Zobrazeno 1 - 10
of 567
pro vyhledávání: '"Cheng Zhiyong"'
Publikováno v:
Xibei Gongye Daxue Xuebao, Vol 42, Iss 2, Pp 241-250 (2024)
Flare folding wing-tips rely on the adaptive deformation of the structure to reduce the flight load, which can effectively simplify the control system, and has more advantages in cost and weight. To study the effect of the elastic folding wingtip as
Externí odkaz:
https://doaj.org/article/ebdb5db03be942019b5c33efb916b0a3
Publikováno v:
Zhongliu Fangzhi Yanjiu, Vol 49, Iss 10, Pp 1021-1027 (2022)
Objective To determine the effect of rapamycin(Rapa) on JAK2, ABCA3, and the immune checkpoint PD-1/PD-L1 in exosomes derived from JAK2 V617F positive HEL cells. Methods Human erythroleukemia HEL cells (JAK2 V617F mutation-positive) were cultured in
Externí odkaz:
https://doaj.org/article/fc8df6ac2dc847dea1ec4c704f744ebf
Multi-behavior recommendation systems enhance effectiveness by leveraging auxiliary behaviors (such as page views and favorites) to address the limitations of traditional models that depend solely on sparse target behaviors like purchases. Existing a
Externí odkaz:
http://arxiv.org/abs/2408.12152
Publikováno v:
Zhongliu Fangzhi Yanjiu, Vol 48, Iss 4, Pp 436-438 (2021)
Externí odkaz:
https://doaj.org/article/e51431252cb247048cf5ee66818062e0
Autor:
ZHANG Lijun, QI Feng, CHENG Zhiyong, ZHANG Zhao, WU Shijie, GUO Yantao, SUN Li'na, PENG Zhanxian, LIANG Wentong
Publikováno v:
Zhongliu Fangzhi Yanjiu, Vol 46, Iss 1, Pp 63-67 (2019)
Objective To explore the effect of interferon-alpha-2b(IFN-alpha 2b) on the expression of programmed death receptor-1(PD-1), programmed death ligand-1(PD-L1) and CD4+ CD25+ Foxp3+ regulatory T cell (Treg) in JAK2 V617F-positive myeloproliferative neo
Externí odkaz:
https://doaj.org/article/dc182308723045c990109737fba441e1
In recommender systems, multi-behavior methods have demonstrated their effectiveness in mitigating issues like data sparsity, a common challenge in traditional single-behavior recommendation approaches. These methods typically infer user preferences
Externí odkaz:
http://arxiv.org/abs/2404.18166
Multi-behavioral recommender systems have emerged as a solution to address data sparsity and cold-start issues by incorporating auxiliary behaviors alongside target behaviors. However, existing models struggle to accurately capture varying user prefe
Externí odkaz:
http://arxiv.org/abs/2404.11519
Graph Convolution Networks (GCNs) have significantly succeeded in learning user and item representations for recommendation systems. The core of their efficacy is the ability to explicitly exploit the collaborative signals from both the first- and hi
Externí odkaz:
http://arxiv.org/abs/2404.10321
Recommendation systems harness user-item interactions like clicks and reviews to learn their representations. Previous studies improve recommendation accuracy and interpretability by modeling user preferences across various aspects and intents. Howev
Externí odkaz:
http://arxiv.org/abs/2312.16275
Publikováno v:
In Proceedings of the 32st ACM International Conference on Multimedia (MM '24), 2024
Recommendation algorithms forecast user preferences by correlating user and item representations derived from historical interaction patterns. In pursuit of enhanced performance, many methods focus on learning robust and independent representations b
Externí odkaz:
http://arxiv.org/abs/2312.14433