Cooperative Clusters Research Articles

Thickness-Dependent Segmental Dynamics in Supported Thin Films: Insights from a Dynamically Correlated Network Model.

A large body of experimental studies shows that the local dynamics in supercooled liquids are significantly altered by spatial nanoconfinement. In a previous study, we proposed a concept of a dynamically correlated network (DCN) model, which assumes that segments in a supercooled liquid undergo cooperative rearrangements within a network-like cluster. We further demonstrated that a model modified for freestanding thin films can predict for the glass transition dynamics in atactic polystyrene (PS) films consistent with experimental results. In this study, we adapted the model to apply it to supported thin films by introducing a layer of virtual vacant segments at the free surface and virtual anchoring segments at the liquid/substrate interface. The latter segments, carrying a finite number of virtual segments, reduce mobility at the interface. We evaluated the cooperative cluster size and distribution with respect to temperature and film thickness, along with the average relaxation time and glass transition temperature Tg for supported thin films of PS. The model predicted that the thickness dependence of Tg for PS becomes stronger with increasing time scale, and this result agreed well with experimental data across different timescales from pseudothermodynamic and dynamic measurements. The results provide insights into the origin of the dynamical decoupling between pseudothermodynamic and dynamic glass transition behaviors.

Low-latency intelligent service combination caching strategy with density peak clustering algorithm in vehicle edge computing

In the dynamic field of Vehicle Edge Computing (VEC), the demand for intelligent vehicular systems to process vast amounts of data is escalating, driven by advancements in autonomous driving and real-time navigation technologies. Optimizing service latency and minimizing transmission costs are crucial for enhancing the performance of vehicular networks. Traditional service caching strategies, which largely rely on the popularity of individual services, often fail to account for the intricate interdependencies between services. The oversight can result in redundant data transfers and inefficient use of storage resources. In response, our paper introduces a novel approach to service combination caching within a heterogeneous computational framework comprising vehicles, edge servers, and the cloud. Our strategy focuses on minimizing user wait times and data transmission costs during task execution, while adhering to the caching budget constraints of service providers. Key contributions include the development of an Improved Density Peak Clustering (IDPC) algorithm to facilitate cooperative clustering among edge servers and the design of a Service Combination Caching Strategy (SCCS). The SCCS approach reduces caching costs by categorizing servers, forming efficient clusters, and strategically allocating storage. Simulation results demonstrate that the method outperforms existing strategies by significantly decreasing task execution delays and transmission costs, thereby greatly enhancing the quality of service in vehicular applications.

Evolution of cooperation with the diversity of cooperation tendencies

The complete cooperation and the complete defection are two typical strategies considered in evolutionary games in many previous works. However, in real life, strategies of individuals are full of variety rather than only two complete ones. In this work, the diversity of strategies is introduced into the weak prisoners’ dilemma game, which is measured by the diversity of the cooperation tendency. A greater diversity means more cooperation tendencies are provided. The complete cooperation strategy is the full cooperation tendency and the complete defection strategy is without any cooperation tendency. Agents with other cooperation tendencies are partial cooperative and defective. The numerical simulation shows that increasing the diversity of the cooperation tendency promotes the cooperation level, not only the number of cooperators but also the average tendency over the whole population, until the diversity reaches its saturated value. Furthermore, our work points out maintaining cooperation is based on the cooperation efficiency. When cooperator clusters can survive the cooperation efficiency slightly oscillates around its equilibrium. When cooperator clusters cannot resist the invasion of defectors the cooperation efficiency oscillates and quickly decreases to zero. The observations above is not only applied on the weak prisoner’s dilemma but also the snowdrift game. When the effect of the noise for the Femi update mechanism is considered, a greater diversity of strategies not only improves the cooperation level of the whole population but also supports the survival of more rational agents.

