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Institution

Beijing Union University

EducationBeijing, China
About: Beijing Union University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Artificial neural network & Tourism. The organization has 3497 authors who have published 3299 publications receiving 20837 citations.


Papers
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Journal ArticleDOI
TL;DR: This paper might be the first attempt to present a comprehensive literature review on different types of big data in tourism research, and facilitates a thorough understanding of this sunrise research and offers valuable insights into its future prospects.

585 citations

Journal ArticleDOI
TL;DR: The study uses citation analysis to detect and visualize disciplinary distributions, keyword co-word networks and journal cocitation networks, highly cited references, as well as highly cited authors to identify intellectual turning points, pivotal points and emerging trends, in innovation systems system research from 1975 to 2012.
Abstract: Despite increasing awareness of the need to trace the trajectory of innovation system research, so far little attention has been given to quantitative depiction of the evolution of this fast-moving research field. This paper uses CiteSpace to demonstrate visually intellectual structures and developments. The study uses citation analysis to detect and visualize disciplinary distributions, keyword co-word networks and journal cocitation networks, highly cited references, as well as highly cited authors to identify intellectual turning points, pivotal points and emerging trends, in innovation systems system research from 1975 to 2012.

287 citations

Journal ArticleDOI
TL;DR: A decentralized security model based on the lightning network and smart contract in the blockchain ecosystem is proposed and can be easily integrated with current scheduling mechanisms to enhance the security of trading between EVs and charging piles.
Abstract: The Internet of Energy (IoE) provides an effective networking technology for distributed green energy, which allows the connection of energy anywhere at any time. As an important part of the IoE, electric vehicles (EVs), and charging pile management are of great significance to the development of the IoE industry. Previous work has mainly focused on network performance optimization for its management, and few studies have considered the security of the management between EVs and charging piles. Therefore, this paper proposes a decentralized security model based on the lightning network and smart contract in the blockchain ecosystem; this proposed model is called the lightning network and smart contract (LNSC). The overall model involves registration, scheduling, authentication, and charging phases. The new proposed security model can be easily integrated with current scheduling mechanisms to enhance the security of trading between EVs and charging piles. Experimental results according to a realistic infrastructure are presented in this paper. These experimental results demonstrate that our scheme can effectively enhance vehicle security. Different performances of LNSC-based scheduling strategies are also presented.

261 citations

Journal ArticleDOI
TL;DR: This phenomenon and its underlying causes are analyzed and practical solutions are suggested to limit discrimination and prejudice driven by fear or misinformation jeopardizing anti-severe acute respiratory syndrome coronavirus 2 efforts.
Abstract: The current corona virus disease 2019 outbreak caused by severe acute respiratory syndrome coronavirus 2 started in Wuhan, China in December 2019 and has put the world on alert. To safeguard Chinese citizens and to strengthen global health security, China has made great efforts to control the epidemic. Many in the global community have joined China to limit the epidemic. However, discrimination and prejudice driven by fear or misinformation have been flowing globally, superseding evidence and jeopardizing the anti-severe acute respiratory syndrome coronavirus 2 efforts. We analyze this phenomenon and its underlying causes and suggest practical solutions.

250 citations

Journal ArticleDOI
TL;DR: How Abeta accumulates, how tau protein is hyperphosphorylated, and how accumulated Abeta initiates hyperph phosphorylation of tauprotein in AD are discussed.
Abstract: The neuropathology associated with Alzheimer's disease (AD) is characterized by the presence of extracellularly neuritic plaques, intracellularly neurofibrillary tangles and the loss of basal forebrain cholinergic neurons. The neuritic plaque is composed of a core of amyloid-beta peptide (Abeta) while the neurofibrillary tangles contain phosphorylated tau protein, and, as such, both Abeta and tau are important molecules associated with AD. In healthy human bodies, clearance mechanisms for Abeta are available; yet if clearance fails, Abeta accumulates, increasing the risk of neurotoxicity in the brain. Tau, one of the main microtubule-associated proteins, will be hyperphosphorylated and lose the ability to bind microtubules when the homeostasis of phosphorylation and dephosphorylation is disturbed in neurons. Accumulated Abeta and hyperphosphorylated tau are thought to be coexistent. Research on the pathological changes in AD indicates that accumulated Abeta in vivo may initiate the hyperphosphorylation of tau. Also, the signal transduction pathways of tau hyperphosphorylation may be related to accumulated Abeta. In this review, we will discuss how Abeta accumulates, how tau protein is hyperphosphorylated, and how accumulated Abeta initiates hyperphosphorylation of tau protein in AD.

245 citations


Authors

Showing all 3506 results

NameH-indexPapersCitations
Xin Zhang87171440102
Ping Wu483518247
Yan Zhang413986669
Wei Wei331846528
Yanling Cheng331094292
IpKin Anthony Wong291212761
Peng Wang251861950
Yunchuan Sun251362538
Bo Meng25662177
Clark Hu25572668
Wenhao Li22701366
Yang Liu19271051
Cheng Xu171001130
Shiliang Jia1520545
Yanzhen Zhang1419547
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
202220
2021269
2020250
2019188
2018159