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    Wyświetlanie 1-4 z 4
    Tytuł:
    Experimental analysis of interfacial properties of sphere oblique impact with initial spin
    Autorzy:
    Wang, Qing-Peng
    Wang, Zheng-Feng
    Wang, Heng
    Li, De-Feng
    Gao, Xian-Kun
    Xu, Guang-Yin
    Powiązania:
    https://bibliotekanauki.pl/articles/2086967.pdf
    Data publikacji:
    2022
    Wydawca:
    Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
    Tematy:
    sphere
    spin
    oblique impact
    contact surface
    slip ratio
    Opis:
    Experiments of a sphere oblique impact with and without an initial spin have been carried out to obtain properties of the impact interface. The contact surface is recorded with a piece of thin carbon paper. The interfacial parameters measured are expressed as axis length, contact area and slip ratio. It is found that for the impact between steels the forward spin can make geometrical sizes of the contact surface increase compared with the case of no initial spin, however, just the reverse for the backward spin. The effect of the initial spin becomes more apparent for the impact with a rubber cushion. Whether the initial spin promotes or hinders the sphere sliding depends on the parameters of tangential velocity and force at the interface.
    Źródło:
    Journal of Theoretical and Applied Mechanics; 2022, 60, 2; 213--225
    1429-2955
    Pojawia się w:
    Journal of Theoretical and Applied Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Analysis of Clothing Image Classification Models: A Comparison Study between Traditional Machine Learning and Deep Learning Models
    Autorzy:
    Xu, Jun
    Wei, Yumeng
    Wang, Aichun
    Zhao, Heng
    Lefloch, Damien
    Powiązania:
    https://bibliotekanauki.pl/articles/2200761.pdf
    Data publikacji:
    2022
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Tematy:
    e-commerce
    clothing image classification
    traditional machine learning
    CNN
    HOG
    SVM
    small VGG network
    Opis:
    Clothing image in the e-commerce industry plays an important role in providing customers with information. This paper divides clothing images into two groups: pure clothing images and dressed clothing images. Targeting small and medium-sized clothing companies or merchants, it compares traditional machine learning and deep learning models to determine suitable models for each group. For pure clothing images, the HOG+SVM algorithm with the Gaussian kernel function obtains the highest classification accuracy of 91.32% as compared to the Small VGG network. For dressed clothing images, the CNN model obtains a higher accuracy than the HOG+SVM algorithm, with the highest accuracy rate of 69.78% for the Small VGG network. Therefore, for end-users with only ordinary computing processors, it is recommended to apply the traditional machine learning algorithm HOG+SVM to classify pure clothing images. The classification of dressed clothing images is performed using a more efficient and less computationally intensive lightweight model, such as the Small VGG network.
    Źródło:
    Fibres & Textiles in Eastern Europe; 2022, 5 (151); 66--78
    1230-3666
    2300-7354
    Pojawia się w:
    Fibres & Textiles in Eastern Europe
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cyanidin and peonidin inhibit SPCA-1 growth in vitro via inducing Cell Cycle Arrest and Apoptosis
    Autorzy:
    Yue, Heng
    Xu, Qianqian
    Lv, Liuzhuang
    Xu, Jianfeng
    Fan, Hua
    Wang, Wenhan
    Powiązania:
    https://bibliotekanauki.pl/articles/895348.pdf
    Data publikacji:
    2019-06-28
    Wydawca:
    Polskie Towarzystwo Farmaceutyczne
    Tematy:
    Lung cancer
    apoptosis
    cell cycle
    SPCA-1
    cyanidin
    peonidin
    Opis:
    Non-small cell lung cancer (NSCLC) accounts for the majority (85%) of all lung cancers. Although many therapies are available, 35–50% of patients with stage I or II NSCLC develop recurrence and metastasis. This study was designed to investigate the anti-tumor activity of cyanidin (Cy) and peonidin (Pn) on NSCLC cells (SPCA-1). SPCA-1 cell proliferation, cell cycle and early apoptosis were investigated after treatment with Cy and Pn. The underlying signaling mechanism was also explored by detecting the levels of apoptosis-related proteins using enzyme-linked immunosorbent assay (ELISA). Cy and Pn inhibited the viability of SPCA-1 cells with an IC50 of 141.08 μg/mL and 161.31 μg/mL, respectively. Meanwhile, Cy and Pn induced cell cycle arrest at G2/M phase. Cy and Pn treatment significantly increased the levels of Bax, P53, and Caspase-3, while decreasing that of Bcl-2, thereby inhibiting the growth of SPCA-1 cells. In conclusion, Cy and Pn induced early apoptosis of NSCLC cells through regulation of the levels on Caspase-3, Bax, Bcl-2, and P53. These results suggest Cy and Pn as potential anticancer drugs for the treatment of lung cancer.
    Źródło:
    Acta Poloniae Pharmaceutica - Drug Research; 2019, 76, 3; 503-509
    0001-6837
    2353-5288
    Pojawia się w:
    Acta Poloniae Pharmaceutica - Drug Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Calcium alginate/activated carbon/humic acid tri-system porous fi bers for removing tetracycline from aqueous solution
    Autorzy:
    Sun, Qinye
    Zheng, Heng
    Li, Yanhui
    Li, Meixiu
    Du, Qiuju
    Wang, Cuiping
    Sui, Kunyan
    Li, Hongliang
    Xia, Yanzhi
    Powiązania:
    https://bibliotekanauki.pl/articles/949364.pdf
    Data publikacji:
    2020
    Wydawca:
    Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
    Tematy:
    Sodium alginate
    Humic acid
    Activated carbon
    Adsorption
    Tetracycline
    Opis:
    In this study, activated carbon and humic acid powder were fixed by the cross-linking reaction of sodium alginate. Calcium alginate/activated carbon/humic acid (CAH) tri-system porous fibers were prepared by the wet spinning method and freeze-dried for the removal of tetracycline in aqueous solution. Subsequently, the morphology and structure of CAH fibers were measured by scanning electron microscopy (SEM) and the Brunauer-Emmett-Teller (BET) method. The effect of pH, contact time, temperature and other factors on adsorption behavior were analyzed. The Langmuir and Freundlich isotherm models were used to fit tetracycline adsorption equilibrium data. The dynamics data were evaluated by the pseudo-second-order model, the pseudo-second-order model and the intraparticle diffusion model. Thermodynamic study confirmed that the adsorption of tetracycline on CAH fibers was a spontaneous process.
    Źródło:
    Polish Journal of Chemical Technology; 2020, 22, 3; 9-16
    1509-8117
    1899-4741
    Pojawia się w:
    Polish Journal of Chemical Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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