Asymmetric population promotes and jeopardizes cooperation in spatial prisoner’s dilemma game

The evolution of cooperation in asymmetric populations has recently garnered widespread attention. In this study, we propose a new asymmetric model to explore the impact of asymmetric behavior on cooperation evolution. Our model assumes that weak players are always forced to cooperate when interacting with strong players, while strong players always receive the temptation payoff. When encountering peers from the same category, players engage in a prisoner’s dilemma game, differing only in the intensity of the dilemma between population categories. Results suggest that in scenarios where traditional network reciprocity can support cooperation, asymmetric interactions between strong and weak players undermine this reciprocity and jeopardize the maintenance of cooperation. Conversely, in scenarios where traditional network reciprocity fails to support cooperation, asymmetric interactions enable strong players to leverage weak cooperative clusters to establish cooperation. However, as the prevalence of asymmetric interactions increases, it becomes detrimental to cooperation within the weak player subgroups, thus undermining overall cooperation. These findings contribute to a deeper understanding of how asymmetry impacts cooperation.

Visual analysis of hot spots and trends in research of meteorology and hemorrhagic fever with renal syndrome: a bibliometric analysis based on CiteSpace and VOSviewer

Objective: We here displayed the global research trends of meteorology and hemorrhagic fever with renal syndrome (HFRS) as a visual knowledge map by using bibliometrics and revealed the research directions, hotspots, trends, and frontiers in this field.Methods: Using Web of Science core collection as the data source and with CiteSpace and VOSviewer software, we collected and analyzed the annual number of papers, cooperative relationships (countries, institutions, authors, etc.), citations (literature citation, literature co-citation, literature publication, etc.), keywords (emergence, clustering, etc.) of meteorology, and HFRS-related research data for the past 30 years, and drew a visual map.Results: In total, this study included 313 papers investigating the relationship between meteorology and HFRS. The first paper was published in 1992. Globally, United States had the largest number of publications in this field, and the Chinese Center for Disease Control and Prevention was the most influential institution conducting related research (20 articles published, and the mediation centrality was 0.24). Several small author cooperation clusters were formed; however, the number of papers published by the same scholar and the co-citation frequency were low. Cazelles Bernard (7 articles) published the highest number of articles in this field, and Gubler DJ was the author with the most co-citations (55 times). The most frequently cited journal was Emerging Infectious Diseases. In this field, the top three high-frequency keywords were “hemorrhagic fever,” “transmission,” and “temperature.” According to keyword cluster analysis, the top three themes were dengue, dechlorane plus, and bank voles. The timeline spectrum exhibited that dengue clustering had a good temporal continuity. The trend analysis of emergent words revealed that the research on “temperature,” “meteorological factors” and “Puumala hantavirus” has gradually appeared in recent years.Conclusion: This study represents the first comprehensive exploration of global trends, hotspots, frontiers, and developments in the relationship between meteorology and HFRS, utilizing CiteSpace and VOSviewer software. The findings of this study are crucial for elucidating the influence of climate change on disease transmission patterns and offering novel insights for forthcoming epidemiological research and public health interventions.

Temporal interaction and its role in the evolution of cooperation.

This research investigates the impact of dynamic, time-varying interactions on cooperative behavior in social dilemmas. Traditional research has focused on deterministic rules governing pairwise interactions, yet the impact of interaction frequency and synchronization in groups on cooperation remains underexplored. Addressing this gap, our work introduces two temporal interaction mechanisms to model the stochastic or periodic participation of individuals in public goods games, acknowledging real-life variances due to exogenous temporal factors and geographical time differences. We consider that the interaction state significantly influences both game payoff calculations and the strategy updating process, offering new insights into the emergence and sustainability of cooperation. Our results indicate that maximum game participation frequency is suboptimal under a stochastic interaction mechanism. Instead, an intermediate activation probability maximizes cooperation, suggesting a vital balance between interaction frequency and inactivity security. Furthermore, local synchronization of interactions within specific areas is shown to be beneficial, as time differences hinder the spread of cross-structures but promote the formation of dense cooperative clusters with smoother boundaries. We also note that stronger clustering in networks, larger group sizes, and lower noise increase cooperation. This research contributes to understanding the role of node-based temporality and probabilistic interactions in social dilemmas, offering insights into fostering cooperation.

