Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Xuanpeng, Li"'
Autor:
Huihui Zhang, Tong Xin, Juntao Yuan, Wenhao Feng, Jufeng Huang, Fengling Tan, Xuanpeng Li, Anqing Fu
Publikováno v:
Materials Research Express, Vol 11, Iss 5, p 056510 (2024)
Microbiologically influenced corrosion has become a predominant cause of pipeline and equipment failure in oil and gas fields. This research examines the corrosion behavior of steels with varying chromium contents in simulated shale gas formation wat
Externí odkaz:
https://doaj.org/article/ed74c16f4d214992bd72143067b655f2
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract 2205 duplex stainless steel (DSS) has good corrosion resistance due to its typical duplex organization, but the increasingly harsh CO2-containing oil and gas environment leads to different degrees of corrosion, especially pitting corrosion,
Externí odkaz:
https://doaj.org/article/ed04dbffce774e499ad85d6ac8c581a7
Autor:
Hongjin Wu, Weiwei Tian, Xiang Tai, Xuanpeng Li, Ziwei Li, Jing Shui, Juehua Yu, Zhihua Wang, Xiaosong Zhu
Publikováno v:
BMC Genomics, Vol 22, Iss 1, Pp 1-14 (2021)
Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer. Approximately 80% of patients initially diagnosed with locally advanced or metastatic disease survive only 4–11 months after diagnosis. Tremendous efforts have been mad
Externí odkaz:
https://doaj.org/article/e2ad0849a2ad476fb109ff4b4278cb8f
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
In the last decade, there have been substantial improvements in the outcome of the management of metastatic hormone-sensitive prostate cancer (mHSPC) following the development of several novel agents as well as by combining several therapeutic strate
Externí odkaz:
https://doaj.org/article/d9316498534c462786d28bbc4b0ad720
Publikováno v:
IEEE Access, Vol 8, Pp 101946-101962 (2020)
Available charging information exchanges between mobile electric vehicles (EVs) and charging stations are significantly critical in spatio-temporal coordinated charging services introduced by smart girds. In this paper, we propose an efficient inform
Externí odkaz:
https://doaj.org/article/a08caf65a49f475a9356f1836a72c59f
Autor:
Arianna Bichicchi, Rachid Belaroussi, Andrea Simone, Valeria Vignali, Claudio Lantieri, Xuanpeng Li
Publikováno v:
IEEE Access, Vol 8, Pp 19638-19645 (2020)
In this study, an improved deep learning model is proposed to explore the complex interactions between the road environment and driver's behaviour throughout the generation of a graphical representation. The proposed model consists of an unsupervised
Externí odkaz:
https://doaj.org/article/bf731998c1e64a90bc92ba6c4fedd46e
Publikováno v:
IEEE Access, Vol 8, Pp 80527-80535 (2020)
Occlusion caused by multi-object interaction makes the traffic scene understanding intractable. In this paper, we focus on predicting the visibility status of vehicle in the framework of causality perception. The visibility fluent is employed to pres
Externí odkaz:
https://doaj.org/article/889e3cef01414ba9a0ae385f1d80bc7f
Autor:
Naixin, Lv, Anqing, Fu, Chao, Chen, Haitao, Bai, Zaipeng, Zhao, Xuanpeng, Li, Zhengyi, Xu, Meng, Guozhe
Publikováno v:
In Vacuum February 2025 232
Publikováno v:
Analog Integrated Circuits and Signal Processing. 115:241-252
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acf56c926369744127a7905cf84415eb
https://doi.org/10.1007/s10470-023-02145-z
https://doi.org/10.1007/s10470-023-02145-z
Purpose This study aims to establish the best prediction model of lymph node metastasis (LNM) in patients with intermediate- and high-risk prostate cancer (PCa) through machine learning (ML), and provide the guideline of accurate clinical diagnosis a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::161feedf6991cc864440cfa0df214fb4
https://doi.org/10.21203/rs.3.rs-2701508/v1
https://doi.org/10.21203/rs.3.rs-2701508/v1
