Institution
Donghua University
Education•Shanghai, 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, Membrane, Electrospinning, Catalysis
Papers published on a yearly basis
Papers
More filters
••
TL;DR: In this paper, a mixture of HFP/TFA solvent was used for electrospinning of the collagen-chitosan complex nanofibers for tissue engineering and to develop functional biomaterials.
211 citations
••
TL;DR: The results indicated that collagen-chitosan-TPU blended nanofibrous scaffolds might be a potential candidate for vascular repair and nerve regeneration.
210 citations
••
TL;DR: Many important features, which are originally hidden in the long amino acid sequences, can be clearly displayed through their cellular automata images, and many image recognition tools can be straightforwardly applied to the target aimed here.
Abstract: The avalanche of newly found protein sequences in the post-genomic era has motivated and challenged us to develop an automated method that can rapidly and accurately predict the localization of an uncharacterized protein in cells because the knowledge thus obtained can greatly speed up the process in finding its biological functions. However, it is very difficult to establish such a desired predictor by acquiring the key statistical information buried in a pile of extremely complicated and highly variable sequences. In this paper, based on the concept of the pseudo amino acid composition (Chou, K. C. PROTEINS: Structure, Function, and Genetics, 2001, 43: 246-255), the approach of cellular automata image is introduced to cope with this problem. Many important features, which are originally hidden in the long amino acid sequences, can be clearly displayed through their cellular automata images. One of the remarkable merits by doing so is that many image recognition tools can be straightforwardly applied to the target aimed here. High success rates were observed through the self-consistency, jackknife, and independent dataset tests, respectively.
210 citations
••
Abstract: Emerging infectious diseases (EIDs) are a significant burden on global economies and public health. Most present personal protective equipment used to prevent EID transmission and infections is typically devoid of antimicrobial activity. We report on green bioprotective nanofibrous membranes (RNMs) with rechargeable antibacterial and antiviral activities that can effectively produce biocidal reactive oxygen species (ROS) solely driven by the daylight. The premise of the design is that the photoactive RNMs can store the biocidal activity under light irradiation and readily release ROS under dim light or dark conditions, making the biocidal function "always online." The resulting RNMs exhibit integrated properties of fast ROS production, ease of activity storing, long-term durability, robust breathability, interception of fine particles (>99%), and high bactericidal (>99.9999%) and virucidal (>99.999%) efficacy, which enabled to serve as a scalable biocidal layer for protective equipment by providing contact killing against pathogens either in aerosol or in liquid forms. The successful synthesis of these fascinating materials may provide new insights into the development of protection materials in a sustainable, self-recharging, and structurally adaptive form.
209 citations
••
TL;DR: In this paper, robust global stability analysis for generalized neural networks (GNNs) with both discrete and distributed delays is addressed. But the authors assume that the parameter uncertainties are time invariant and bounded, and belong to given compact sets.
Abstract: This paper is concerned with the problem of robust global stability analysis for generalized neural networks (GNNs) with both discrete and distributed delays. The parameter uncertainties are assumed to be time-invariant and bounded, and belong to given compact sets. The existence of the equilibrium point is first proved under mild conditions, assuming neither differentiability nor strict monotonicity for the activation function. Then, by employing a Lyapunov–Krasovskii functional, the addressed stability analysis problem is converted into a convex optimization problem, and a linear matrix inequality (LMI) approach is utilized to establish the sufficient conditions for the globally robust stability for the GNNs, with and without parameter uncertainties. These conditions can be readily checked by utilizing the Matlab LMI toolbox. A numerical example is provided to demonstrate the usefulness of the proposed global stability condition.
209 citations
Authors
Showing all 21321 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dongyuan Zhao | 160 | 872 | 106451 |
Xiang Zhang | 154 | 1733 | 117576 |
Seeram Ramakrishna | 147 | 1552 | 99284 |
Kuo-Chen Chou | 143 | 487 | 57711 |
Shuai Liu | 129 | 1095 | 80823 |
Chao Zhang | 127 | 3119 | 84711 |
Tao Zhang | 123 | 2772 | 83866 |
Zidong Wang | 122 | 914 | 50717 |
Xinchen Wang | 120 | 349 | 65072 |
Zhenyu Zhang | 118 | 1167 | 64887 |
Benjamin S. Hsiao | 108 | 602 | 41071 |
Qian Wang | 108 | 2148 | 65557 |
Jian Zhang | 107 | 3064 | 69715 |
Yan Zhang | 107 | 2410 | 57758 |
Richard B. Kaner | 106 | 557 | 66862 |