The evolution of cooperation and global synchronization in the evolutionary Kuramoto dilemma combined with the prisoner's dilemma

In this work, we have studied the evolution of the cooperation and the global synchronization on the Kuramoto model upon random networks with two games, in which one is the evolutionary Kuramoto dilemma and the other is the weak prisoner's dilemma. Agents can gain their payoffs from these two games synchronously. In the evolutionary Kuramoto game, cooperators prefer the formation of local synchronization but pay less cooperative cost. Cooperators in weak prisoner's dilemma can form cooperator clusters because of the network reciprocity. Combining these two games shows a mutual promotion effect upon the order of the global synchronization but a competition effect on the cooperation level. The global synchronization begins to rise only when most agents choose cooperation. It is manifested by the fact that the optimal coupling strength for the highest cooperation level is smaller than that for the highest synchronization level. The high cooperation cost makes defection the most advantageous strategy when the coupling strength reaches rather high, which diminishes the effect of cooperator clusters, and ultimately results in the absence of both cooperators and global synchronization. When agents have more neighbors in the random network, it is observed that cooperation is consistently hindered unless the coupling strength is relatively small. Additionally, there is always an optimal average degree that allows for global synchronization.

Intermediate Intercluster Bond Orders. Electronic Communication in Au38(SR)24 Superatomic Molecules.

Ligand-protected gold clusters remain potential building blocks for envisaged molecular materials. The archetypal Au38(SR)24 cluster can be viewed as a robust template for the fusion of two Au25(SR)18 - cluster units, retaining a bi-icosahedral Au23 core. Via electrochemical properties, the overall charge state can be selectively tuned, enabling the access of 14 valence electron (ve) species featuring a single intercluster bond and nearby charge from -1 to +3, achieving related species bearing 15- to 11-ve with variable intercluster bond orders. Here, we explore the characteristics of intermediate intercluster bond orders in order to provide insights into the plausible electron communication between the constituent building blocks, with Au38(SR)24, as a representative template. Our results denote a small structural variation along -1 to +3 charge states, provided by the core-protecting ligand interaction, which is enhanced towards more oxidized species. The remaining unpaired electron from intermediate intercluster bond orders of 1.5 for Au38(SR)24 1-, 1.5 for Au38(SR)24 1+, and 2.5 for Au38(SR)24 3+, holds delocalized characteristics between the building block units, favoring electron communication for conductive and cooperative cluster aggregates. Such features are relevant for the formation of molecular electronic device applications, favoring the rationalization prior to engaging in explorative synthesis of larger ligand-protected cluster aggregates.

The impact of dynamic linking on cooperation on complex networks.

In complex social systems, individual relationships and the surrounding environment are constantly changing, allowing individuals to interact on dynamic networks. This study aims to investigate how individuals in a dynamic network engaged in a prisoner's dilemma game adapt their competitive environment through random edge breaks and reconnections when faced with incomplete information and adverse local conditions, thereby influencing the evolution of cooperative behavior. We find that random edge breaks and reconnections in dynamic networks can disrupt cooperative clusters, significantly hindering the development of cooperation. This negative impact becomes more pronounced over larger time scales. However, we also observe that nodes with higher degrees of connectivity exhibit greater resilience to this cooperation disruption. Our research reveals the profound impact of dynamic network structures on the evolution of cooperation and provides new insights into the mechanisms of cooperation in complex systems.

Emergence of cooperation under punishment: A reinforcement learning perspective.

