Fence-sitters Protect Cooperation in Complex Networks

Evolutionary game theory is one of the key paradigms behind many scientific disciplines from science to engineering. In complex networks, because of the difficulty of formulating the replicator dynamics, most of previous studies are confined to a numerical level. In this paper, we introduce a vectorial formulation to derive three classes of individuals' payoff analytically. The three classes are pure cooperators, pure defectors, and fence-sitters. Here, fence-sitters are the individuals who change their strategies at least once in the strategy evolutionary process. As a general approach, our vectorial formalization can be applied to all the two-strategies games. To clarify the function of the fence-sitters, we define a parameter, payoff memory, as the number of rounds that the individuals' payoffs are aggregated. We observe that the payoff memory can control the fence-sitters' effects and the level of cooperation efficiently. Our results indicate that the fence-sitters' role is nontrivial in the complex topologies, which protects cooperation in an indirect way. Our results may provide a better understanding of the composition of cooperators in a circumstance where the temptation to defect is larger.Comment: an article with 6 pages, 3 figure

Emergence of Cooperation in Non-scale-free Networks

Evolutionary game theory is one of the key paradigms behind many scientific disciplines from science to engineering. Previous studies proposed a strategy updating mechanism, which successfully demonstrated that the scale-free network can provide a framework for the emergence of cooperation. Instead, individuals in random graphs and small-world networks do not favor cooperation under this updating rule. However, a recent empirical result shows the heterogeneous networks do not promote cooperation when humans play a Prisoner's Dilemma. In this paper, we propose a strategy updating rule with payoff memory. We observe that the random graphs and small-world networks can provide even better frameworks for cooperation than the scale-free networks in this scenario. Our observations suggest that the degree heterogeneity may be neither a sufficient condition nor a necessary condition for the widespread cooperation in complex networks. Also, the topological structures are not sufficed to determine the level of cooperation in complex networks.Comment: 6 pages, 5 figure

Rumor Evolution in Social Networks

Social network is a main tunnel of rumor spreading. Previous studies are concentrated on a static rumor spreading. The content of the rumor is invariable during the whole spreading process. Indeed, the rumor evolves constantly in its spreading process, which grows shorter, more concise, more easily grasped and told. In an early psychological experiment, researchers found about 70% of details in a rumor were lost in the first 6 mouth-to-mouth transmissions \cite{TPR}. Based on the facts, we investigate rumor spreading on social networks, where the content of the rumor is modified by the individuals with a certain probability. In the scenario, they have two choices, to forward or to modify. As a forwarder, an individual disseminates the rumor directly to its neighbors. As a modifier, conversely, an individual revises the rumor before spreading it out. When the rumor spreads on the social networks, for instance, scale-free networks and small-world networks, the majority of individuals actually are infected by the multi-revised version of the rumor, if the modifiers dominate the networks. Our observation indicates that the original rumor may lose its influence in the spreading process. Similarly, a true information may turn to be a rumor as well. Our result suggests the rumor evolution should not be a negligible question, which may provide a better understanding of the generation and destruction of a rumor.Comment: a regular paper with 6 pages, 3 figure

Research on the Application of Deep Learning-based BERT Model in Sentiment Analysis

This paper explores the application of deep learning techniques, particularly focusing on BERT models, in sentiment analysis. It begins by introducing the fundamental concept of sentiment analysis and how deep learning methods are utilized in this domain. Subsequently, it delves into the architecture and characteristics of BERT models. Through detailed explanation, it elucidates the application effects and optimization strategies of BERT models in sentiment analysis, supported by experimental validation. The experimental findings indicate that BERT models exhibit robust performance in sentiment analysis tasks, with notable enhancements post fine-tuning. Lastly, the paper concludes by summarizing the potential applications of BERT models in sentiment analysis and suggests directions for future research and practical implementations

5,13-Disulfamoyl-1,9-diazatetracyclo[7.7.1.02,7.010,15]heptadeca-2(7),3,5,10,12,14-hexaen-1-ium chloride

In the title salt, C15H17N4O4S2 +·Cl−, the chloride anion is disordered over two positions with occupancies of 0.776 (6) and 0.224 (6). The cation adopts an L shape and the dihedral angle between the benzene rings is 82.5 (3)°. In the crystal, inversion dimers of cations linked by pairs of N—H⋯N hydrogen bonds occur, with the bond arising from the protonated N atom. The cationic dimers are linked into chains via the disordered chloride ions by way of N—H⋯Cl hydrogen bonds and N—H⋯O, C—H⋯O and C—H⋯Cl inter­actions also occur, which help to consolidate the three-dimensional network

Traffic Fluctuations on Weighted Networks

Traffic fluctuation has so far been studied on unweighted networks. However many real traffic systems are better represented as weighted networks, where nodes and links are assigned a weight value representing their physical properties such as capacity and delay. Here we introduce a general random diffusion (GRD) model to investigate the traffic fluctuation in weighted networks, where a random walk's choice of route is affected not only by the number of links a node has, but also by the weight of individual links. We obtain analytical solutions that characterise the relation between the average traffic and the fluctuation through nodes and links. Our analysis is supported by the results of numerical simulations. We observe that the value ranges of the average traffic and the fluctuation, through nodes or links, increase dramatically with the level of heterogeneity in link weight. This highlights the key role that link weight plays in traffic fluctuation and the necessity to study traffic fluctuation on weighted networks.Comment: a paper with 11 pages, 6 figures, 40 reference

Fabrication and Characterization of Al/NiO Energetic Nanomultilayers

The redox reaction between Al and metallic oxide has its advantage compared with intermetallic reaction and Al/NiO nanomutlilayers are a promising candidate for enhancing the performance of energetic igniter. Al/NiO nanomutlilayers with different modulation periods are prepared on alumina substrate by direct current (DC) magnetron sputtering. The thicknesses of each period are 250 nm, 500 nm, 750 nm, 1000 nm, and 1500 nm, respectively, and the total thickness is 3 μm. The X-ray diffraction (XRD) and scanning electron microscope (SEM) results of the as-deposited Al/NiO nanomutlilayers show that the NiO films are amorphous and the layered structures are clearly distinguished. The X-ray photoelectron spectroscopy (XPS) demonstrates that the thickness of Al2O3 increases on the side of Al monolayer after annealing at 450°C. The thermal diffusion time becomes greater significantly as the amount of thermal boundary conductance across the interfaces increases with relatively smaller modulation period. Differential scanning calorimeter (DSC) curve suggests that the energy release per unit mass is below the theoretical heat of the reaction due to the nonstoichiometric ratio between Al and NiO and the presence of impurities

Experimental Evaluation of Fragments from TBM Disc Cutting under Different Load Cases

The Tunnel Boring Machine (TBM) tunneling process always contains a certain degree of vibrations due to the step broken phenomenon of the cutting tools. Undoubtedly, there is a quite difference in the fragment characteristics which are related to the construction efficiency of TBM under the static load and the combination of static and impact load. In this study, a series of rock breaking tests with a 216 mm diameter disc cutter and marble samples were conducted under different load cases. Based on the Rosin–Rammler distribution curve, the fragments from the cutting tests were also sieved to calculate the absolute size constant (x’) and coarseness index (CI). The relationship between coarseness index, absolute size parameter and the cutting parameters, specific energy, production rate was evaluated. The results show that there is an increasing trend of x’ and CI with the increase of cut spacing and penetration as well as adding impact load component. An overall downtrend in specific energy and upward trend in production rate which are associated with the high efficiency can be observed with the increasing CI and x’. It is believed that the conclusions are of great significance for improving TBM construction efficiency and cutterhead design