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The key to intelligent seed potato cutting technology lies in the accurate and rapid identification of potato bud eyes. Existing detection algorithms suffer from low recognition accuracy and high model complexity, resulting in an increased miss rate. To address these issues, this study proposes a potato bud-eye-detection algorithm based on an improved YOLOv8s. First, by integrating the Faster Neural Network (FasterNet) with the Efficient Multi-scale Attention (EMA) module, a novel Faster Block-EMA network structure is designed to replace the bottleneck components within the C2f module of YOLOv8s. This enhancement improves the model's feature-extraction capability and computational efficiency for bud detection. Second, this study introduces a weighted bidirectional feature pyramid network (BiFPN) to optimize the neck network, achieving multi-scale fusion of potato bud eye features while significantly reducing the model's parameters, computation, and size due to its flexible network topology. Finally, the Efficient Intersection over Union (EIoU) loss function is employed to optimize the bounding box regression process, further enhancing the model's localization capability. The experimental results show that the improved model achieves a mean average precision (mAP@0.5) of 98.1% with a model size of only 11.1 MB. Compared to the baseline model, the mAP@0.5 and mAP@0.5:0.95 were improved by 3.1% and 4.5%, respectively, while the model's parameters, size, and computation were reduced by 49.1%, 48.1%, and 31.1%, respectively. Additionally, compared to the YOLOv3, YOLOv5s, YOLOv6s, YOLOv7-tiny, and YOLOv8m algorithms, the mAP@0.5 was improved by 4.6%, 3.7%, 5.6%, 5.2%, and 3.3%, respectively. Therefore, the proposed algorithm not only significantly enhances the detection accuracy, but also greatly reduces the model complexity, providing essential technical support for the application and deployment of intelligent potato cutting technology. [ABSTRACT FROM AUTHOR]

Slope stability control is crucial for safe and efficient coal mining challenge of stabilizing dip soft rock slope rock slopes, the treatment engineering of inner row tracking pressure side of dip soft rock slope in open-pit mine is proposed based on the analysis of the main controlling factors of slope stability. This study takes the south side of the first mining area of Hesigewula south open-pit coal mine as the engineering background and proposes a synergistic treatment scheme for the slope stability of the stope and inner dump, utilizing the combination of limit equilibrium method and numerical simulation to design the spatial form of the stope slope. This treatment scheme maximizes the safe recovery of the coal resources covered by the slope. The research results indicate that the length of exposed weak layer is the primary controlling factor of the stability in inclined soft rock slopes in open-pit mines. Controlling the tracking distance between the stope and the inner dump is an effective way to improve slope stability. With an increase in tracking distance, the slope damage mode transitions from the cut-layer-sublayer-shear-out sliding with an arc as the side interface and the weak layer as the bottom interface to cut-layer-sublayer sliding with an arc as the side interface and weak layer as the bottom interface, leading to a gradual decrease in slope stability. Moreover, the stability of the inner dump and its composite slope with the stope increases exponentially with an increase in the backfill rock range of the weak layer of the failure floor. The study sets the shallow slope of the south slope of the first mining area of Hesigewula coal mine to be 40 m transportation flat and 15 m security flat, and the deep slope angle of the bottom slope is 29°. When the tracking distance is controlled within 50 m, it can meet the safety requirements. When the weak layer of the inner dump base is destroyed, and the inclined length of the backfill rock is 60 m, it can also meet the safety requirements. The study provides new insights into slope stability control in soft rock open-pit coal mines. [ABSTRACT FROM AUTHOR]

Online mutual aid (MA) is a novel form of ex‐post risk sharing empowered by InsurTech to provide critical illness coverage without involving an insurer. In this paper, we first provide a rigorous examination of the underpinning theory and analyze MA model's cost‐effectiveness. In addition, we theoretically investigate the condition for MA's actuarial fairness among all participants. Our numerical illustration also shows that current MA plans lack the consideration of actuarial fairness as they differentiate members only by gender and age group of large bandwidths. Last, our empirical analysis confirms the existence of adverse selection due to the lack of actuarial fairness. [ABSTRACT FROM AUTHOR]

Dye wastewater discharges threaten fragile aquatic ecosystems. Photocatalysis has been applied as an effective, viable, and economical option to achieve dye degradation. However, current photocatalysts suffer from large bandgaps, powder agglomeration, difficult recovery, and cannot be recycled. Herein, a novel Bi2S3/ZnS heterojunction loaded cellulose/chitosan (BiZnCCS) with highly efficient photocatalytic activities for CR pollutant degradation was designed and fabricated via a simple hydrothermal method. BiZnCCS has a large pore size of 2 μm with a high porosity of 71.62%, which increases the contact area with CR and facilitates the adsorption of CR. The pore wall was uniformly loaded with Bi2S3/ZnS particles, and the degradation rate of CR could reach 97.8% under simulated visible light irradiation. By adjusting the composition ratio, BiZnCCS was able to withstand a stress of about 82.45 kPa, and the CR removal rate was still maintained at about 85% after 7 cycles of testing. By creating a synergistic adsorption-photocatalytic degradation mechanism, BiZnCCS has the ability to efficiently remove CR under visible light, which provides a new material for the treatment of dye wastewater. [ABSTRACT FROM AUTHOR]

Three previously undescribed compounds including two aromatic acid derivatives (1–2), and one xanthone (3), together with ten known compounds (4–13) were isolated from the aerial part of Hypericum hengshanense. The planar structures of three new compounds were established by 1 D and 2 D NMR and MS data. And the absolute configurations of compounds 1–2 were determined by the quantum chemical ECD calculations. Compounds 1–2 showed weak cytotoxicity against Hep-2 human cancer cell lines with IC50 values of 65.1 ± 2.7 and 78.0 ± 1.0 μg/mL, respectively. [ABSTRACT FROM AUTHOR]