Punishment is a common tactic to sustain cooperation and has been extensively studied for a long time. While most of previous game-theoretic work adopt the imitation learning framework where players imitate the strategies of those who are better off, the learning logic in the real world is often much more complex. In this work, we turn to the reinforcement learning paradigm, where individuals make their decisions based upon their experience and long-term returns. Specifically, we investigate the prisoners' dilemma game with a Q-learning algorithm, and cooperators probabilistically pose punishment on defectors in their neighborhood. Unexpectedly, we find that punishment could lead to either continuous or discontinuous cooperation phase transitions, and the nucleation process of cooperation clusters is reminiscent of the liquid-gas transition. The analysis of a Q-table reveals the evolution of the underlying "psychologic" changes, which explains the nucleation process and different levels of cooperation. The uncovered first-order phase transition indicates that great care needs to be taken when implementing the punishment compared to the continuous scenario.

Promoting cooperation through dynamic trustworthiness in spatial public goods games

The established imitation protocol mandates that participants observe and learn strategies from the most successful individuals in their vicinity. Previous studies have highlighted the critical role of this protocol in understanding the mechanisms that drive the evolution of cooperation. Nevertheless, individuals often exhibit a natural reluctance to adopt substantial changes rapidly. In this context, we integrate the concept of investment trustworthiness into the strategy updating process and explore the outcomes of dynamic beliefs through numerical simulations. Our results demonstrate that dynamic trustworthiness significantly supports cooperation. Cooperators impede the incursion of defectors by progressively reducing their willingness to invest, thus fostering the formation of cooperative clusters. Our findings suggest that while sensitivity to higher payoffs bolsters cooperation, a tempered response to negative payoffs is advantageous. Additionally, the initial distribution of willingness is pivotal for the success of this dynamic. Our study expands the repertoire of strategy update techniques in investigating the evolution of cooperation and offers profound insights into the complexities of human cooperative behaviour.

Enhancing social cohesion with cooperative bots in societies of greedy, mobile individuals.

Addressing collective issues in social development requires a high level of social cohesion, characterized by cooperation and close social connections. However, social cohesion is challenged by selfish, greedy individuals. With the advancement of artificial intelligence (AI), the dynamics of human-machine hybrid interactions introduce new complexities in fostering social cohesion. This study explores the impact of simple bots on social cohesion from the perspective of human-machine hybrid populations within network. By investigating collective self-organizing movement during migration, results indicate that cooperative bots can promote cooperation, facilitate individual aggregation, and thereby enhance social cohesion. The random exploration movement of bots can break the frozen state of greedy population, help to separate defectors in cooperative clusters, and promote the establishment of cooperative clusters. However, the presence of defective bots can weaken social cohesion, underscoring the importance of carefully designing bot behavior. Our research reveals the potential of bots in guiding social self-organization and provides insights for enhancing social cohesion in the era of human-machine interaction within social networks.

A Bibliometrics Analysis Related to the Built Environment and Walking

The built environment and walking are hot topics in human settlement environment and health. It is essential for both built environment and walking research to clarify the knowledge base, development context, and cooperation network, and to explore the cutting-edge hot spots and development trends. We collected research data from the Web of Science core collection database. This study used analysis techniques including country and institution cooperation networks, keyword co-occurrences, burst keywords, reference co-citations, and cluster analysis to systematically analyze the built environment and walking research. The study found that research on built environment and walking was developed in the United States, Australia, and Canada. Then, it was carried out in Asian countries. Current research on the built environment and walking has multiple research themes. Among them, walkability is a common content covered by various research themes. Research based on street view environment is the latest hot research and there are still a lot of gaps in combining traditional topics with it. This research provides new directions and theoretical references for the built environment and walking research scholars and policymakers.

