Zobrazeno 1 - 10
of 865
pro vyhledávání: '"Liu Zewen"'
Publikováno v:
Open Life Sciences, Vol 19, Iss 1, Pp p. 9-112 (2024)
Tubular adenomas of the breast are rare benign epithelium-derived tumours, and so few cases have been reported. Most often, the tumours are palpable, well-circumscribed masses in women of childbearing age and are commonly diagnosed as fibroadenomas b
Externí odkaz:
https://doaj.org/article/73201007b7da43a7bb99a5b4aa0002d2
Autor:
Liu Zewen, Li Huixia, Gao Dandan, Su Junhong, Su Yuxin, Ma Zhongren, Li Zhiqiang, Qi Yanjiao, Ding Gongtao
Publikováno v:
Open Life Sciences, Vol 17, Iss 1, Pp 1629-1640 (2022)
Ghee is a traditional Tibetan dairy product with high-fat content, low yield, plasticity, caseation, and rich nutrition. In this study, we analyzed the diversity of microbial communities in yak milk and ghee samples at high and low altitudes, especia
Externí odkaz:
https://doaj.org/article/d7d1f1d466b0466ca2e7fdf7a671b425
Effective epidemic forecasting is critical for public health strategies and efficient medical resource allocation, especially in the face of rapidly spreading infectious diseases. However, existing deep-learning methods often overlook the dynamic nat
Externí odkaz:
http://arxiv.org/abs/2410.00049
Autor:
Zhongren Ma, Sakinah Idris, Yinxia Zhang, Liu Zewen, Amaad Wali, Yunpeng Ji, Qiuwei Pan, Zulqarnain Baloch
Publikováno v:
BMC Pediatrics, Vol 21, Iss 1, Pp 1-8 (2021)
Abstract Background The emerging of psychological problems triggered by COVID-19 particularly in children have been extensively highlighted and emphasized, but original research in this respect is still lagging behind. Therefore, we designed this stu
Externí odkaz:
https://doaj.org/article/cf878670ff644ad29c8996b56ee282c4
Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing tasks. Recently, several LLMs-based pipelines have been developed to enhance learning on graphs with text attributes, showcasing promisin
Externí odkaz:
http://arxiv.org/abs/2407.12068
EpiLearn is a Python toolkit developed for modeling, simulating, and analyzing epidemic data. Although there exist several packages that also deal with epidemic modeling, they are often restricted to mechanistic models or traditional statistical tool
Externí odkaz:
http://arxiv.org/abs/2406.06016
Autor:
Deng Tao, Li Shasha, Li Yuning, Zhang Yang, Sun Jingye, Yin Weijie, Wu Weidong, Zhu Mingqiang, Wang Yingxin, Liu Zewen
Publikováno v:
Nanophotonics, Vol 9, Iss 16, Pp 4719-4728 (2020)
The molybdenum disulfide (MoS2)-based photodetectors are facing two challenges: the insensitivity to polarized light and the low photoresponsivity. Herein, three-dimensional (3D) field-effect transistors (FETs) based on monolayer MoS2 were fabricated
Externí odkaz:
https://doaj.org/article/01852bc894b44759b2a6a4f4dfb4dc71
Publikováno v:
Nanophotonics, Vol 8, Iss 5, Pp 899-908 (2019)
Sensitive solar-blind ultraviolet (UV) photodetectors are important to various military and civilian applications, such as flame sensors, missile interception, biological analysis, and UV radiation monitoring below the ozone hole. In this paper, a so
Externí odkaz:
https://doaj.org/article/226514fbfa8840c5b9fcffb5ed87e486
Since the onset of the COVID-19 pandemic, there has been a growing interest in studying epidemiological models. Traditional mechanistic models mathematically describe the transmission mechanisms of infectious diseases. However, they often suffer from
Externí odkaz:
http://arxiv.org/abs/2403.19852
Publikováno v:
In Journal of Hazardous Materials 5 November 2024 479