Zobrazeno 1 - 10
of 170
pro vyhledávání: '"JIANBIN SU"'
Autor:
Caixia Liang, Hongjian Lu, Xueqin Wang, Jianbin Su, Feng Qi, Yanxing Shang, Yu Li, Dongmei Zhang, Chengwei Duan
Publikováno v:
Frontiers in Endocrinology, Vol 15 (2024)
ObjectiveEnergy homeostasis is modulated by the hypothalamic is essential for obesity progression, however, the gene expression profiling remains to be fully understood.MethodsGEO datasets were downloaded from the GEO website and analyzed by the R pa
Externí odkaz:
https://doaj.org/article/c32c960cdbf14b77a6fa5c9b6a92234e
Publikováno v:
Electrochemistry, Vol 92, Iss 10, Pp 107004-107004 (2024)
This paper developed a one-dimensional multiphase model to analyze the cold start behavior of fuel cell, focusing on the effects of various parameters such as loading rates, maximum loading current densities, and coolant flow rates. The findings reve
Externí odkaz:
https://doaj.org/article/d9b640a333e442a0b8628b40d8f6fb2c
Autor:
Zhiyuan Li, Jianbin Su, Jinjing Wang, Li Yan, Huiqiang Zhang, Xinyu Li, Yanhong Tai, Yi Fang, Tao Yan
Publikováno v:
Clinical Case Reports, Vol 12, Iss 6, Pp n/a-n/a (2024)
Key Clinical Message Ultrasound‐guided core needle biopsy combined with immunohistochemistry and molecular testing could improve the diagnostic accuracy of bone metastases from follicular thyroid carcinoma, help to predict distant metastasis and pr
Externí odkaz:
https://doaj.org/article/bee98697bf9e463299741d79615fff57
Publikováno v:
Química Nova, Vol 47, Iss 8 (2024)
The article establishes a three-dimensional multiphase proton exchange membrane single-cell model and investigates the impact of precision flow field design on the electrochemical characteristics, heat mass transfer properties, and phase change chara
Externí odkaz:
https://doaj.org/article/210368d91b0b4374a36f40dfd6d5ae1c
Autor:
Xiaoyi Wang, Gerald Corzo, Haishen Lü, Shiliang Zhou, Kangmin Mao, Yonghua Zhu, Santiago Duarte, Mingwen Liu, Jianbin Su
Publikováno v:
Agricultural Water Management, Vol 295, Iss , Pp 108772- (2024)
Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compar
Externí odkaz:
https://doaj.org/article/b9e2497f7b6c413f8bd5542a232fbd4a
Autor:
Xiaoyi Wang, Lifu Chai, Sidong Zeng, Jianbin Su, Bin Ye, Haishen Lü, Changqing Chen, Junfu Gong, Mingwen Liu, Xiaoqing Wang, Shiliang Zhou
Publikováno v:
Land, Vol 13, Iss 9, p 1444 (2024)
Cultivated reserved land resources are pivotal for achieving food security and sustainable agricultural development. However, existing research on these resources often grapples with issues such as the lack of current data and underutilization of ava
Externí odkaz:
https://doaj.org/article/170cba9587154536b5d055f2ab3a6290
Publikováno v:
Remote Sensing, Vol 16, Iss 6, p 956 (2024)
Accurately simulating glacier mass balance (GMB) data is crucial for assessing the impacts of climate change on glacier dynamics. Since physical models often face challenges in comprehensively accounting for factors influencing glacial melt and uncer
Externí odkaz:
https://doaj.org/article/c03aff122c594d5ba86542286152dd44
Autor:
Jianbin Su, Walter Gassmann
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Accumulating evidence suggests that chloroplasts are an important battleground during various microbe-host interactions. Plants have evolved layered strategies to reprogram chloroplasts to promote de novo biosynthesis of defense-related phytohormones
Externí odkaz:
https://doaj.org/article/b2c029ea41814374aed0b7101cc459ce
Autor:
Xiaoyi Wang, Haishen Lü, Wade T. Crow, Gerald Corzo, Yonghua Zhu, Jianbin Su, Jingyao Zheng, Qiqi Gou
Publikováno v:
iScience, Vol 26, Iss 1, Pp 105853- (2023)
Summary: The soil moisture active/passive (SMAP) mission represents a significant advance in measuring soil moisture from satellites. However, its large spatial-temporal data gaps limit the use of its values in near-real-time (NRT) applications. Cons
Externí odkaz:
https://doaj.org/article/c67703e46c9e44c7a3302643343998bb
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4527 (2023)
Due to the scarcity of observational data and the intricate precipitation–runoff relationship, individually applying physically based hydrological models and machine learning (ML) techniques presents challenges in accurately predicting floods withi
Externí odkaz:
https://doaj.org/article/c04805aedc634987bf410a6ec4d4fc75