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Institution

Donghua University

EducationShanghai, China
About: Donghua University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Fiber & Nanofiber. The organization has 21155 authors who have published 21841 publications receiving 393091 citations. The organization is also known as: Dōnghuá Dàxué & China Textile University.
Topics: Fiber, Nanofiber, Electrospinning, Membrane, Graphene


Papers
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Journal ArticleDOI
TL;DR: A diagonal recurrent wavelet neural network (DRWNN) is newly established in this paper to perform fine forecasting of hourly and daily global solar irradiance and comparisons between irradiation models show that the DRWNN models are definitely more accurate.

161 citations

Journal ArticleDOI
TL;DR: The optimal control problem is solved for the fractional-order optimality system with minimal dosage of anti-HIV drugs and the effects of mathematically optimal therapy are demonstrated.
Abstract: The fact that fractional-order models possess memory leads to modeling a fractional-order HIV-immune system. We discuss the necessary conditions for the optimality of a general fractional optimal control problem whose fractional derivative is described in the Caputo sense. Using an objective function that minimizes the infectious viral load and count of infected T cells, the optimal control problem is solved for the fractional-order optimality system with minimal dosage of anti-HIV drugs and the effects of mathematically optimal therapy are demonstrated. Simulation results show that the fractional-order optimal control scheme can achieve improved quality of the treatment.

161 citations

Journal ArticleDOI
TL;DR: This microreview summarizes important advances in the synthesis of fluorinated amino acids since 2005 and is divided into three groups on the basis of amino acid types: fluorinated α-amino acids (F-αAAs), fluorinated β-aminos acids (f-βAAs, and fluorinated cyclic amino acids ( F-CAAs).

161 citations

Journal ArticleDOI
TL;DR: The distributed weighted robust Kalman filter developed in this paper has stronger fault-tolerance ability and is derived for uncertain systems with multiple sensors.

160 citations

Journal ArticleDOI
TL;DR: The present review is intended to direct the reader’s attention to the important subjects of synthetic and natural polymers with HA for bone tissue engineering.
Abstract: The fracture of bones and large bone defects owing to various traumas or natural ageing is a typical type of tissue malfunction. Surgical treatment frequently requires implantation of a temporary or permanent prosthesis, which is still a challenge for orthopaedic surgeons, especially in the case of large bone defects. Mimicking nanotopography of natural extracellular matrix (ECM) is advantageous for the successful regeneration of damaged tissues or organs. Electrospun nanofibre-based synthetic and natural polymer scaffolds are being explored as a scaffold similar to natural ECM for tissue engineering applications. Nanostructured materials are smaller in size falling, in the 1–100 nm range, and have specific properties and functions related to the size of the natural materials (e.g. hydroxyapatite (HA)). The development of nanofibres with nano-HA has enhanced the scope of fabricating scaffolds to mimic the architecture of natural bone tissue. Nanofibrous substrates supporting adhesion, proliferation, differentiation of cells and HA induce the cells to secrete ECM for mineralization to form bone in bone tissue engineering. Our laboratory (NUSNNI, NUS) has been fabricating a variety of synthetic and natural polymer-based nanofibrous substrates and synthesizing HA for blending and spraying on nanofibres for generating artificial ECM for bone tissue regeneration. The present review is intended to direct the reader’s attention to the important subjects of synthetic and natural polymers with HA for bone tissue engineering.

160 citations


Authors

Showing all 21321 results

NameH-indexPapersCitations
Dongyuan Zhao160872106451
Xiang Zhang1541733117576
Seeram Ramakrishna147155299284
Kuo-Chen Chou14348757711
Shuai Liu129109580823
Chao Zhang127311984711
Tao Zhang123277283866
Zidong Wang12291450717
Xinchen Wang12034965072
Zhenyu Zhang118116764887
Benjamin S. Hsiao10860241071
Qian Wang108214865557
Jian Zhang107306469715
Yan Zhang107241057758
Richard B. Kaner10655766862
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202371
2022421
20212,465
20202,190
20192,003
20181,605