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To fully harness the burgeoning array of in-orbit satellite resources and augment the efficacy of dynamic surveillance of densely clustered terrestrial targets, this paper delineates the following methodologies. Initially, we leverage the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm to aggregate the concentrated terrestrial targets, taking into account the field-of-view peculiarities of agile staring satellites. Subsequently, we architect a model for a synergistic multiple angle earth observation satellites (AEOSs) mission planning with the optimization objectives of observational revenue, minimal energy expenditure, and load balancing, factoring in constraints such as target visibility time window, AEOSs maneuverability, and satellite storage. To tackle this predicament, we propose an improved heuristic ant colony optimization (ACO) algorithm, utilizing the task interval, task priority, and the length of time a task can start observation as heuristic information. Furthermore, we incorporate the notion of the max–min ant system to regulate the magnitude of pheromone concentration, and we amalgamate global and local pheromone update strategies to expedite the convergence rate of the algorithm. We also introduce the Lévy flight improved pheromone evaporation coefficient to bolster the algorithm's capacity to evade local optima. Ultimately, through a series of simulation experiments, we substantiate the significant performance improvements achieved by the improved heuristic ant colony algorithm compared to the standard ant colony algorithm. We furnish proof of its efficacy in resolving the planning of multiple AEOS staring observation missions. [ABSTRACT FROM AUTHOR]

Intense and excessive exercise-induced fatigue has become an important health issue and can damage intestinal health. Deer blood, as a food byproduct with nutritional value, has been found to restore physical strength. However, little is known about the antifatigue effect of fermented deer blood (FDB) on intense exercise mice. The purpose of the present study is to investigate the antifatigue effect of FDB, and whether this effect is correlated with the altered small intestinal microbiota and metabolites in exercise mice. In this study, 5-week-old male C57BL/6J mice are given treadmill exercise with or without FDB supplementation (30 and 150 mg/kg/d) for 3 weeks. FDB significantly reduces metabolic byproduct accumulation, liver and intestinal damage, and enhances glycogen storage and antioxidant capacity in intense exercise mice. Moreover, FDB restructures the small intestinal microbiota by increasing the abundance of probiotics and butyric acid producing bacteria and decreasing the abundance of pathogenic bacteria. FDB also regulates the levels of metabolites involved in TCA cycle and amino acid metabolism in urine and small intestine content. Correlation analysis shows that FDB-modulated microbiota is highly associated with its antifatigue effect. FDB may ameliorate fatigue and intestinal injury through targeting small intestinal microbiota. [ABSTRACT FROM AUTHOR]

Based on computer vision technology, this paper proposes a method for identifying and locating crops in order to successfully capture crops in the process of automatic crop picking. This method innovatively combines the YOLOv3 algorithm under the DarkNet framework with the point cloud image coordinate matching method, and can achieve the goal of this paper very well. Firstly, RGB (RGB is the color representing the three channels of red, green and blue) images and depth images are obtained by using the Kinect v2 depth camera. Secondly, the YOLOv3 algorithm is used to identify the various types of target crops in the RGB images, and the feature points of the target crops are determined. Finally, the 3D coordinates of the feature points are displayed on the point cloud images. Compared with other methods, this method of crop identification has high accuracy and small positioning error, which lays a good foundation for the subsequent harvesting of crops using mechanical arms. In summary, the method used in this paper can be considered effective. [ABSTRACT FROM AUTHOR]

As one of the conventional treatment methods, acupuncture is an indispensable component of Traditional Chinese Medicine. Currently, acupuncture has been partly accepted throughout the world, but the mechanism of acupuncture is still unclear. Since the theory of the neuro-endocrine-immune network was put forward, new insights have been brought into the understanding of the mechanism of acupuncture. Studies have proven that acupuncture is a mechanical stimulus that can activate local cell functions and neuroreceptors. It also regulates the release of related biomolecules (peptide hormones, lipid hormones, neuromodulators and neurotransmitters, and other small and large biomolecules) in the microenvironment, where they can affect each other and further activate the neuroendocrine-immune network to achieve holistic regulation. Recently, growing efforts have been made in the research on the mechanism of acupuncture. Some researchers have transitioned from studying the mechanism of acupuncture as a single linear pathway to using systems approaches, including metabolomics, genomics, proteomics and biological pathway analysis. This review summarizes the research progress on the neuro-endocrine-immune network related mechanism of acupuncture and discusses its current challenges and future directions.