590 research outputs found
Strategically positioning cooperators can facilitate the contagion of cooperation
No full textAbstractThe spreading of cooperation in structured population is a challenging problem which can be observed at different scales of social and biological organization. Generally, the problem is studied by evaluating the chances that few initial invading cooperators, randomly appearing in a network, can lead to the spreading of cooperation. In this paper we demonstrate that in many scenarios some cooperators are more influential than others and their initial positions can facilitate the spreading of cooperation. We investigate six different ways to add initial cooperators in a network of cheaters, based on different network-based measurements. Our research reveals that strategically positioning the initial cooperators in a population of cheaters allows to decrease the number of initial cooperators necessary to successfully seed cooperation. The strategic positioning of initial cooperators can also help to shorten the time necessary for the restoration of cooperation. The optimal ways in which the initial cooperators should be placed is, however, non-trivial in that it depends on the degree of competition, the underlying game, and the network structure. Overall, our results show that, in structured populations, few cooperators, well positioned in strategically chosen places, can spread cooperation faster and easier than a large number of cooperators that are placed badly.</jats:p
Identification of influential invaders in evolutionary populations
No full textThe identification of the most influential nodes has been a vibrant subject of research across the whole of network science. Here we map this problem to structured evolutionary populations, where strategies and the interaction network are both subject to change over time based on social inheritance. We study cooperative communities, which cheaters can invade because they avoid the cost of contributions that are associated with cooperation. The question that we seek to answer is at which nodes cheaters invade most successfully. We propose the weighted degree decomposition to identify and rank the most influential invaders. More specifically, we distinguish two kinds of ranking based on the weighted degree decomposition. We show that a ranking strategy based on negative-weighted degree allows to successfully identify the most influential invaders in the case of weak selection, while a ranking strategy based on positive-weighted degree performs better when the selection is strong. Our research thus reveals how to identify the most influential invaders based on statistical measures in dynamically evolving cooperative communities
Cooperation and social organization depend on weighing private and public reputations
No full text: To avoid exploitation by defectors, people can use past experiences with others when deciding to cooperate or not ('private information'). Alternatively, people can derive others' reputation from 'public' information provided by individuals within the social network. However, public information may be aligned or misaligned with one's own private experiences and different individuals, such as 'friends' and 'enemies', may have different opinions about the reputation of others. Using evolutionary agent-based simulations, we examine how cooperation and social organization is shaped when agents (1) prioritize private or public information about others' reputation, and (2) integrate others' opinions using a friend-focused or a friend-and-enemy focused heuristic (relying on reputation information from only friends or also enemies, respectively). When agents prioritize public information and rely on friend-and-enemy heuristics, we observe polarization cycles marked by high cooperation, invasion by defectors, and subsequent population fragmentation. Prioritizing private information diminishes polarization and defector invasions, but also results in limited cooperation. Only when using friend-focused heuristics and following past experiences or the recommendation of friends create prosperous and stable populations based on cooperation. These results show how combining one's own experiences and the opinions of friends can lead to stable and large-scale cooperation and highlight the important role of following the advice of friends in the evolution of group cooperation
supplementary_Figures – Supplemental material for The effect of methylprednisolone prophylaxis on inflammatory monocyte subsets and suppressive regulatory T cells of patients undergoing cardiopulmonary bypass
No full textSupplemental material, supplementary_Figures for The effect of methylprednisolone prophylaxis on inflammatory monocyte subsets and suppressive regulatory T cells of patients undergoing cardiopulmonary bypass by Xing Hao, Junyan Han, Hui Zeng, Hong Wang, Guoli Li, Chunjing Jiang, Zhichen Xing, Yu Hao, Feng Yang and Xiaotong Hou in Perfusion</p
Learning in adaptive networks: analytical and computational approaches
No full textThe dynamics on networks and the dynamics of networks are usually entangled with
each other in many highly connected systems, where the former means the evolution
of state and the latter means the adaptation of structure. In this thesis, we will study
the coupled dynamics through analytical and computational approaches, where the
adaptive networks are driven by learning of various complexities.
Firstly, we investigate information diffusion on networks through an adaptive voter
model, where two opinions are competing for the dominance. Two types of dynamics
facilitate the agreement between neighbours: one is pairwise imitation and the other is
link rewiring. As the rewiring strength increases, the network of voters will transform
from consensus to fragmentation. By exploring various strategies for structure adaptation
and state evolution, our results suggest that network configuration is highly influenced
by range-based rewiring and biased imitation. In particular, some approximation
techniques are proposed to capture the dynamics analytically through moment-closure
differential equations.