Conformity poses a double-edged sword effect on the evolution of cooperation within heterogeneous endowment populations

Understanding the emergence and maintenance of cooperation is crucial for social development, particularly in the context of contemporary wealth inequality. However, the prevalent phenomenon of individual conformity in humans and social animals is often overlooked in the presence of heterogeneous endowments. Motivated by these considerations, we investigate the impact of conformists on cooperation within the population characterized by binary heterogeneous endowments. Our results reveal that the presence of conformists in a population can influence payoff-driven individuals. These conformists can catalyze the establishment of cooperation across rich and poor individuals, enhancing network reciprocity when the multiplication factor is high (i.e., the degree of cooperation synergy is high), but act as Trojan horses eroding cooperation clusters centered around rich cooperators under a low multiplication factor, thus exhibiting a double-edged sword impact on cooperation. Furthermore, consistent results are observed when accounting for individual conformity biases and multiplayer public goods game. Our research findings reveal the impact of conformity-driven behavior on cooperation in the context of heterogeneous endowments, contributing to a more comprehensive understanding of cooperative evolution amidst inequality.

C-terminal Domain of T4 gene 32 Protein Enables Rapid Filament Reorganization and Dissociation

Bacteriophage T4 gene 32 protein (gp32) is a single-stranded DNA (ssDNA) binding protein essential for DNA replication. gp32 forms stable protein filaments on ssDNA through cooperative interactions between its core and N-terminal domain. gp32′s C-terminal domain (CTD) is believed to primarily help coordinate DNA replication via direct interactions with constituents of the replisome. However, the exact mechanisms of these interactions are not known, and it is unclear how tightly-bound gp32 filaments are readily displaced from ssDNA as required for genomic processing. Here, we utilized truncated gp32 variants to demonstrate a key role of the CTD in regulating gp32 dissociation. Using optical tweezers, we probed the binding and dissociation dynamics of CTD-truncated gp32, *I, to an 8.1 knt ssDNA molecule and compared these measurements with those for full-length gp32. The *I-ssDNA helical filament becomes progressively unwound with increased protein concentration but remains significantly more stable than that of full-length, wild-type gp32. Protein oversaturation, concomitant with filament unwinding, facilitates rapid dissociation of full-length gp32 from across the entire ssDNA segment. In contrast, *I primarily unbinds slowly from only the ends of the cooperative clusters, regardless of the protein density and degree of DNA unwinding. Our results suggest that the CTD may constrain the relative twist angle of proteins within the ssDNA filament such that upon critical unwinding the cooperative interprotein interactions largely vanish, facilitating prompt removal of gp32. We propose a model of CTD-mediated gp32 displacement via internal restructuring of its filament, providing a mechanism for rapid ssDNA clearing during genomic processing.

A comprehensive literature review of the digital business ecosystem and digital business model with comparison in China, Japan and South Korea

ABSTRACT Digitalization has led to new value co-creation networks in the form of digital business ecosystems and digital business models. This paper systematically analyses the research on digital business ecosystems and digital business models by applying the bibliometric analysis method to investigate current research on cooperation networks and clusters. We have found that the current research can be mainly divided into the following topics: the adoption of digital technologies, digital innovation and digital transition, platforms and the sharing economy, dynamic capabilities and sustainable development. Additionally, we further analyse future research directions and compare research hotspots in the Asia Pacific region.

C4O: chain-based cooperative clustering using coati optimization algorithm in WSN

In order to provide sensing services to low-powered IoT devices, wireless sensor networks (WSNs) organize specialized transducers into networks. Energy usage is one of the most important design concerns in WSN because it is very hard to replace or recharge the batteries in sensor nodes. For an energy-constrained network, the clustering technique is crucial in preserving battery life. By strategically selecting a cluster head (CH), a network's load can be balanced, resulting in decreased energy usage and extended system life. Although clustering has been predominantly used in the literature, the concept of chain-based clustering has not yet been explored. As a result, in this paper, we employ a chain-based clustering architecture for data dissemination in the network. Furthermore, for CH selection, we employ the coati optimisation algorithm, which was recently proposed and has demonstrated significant improvement over other optimization algorithms. In this method, the parameters considered for selecting the CH are energy, node density, distance, and the network’s average energy. The simulation results show tremendous improvement over the competitive cluster-based routing algorithms in the context of network lifetime, stability period (first node dead), transmission rate, and the network's power reserves.

Refined Dynamic Event-Triggering Cluster Consensus of Multiagent Systems With Fixed/Switching Topology.

