Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "Zhang, Xinfei" wg kryterium: Autor

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-2 z 2
    Tytuł:
    Effects of Tremella fuciformis-Derived Polysaccharides with Different Molecular Weight on D-Galactose-Induced Aging of Mice
    Autorzy:
    Luo, Donghui
    Liu, Xiaofei
    Guan, Jingjing
    Jang, Guili
    Hua, Yanglin
    Zhang, Xinfei
    Xu, Xiaofei
    Powiązania:
    https://bibliotekanauki.pl/articles/16538544.pdf
    Data publikacji:
    2023-05-25
    Wydawca:
    Instytut Rozrodu Zwierząt i Badań Żywności Polskiej Akademii Nauk w Olsztynie
    Tematy:
    mushroom
    polysaccharide purification
    anti-oxidant activity
    anti-aging activity
    structure-function relationship
    anti-oxidant enzyme
    Opis:
    The structure-bioactivity relationship of Tremella fuciformis polysaccharides (TFPs) in anti-aging in vivo is rarely reported. In the present study, a purified TFP, named HM, mainly composed of mannose, fucose, xylose, and glucose in a molar ratio of 4.14:0.98:0.81:0.62, was obtained from the fruiting body of T. fuciformis. Subsequently, two differentially degraded TFPs, named MM and LM, respectively, were prepared by a combined method of ultrasonic irradiation (US) and H2O2 treatment. Their structural properties, scavenging activities against free radicals in vitro, and anti-aging effects on D-galactose-induced aging of mice were determined. The average molecular weight of HM, MM, and LM was 58.3×106, 4.68×106, and 3.14×105 Da, respectively. All three TFPs were devoid of triple helix conformation and exhibited concentration- and molecular weight-dependent scavenging activity against radicals. The TFPs markedly relieved skin aging, effectively attenuated oxidative stress, and significantly decreased inflammation in D-galactose-induced aging mice. MM exhibited the best anti-aging effect among the TFPs. Additionally, TFPs partially restored the alterations in pH and the total content of short-chain fatty acids (SCFAs) in the colon but exhibited various impacts on the content of the individual SCFAs. These findings would provide rational guidance for a better application of TFPs in anti-aging foods and expand our understanding of the structure-function relationship of mushroom polysaccharides.
    Źródło:
    Polish Journal of Food and Nutrition Sciences; 2023, 73, 2; 163-174
    1230-0322
    2083-6007
    Pojawia się w:
    Polish Journal of Food and Nutrition Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An automated driving strategy generating method based on WGAIL–DDPG
    Autorzy:
    Zhang, Mingheng
    Wan, Xing
    Gang, Longhui
    Lv, Xinfei
    Wu, Zengwen
    Liu, Zhaoyang
    Powiązania:
    https://bibliotekanauki.pl/articles/2055167.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    automated driving system
    deep learning
    deep reinforcement learning
    imitation learning
    deep deterministic policy gradient
    system jezdny
    uczenie głębokie
    uczenie przez naśladowanie
    Opis:
    Reliability, efficiency and generalization are basic evaluation criteria for a vehicle automated driving system. This paper proposes an automated driving decision-making method based on the Wasserstein generative adversarial imitation learning–deep deterministic policy gradient (WGAIL–DDPG(λ)). Here the exact reward function is designed based on the requirements of a vehicle’s driving performance, i.e., safety, dynamic and ride comfort performance. The model’s training efficiency is improved through the proposed imitation learning strategy, and a gain regulator is designed to smooth the transition from imitation to reinforcement phases. Test results show that the proposed decision-making model can generate actions quickly and accurately according to the surrounding environment. Meanwhile, the imitation learning strategy based on expert experience and the gain regulator can effectively improve the training efficiency for the reinforcement learning model. Additionally, an extended test also proves its good adaptability for different driving conditions.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 461--470
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies