Models of strategy evolution on static networks help us understand how population structure can promote the spread of traits like cooperation. One key mechanism is the formation of altruistic spatial clusters, where n...
Economic studies have shown that there are two types of regulation schemes which can be considered as a vital part of today’s global economy: self-regulation enforced by self-regulation organizations to govern indust...
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Economic studies have shown that there are two types of regulation schemes which can be considered as a vital part of today’s global economy: self-regulation enforced by self-regulation organizations to govern industry practices, and government regulation which is considered as another scheme to sustain corporate adherence. An outstanding problem of particular interest is to understand quantitatively the role of these regulation schemes in evolutionary dynamics. Typically, punishment usually occurs for enforcement of regulations. Taking into account both types of punishments to curve the regulations, we develop a game model where six evolutionary situations with corresponding combinations of strategies are considered. Furthermore, a semi-analytical method is developed to allow us to give an accurate estimations of the boundaries between the phases of full defection and nondefection. We find that, associated with the evolutionary dynamics, for infinite well-mixed population, the mix of both punishments performs better than one punishment alone in promoting public cooperation, but for networked population the cooperator-driven punishment turns out to be a better choice. We also uncover monotonous facilitating effects of synergy effect, punishment fine and feedback sensitivity on the public cooperation for infinite well-mixed population. Conversely, for networked population an optimal intermediate range of feedback sensitivity is needed to best promote punishers’ populations. Overall, networked structure is overall more favorable for punishers and further for public cooperation, because of both network reciprocity and mutualism between punishers and cooperators who do not punish defectors. We provide physical understandings of the observed phenomena, through a detailed statistical analysis of frequencies of different strategies and spatial pattern formations in different evolution situations. These results provide valuable insights into how to select and enforce suitab
Pavement Distress Recognition (PDR) is an important step in pavement inspection and can be powered by image-based automation to expedite the process and reduce labor costs. Pavement images are often in high-resolution...
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Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the most complex systems in the universe. On...
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Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the most complex systems in the universe. One fundamental critical question which would affect human sustainability remains open: Will artificial intelligence (AI) evolve to surpass human intelligence in the future? This paper shows that in theory new AI twins with fresh cellular level of AI techniques for neuroscience could approximate the brain and its functioning systems (e.g. perception and cognition functions) with any expected small error and AI without restrictions could surpass human intelligence with probability one in the end. This paper indirectly proves the validity of the conjecture made by Frank Rosenblatt 70 years ago about the potential capabilities of AI, especially in the realm of artificial neural networks. This paper also gives the answer to the two widely discussed fundamental questions: 1) whether AI could have potentials of discovering new principles in nature;2) whether error backpropagation (BP) algorithm commonly and efficiently used in tuning parameters in AI applications is also adopted in the brain. Intelligence is just one of fortuitous but sophisticated creations of the nature which has not been fully discovered. Like mathematics and physics, with no restrictions artificial intelligence would lead to a new subject with its self-contained systems and principles. We anticipate that this paper opens new doors for 1) AI twins and other AI techniques to be used in cellular level of efficient neuroscience dynamic analysis, functioning analysis of the brain and brain illness solutions;2) new worldwide collaborative scheme for interdisciplinary teams concurrently working on and modelling different types of neurons and synapses and different level of functioning subsystems of the brain with AI techniques;3) development of low energy of AI techniques with the aid of fundament
In the third catalog of active galactic nuclei detected by the Fermi Large Area Telescope Clean (3LAC) sample, there are 402 blazars candidates of uncertain type (BCU). The proposed analysis will help to evaluate the ...
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Coordinatively unsaturated (CUS) iron sites are highly active in catalytic oxidation reactions;however, maintaining the CUS structure of iron during heterogeneous catalytic reactions is a great challenge. Here, we rep...
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This paper begins with solving the linear elastodynamic equation with forcing by expanding it into Fourier series. We then proceed to prove the conservation laws of momentum, angular momentum, and energy. We intend th...
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The involvement of yellow genes y-b, y-c, y-e , and y-h in cuticle tanning has poorly been clarified. In the present paper, six putative yellow ( y-y, y-b, y-c, y-e y-f , and y-h ) genes were identified in Henosepilac...
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The involvement of yellow genes y-b, y-c, y-e , and y-h in cuticle tanning has poorly been clarified. In the present paper, six putative yellow ( y-y, y-b, y-c, y-e y-f , and y-h ) genes were identified in Henosepilachna vigintioctopunctata . Hvy-b, Hvy-c, Hvy-e , and Hvy-h were abundantly transcribed at early larval and late pupal stages, especially in the epidermis. Accordingly, RNA interference (RNAi) experiments were performed by an injection of ds y-b , ds y-c , ds y-e , or ds y-h into the second instar larvae and 1-day-old pupae. The head capsule, scoli and strumae, and legs in the fourth-instar larvae became blacker; the blackish spots in the pupae were darkened and widened after RNAi of Hvy-b , compared with those of ds egfp -treated controls. Depletion of Hvy-b at the 1-day-old pupal stage expanded two pair of black markings on the sternum of the metathorax, and darkened the black patched on the sterna of the abdomen segments I–VI in the resultant adults. Depletion of Hvy-e caused darker pigmented adult body and elytral cuticles than those of ds egfp -introduced controls. However, there was no obvious difference in pigmentation of the black markings. Hvy-h -deficient larvae displayed dark yellow body color, whereas the body color of the ds egfp -injected control was pale yellow. There was no obvious difference in coloration of larval specific-black markings or pupal cuticle between ds Hvy-h - and ds egfp- treated animals. Moreover, silence of Hvy-c at the second instar larval stage lightened black markings in the resulting larvae and pupae, but had no influence on pale yellow body color. Our results demonstrated their different roles of the four yellow genes during body pigmentation: Hv Y-b and Hv Y-c, respectively, inhibit and facilitate the coloration within dark markings, whereas Hv Y-e and Hv Y-h, respectively, repress the pigmentation in adult and larval body cuticles outside the black patches in H. vigintioctopunctata . Hvy-b, Hvy-c, Hvy-e and Hvy-h a
4Cr5MoSiV (H11) steel machining chips were crushed to a powder and then consolidated into discs by hot pressing under various consolidation parameters. The discs were subjected to modified spheroidizing annealing trea...
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Nowadays, research on session-based recommender systems (SRSs) is one of the hot spots in the recommendation domain. Existing methods make recommendations based on the user’s current intention (also called short-term...
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Nowadays, research on session-based recommender systems (SRSs) is one of the hot spots in the recommendation domain. Existing methods make recommendations based on the user’s current intention (also called short-term preference) during a session, often overlooking the specific preferences associated with these intentions. In reality, users usually exhibit diverse preferences for different intentions, and even for the same intention, individual preferences can vary significantly between users. As users interact with items throughout a session, their intentions can shift accordingly. To enhance recommendation quality, it is crucial not only to consider the user’s intentions but also to dynamically learn their varying preferences as these intentions change. In this paper, we propose a novel Intention-sensitive Preference Learning Network (IPLN) including three main modules: intention recognizer, preference detector, and prediction layer. Specifically, the intention recognizer infers the user’s underlying intention within his/her current session by analyzing complex relationships among items. Based on the acquired intention, the preference detector learns the intention-specific preference by selectively integrating latent features from items in the user’s historical sessions. Besides, the user’s general preference is utilized to refine the obtained preference to reduce the potential noise carried from historical records. Ultimately, the fine-tuned preference and intention collaborate to instruct the next-item recommendation in the prediction layer. To prove the effectiveness of the proposed IPLN, we perform extensive experiments on two real-world datasets. The experiment results demonstrate the superiority of IPLN compared with other state-of-the-art models.
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