Secondly, we study an evolutionary model under the framework of natural selection.
In a structured community made up of cooperators and cheaters (or defectors), a
new-born player will adopt a strategy and reorganise its neighbourhood based on social
inheritance. Starting from a cooperative population, an invading cheater may spread
in the population occasionally leading to the collapse of cooperation. Such a collapse
unfolds rapidly with the change of external conditions, bearing the traits of a critical
transition. In order to detect the risk of invasions, some indicators based on population
composition and network structure are proposed to signal the fragility of communities.
Through the analyses of consistency and accuracy, our results suggest possible avenues
for detecting the loss of cooperation in evolving networks.
Lastly, we incorporate distributed learning into adaptive agents coordination, which
emerges as a consequence of rational individual behaviours. A generic framework of
work-learn-adapt (WLA) is proposed to foster the success of agents organisation. To
gain higher organisation performance, the division of labour is achieved by a series of
events of state evolution and structure adaptation. Importantly, agents are able to adjust
their states and structures through quantitative information obtained from distributed
learning. The adaptive networks driven by explicit learning pave the way for a better
understanding of intelligent organisations in real world
Learning in open adaptive networks
No full textWe propose a generic distributed learn-and-adapt model for high performance and high resilience configuration of open cooperative agent networks. Agents are involved into three interconnected types of activities. Firstly, agents bid for participation to the processing of a steady random flow of structured tasks. Secondly, agents learn the (exogenous) features of the random task source, by aggregating local information (such as success rates, average load, etc). And, thirdly, agents adapt the composition of their neighbourhoods following the (endogenous) targets set by their learning process. Neighbourhood readjustment proceeds by judicious rewiring steps which stay entirely local. Thus an agent continuously works, adjusts its neighbourhood, and based on his local metrics, learns how to inflect its own adaptation targets. Because of this tight coupling of all three activities, the network as a whole can reconfigure in a fully decentralized way to cope with changes in: the network composition (node failures, new incoming nodes, etc), and the parameters of the task source (changes in the size, structure, and frequency), while attaining robustly a near-optimal performance level (compared to the centralised solution)
Cultural identities as reflected in the literature of the Northern and Southern dynasties period (4th-6th centuries A.D.)
No full textDuring the period of the Northern and Southern dynasties of China identity questions became serious in a society thrown into disorder by political, religious and ethnic problems. This thesis uses three books written in the sixth century to
discuss how educated Chinese faced identity problems and how they dealt with them.
The Buddhist monk Huijiao, dealt with the problems of sinifying a foreign religion. He constructed many different identities in addition to the Buddhist one for the monks in his book Gaoseng zhuan, (Lives of Eminent Monks), a collection of biographies of Buddhist monks, to bring Buddhism closer to Chinese tradition and more acceptable by Confucian standards. Through the identity construction he
also made responses to anti-Buddhist ideas.
Yang Xuanzhi's Luoyang qielan ji, (Record of the Monasteries of Luoyang), deals with the identity problems of Chinese officials serving a Xianbei regime in
the north and of the short-lived capital of the Northern Wei in Luoyang. Yang reconstructed a Chinese identity for the lost capital as a true heir of Chinese tradition, as were the emperors, princes and officials who lived there. He created an identity defined not by ethnicity but by culture.
Yan Zhitui's Tanshi jiaxun, (Family Instruction of the Yan Clan), is a book which tells his descendants how to construct and maintain the future identity of his
own family. He drew on his own experience of recovering from repeated political catastrophes to set out an identity that would help the family to survive disordered times and maintain their status in society
Supplemental Material - Running ahead of evolution—AI-based simulation for predicting future high-risk SARS-CoV-2 variants
No full textSupplemental Material for Running ahead of evolution—AI-based simulation for predicting future high-risk SARS-CoV-2 variants by Jie Chen, Zhiwei Nie, Yu Wang, Kai Wang, Fan Xu, Zhiheng Hu, Bing Zheng, Zhennan Wang, Guoli Song, Jingyi Zhang, Jie Fu, Xiansong Huang, Zhongqi Wang, Zhixiang Ren, Qiankun Wang, Daixi Li, Dongqing Wei, Bin Zhou, Chao Yang, and Yonghong Tian in The International Journal of High-Performance Computing Applications</p
Author Correction: A novel microRNA signature predicts survival in liver hepatocellular carcinoma after hepatectomy
No full textA correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.</jats:p
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