This article is concerned with cluster consensus control of multiagent systems (MASs) with the fixed/switching topology under a dynamic event-trigger (DET) mechanism. A refined sampled-data-based DET scheme is proposed by introducing two dynamically adjusting threshold parameters to distinguish the different transmission requirements for neighboring agents intra and outer cluster. Faced with the difficulties of acquiring full state information among spatially distributed agents, output feedback is employed to construct cooperative control protocols. Both fixed and switching topologies are considered to execute the designed DET-based cooperative cluster consensus control protocols. By constructing appropriate Lyapunov-Krasovskii functionals (LKFs), some sufficient criteria in terms of matrix inequalities for the cluster consensus of MASs are derived, which can ensure that the error system with the proposed DET-based control strategy is asymptotically stable. Facing the nonconvex issue induced by output feedback, a particle swarm optimization (PSO)-based control design algorithm is novelly developed to calculate the control gains and event-triggering parameters jointly based on the derived stability criteria. The elements of the matrix variables are valued stochastically in certain ranges and the fitness function is designed as the accumulation of the weighting value of each matrix inequality. Finally, an application of multiple satellites formation flying is applied to numerically illustrate the effectiveness of the cluster consensus control strategy with the designed DET mechanism.

Complex pathways to cooperation emergent from asymmetry in heterogeneous populations.

Cooperation within asymmetric populations has garnered significant attention in evolutionary games. This paper explores cooperation evolution in populations with weak and strong players, using a game model where players choose between cooperation and defection. Asymmetry stems from different benefits for strong and weak cooperators, with their benefit ratio indicating the degree of asymmetry. Varied rankings of parameters including the asymmetry degree, cooperation costs, and benefits brought by weak players give rise to scenarios including the prisoner's dilemma (PDG) for both player types, the snowdrift game (SDG), and mixed PDG-SDG interactions. Our results indicate that in an infinite well-mixed population, defection remains the dominant strategy when strong players engage in the prisoner's dilemma game. However, if strong players play snowdrift games, global cooperation increases with the proportion of strong players. In this scenario, strong cooperators can prevail over strong defectors when the proportion of strong players is low, but the prevalence of cooperation among strong players decreases as their proportion increases. In contrast, within a square lattice, the optimum global cooperation emerges at intermediate proportions of strong players with moderate degrees of asymmetry. Additionally, weak players protect cooperative clusters from exploitation by strong defectors. This study highlights the complex dynamics of cooperation in asymmetric interactions, contributing to the theory of cooperation in asymmetric games.

Agricultural clusters: formation of food resources in Kazakhstan

Goal - main problems of ensuring food security in Kazakhstan, formation and development of agricultural clusters as a strategic direction of agriculture in the republic are considered. Methods – empirical methods of research, analysis, synthesis, comparative characteristics, generalization were used. Results - the authors indicate that agro-clusters, by facilitating cooperation between stakeholders, play a key role in diversifying agricultural production, reducing post-harvest losses and improving access to markets. From environmental and economic perspective, they are an effective integration structure that allows one to gain a competitive advantage. The realization of agricultural potential is possible through the strengthening of cooperative principles and clustering of the agricultural sector. Cluster management will be aimed at creating conditions for the active use of innovations in technology, management, marketing, as well as to increase the competitiveness of the agricultural sector. The main objectives of the long-term cluster policy are: stabilization of the development of AIC; increasing the share of products and services in the total volume of gross output and exports; increasing the investment attractiveness of the agricultural industry; creating favorable conditions for business activity in rural areas; increasing employment, income and quality of life of the rural population. Based on a detailed study of these issues, conclusions were drawn: the practice of spreading agricultural clusters is significantly influenced by improving the legislative framework, eliminating barriers to internal competition, promoting the expansion of sales markets, and creating specialized training programs. When creating agricultural clusters, national and regional interests must be taken into account; they become driving forces in solving issues of food supply for the region and the country as a whole.