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  • Open Access


    Does young feces make the elderly live better? Application of fecal microbiota transplantation in healthy aging


    BIOCELL, Vol.48, No.6, pp. 873-887, 2024, DOI:10.32604/biocell.2024.050324

    Abstract As we are facing an aging society, anti-aging strategies have been pursued to reduce the negative impacts of aging and increase the health span of human beings. Gut microbiota has become a key factor in the anti-aging process. Modulation of gut microbiota by fecal microbiota transplantation (FMT) to prevent frailty and unhealthy aging has been a hot topic of research. This narrative review summarizes the benefits of FMT for health span and lifespan, brains, eyes, productive systems, bones, and others. The mechanisms of FMT in improving healthy aging are discussed. The increased beneficial bacteria and More >

  • Open Access


    Research on the Bending Impact Resistance and Transverse Fracture Characteristics of Bamboo under the Action of Falling Weight

    Hao Jia1,2, Benhua Fei1,2, Changhua Fang1,2, Huanrong Liu1,2, Xiubiao Zhang1,2, Xinxin Ma1,2, Fengbo Sun1,2,*

    Journal of Renewable Materials, Vol.11, No.1, pp. 473-490, 2023, DOI:10.32604/jrm.2022.023548

    Abstract Drop weight impact tester was used to accurately measure the bending impact resistance of various parts of Phyllostachys edulis, commonly known as moso bamboo, with a growth cycle of 3–8 years. Cellulose crystallinity in the bottom (B), middle (M) and top (T) of bamboo at different ages was calculated using peak height analysis in X-ray diffraction. Heatmap of Spearman correlation analysis was used to represent the correlation between chemical composition and impact mechanics. The breaking load (BL), fracture energy (FE) and impact deflection (ID) of 3–8-yearold bamboo were found to be in the range of ~670–2120 N, ~5.17–15.55 J,… More > Graphic Abstract

    Research on the Bending Impact Resistance and Transverse Fracture Characteristics of Bamboo under the Action of Falling Weight

  • Open Access


    Hybrid Optimisation with Black Hole Algorithm for Improving Network Lifespan

    S. Siamala Devi1, Chandrakala Kuruba2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1873-1887, 2023, DOI:10.32604/iasc.2023.025504

    Abstract Wireless sensor networks (WSNs) are projected to have a wide range of applications in the future. The fundamental problem with WSN is that it has a finite lifespan. Clustering a network is a common strategy for increasing the lifetime of WSNs and, as a result, allowing for faster data transmission. The clustering algorithm’s goal is to select the best cluster head (CH). In the existing system, Hybrid grey wolf sunflower optimization algorithm (HGWSFO)and optimal cluster head selection method is used. It does not provide better competence and output in the network. Therefore, the proposed Hybrid… More >

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