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Mingyang Zhang

Researcher at Aalto University

Publications -  109
Citations -  2821

Mingyang Zhang is an academic researcher from Aalto University. The author has contributed to research in topics: Neuroprotection & Computer science. The author has an hindex of 24, co-authored 82 publications receiving 1600 citations. Previous affiliations of Mingyang Zhang include China University of Political Science and Law & National University of Singapore.

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Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters

TL;DR: In this article, a modified model of the Human Factors Analysis and Classification System (HFACS) for collision accidents between a ship and an icebreaker in ice-covered waters is proposed, which helps to analyze ship collision reports.
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Necrostatin-1 Suppresses Autophagy and Apoptosis in Mice Traumatic Brain Injury Model

TL;DR: Results revealed that multiple cell death pathways participated in the development of TBI, and NEC-1 inhibited apoptosis and autophagy simultaneously, and these coactions may further explain how can NEC- 1 reduce TBI-induced tissue damage and functional deficits.
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Deep learning for autonomous ship-oriented small ship detection

TL;DR: Experimental results show that the proposed deep learning method is competent to generate sufficient informative small ship samples and can obtain significantly improved and robust results of small ship detection, and indicate that the method can be effectively applied to ensuring autonomous ship safety.
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Hydrogen Sulfide Offers Neuroprotection on Traumatic Brain Injury in Parallel with Reduced Apoptosis and Autophagy in Mice

TL;DR: Compared to TBI groups, H2S pretreatment had reduced brain edema, improved motor performance and ameliorated performance in Morris water maze test after TBI and the protective effect against TBI may be associated with regulating apoptosis and autophagy.
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A Big Data Analytics Method for the Evaluation of Ship - Ship Collision Risk reflecting Hydrometeorological Conditions

TL;DR: The proposed method may assist with the identification of critical scenarios in various voyages not currently accounted for by existing accident databases, the definition of commonly agreed risk criteria to set off alarms, and the estimation of risk profile over the life cycle of fleet operations.