Iskanje po katalogu digitalne knjižnice

Opis: The 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.
Ključne besede: theoretical biology, evolution, agent-based modeling, complex system, network science, evolutionary game theory
Objavljeno v DKUM: 26.02.2025; Ogledov: 0; Prenosov: 4
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Opis: The spreading of cooperation in structured population is a challenging problem which can be observed at diferent 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 infuential than others and their initial positions can facilitate the spreading of cooperation. We investigate six diferent ways to add initial cooperators in a network of cheaters, based on diferent 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.
Ključne besede: cooperation, evolutionary game theory, social physics, collective dynamics, complex system
Objavljeno v DKUM: 22.10.2024; Ogledov: 0; Prenosov: 3
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Opis: In 2020, the CoViD-19 pandemic spread worldwide in an unexpected way and suddenly modified many life issues, including social habits, social relationships, teaching modalities, and more. Such changes were also observable in many different healthcare and medical contexts. Moreover, the CoViD-19 pandemic acted as a stress test for many research endeavors, and revealed some limitations, especially in contexts where research results had an immediate impact on the social and healthcare habits of millions of people. As a result, the research community is called to perform a deep analysis of the steps already taken, and to re-think steps for the near and far future to capitalize on the lessons learned due to the pandemic. In this direction, on June 09th–11th, 2022, a group of twelve healthcare informatics researchers met in Rochester, MN, USA. This meeting was initiated by the Institute for Healthcare Informatics—IHI, and hosted by the Mayo Clinic. The goal of the meeting was to discuss and propose a research agenda for biomedical and health informatics for the next decade, in light of the changes and the lessons learned from the CoViD-19 pandemic. This article reports the main topics discussed and the conclusions reached. The intended readers of this paper, besides the biomedical and health informatics research community, are all those stakeholders in academia, industry, and government, who could benefit from the new research findings in biomedical and health informatics research. Indeed, research directions and social and policy implications are the main focus of the research agenda we propose, according to three levels: the care of individuals, the healthcare system view, and the population view.
Ključne besede: biomedical and health informatics, artificial intelligence in medicine, research trends, CoViD-19
Objavljeno v DKUM: 03.04.2024; Ogledov: 333; Prenosov: 240
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Opis: On 5 October 2015, the Trans-Pacific Partnership Agreement (TPP) led by the U.S. was signed. Already, 12 countries1 have joined the agreement, but China has not. Thus, lots of research has focused on the negative effect of the TPP on China’s foreign trade. On the other hand, China is moving forward in its own efforts to establish bilateral free trade agreements (FTAs) and free trade zones. In June 2015, China-South Korea and China-Australia signed bilateral FTAs which went into effect in December 2015. Several questions were raised: Since South Korea and Australia are the major trade partners in the Pacific area and the bilateral FTAs will be effective before the TPP, will these FTAs’ positive effects on China’s foreign trade offset some of the negative effects of the TPP? If China and the U.S. adopted a competitive trade policy, which countries would benefit? If China and the U.S. adopted a cooperative trade policy, how would the trade value and economic welfare change? This paper simulates and analyses the mutual effects of China-South Korea and China-Australia FTAs and the enlarging TPP using the computable general equilibrium model. The major conclusions drawn suggest that China-South Korea and China-Australia FTAs will significantly offset the TPP’s negative effect on China’s foreign trade. If China is not included, the U.S. economic benefit from the TPP will be limited. The economic welfare for a country like Australia, which joined both the bilateral FTA and the TPP, will be increased the most. In the long run, China joining the TPP would be the most beneficial decision for its national interest. However, if the TPP cannot be approved by the US congress, the U.S.’s economic indicators and export would be decreasing sharply. China’s economy and export will benefit from FTAs.
Ključne besede: China-South Korea FTA, China-Australia FTA, TPP, interaction effects
Objavljeno v DKUM: 03.05.2018; Ogledov: 1175; Prenosov: 306
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Opis: The significant development of the Internet has posed some new challenges and many new programming tools have been developed to address such challenges. Today, semantic web is a modern paradigm for representing and accessing knowledge data on the Internet. This paper tries to use the semantic tools such as resource definition framework (RDF) and RDF query language (SPARQL) for the optimization purpose. These tools are combined with particle swarm optimization (PSO) and the selection of the best solutions depends on its fitness. Instead of the local best solution, a neighborhood of solutions for each particle can be defined and used for the calculation of the new position, based on the key ideas from semantic web domain. The preliminary results by optimizing ten benchmark functions showed the promising results and thus this method should be investigated further.
Ključne besede: resource definition framework, SPARQL, best solutions, RDF, PSO
Objavljeno v DKUM: 15.06.2017; Ogledov: 1658; Prenosov: 438
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