, we characterize a class IV homeodomain‐leucine zipper (HD‐ZIP IV) transcription factor, GLABRA2 (MtGL2), which contributes to PA biosynthesis in the seed coat of M. truncatula. Null mutation of MtGL2 results in dark brown seed coat, which is accompanied by reduced PAs accumulation and increased anthocyanins content. The MtGL2 gene is predominantly expressed in the seed coat during the early stages of seed development. Genetic and molecular analyses indicate that MtGL2 positively regulates PA biosynthesis by directly activating the expression of MtANR. Additionally, our results show that MtGL2 is strongly induced by the MBW activator complexes that are involved in PA biosynthesis. Taken together, our results suggest that MtGL2 acts as a novel positive regulator in PA biosynthesis, expanding the regulatory network and providing insights for genetic engineering of PA production. [ABSTRACT FROM AUTHOR]

To quickly manufacture multi-variety and low-volume products, manufacturing factories are increasingly sharing resources on collaborative production networks. However, the reliability of communication between factories cannot be fully guaranteed using traditional centralised approaches. Emerging blockchain technology can solve this problem due to its characteristics such as decentralisation and security. In this context, an integrated optimisation problem of multi-factory production and blockchain-secured collaborative maintenance is studied in this paper. Two scenarios are introduced with respective Q learning-based solution frameworks to solve the integrated problem. In the simulation scenario, preventive maintenance (PM) with flexible time windows is integrated with multi-factory production scheduling for reducing the probability of machine failures, and an initial integrated optimisation scheme is obtained. To make it more realistic, inevitable failures are considered in the actual production scenario, and the proposed collaborative maintenance strategy is triggered. Specifically, a corrective maintenance (CM) strategy is carried out immediately on the failed machine in case of a failure, followed by the PM on machines of the same type as the failed machine in other factories and the rescheduling of unprocessed jobs. Through a series of numerical studies, the effectiveness of the proposed optimisation approach and maintenance strategy is validated, and some interesting managerial implications also rise. [ABSTRACT FROM AUTHOR]

Synchronisation of operations and maintenance means that production and maintenance departments work together effectively to achieve integrated optimisation of production scheduling and maintenance activities. This paper addresses such an integrated optimisation problem towards distributed unrelated parallel machine systems, where deteriorating processing time and machine failures are considered. For the trade-off between production and maintenance to obtain a minimal makespan in the worst-case scenario, a hierarchical optimisation framework with reinforcement learning-based encoder and knowledge-based intelligent optimiser (HOFRK) is developed. Experimental results show that HOFRK can be treated as an excellent optimiser for enterprise information systems to solve the proposed problem. [ABSTRACT FROM AUTHOR]