Zobrazeno 1 - 10
of 5 397
pro vyhledávání: '"SHENG FENG"'
Autor:
Yaru Yang, Hongyan Qiu, Yuru Fan, Qin Zhang, Huiling Qin, Juan Wu, Xuan Zhang, Yueyue Liu, Renpeng Zhou, Qian Zhang, Zi Ye, Jingyue Ma, Ye Xu, Sheng Feng, Yue Fei, Na Li, Xiaojing Cui, Fangli Dong, Quanren Wang, Kai Shen, Sepehr Shakib, Jasmine Williams, Wei Hu
Publikováno v:
Alzheimer’s Research & Therapy, Vol 16, Iss 1, Pp 1-11 (2024)
Abstract Background SHR-1707 is a novel humanized anti-Aβ IgG1 monoclonal antibody that binds to Aβ fibrils and monomers to block the formation of Aβ plaques or to promote the microglial phagocytosis of Aβ. Preclinical studies showed that SHR-170
Externí odkaz:
https://doaj.org/article/c235061a1161431ba736e7493e4d3bee
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 10931 (2024)
In complex marine environments, extracting target features from acoustic signal is very difficult, making the targets hard to be recognized. Therefore, it is necessary to perform denoising method on the acoustic signal to highlight the target feature
Externí odkaz:
https://doaj.org/article/798e70177c0a4cb799837491ae1568b9
Publikováno v:
Advances in Mechanical Engineering, Vol 16 (2024)
The dynamic coefficients (dynamic stiffness coefficient and dynamic damping coefficient) of gas foil bearings (GFBs) are important for transient dynamics calculation and stability analysis of the GFBs-rotor system. Although the perturbation method ca
Externí odkaz:
https://doaj.org/article/65a1df2a7bf64ebab6963202207d067e
Publikováno v:
Remote Sensing, Vol 16, Iss 17, p 3333 (2024)
Underwater acoustic target recognition has always played a pivotal role in ocean remote sensing. By analyzing and processing ship-radiated signals, it is possible to determine the type and nature of a target. Historically, traditional signal processi
Externí odkaz:
https://doaj.org/article/e339ff1d001846c1b49dc46288e67248
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Abstract Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel dee
Externí odkaz:
https://doaj.org/article/0f70c7e1d0e0458cab2d80da0d7f4c6e
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-17 (2023)
Abstract To detect lanes at night, each detecting image is the fusion of the multiple images in a video sequence. The valid lane line detection region is identified on region merging. Then, the image preprocessing algorithm based on the Fragi algorit
Externí odkaz:
https://doaj.org/article/264cb528a120472e92a5a23ecfb2087d
Autor:
Ke-Guang Chen, Ye-Hui Zhang, Pan-Pan Ye, Xue-Hu Gao, Lin-Lin Song, Hai-Yan Zhou, Qian Li, Fu-Rong Zhao, Jin-Yi Shi, Xin-Mei Yang, Kai Shen, Sheng Feng, Wei Zhao
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Objectives: INS068 is a novel, soluble, and long-acting insulin analog. In this study, we evaluated the pharmacokinetics and relative bioavailability of two formulations of INS068 in healthy Chinese subjects: a reference formulation packaged in vials
Externí odkaz:
https://doaj.org/article/f45dc0a27fd447838e79e84cb91c38fc
Autor:
Luyan Gao, Xuefeng Chen, Sheng Feng, Ying Lu, Kai Song, Huaying Shen, Yun Wang, Linsen Jiang, Zhi Wang
Publikováno v:
Renal Failure, Vol 45, Iss 2 (2023)
Objective To analyze the clinical data of elderly patients with peritoneal dialysis (PD) and compare patient and technique survival rates between Group 1 (65–74 years old) and Group 2 (≥75 years old).Methods This retrospective study enrolled 296
Externí odkaz:
https://doaj.org/article/3ccfc6f8b0a54f10952d47242f72102e
Publikováno v:
ACS Measurement Science Au, Vol 2, Iss 5, Pp 414-421 (2022)
Externí odkaz:
https://doaj.org/article/94c60a09394c493783faffba8cb34102
Publikováno v:
Remote Sensing, Vol 15, Iss 22, p 5386 (2023)
Deep learning models can produce unstable results by introducing imperceptible perturbations that are difficult for humans to recognize. This can have a significant impact on the accuracy and security of deep learning applications due to their poorly
Externí odkaz:
https://doaj.org/article/421e15783a0b45699b58dfcb51274c28